IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\n
By listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
All three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n
"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n
"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\n
In conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n
“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\n
We invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\n
Feel free to share this news on social media and help us mark this memorable moment!
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\n
By listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
All three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n
"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n
"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\n
In conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n
“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\n
We invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\n
Feel free to share this news on social media and help us mark this memorable moment!
\n\n
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"2220",leadTitle:null,fullTitle:"Reinforcement Learning",title:"Reinforcement Learning",subtitle:null,reviewType:"peer-reviewed",abstract:"Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. 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1. Introduction
Rice (Oryza sativa L.) production systems occupy 156 million hectares of soil around the world (USDA-FAS, 2012) and rice is considered the world’s most important staple food crop due to its prevalence and societal longevity. As a result of human activities, such as cultivation, domestication, dispersal, and diversification, rice is now grown in more than 100 countries across the latitudinal span of 40°S to 53°N (Chang, 2003), accounting for 20% of annual worldwide grain production (USDA-FAS, 2012). In the United States, 82% of the land area used for domestic rice production (1.1 million hectares) occurs in Arkansas (44%), California (22%) and Louisiana (16%), but smaller quantities of rice are also produced in Texas (8%), Mississippi (7%), and Missouri (6%; USDA-NASS, 2012). Rice production in the Mississippi Delta region of the United States is primarily drill-seeded during dry conditions as opposed to wet- or transplant-seeded during flooded conditions. These are the two most common methods used in most rice-producing areas of the world (De Datta, 1981).
Drill-seeded rice production systems are unique from other row-crop production systems in that the crop is grown under flood-irrigated conditions from about one month post-emergence until a few weeks prior to harvest, where the upper-most part of the soil profile is nearly to completely saturated (Norman et al., 2003). Drill-seeded rice production systems are also unique from wet- or transplant-seeded rice production systems because they involve shorter periods of saturated soil conditions and longer periods of dry soil conditions as a result of delayed flooding and time allowed between cropping periods. Since the cycling of waterlogged and dry soil conditions has been known to greatly influence the storage and cycling of soil organic matter (SOM; IPCC, 2007), drill-seeded rice production systems can play an influential role in the biogeochemical cycling of carbon (C) and nitrogen (N) in agriculturally managed systems.
Soil organic matter is one of the main reservoirs of C in the biosphere (Bernsten et al., 2006). The actual C content in SOM is approximately 57% by weight (Sundermeiser et al., 2005), with the remaining components made up of oxygen (O2), hydrogen, N, and smaller amounts of other nutrients (Bot and Benites, 2005). Follett (2001) estimated that there are about 1550 petagrams (Pg) of soil organic carbon (SOC) stored in the world’s soils. This is more than twice the estimated C contained in living vegetation (560 Pg) or in the atmosphere (750 Pg; Sunquist, 1993). Information on the dynamics of SOM and the associated SOC and N storage in agricultural soils has gained interest over recent years because of its influences on global climate change and crop productivity (Majumder et al., 2007; IPCC, 2007).
The concept of global warming is primarily attributed to three C and N greenhouse gases that are present both naturally and from anthropogenic sources: carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O; IPCC, 2007). According to Lal (2004), land management practices have the potential to enhance SOC accumulation, thereby easing the gaseous C load to the atmosphere and enriching the soil. The decomposition of SOM, and thus the loss of C from the soil through the conversion of SOC into the gaseous compounds of CO2 under aerobic conditions and CH4 under anaerobic conditions is promoted by an array of factors, such as location in the soil, fibrous composition of the substrate, nutrient content, soil texture, soil pH, moisture conditions, and soil temperature (Denman et al, 2004; Wolf and Snyder, 2003; Seiter and Horwath, 2004; Alvarez and Lavado, 1998; Bayer, 1996; Filcheva and Mitova, 2002).
The SOM content present in the soil is a reflection of a long-term balance between additions and losses, thus the SOM content is greater when there is a large annual plant productivity rate and a low decomposition rate (Weil and Magdoff, 2004). Therefore, crops that produce large amounts of above-ground biomass have a greater contribution to the overall SOM content. The length of time SOC can be stored in the soil is controlled by the chemical composition of the biomass, which in turn determines the microbial breakdown potential of the substrate (Debusk et al., 2001; Farquhar et al., 2001). In relation to nutrient content, a large portion of the total nitrogen (TN) within soil (90 to 95%; Smith et al., 1993) occurs along with SOC in the constituents of SOM, and the ratio of N available in the substrate directly affects the rate of microbial SOM decomposition (McGill and Cole, 1981; Weil and Magdoff, 2004). Thus, the C and N cycles are directly linked and the C cycle of an ecosystem and cannot be properly examined or modeled without giving reference to N cycling (McGill and Cole, 1981; Weil and Magdoff, 2004). Furthermore, the presence or absence of O2 plays an important role in the process dynamics and management responses of decomposition systems. Generally, an abundant O2 supply promotes rapid decomposition, whereas a deficiency in O2 results in a substantially lower decomposition rate (DeBusk et al., 2001; Shaffer and Ma, 2001). Under extremely wet conditions, decomposition can become limited by O2 availability (Wolf and Snyder, 2003). Decreased decomposition rates result in greater accumulations of SOM in saturated soils, which essentially increase the amount of stored SOC and TN within the soil (DeBusk et al., 2001).
Since soil moisture conditions substantially influence the availability of O2, and consequently, the overall storage of SOC and the cycling of N in the soil, examining crop production systems that contain periods of both aerobic and anaerobic conditions is an important component in accurately estimating the global storage of SOC and TN in agricultural production systems. The most essential aspect of soil management practices is to maintain soil physical properties in a way that supports crop growth and ensures an adequate amount of the biomass gets recycled back to the soil to serve as a long-term organic nutrient source (Lal, 2007). There have been a number of studies examining the changes in SOC due to different production practices, such as crop variety, tillage, fertilization and climate. However, much of the previous research has been conducted in dryland cropping systems across the globe or in paddy-grown rice in Asia. Hence, there is a great deficiency in research pertaining to SOC and TN storage and cycling in other production systems, such as the dry-seeded, delayed-flood rice production system common in the main rice-production region of the United States.
1.1. Research objectives and hypotheses
The objective of this study was to evaluate the long-term effects of rice-based crop rotations [i.e., with corn (Zea mays L.), soybean (Glycine max L.), and winter wheat (Triticum aestivum L.)], tillage [conventional tillage (CT) and no-tillage (NT)], and soil fertility (optimal and sub-optimal) on SOC and TN contents, the partitioning of SOC and TN in SOM, and C:N soil ratios in the top 10 cm of a silt-loam soil after 11 years (1999 to 2010) of consistent management. Furthermore, SOC and TN contents were modeled for the 11-year period and into the future using the Century soil organic model (Parton et al., 1987; NREL, 2006). It was hypothesized that: (1) NT practices would have greater SOC and TN than that under CT over time as a result of decreased aeration and soil disturbance; (2) rotations with increased frequencies of high-residue-producing crops, such as rice, corn, and those double-cropped with wheat, would have greater SOC and TN from greater amounts of biomass returned to the soil than lower-residue producing crop rotations, such as those with greater frequencies of soybean; (3) the optimal fertility regime would have greater SOC and TN than that in the sub-optimal fertility regime over time as a result of increased biomass production related with greater nutrient inputs from fertilizer; (4) the partitioning of SOC and TN in SOM would not vary greatly as a result of treatment combinations; (5) soil C:N ratios would be greater in high-residue-producing rotations, such as rice and corn, and would be lower in rotations including soybean, as a result of crop residue inputs; and (6) the Century model outcomes are expected to be correlated with measured SOC and TN obtained in the study. The Century model is expected to show that systems with high-residue-producing crops, NT, and optimal fertility result in greater SOM in the soil, thus increasing the SOC and TN contents over time more in these treatment combinations than in others.
2. Materials and methods
2.1. Site description
This field study was conducted at the University of Arkansas’ Rice Research and Extension Center (RREC) near Stuttgart (34°27\' N, 91°24\' W), which is located in the Mississippi Delta region of eastern Arkansas in an area known as the Grand Prairie (USACE, 2000). The geographic area is made up of silt-loam and clay-textured soils from the Southern Mississippi River Alluvium and terraces and the Arkansas River Alluvium, which are Major Land Resource Areas 131A and 131B, respectively (USDA-NRCS, 2008). The 30-yr mean monthly air temperature ranges from a minimum of 0.2 °C in January to a maximum of 33.1 °C in July, and the 30-yr mean annual precipitation is 132 cm (SRCC, 2012).
The study began in 1999 on a Dewitt silt loam (fine, smectitic, thermic, Typic Albaqualf; USDA-NRCS, 2008), which is a common soil present in the Grand Prairie region. The Dewitt series is made up of very deep, poorly drained, slowly permeable soils that formed in alluvium (USDA-NRCS, 2008). The top 10 cm are primarily dark grayish brown (10YR 4/2) in color when the soil is moist and have a moderate medium granular structure near the surface and weak medium and course subangular blocky structure in the sub-soil (USDA-NRCS, 2008).
Prior to the initiation of the study in 1999, the study area had been fallow for numerous years due to a lack of irrigation capability. Vegetation present consisted of a mixture of grasses and weeds that were mowed in the summer. In preparation for the study, the site was land leveled to a 0.15% grade in Fall 1998, which is common practice in the area to facilitate uniform distribution of flood-irrigation water (Brye et al., 2003). Top soil was first removed, piled off to the side of the area, and then spread back over the area that was leveled.
2.2. Experimental design and field treatments
The experimental design for this study was a randomized complete block, with each block partitioned as a split-strip-split plot. The blocks included four rectangular sections 76-m long by 120-m wide (9120 m2) within the 1.9-ha experimental site. Each block was divided into two tillage treatments (CT and NT) and each tillage treatment was split into two fertility regimes (optimal and sub-optimal). Each of the tillage-fertility combinations were stripped across with six crop rotations and split across time (1999 and 2010). The six crop rotations included continuous rice (R), rice-soybean (RS), rice-corn (RC), rice (winter wheat) [R(W)], rice (winter wheat)-soybean (winter wheat) [R(W)S(W)], and rice-corn-soybean (RCS). All rotations evaluated started with rice during the first year of the study and followed the respective rotations in successive years (Table 1). There were 96 plots evaluated and each plot representing a tillage-fertility-rotation treatment combination measured 6- by 19-m.
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\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\tRotation\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tYear\n\t\t\t
\n\t\t\t
\n\t\t\t\tR\n\t\t\t
\n\t\t\t
\n\t\t\t\tRS\n\t\t\t
\n\t\t\t
\n\t\t\t\tRC\n\t\t\t
\n\t\t\t
\n\t\t\t\tR(W)\n\t\t\t
\n\t\t\t
\n\t\t\t\tR(W)S(W)\n\t\t\t
\n\t\t\t
\n\t\t\t\tRCS\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
1999
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t
\n\t\t
\n\t\t\t
2000
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t
\n\t\t
\n\t\t\t
2001
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t
\n\t\t
\n\t\t\t
2002
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Rice
\n\t\t
\n\t\t
\n\t\t\t
2003
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Corn
\n\t\t
\n\t\t
\n\t\t\t
2004
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Soybean
\n\t\t
\n\t\t
\n\t\t\t
2005
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t
\n\t\t
\n\t\t\t
2006
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t
\n\t\t
\n\t\t\t
2007
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t
\n\t\t
\n\t\t\t
2008
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Rice
\n\t\t
\n\t\t
\n\t\t\t
2009
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Rice
\n\t\t\t
Corn
\n\t\t
\n\t\t
\n\t\t\t
2010
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Corn
\n\t\t\t
Rice
\n\t\t\t
Soybean
\n\t\t\t
Soybean
\n\t\t
\n\t
Table 1.
Summary of summer crop rotations by year with all rotations tilled prior to planting in 1999 and the no-tillage treatment starting in 2000. Crops used in the rotations include rice (R), soybean (S), corn (C), and winter wheat [(W)]. Crops in parentheses were grown in the winter.
In the CT treatment, crop residues were incorporated into the soil by disking one to two months following harvest and prior to spring planting. Spring field preparation was also followed by multiple passes with a light field cultivator (i.e., Triple-K) to achieve the desired seedbed for rice planting. In the NT treatment, crop residues were left on the surface after harvest and were not manipulated by any means prior to planting in the spring. Rice, soybean, and wheat were sown into 19-cm rows in both tillage treatments using an Almaco NT drill (Almaco, Nevada, IA). Rice was drill-seeded at a rate of 100 kg seed ha-1, soybean at a rate of 56 kg seed ha-1, and wheat at a rate of 67 kg seed ha-1. Corn was planted in 76-cm rows at a plant population of 79,000 seeds ha-1. Fertility treatments applied were based on soil analyses from the study site at the beginning of the study in 1999 (Table 2). Each year, phosphorus (P) was applied as triple super phosphate and potassium (K) was applied as muriate of potash, which were broadcast pre-plant and pre-tillage with a hand-spreader. During the years rice was grown, zinc (Zn) was applied as zinc sulfate, which was also broadcast pre-plant and pre-tillage with a hand-spreader. Nitrogen was applied as urea with a hand-spreader pre-flood approximately one month after planting. Phosphorous, K, and Zn were incorporated into the soil in the CT treatment and were applied to the surface in the NT treatment.
Summary of the annual nitrogen (N), phosphorous (P), potassium (K), and zinc (Zn) added to corn, soybean, rice and winter wheat to comprise the optimal soil fertility treatments in a long-term, rice-based rotation study at the Rice Research and Extension Center near Stuttgart, AR on a silt-loam soil.
Following N fertilization of the rice, a 5- to 10-cm permanent flood was established, which was maintained on all of the rice plots throughout the growth period. Corn and soybean were furrow-irrigated on an as-needed basis during the summer growth period, with the irrigation amount varying based on the rainfall received and the growth of the crop. Irrigation water originated from a nearby surface reservoir, with water additions mainly from an adjacent stream channel and some groundwater. Wheat grown during the winter was rainfed only. All recommendations for stand establishment, irrigation, weed control and pest management for rice (Slaton, 2001), soybean (Ashlock, 2000), corn (Espinoza and Ross, 2003) and wheat (Kelley, 1999) followed the University of Arkansas Cooperative Extension Service recommendations for the duration of the study.
2.3. Soil sampling and analyses
Soil samples were collected from the top 10 cm in each tillage-fertility-rotation treatment combination prior to spring planting in March during both evaluation years. The 1999 samples were collected after land leveling had occurred and prior to any actual field treatment. The 2010 samples were collected prior to the spring planting of rice, corn or soybean. During the time of sampling in 2010, wheat was present in the R(W) and R(W)S(W) rotations, whereas the R, RS, RC, and RCS rotations were still fallow from the winter. Soil samples for both years were dried at 70°C in a forced-draft oven for 48 hours. In 2010, soil samples were acquired using a 4.7-cm diameter stainless steel cylinder. Following drying, samples were weighed for bulk density determination. In 1999, bulk density was not measured; therefore, soil particle-size analyses were conducted on all of the 2010 soil samples from the top 10 cm in order to estimate bulk density. The percentages of sand and clay measured from the 2010 samples were combined with measured SOM concentrations from 1999 to estimate bulk density for the 1999 samples on a plot-by-plot basis, using the bulk density prediction equation incorporated in the Soil-Plant-Atmosphere-Water (SPAW) model (Saxton and Rawls, 2006).
In both 1999 and 2010, total C and TN were measured by high-temperature combustion after samples were crushed to pass a 2-mm mesh screen. All measured C was assumed to be associated with the organic fraction of the soil because, upon treatment with concentrated hydrochloric acid (HCl), there was no effervescence. Therefore, all measured C is hereafter referred to as SOC. Measured SOC and TN concentrations (mg kg-1) were converted to contents (kg m-2) using the 10-cm sampling depth and soil bulk densities. The partitioning of SOC and TN within SOM, in addition to C:N ratios, were calculated from SOM, SOC, and TN concentrations measured in each tillage-fertility-rotation treatment combination.
When the 2010 samples were collected after 11 years of management, R and R(W) rotations had produced 11 rice crops, and the RS, RC, and R(W)S(W) rotations had produced six rice crops with five crops in the respective rotation with corn or soybean (Table 3). Furthermore, the RCS rotation had produced four rice crops, four corn crops, and three soybean crops, and the R(W) and R(W)S(W) rotations with had produced 11 winter wheat crops (Table 3). Tillage had occurred in the tilled plots five months before (late-October 2009) the collection of samples in March 2010.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tRotation\n\t\t\t
\n\t\t\t
\n\t\t\t\tNumber of Crops\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tRice\n\t\t\t
\n\t\t\t
\n\t\t\t\tCorn\n\t\t\t
\n\t\t\t
\n\t\t\t\tSoybean\n\t\t\t
\n\t\t\t
\n\t\t\t\tWheat\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Continuous Rice
\n\t\t\t
11
\n\t\t\t
-
\n\t\t\t
-
\n\t\t\t
-
\n\t\t
\n\t\t
\n\t\t\t
Rice-Soybean
\n\t\t\t
6
\n\t\t\t
-
\n\t\t\t
5
\n\t\t\t
-
\n\t\t
\n\t\t
\n\t\t\t
Rice-Corn
\n\t\t\t
6
\n\t\t\t
5
\n\t\t\t
-
\n\t\t\t
-
\n\t\t
\n\t\t
\n\t\t\t
Rice-(Wheat)
\n\t\t\t
11
\n\t\t\t
-
\n\t\t\t
-
\n\t\t\t
11
\n\t\t
\n\t\t
\n\t\t\t
Rice-(Wheat)-Soybean-(Wheat)
\n\t\t\t
6
\n\t\t\t
-
\n\t\t\t
5
\n\t\t\t
11
\n\t\t
\n\t\t
\n\t\t\t
Rice-Corn-Soybean
\n\t\t\t
4
\n\t\t\t
4
\n\t\t\t
3
\n\t\t\t
-
\n\t\t
\n\t
Table 3.
Summary of the crop rotations and the number of crops grown in the respective rotations during the 11-yr study period (1999 to 2010) at the Rice Research and Extension Center near Stuttgart, AR on a silt-loam soil. Crops in parentheses were grown during the winter.
2.4. Century model simulation
For comparison to measured data over time, simulations using the Century model were conducted for each tillage-fertility-rotation treatment combination. Century is a SOM model that simulates C and N cycling in different plant production systems based on a monthly time step (Parton et al., 1987, 1988; Parton and Rasmussen, 1994). The model works by allocating various plant components and animal excreta into different SOM pools with varying timescales of decomposition, which include the active (a few months to a few years), slow (20 to 50 years), or passive (400 to 2000 years) pools. This is done by partitioning plant residues as either structural or metabolic organic pools based on their lignin:N ratio (Shibu et al., 2006), in that plant parts with a larger ratio take longer to decompose. The model works by dividing the structural pool into lignin and cellulose components (NREL, 2006). The lignin is moved to the slow decomposition pool, whereas the cellulose and metabolic C (i.e., microbial biomass) are added to the active pool. The actual decomposition rates of the SOM from the active pool are calculated based on soil texture, soil temperature and soil moisture and the decomposition rates of the structural pool are determined based upon the lignin content of the plant material. In the Century model, the nitrification process is not incorporated because there is no distinction made within the mineral-N pool between nitrate and ammonium (Shibu et al., 2006).
The limitations of the model in relation to rice-based cropping systems are that it was originally designed for grasslands, arable lands, forests and savanna ecosystems under aerobic conditions (NREL, 2006; Parton et al., 1988), not periodically flooded ecosystems. This has resulted in the Century model not being extensively used to simulate rice-based crop rotations. However, Bhattacharyya et al. (2007) used Century to model a jute (Cochorus capsularis L.)-rice-wheat rotation in West Bengal, India and Milne et al. (2008) modeled a 3-year rice-soybean, wheat-soybean rotation in eastern Arkansas, United States, in which the field was flooded for rice production once every three years. Bharracharyya et al. (2007) reported that the model overestimated SOC content, but was able to simulate trends in SOC cycling over the 30-year study period. Milne et al. (2008) reported that the model underestimated the increase of SOC content in the first year, but concluded that Century could be used to accurately predict the long-term SOC dynamics in rice-based crop rotations that are flooded every three years.
Parameters for the Century SOM model (Parton et al., 1987; NREL, 2006) simulation in this study were adjusted using a combination of recorded historic climatic data, measured plant properties and responses, and measured soil data for the top 10 cm that were adjusted to reflect a depth of 20 cm. In 1999, soil samples had only been collected from the top 10 cm, whereas 2010 samples were collected from both the 0- to 10- and 10- to 20-cm depths. In order to model trends over time using Century, which only simulates C and N cycling in a fixed depth of the top 20 cm, depth adjustments had to be made from the measured 0- to 10-cm sampling depth to reflect the top 20 cm. In order to calculate the percentage of SOC and TN that was contained in the top 10 cm of the 0- to 20-cm depth interval, the average percent content was calculated from the 2010 soil samples. Based on 192 samples from both the top 10 cm and the 10- to 20-cm depth, the top 10 cm contained an average of 66% of the SOC and 61% of the TN in the top 20 cm of soil. To facilitate comparison to measured data from the top 10 cm, output values from Century from the top 20 cm were adjusted to SOC and TN contents for the top 10 cm based on the average calculated percentages from observed data.
Different simulated model designs for field treatments were set up for each tillage-fertility-rotation treatment combination. However, the input file for all model designs used the same values for monthly average maximum and minimum air temperature (SRCC, 2012), monthly precipitation (SRCC, 2012), soil texture, soil bulk density, soil pH, and initial SOC and TN contents from 1999. This approach was justified because the entire study site was uniformly maintained and land leveled prior to the initiation of the study and SOC and TN concentrations were similar across the study site in 1999. Therefore, all model input files started with the same site and control parameters for the model. The initial values for soil texture, soil bulk density, and SOC and TN contents were fixed based on the average values across all preassigned tillage-fertility-rotation treatment combinations. Any observed differences among tillage-fertility-rotation treatment combinations over time were assumed to be a result of the imposed treatments instead of inherent differences in soil physical and chemical properties. Anaerobic conditions associated with flooding during the rice growing season, which results in slower decomposition rates, were accounted for by adjusting the drainage potential of the soil and the irrigation frequency.
2.5. Data analyses
Initial soil properties in 1999, in addition to the effects of tillage, fertility regime, crop rotation, over time (1999-2010) on SOC and TN contents, the partitioning of SOC and TN in SOM, and C:N ratios were evaluated by analysis of variance (ANOVA) using the PROC MIXED procedure in SAS® (version 9.2, SAS Institute, Inc., Cary, NC). When appropriate, means were separated using Fisher’s protected least significant difference (LSD) at the 0.05 level. Modeled results for SOC and TN storage trends over time were compared to direct observations via a linear regression analyses using Minitab (version 15, Minitab, Inc., State College, PA).
3. Results and discussion
3.1. Initial soil properties
Samples collected at the initiation of the study in 1999, which were collected after land leveling and prior to the implementation of tillage, fertility, and rotation treatments, showed that soil properties in the top 10 cm were primarily uniform among preassigned tillage-fertility-rotation treatment combinations. There were no differences in SOC and TN contents, the partitioning of SOC and TN within SOM, and soil C:N ratios among preassigned tillage, fertility, and/or rotation treatments (P > 0.05; Table 4). Furthermore, the soil particle-size distribution did not differ among any treatment combinations when measured in 2010 (P > 0.05; Table 4).
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tTreatment Effect\n\t\t\t
\n\t\t\t
\n\t\t\t\tBD\n\t\t\t
\n\t\t\t
\n\t\t\t\tSOC\n\t\t\t
\n\t\t\t
\n\t\t\t\tTN\n\t\t\t
\n\t\t\t
\n\t\t\t\tSOC/SOM\n\t\t\t
\n\t\t\t
\n\t\t\t\tTN/SOM\n\t\t\t
\n\t\t\t
\n\t\t\t\tC:N\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t________________________________________ P ___________________________________________\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Tillage
\n\t\t\t
0.595
\n\t\t\t
0.345
\n\t\t\t
0.139
\n\t\t\t
0.382
\n\t\t\t
0.683
\n\t\t\t
0.452
\n\t\t
\n\t\t
\n\t\t\t
Fertility
\n\t\t\t
0.569
\n\t\t\t
0.550
\n\t\t\t
0.396
\n\t\t\t
0.392
\n\t\t\t
0.588
\n\t\t\t
0.531
\n\t\t
\n\t\t
\n\t\t\t
Fertility* Tillage
\n\t\t\t
0.517
\n\t\t\t
0.544
\n\t\t\t
0.523
\n\t\t\t
0.451
\n\t\t\t
0.484
\n\t\t\t
0.553
\n\t\t
\n\t\t
\n\t\t\t
Rotation
\n\t\t\t
\n\t\t\t\t0.005\n\t\t\t
\n\t\t\t
0.113
\n\t\t\t
0.671
\n\t\t\t
0.320
\n\t\t\t
0.921
\n\t\t\t
0.349
\n\t\t
\n\t\t
\n\t\t\t
Rotation*Tillage
\n\t\t\t
0.316
\n\t\t\t
0.999
\n\t\t\t
1.000
\n\t\t\t
0.873
\n\t\t\t
0.811
\n\t\t\t
0.993
\n\t\t
\n\t\t
\n\t\t\t
Rotation*Fertility
\n\t\t\t
0.418
\n\t\t\t
0.400
\n\t\t\t
0.397
\n\t\t\t
0.488
\n\t\t\t
0.762
\n\t\t\t
0.760
\n\t\t
\n\t\t
\n\t\t\t
Rotation*Tillage*Fertility
\n\t\t\t
0.313
\n\t\t\t
0.253
\n\t\t\t
0.305
\n\t\t\t
0.515
\n\t\t\t
0.189
\n\t\t\t
0.772
\n\t\t
\n\t
Table 4.
Analysis of variance summary of the inherent differences of soil properties before tillage, fertility and crop rotation treatments. Soil properties and their interactions related to the inherent soil differences in the assigned treatment combinations on soil bulk density (BD), soil organic carbon (SOC) content, total nitrogen (TN) content, portion of SOC in soil organic matter (SOM), portion of TN in SOM, and carbon to nitrogen ratios (C:N) prior to any treatment being imposed in 1999. The study site was located at the Rice Research and Extension Center near Stuttgart, AR on a silt-loam soil. Treatment effects in bold are considered non-significant (P > 0.05).
Although there were no SOC and TN related soil property differences among preassigned treatments in 1999, there were a few minor inherent differences in estimated soil bulk density (P = 0.005) among preassigned rotations (Table 4). Estimated soil bulk density in the R(W) (1.44 g cm-3) rotation was 2 to 4% greater than that in the R (1.41 g cm-3), RC (1.40 g cm-3), and RCS (1.38 g cm-3) rotations, when averaged across preassigned tillage and fertility treatments. Furthermore, estimated soil bulk density was 3% greater in the R(W)S(W) and RS (both 1.42 g cm-3) rotations than in the RCS rotation. Though statistically different, all differences in soil bulk density were ≤ 0.06 g cm-3, which are not large enough to cause substantial differences in SOC and TN contents.
3.2. Tillage effects on SOC and TN
Similar to that hypothesized, when averaged across fertility regimes, crop rotations and time, SOC content (kg m-2) in the top 10 cm was affected by tillage (P = 0.012), and when averaged across fertility regimes and crop rotations, TN content (kg N m-2) differed over time between tillage treatments (P = 0.019; Table 5). Soil organic carbon content was 14% greater under NT (1.14 kg m-2) than under CT (1.00 kg m-2; Figure 1), but unlike what was expected, SOC content did not differ between the tillage treatments over time (i.e., 1999 to 2010; P = 0.075). However, as expected, TN content increased 34% from 1999 (0.10 kg m-2) to 2010 (0.13 kg m-2) under NT, but did not differ over time under CT (Figure 2). Consequently, NT management resulted in a net TN sequestration rate of about 0.003 kg m-2 yr-1 from 1999 to 2010.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tTreatment Effect\n\t\t\t
\n\t\t\t
\n\t\t\t\tSOC\n\t\t\t
\n\t\t\t
\n\t\t\t\tTN\n\t\t\t
\n\t\t\t
\n\t\t\t\tSOC/SOM\n\t\t\t
\n\t\t\t
\n\t\t\t\tTN/SOM\n\t\t\t
\n\t\t\t
\n\t\t\t\tC:N\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t_____________________________________ P ______________________________________\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Tillage
\n\t\t\t
\n\t\t\t\t0.012\n\t\t\t
\n\t\t\t
\n\t\t\t\t0.002\n\t\t\t
\n\t\t\t
\n\t\t\t\t0.007\n\t\t\t
\n\t\t\t
0.169
\n\t\t\t
0.861
\n\t\t
\n\t\t
\n\t\t\t
Fertility
\n\t\t\t
0.469
\n\t\t\t
0.080
\n\t\t\t
0.589
\n\t\t\t
0.167
\n\t\t\t
0.349
\n\t\t
\n\t\t
\n\t\t\t
Fertility* Tillage
\n\t\t\t
0.538
\n\t\t\t
0.678
\n\t\t\t
0.319
\n\t\t\t
0.322
\n\t\t\t
0.377
\n\t\t
\n\t\t
\n\t\t\t
Rotation
\n\t\t\t
0.120
\n\t\t\t
\n\t\t\t\t0.010\n\t\t\t
\n\t\t\t
0.941
\n\t\t\t
0.591
\n\t\t\t
0.231
\n\t\t
\n\t\t
\n\t\t\t
Rotation*Tillage
\n\t\t\t
0.543
\n\t\t\t
0.548
\n\t\t\t
0.495
\n\t\t\t
0.635
\n\t\t\t
0.964
\n\t\t
\n\t\t
\n\t\t\t
Rotation*Fertility
\n\t\t\t
0.535
\n\t\t\t
0.364
\n\t\t\t
0.517
\n\t\t\t
0.352
\n\t\t\t
0.670
\n\t\t
\n\t\t
\n\t\t\t
Rotation*Tillage*Fertility
\n\t\t\t
0.839
\n\t\t\t
0.441
\n\t\t\t
0.464
\n\t\t\t
0.457
\n\t\t\t
0.447
\n\t\t
\n\t\t
\n\t\t\t
Time
\n\t\t\t
\n\t\t\t\t0.039\n\t\t\t
\n\t\t\t
\n\t\t\t\t0.036\n\t\t\t
\n\t\t\t
0.837
\n\t\t\t
0.214
\n\t\t\t
0.155
\n\t\t
\n\t\t
\n\t\t\t
Time*Tillage
\n\t\t\t
0.075
\n\t\t\t
\n\t\t\t\t0.019\n\t\t\t
\n\t\t\t
0.595
\n\t\t\t
0.098
\n\t\t\t
0.193
\n\t\t
\n\t\t
\n\t\t\t
Time*Fertility
\n\t\t\t
0.466
\n\t\t\t
0.064
\n\t\t\t
0.526
\n\t\t\t
0.099
\n\t\t\t
0.179
\n\t\t
\n\t\t
\n\t\t\t
Time*Rotation
\n\t\t\t
\n\t\t\t\t< 0.001\n\t\t\t
\n\t\t\t
\n\t\t\t\t0.003\n\t\t\t
\n\t\t\t
\n\t\t\t\t0.047\n\t\t\t
\n\t\t\t
\n\t\t\t\t0.037\n\t\t\t
\n\t\t\t
0.654
\n\t\t
\n\t\t
\n\t\t\t
Time*Tillage*Fertility
\n\t\t\t
0.623
\n\t\t\t
0.738
\n\t\t\t
0.348
\n\t\t\t
0.344
\n\t\t\t
0.580
\n\t\t
\n\t\t
\n\t\t\t
Time*Tillage*Rotation
\n\t\t\t
0.275
\n\t\t\t
0.820
\n\t\t\t
0.533
\n\t\t\t
0.871
\n\t\t\t
0.643
\n\t\t
\n\t\t
\n\t\t\t
Time*Fertility*Rotation
\n\t\t\t
0.505
\n\t\t\t
0.302
\n\t\t\t
0.464
\n\t\t\t
0.235
\n\t\t\t
0.898
\n\t\t
\n\t\t
\n\t\t\t
Time*Tillage*Fertility*Rotation
\n\t\t\t
0.786
\n\t\t\t
0.439
\n\t\t\t
0.568
\n\t\t\t
0.605
\n\t\t\t
0.312
\n\t\t
\n\t
Table 5.
Analysis of variance summary of the effects of tillage, fertility, crop rotation and time on soil organic carbon (SOC) and total nitrogen (TN) contents, SOC and TN fractions of the soil organic matter (SOM), and carbon to nitrogen ratios (C:N) after 11 years of consistent management.
Figure 1.
Tillage [conventional tillage (CT) and no-tillage (NT)] and time (1999 and 2010) effects on total nitrogen (TN) in the top 10 cm. Different letters atop bars are significantly different at the 0.05 level.
Figure 2.
Rotation [rice (R), soybean (S), corn (C) and winter wheat (W)] and time (1999 and 2010) effects on soil organic carbon (SOC) [A] and total nitrogen (TN) [B] in the top 10 cm. Different letters atop bars within a panel are significantly different at the 0.05 level.
Tillage effects on SOC and TN contents appear to be directly related to SOM content differences, whereas the SOM content was 9% greater under NT (2.88 kg m-2) than under CT (2.64 kg m-2), when averaged across all other treatments (Motschenbacher et al., 2012). Although SOC content did not differ over time, the increase in TN content over time under NT corresponded to the 14% increase in SOM content over the same time period [1999 (2.58 kg m-2) to 2010 (2.95 kg m-2); Motschenbacher et al., 2012], when averaged across all other treatments. Similar to results observed in this study, greater SOC under NT as opposed to that under CT is a common occurrence, widely reported in past agronomic studies (West and Post, 2002; McCarty et al., 1998; Xu et al., 2007). Soils that have been degraded through excessive tillage tend to have less SOM due to an increased amount of exposed surface area, which facilitates aerobic decomposition (DeBusk et al., 2001). Carbon makes up more than half the mass of SOM (Montgomery et al., 2000), and it has been shown that cultivating the land influences the dynamics of SOC and, in turn, the amount of C emitted from the soil as CO2 due to the oxidation or decomposition of SOM (Paustian et al, 1995; Reicosky et al., 1995).
Although flooded-soil conditions in rice-based crop rotations alter the environmental conditions contributing to C and N sequestration and cycling, due to slower decomposition rates and increased CH4 emissions as opposed to CO2 emissions, studies of long-term effects of different tillage regimes implemented in non-flooded upland soils can also provide insight on the impacts of soil disturbance from tillage. Salinas-Garcia et al. (1997) reported that a decrease in tillage increased SOM, microbial biomass C, inorganic N, and labile C and N pools compared to tilled systems in a long-term quadrennial corn-cotton (Gossypium hirsutum) rotation on a sandy-clay-loam soil in Texas. Furthermore, West and Post (2002) showed that among 67 non-flooded, long-term studies of various soil textures in countries throughout the world, the average soil C sequestration rate was 57 ± 14 g C m-2 yr-1 on land converted from CT to NT systems, with the exclusion of wheat-fallow systems. West and Post (2002) also estimated that C sequestration reaches a maximum between 5 and 10 years after conversion from CT to NT, and after 15 to 20 years the soil reaches a greater equilibrium C concentration.
In a study evaluating a wheat-soybean double-cropping system on a silt-loam soil in east-central eastern Arkansas, SOC content was greater under NT in the top 10 cm than that under CT after two years of continuous cultivation (Brye et al., 2006a) and C lost as CO2 from soil respiration was 38% greater from CT than from NT (Brye et al., 2006b). Reicosky and Lindstrom (1993) attributed the large initial rate of soil surface CO2 flux after tillage to the release of CO2 in newly exposed soil pores and from dissolution or direct oxidation of C substrates, which further demonstrates the loss of C through increased decomposition rates as a result of aeration from tillage. Furthermore, SOM is made up of approximately 5% N, which is mineralized into ammonium (NH4+) during the decomposition process. Mineralized N is susceptible to removal from or translocation within the soil after nitrification through the leaching of nitrate (NO3-) and through gaseous losses during denitrification (Havlin et al., 2005; Schlesinger, 1997).
The reduction of tillage intensity by switching from CT to NT has been widely recognized as management practice that increases the amount of C storage in soils (Lal and Kimble, 1997; Doa, 1998; Kern and Johnson, 1993; Dick et al.,1998) and influences N cycling (Shaffer and Ma, 2001) in the near-surface soil. McCarty et al. (1998) reported increased SOC (38%), microbial biomass C (33%), TN (30%), and microbial biomass N (87%) concentrations in the top 2.5 cm of a silt-loam soil three years after the transition from CT to NT on a continuous corn rotation in the United States, whereas SOC (7%), microbial biomass C (15%), TN (6%), and microbial biomass N (35%) concentrations in the 12.5 to 20 cm depth decreased. An 18-year study of a rice-wheat rotation on a clay-loam soil in China also showed greater SOC, TN, and microbial biomass C and N concentrations in the top 5 cm under NT compared with CT, whereas SOC and TN concentrations were greater in the 5- to 10-cm and 10- to 20-cm depths under CT compared with NT (Xu et al., 2007). The results of previous studies suggest the elimination of tillage greatly influences the stratification of SOC and TN in the near-surface soil layers, whereas there are greater quantities of less-decomposed residue in the upper-most soil layers under NT and that the SOC and TN contents decrease with depth.
In contrast, SOC and TN contents are commonly unstratified and similar throughout the plow layer under CT because the mechanical mixing action of tillage distributes residue more evenly. Tillage also allows for the incorporation of SOM deeper into the soil by mixing plant residue and microbial biomass that usually remains in the upper-most layers under undisturbed conditions. This mixing action in the plow layer can result in greater SOC and TN contents in soil depths immediately below the plow depth under CT than that under NT due to the placement of the SOM near the bottom of the plow layer under full-inversion tillage (Angers and Eriksen-Hamel, 2008).
3.3. Fertility regime effects on SOC and TN
In contrast to that hypothesized, SOC and TN contents in the top 10 cm did not differ between fertility regimes imposed in the study (P > 0.05; Table 5). Fertilization of the soil has been well documented as being directly correlated to the quantity of biomass produced, which in turn is directly correlated with the amount of crop residues that are returned to the soil to become SOM, thus contributing to the SOC and TN pools (Follett, 2001). However, in this study the differences among optimal and sub-optimal fertility treatments (Table 2) were likely not great enough to significantly affect SOC and TN contents even after 11 years of consistent management. The lack of fertility treatment differences in SOC and TN contents between optimal and sub-optimal fertility directly correspond to the lack of differences in SOM contents that were also observed in this study, when averaged across all other treatment factors (P > 0.05; Motschenbacher et al., 2012). However, the lack of SOC and TN content differences under optimal and sub-optimal fertility do not mean that soil fertilizer treatments failed to increase the overall input of crop residues added to the soil when compared to the quantity that would be added upon the elimination of N-P-K treatments. For the purposes of this, only the effects of commonly recommended fertilizer rates provided to producers in the Mississippi Delta area of eastern Arkansas were evaluated (Table 2; Espinoza et al., 2007). Therefore, the design of this study did not include a control treatment in which no fertilizer was applied, as that would not be a common recommendation for field-crop production in the geographic study area.
Furthermore, there is a chance that differences in the fertility treatments over time might have existed if soil of a greater depth interval was compared. Electrical conductivity (EC) values evaluated in Motschenbacher et al. (2012) decreased substantially over the 11-year time period evaluated, which suggests that nutrient leaching beyond the top 10 cm occurred from the infiltration and movement of irrigation water. Therefore, it is reasonable to assume that some of the SOC and TN could have also leached further into the profile with the irrigation water. Therefore, differences between fertilizer treatments might have been too small to be significant in analyses from the top 10 cm, but lower soil depths could potentially show differences related to imposed fertility regimes.
Based on past studies, it can be assumed that both fertilization treatments allowed a greater quantity of above-ground biomass to be returned to the soil than would have been returned without fertilization. Halvorson et al. (2002) reported that N fertilization increased the quantity of crop residue returned to the soil in the top 30 cm of a loam soil after 12 years in two dryland cropping systems in North Dakota. The dryland cropping systems used in the study included spring wheat-winter wheat-sunflower (Helianthus annuus L.) and spring wheat-fallow rotations under different tillage treatments (Halvorson et al., 2002). Clapp et al. (2000) had similar findings in a 13-year study in the 15- to 30-cm depth of a silt-loam soil in Minnesota, which showed that adding N fertilizer to a corn cropping system increased SOC content when residues were returned to the soil in NT systems. On average, soil fertility management practices are estimated to add roughly 50 to 150 kg ha-1 of SOC to the soil every year, depending on the cropping system (Lal et al., 1998).
In the United States, most of the rice cultivars grown require 135 to 200 kg ha-1 of N fertilizer to produce profitable grain yields (Norman et al., 2003). Shen et al. (2007) indicated that chemical fertilizer treatments produced a net gain of 16 to 18 g SOC kg soil-1 in rice-wheat agroecosystems in China when compared to untreated rice-wheat agroecosystems. In an 18-year study of a rice-wheat rotation in China, Xu et al. (2007) reported greater SOC and TN concentration increases in the top 10 cm when a combination of organic and inorganic N-P-K fertilization treatments were applied to a clay-loam soil than with no fertilization. Furthermore, Pampolino et al. (2008) reported that cropping systems delivering two to three rice crops per year on silty-clay or clay soils in the Philippines had greater SOC and TN concentrations in the top 20 cm with the application of N-K, N-P and N-P-K fertilization than in areas with no fertilization after 17 to 21 years of continuous production.
3.4. Crop rotation effects on SOC and TN
As hypothesized, SOC (P < 0.001) and TN (P = 0.003) contents (kg m-2) in the top 10 cm were affected by crop rotation and time, when averaged across tillage treatments and fertility regimes (Table 5). The SOC content in rotations that included winter wheat [i.e., R(W) and R(W)S(W)] increased more than 30% for a sequestration rate of 0.028 kg-1 SOC m-2 yr-1 and the continuous rotation increased 16% for a sequestration rate of 0.014 kg-1 SOC m-2 yr-1 from 1999 to 2010, whereas SOC contents in the RS, RC, and RCS rotations did not differ over the 11-year time period (Figure 1A). Likewise, TN contents increased 36 to 46% in the R(W) rotation for a sequestration rate of 0.003 kg-1 TN m-2 yr-1 and in the R(W)S(W) rotation for a sequestration rate of 0.004 kg-1 TN m-2 yr-1 (Figure 1B). However, the RS rotation increased 19% for a sequestration rate of 0.002 kg-1 TN m-2 yr-1 from 1999 to 2010, whereas the TN contents in R, RC, and RCS rotations did not differ over time (Figure 1B). The greater increase of SOC and TN over time in rotations with wheat could be partially due to greater quantities of annual biomass from the double-cropped rotations, as opposed to rotations that were fallow in the winter, and partially due to the presence of wheat in the ground during sampling. The presence of the wheat crop suggests there were greater concentrations of fresh root biomass and increased microbial activity in the near-surface soil compared to rotations that were fallow during the winter.
The increases in SOC and TN correspond to similar observed differences in SOM among rotations and increases in SOM content over time. Soil organic matter content increased 14% from 1999 (2.58 kg m-2) to 2010 (2.95 kg m-2), when averaged across all tillage, fertility and rotation treatment combinations, and SOM content was 5 to 13% greater in R(W) (3.01 kg m-2) than in all other crop rotations (2.67 to 2.78 kg m-2), when averaged across tillage, fertility and time (Motschenbacher et al., 2012). However, SOC contents only increased in the R(W), R(W)S(W), and R rotations and TN contents only increased in the R(W), R(W)S(W), and RS rotations over the 11-year period, whereas SOM content changes over time were unaffected by individual crop rotations (Motschenbacher et al., 2012).
Increasing the amount of SOC, and associated TN, in the soil requires the addition of enough crop residue to exceed the losses from SOM decomposition, erosion and leaching (Follett, 2001). This can be accomplished by using crop rotation systems that can influence the volume, distribution and turnover of the active and passive pools of SOC (Franzluebbers et al., 1994). Examining each year separately and averaged across tillage and fertility regimes, SOC content in the RCS (1.04 kg m-2) rotation was 14% greater than that in the R(W)S(W) (0.91 kg m-2) rotation at the beginning of the study in 1999, while SOC contents in all other rotations did not differ (Figure 1A). For TN content, there were no differences among crop rotations in 1999 (Figure 1B). However, after 11 years of continuous management, the R(W) (1.32 kg m-2) and R(W)S(W) (1.22 kg m-2) rotations had 15 to 28% greater SOC contents than rotations that included corn [i.e. RC (1.03 kg m-2) and RCS (1.06 kg m-2); Figure 1A]. Furthermore, the R(W) rotation had 15 to 28% greater SOC content in 2010 than that in the R, RS, RC, and RCS rotations (1.03 to 1.15 kg m-2), which did not differ between one another (Figure 1A). In 2010, TN content was 14 to 27% greater in the R(W) (0.14 kg m-2) and R(W)S(W) (0.13 kg m-2) rotations than that in any of the other crop rotations (0.11 to 0.12 kg m-2), whereas TN content among the R, RS, RC, and RCS rotations in 2010 did not differ (Figure 1B). Greater TN contents in winter-wheat rotations [i.e., R(W) and R(W)S(W)] compared to the R, RS, RC, and RCS rotations could partially be due to the timing of the last fertilizer-N application prior to the 2010 sampling date in mid-March. The R(W) and R(W)S(W) rotations received N fertilization at the beginning of March 2009 for the winter-wheat crop, whereas the last application of N fertilizer was in the previous spring (i.e., Spring 2009) for all other crop rotations (Table 2).
Dick et al. (1998) concluded that crop rotation and cover crops are an effective way to facilitate C sequestration, especially when combined with NT and optimal fertilization. After evaluating 67 long-term agricultural studies, West and Post (2002) estimated that enhancing the rotation complexity, including changing from monoculture to continuous rotation cropping, crop-fallow to continuous monoculture or rotation cropping, or increasing the number of crops in a rotation system, can sequester an average of 0.02 ± 0.01 kg C m-2 yr-1 in the top 30 cm of dryland systems. However, these results excluded the change from continuous corn to corn-soybean, which may not lead to a significant change in SOC (West and Post, 2002). The rate reported in West and Post (2002) is comparable to the SOC sequestration rate of 0.03 kg-1 m-2 yr-1 in the top 10 cm for rotations which included winter wheat [i.e., R(W) and R(W)S(W)] in this study compared to continuous rice (0.01 kg-1 m-2 yr-1) and other rotations, which did not significantly sequester SOC over time.
In this study, crop rotation appeared to be a major contributor to the quantity of SOC present in the top 10 cm. Rice and corn are two high-residue-producing crops that are capable of producing 6.5 Mg ha-1 (rice) to 8.0 Mg ha-1 (corn) of above-ground dry matter per crop produced under adequate fertilization, whereas soybean is only capable of producing around 2.2 Mg ha-1 of above-ground dry matter during a cropping season (USDA-NASS, 2012). The above-ground biomass quantities produced annually can also be increased by double-cropping a system with wheat (West and Post, 2002), which is capable of producing an additional 3.3 Mg dry matter ha-1 per year (USDA-NASS, 2012), as opposed to keeping the rotation fallow for the winter. For this study, rotations that produced rice and wheat during a year [i.e., R(W) and R(W)S(W)] were capable of producing 9.8 Mg dry matter ha-1 per year, and during the years soybean and wheat were grown, the R(W)S(W) rotation produced roughly 5.5 Mg dry matter ha-1 per year (USDA-NASS, 2012). Therefore, a greater SOC content in the R(W) rotation after 11 years of rotation management was expected due to the consistent input of at least 23% more above-ground dry matter added annually than that from the RS, RC, and RCS rotations, and the R(W)S(W) rotation during the years soybean and wheat were produced (Figure 1A).
In addition to large above-ground biomass inputs, rice is a unique crop to include in a crop rotation because unlike all other row crops, rice is grown under nearly to completely saturated soil conditions (Norman et al., 2003), which slows the rate of SOM decomposition and affects N cycling dynamics. Thus, flooding the soil during the period rice is produced greatly affects SOM, and consequently SOC, accumulation in the soil, which is then susceptible to rapid decomposition when the field is drained for harvest and during the fallow period. Although crop rotations involving high-residue-producing crops like corn typically facilitate substantial increases in SOC, the anaerobic conditions under which rice is grown also affect the breakdown of crop residues in the soil. Witt et al. (2000) demonstrated that soils continuously cropped with flooded rice had 11 to 12% more C sequestration and 5 to 12% more N accumulation than soils which supported a dry-season, maize-flooded-rice rotation. The results were attributed to a 33 to 41% increase in the estimated amount of mineralized-C and decreased input of N from biological N fixation during the dry-season, maize-cropping period (Witt et al., 2000). Aulakh et al. (2001) reported that C sequestration in a sandy-loam soil in India was 69 to 107% greater when wheat residues were added to flooded rice. Furthermore, Aulakh et al. (2001) also showed that adding wheat residue immobilized mineral-N during the fallow period, but the amount of mineral-N increased rapidly at the start of the flooded rice season when green manure or urea-N were applied.
The increase in TN in the RS rotation over time in this study can be explained by the increased frequency of an N-fixing legume crop in the rotation, whereas the R, RC, and RCS did not result in increased TN over time (Figure 1B). This is because the Rhizobia bacteria present in the nodules on legume roots are able to absorb dinitrogen gas (N2) from the air and convert it to NH4+, which can either be released into the soil or taken up by the plant and returned to the soil as residue-N at a later time (Havlin et al., 2005). The R(W)S(W) rotation also had a biennial rotation with soybean, but it is unclear whether the increase in TN content over time was a result of having a leguminous crop present in the rotation or related to the application of fertilizer-N in the fall. The R(W)S(W) rotation had a similar TN content as the R(W) rotation in 2010, which also had fertilizer-N applied in the fall, but did not include a leguminous crop (Figure 1B). These results are similar to those of Granatstein et al. (1987) from a 10-year study of winter wheat-legume rotations using different tillage regimes. They reported the greatest increase in TN in the top 5 cm was in rotations with greater frequencies of N-fixing legume crops in the rotation.
3.5. Partitioning of SOC and TN within SOM
Similar to SOC and TN contents, the fraction of SOM made up by SOC in the top 10 cm differed between tillage treatments (P = 0.007), when averaged across fertility, rotation and time. Also similar to SOC and TN contents, the fraction of SOM made up by SOC (P = 0.047) and TN (P = 0.037) differed by rotation and time, when averaged across tillage and fertility regimes, but SOC and TN fractions of SOM were unaffected by fertility regime (P > 0.05; Table 5).
The fraction of SOM made up of SOC was 5% greater under NT (39.7%) than that under CT (37.7%). Furthermore, the fraction of SOM made up of SOC was roughly 1.4% greater in the RS rotation in 1999 (40.7%) and R(W)S(W) rotation in 2010 (40.4%) than the R(W)S(W) rotation in 1999 (35.6%), whereas there were no differences in the SOC fraction of SOM among any other rotation-time combinations. Therefore, the fraction of SOM made up of SOC increased 13% over 11 years in the R(W)S(W) rotation, but the SOC fraction of SOM did not change over time in any other rotation evaluated. The fraction of SOM made up of TN was 2% greater in the R(W)S(W) rotation in 2010 (4.4%) than in the R, RC, R(W), R(W)S(W), and RCS rotations in 1999 and the R and RC rotations in 2010 (both years ranged from 3.7 to 3.9%). Similar to SOC, the TN fraction of SOM in the R(W)S(W) increased 21% from 1999 (3.6%) to 2010 (4.4%).
Although there were differences in the SOC and TN fractions of SOM, these differences only ranged from 1 to 5%. With the exception of the RS rotation in 1999, which had a greater fraction of SOC in SOM, only the R(W)S(W)/2010 treatment combination had greater SOC and TN fractions of SOM than a majority of the other rotation-time combinations. Furthermore, the R, RC, R(W), R(W)S(W), and RCS rotations in 1999 and the R, RS, RC, R(W), and RCS rotations in 2010 did not differ in their SOC and TN fractions of SOM. Therefore, there is a possibility that the greater SOC and TN fractions of SOM in R(W)S(W) in 2010 could be an isolated sampling discrepancy instead of a true rotation effect over time.
3.6. Soil C:N ratio
The soil C:N ratio in the top 10 cm was unaffected by tillage, fertility, rotation or time (P > 0.05; Table 5). Carbon:N ratios ranged from 8.1 to 14.0 in both 1999 and 2010. The C:N ratio of the soil is important because N is essential to microbial growth and reproduction, thus the microorganisms must obtain N either from the material being decomposed or an external source (i.e., inorganic N fertilizer compounds in the soil) in order to continue consuming SOM (Wolf and Snyder, 2003). If the SOM being decomposed has a large C:N ratio, then soil microbes either have to acquire N from the surrounding soil or decrease the rate of decomposition (Havlin, 2005). A common rule of thumb is that a C:N ratio of 20 to 30 in crop residues maintains an equilibrium mineral-N level in the soil, whereas any C:N ratio above 30 results in a net loss of NH4+- and NO3--N, and a C:N ratio below 20 results in a net gain of NH4+- and NO3--N (Stevenson and Cole, 1999). However, in this study there were no differences in soil C:N ratios among treatment combinations evaluated.
3.7. Century model SOC and TN contents
The linear relationship between Century-modeled and measured SOC (P = 0.010) and soil TN (P = 0.024) after 11 years of consistent management was significant, but there were relatively weak predictive relationships between modeled and measured SOC (r2 = 0.14; Figure 3A) and TN (r2 = 0.10; Figure 3 B) contents. For the analyses of SOC and soil TN contents, all modeled estimations for the 24 tillage-fertility-rotation treatment combinations were evaluated against the means of direct observation from 2010. The mean values of the direct observations were used to get a direct comparison between modeled and measured SOC and soil TN contents.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
Rotation
\n\t\t\t
SOC (kg m-2)
\n\t\t\t
TN (kg m-2)
\n\t\t
\n\t\t
\n\t\t\t
Measured
\n\t\t\t
Modeled
\n\t\t\t
Measured
\n\t\t\t
Modeled
\n\t\t
\n\t\t
\n\t\t\t
CT
\n\t\t\t
NT
\n\t\t\t
CT
\n\t\t\t
NT
\n\t\t\t
CT
\n\t\t\t
NT
\n\t\t\t
CT
\n\t\t\t
NT
\n\t\t
\n\t\t
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t\t
O
\n\t\t\t
SO
\n\t\t
\n\t\t
\n\t\t\t
R
\n\t\t\t
1.11
\n\t\t\t
0.97
\n\t\t\t
1.28
\n\t\t\t
1.22
\n\t\t\t
1.72
\n\t\t\t
1.67
\n\t\t\t
1.95
\n\t\t\t
1.67
\n\t\t\t
0.12
\n\t\t\t
0.12
\n\t\t\t
0.11
\n\t\t\t
0.09
\n\t\t\t
0.15
\n\t\t\t
0.13
\n\t\t\t
0.17
\n\t\t\t
0.14
\n\t\t
\n\t\t
\n\t\t\t
RS
\n\t\t\t
0.96
\n\t\t\t
0.93
\n\t\t\t
1.24
\n\t\t\t
1.26
\n\t\t\t
1.42
\n\t\t\t
1.38
\n\t\t\t
1.38
\n\t\t\t
1.34
\n\t\t\t
0.14
\n\t\t\t
0.13
\n\t\t\t
0.10
\n\t\t\t
0.10
\n\t\t\t
0.12
\n\t\t\t
0.11
\n\t\t\t
0.12
\n\t\t\t
0.11
\n\t\t
\n\t\t
\n\t\t\t
RC
\n\t\t\t
0.84
\n\t\t\t
0.90
\n\t\t\t
1.19
\n\t\t\t
1.18
\n\t\t\t
1.94
\n\t\t\t
1.86
\n\t\t\t
1.95
\n\t\t\t
1.84
\n\t\t\t
0.13
\n\t\t\t
0.12
\n\t\t\t
0.09
\n\t\t\t
0.10
\n\t\t\t
0.17
\n\t\t\t
0.15
\n\t\t\t
0.17
\n\t\t\t
0.15
\n\t\t
\n\t\t
\n\t\t\t
R(W)
\n\t\t\t
1.20
\n\t\t\t
1.21
\n\t\t\t
1.45
\n\t\t\t
1.43
\n\t\t\t
1.38
\n\t\t\t
1.38
\n\t\t\t
1.43
\n\t\t\t
1.42
\n\t\t\t
0.15
\n\t\t\t
0.15
\n\t\t\t
0.13
\n\t\t\t
0.12
\n\t\t\t
0.12
\n\t\t\t
0.12
\n\t\t\t
0.13
\n\t\t\t
0.12
\n\t\t
\n\t\t
\n\t\t\t
R(W)S(W)
\n\t\t\t
1.08
\n\t\t\t
1.08
\n\t\t\t
1.49
\n\t\t\t
1.22
\n\t\t\t
1.46
\n\t\t\t
1.41
\n\t\t\t
1.37
\n\t\t\t
1.37
\n\t\t\t
0.17
\n\t\t\t
0.13
\n\t\t\t
0.12
\n\t\t\t
0.12
\n\t\t\t
0.13
\n\t\t\t
0.13
\n\t\t\t
0.13
\n\t\t\t
0.12
\n\t\t
\n\t\t
\n\t\t\t
RCS
\n\t\t\t
1.01
\n\t\t\t
1.06
\n\t\t\t
1.10
\n\t\t\t
1.07
\n\t\t\t
1.74
\n\t\t\t
1.66
\n\t\t\t
1.72
\n\t\t\t
1.62
\n\t\t\t
0.12
\n\t\t\t
0.12
\n\t\t\t
0.11
\n\t\t\t
0.10
\n\t\t\t
0.15
\n\t\t\t
0.13
\n\t\t\t
0.15
\n\t\t\t
0.13
\n\t\t
\n\t
Table 6.
Measured and Century-estimated soil organic carbon (SOC) and total nitrogen (TN) contents under different tillage [conventional tillage (CT) and no-tillage (NT)], fertility [optimal (O) and sub-optimal (SO)] and crop rotation [with soybean (S), corn (C), and/or wheat (W)] treatment combinations after an 11-yr study period (1999 to 2010). The study site was located at the Rice Research and Extension Center near Stuttgart, AR on a silt-loam soil. Values presented are the measured and model predictions from the 2010 sampling period. Crops in parentheses were grown during the winter.
Figure 3.
Century-modeled verses measured soil organic carbon (SOC) [A] and total nitrogen (TN) [B] contents in the top 10 cm after 11 years of management for 24 different tillage-fertility-rotation treatment combinations.
A numerical evaluation of Century-estimated values and direct observations over the 11-year study period (1999 to 2010) indicated that the Century model estimated greater SOC (Figure 4A) and TN (Figure 4B) contents than that measured in 2010 (Table 6). Century-modeled SOC contents were numerically greater than measured SOC contents by 6% (0.08 kg SOC m-2) to 56% (1.10 kg SOC m-2) in all tillage-fertility-rotation treatment combinations except for the NT/optimal/R(W), NT/sub-optimal/R(W), and the NT/optimal/R(W)S(W) treatment combinations, which were slightly underestimated by 1% (0.01 kg SOC m-2) to 8% (0.12 kg SOC m-2; Table 6).
Figure 4.
Century-modeled and measured soil organic carbon (SOC) [A] and total nitrogen (TN) [B] contents in the top 10 cm over time (1999 and 2010) for 24 different tillage-fertility-rotation treatment combinations. The regression equations on each graph represent the average modeled and measured SOC and TN contents across all treatment combinations over time.
On average, Century-modeled SOC contents overestimated SOC by 26%. Estimated SOC in 8 of the 24 treatment combinations differed less than 14% from directly measured SOC in 2010, while the other 16 treatment combinations exceeded a 23% difference from measured SOC (Table 6). It appears that this overestimation by Century would increase into the future if management practices continued into the future (Figure 3A). The overestimation of SOC during a longer time period in this study is similar to modeling results reported by Bhattacharyya et al. (2007) in a jute (Cochorus capsularis L.)-rice-wheat rotation over a 30-year period. Bhattacharyya et al. (2007) reported that SOC was generally overestimated by 15% in the top 20 cm when modeled in Century. Therefore, if the model were to be used for more accurate prediction in the rice-based rotations, such as those used in this study, a more in-depth evaluation and further adjustments of the Century modeling environment for flood-irrigation would be necessary.
Similar to modeled SOC, Century-modeled soil TN contents were also generally greater than the direct measurements after 11 years of management. Soil TN was greater by 1% (1.0 g SOC m-2) to 45% (78 g SOC m-2) in most treatment combinations except in the NT/optimal/R(W), CT/optimal/RS, CT/optimal/R(W), CT/optimal/R(W)S(W), CT/sub-optimal/RS, CT/sub-optimal/R(W), and CT/sub-optimal/R(W)S(W), which were underestimated by 1% (< 0.01 kg TN m-2) to 26% (0.03 kg TN m-2; Table 6). On average, the modeled soil TN content was overestimated by 10% across all tillage-fertility-rotation treatment combinations, which was a more accurate value than that of the average estimated SOC content over time. Century-modeled soil TN in 14 of the 24 treatment combinations had a range of less than 19% different from measured observations, whereas the other 10 treatment combinations exceeded a 23% difference from measured observations (Table 6). Similar to the pattern of modeled SOC, it appears that this overestimation of soil TN by Century would also continue to increase slightly over time if management practices continued into the future (Figure 3B).
Based on numeric values for modeled estimations and direct observations, it appears that Century can predict SOC and TN contents more accurately for certain tillage-fertility-rotation treatment combinations compared to other modeled treatment combinations (Table 6). The closest estimations of SOC to direct observations were for treatment combinations that included rotations with winter wheat [i.e., R(W) and R(W)S(W)] during the study period, and the closest estimations for soil TN over time occurred in treatment combinations that included the R(W)S(W) rotation (Table 6). The least accurate estimations of SOC compared to direct observations were for treatment combinations that included rotations with corn (i.e., RC and RCS), and the closest estimations for soil TN were in treatment combinations that included the R(W) rotation (Table 6). The predicted estimates of SOC and soil TN contents for rotations that included wheat could be a result of overestimating or underestimating the inputs from the winter wheat crop, which was in the ground during the time of soil sampling. The overestimation of SOC contents for rotations with corn could be a result of reduced yields at the study site compared to common yield values produced in the local geographic area, which is the yield value simulated in the Century model. This could be a result of many factors, but the more likely scenario is that the size of the research plot resulted in essentially an edge effect that would not be present in larger production fields.
The inaccuracies associated with the modeling results suggest that a few input parameters could be better adjusted in the Century model to more accurately predict SOC and TN cycling in rice-based crop rotations that are flooded for a majority of the growing season. Perhaps incorporation of the measured plant nutrient composition of the specific crop varieties grown during the study period and specific yields in each research area sampled over the 11-year period would improve the accuracy of specific input variables. Furthermore, soil sampling to a greater soil depth for more direct comparison to Century-modeled results might create not only a greater understanding of soil cycling in the near-surface soil, but also could help improve the overall accuracy of the model.
4. Summary and conclusions
This study demonstrated SOC and soil TN contents in the top 10 cm were affected by tillage, rotation and/or time after 11 years of consistent management. As hypothesized, soil TN contents increased over time under NT, but SOC contents did not differ under either tillage treatment (i.e., NT and CT) over the 11-year study period. Furthermore, soil under high-residue-producing rotations double-cropped with winter wheat [i.e. R(W) and R(W)S(W)] had greater increases in both SOC and TN contents over time compared to all other crop rotations. The only high-residue-producing, mono-cropped rotation with greater SOC over time was continuous rice, whereas SOC contents in all other crop rotations (i.e., RS, RC, and RCS) did not differ during the 11-year study period. Similar to the double-cropped rotations, the RS rotation also had an increase of soil TN over time. However, other crop rotations (i.e., R, RC, and RCS) did not differ in soil TN contents over time. In contrast to that hypothesized, fertility treatments had no effect on SOC and TN contents. The primary difference in SOC and TN contents among treatment combinations included the presence or absence of a winter wheat crop.
The Century model is a predictive tool for future environmental nutrient cycling estimations. Results from this study suggest that Century can be used to predict general trends in SOC and TN cycling in rice-based crop rotations over time, but further adjustment of the model is needed to increase accuracy. The direct measurements and the modeled estimations from this study are important because there has not been a great amount of research conducted on SOC and TN storage in dry-seeded, delayed-flooded rice production systems. A majority of C and N research in agricultural systems has either been conducted on non-flooded crops or in paddy-grown rice. Relatively few studies have actually evaluated long-term SOC and TN storage using dry-seeded, delayed-flood rice production practices commonly used in the Unites States.
This study was meant to provide a long-term evaluation of SOC and TN storage in soil used for flood-irrigated, rice-based crop rotations. Because soil moisture conditions have such a large impact on the overall storage of SOC and the cycling of N in the soil, examining crop production systems that contain periods of both aerobic and anaerobic conditions is an important component in obtaining a more accurate global estimate of SOC and TN storage in agricultural production systems. The results obtained from this study can help contribute to the ongoing effort to study the sustainability of rice cropping in the United States by enabling the direct quantification of C and N storage in the soil over time.
Acknowledgments
This study was partially funded by the Arkansas Rice Research and Promotion Board. Field assistance provided by Terry Sells, Daniel McCarty and Tara Moss Clayton is gratefully acknowledged.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/45823.pdf",chapterXML:"https://mts.intechopen.com/source/xml/45823.xml",downloadPdfUrl:"/chapter/pdf-download/45823",previewPdfUrl:"/chapter/pdf-preview/45823",totalDownloads:1773,totalViews:191,totalCrossrefCites:1,totalDimensionsCites:2,totalAltmetricsMentions:0,impactScore:1,impactScorePercentile:70,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"September 18th 2013",dateReviewed:"September 19th 2013",datePrePublished:null,datePublished:"March 12th 2014",dateFinished:"November 5th 2013",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/45823",risUrl:"/chapter/ris/45823",book:{id:"3831",slug:"co2-sequestration-and-valorization"},signatures:"Jill M. Motschenbacher, Kristofor R. Brye, Merle M. Anders, Edward\nE. Gbur, Nathan A. Slaton and Michelle A. Evans-White",authors:[{id:"169375",title:"Dr.",name:"Jill M.",middleName:"M.",surname:"Motschenbacher",fullName:"Jill M. Motschenbacher",slug:"jill-m.-motschenbacher",email:"jmotsche@email.uark.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169376",title:"Dr.",name:"Kristofor",middleName:null,surname:"Brye",fullName:"Kristofor Brye",slug:"kristofor-brye",email:"kbrye@uark.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Arkansas at Fayetteville",institutionURL:null,country:{name:"United States of America"}}},{id:"169377",title:"Dr.",name:"Merle",middleName:null,surname:"Anders",fullName:"Merle Anders",slug:"merle-anders",email:"rrec_manders@futura.net",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169378",title:"Dr.",name:"Edward",middleName:null,surname:"Gbur",fullName:"Edward Gbur",slug:"edward-gbur",email:"egbur@uark.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"170561",title:"Dr.",name:"Nathan A.",middleName:null,surname:"Slaton",fullName:"Nathan A. Slaton",slug:"nathan-a.-slaton",email:"nslaton@uark.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"170562",title:"Dr.",name:"Michelle A.",middleName:null,surname:"Evans-White",fullName:"Michelle A. Evans-White",slug:"michelle-a.-evans-white",email:"mevanswh@uark.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Research objectives and hypotheses",level:"2"},{id:"sec_3",title:"2. Materials and methods",level:"1"},{id:"sec_3_2",title:"2.1. Site description",level:"2"},{id:"sec_4_2",title:"2.2. Experimental design and field treatments",level:"2"},{id:"sec_5_2",title:"2.3. Soil sampling and analyses",level:"2"},{id:"sec_6_2",title:"2.4. Century model simulation",level:"2"},{id:"sec_7_2",title:"2.5. Data analyses",level:"2"},{id:"sec_9",title:"3. Results and discussion",level:"1"},{id:"sec_9_2",title:"3.1. Initial soil properties",level:"2"},{id:"sec_10_2",title:"3.2. Tillage effects on SOC and TN",level:"2"},{id:"sec_11_2",title:"3.3. Fertility regime effects on SOC and TN",level:"2"},{id:"sec_12_2",title:"3.4. Crop rotation effects on SOC and TN",level:"2"},{id:"sec_13_2",title:"3.5. Partitioning of SOC and TN within SOM",level:"2"},{id:"sec_14_2",title:"3.6. Soil C:N ratio",level:"2"},{id:"sec_15_2",title:"3.7. Century model SOC and TN contents",level:"2"},{id:"sec_17",title:"4. Summary and conclusions",level:"1"},{id:"sec_18",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Alvarez, R., and R.S. Lavado. 1998. Climate, organic matter and clay content relationship in the Pampa and Chaco soils, Argentina. Geoderma 83:127-141.'},{id:"B2",body:'Angers, D.A., and N.S. Eriksen-Hamel. 2008. Full-inversion tillage and organic carbon distribution: A meta-analysis. Soil Sci. Soc. J. 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Hons, and J.E. Matocha. 1997. Long-term effects of tillage and fertilization on soil organic matter dynamics. Soil Sci. Soc. Am. J. 61:152-159.'},{id:"B48",body:'Saxton, K.E., and W.J. Rawls. 2006. Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci. Soc. Am. J. 70:1569-1578.'},{id:"B49",body:'Schlesinger, W.H. 1997. Biogeochemistry: An analysis of global change, 2nd ed. Academic Press, San Diego, CA.'},{id:"B50",body:'Seiter, S., and W.R. Horwath. 2004. Strategies for managing soil organic matter to supply plant nutrients. pp. 269-293. In F. Magdoff and R. R. Weil. (eds.) Soil organic matter in sustainable agriculture. CRC Press, Boca Raton, FL.'},{id:"B51",body:'Shaffer, M.J., and L. Ma. 2001. Carbon and nitrogen dynamics in upland soils. pp. 11-26. In M.J. Shaffer, L. Ma, and S. Hansen. (eds.) Modeling carbon and nitrogen dynamics for soil management. CRC Press, Boca Raton, FL.'},{id:"B52",body:'Shen, M.X., L.Z. Yang, Y.M. Yao, D.D. Wu., J. Wang, R. Guo, and S. Yin. 2007. Long-term effects of fertilizer management on crop yields and organic carbon storage of a typical rice-wheat agroecosystem of China. Biol. Fertil. Soils 44:187-200.'},{id:"B53",body:'Shibu, M.E., P.A. Leffelaar, H. Van Keulen, and P.K. Aggarwal. 2006. Quantitative description of soil organic matter dynamics: A review of approaches with reference to rice-based cropping systems. Geoderm 137:1-18.'},{id:"B54",body:'Slaton, N.A. 2001. Rice production handbook. Handbook. MP 192. Univ. of Arkansas Coop. Ext. Serv., Little Rock.'},{id:"B55",body:'Smith, J.L., R.I. Papendick, D.F. Bezdicek, and J.M. Lynch. 1993. Soil organic dynamics and crop residue management. pp. 65-94. In F.B. Metting, Jr. (ed.) Soil microbial ecology. Marcel Dekker, Inc., New York.'},{id:"B56",body:'Southern Region Climate Center (SRCC). 2012. Louisiana State University. Baton Rouge, LA. [online]. Available at http://www.srcc.lsu.edu/stations/index.php?action=metadata&network_station_id=030240 (verified 23 July, 2012).'},{id:"B57",body:'Stevenson, F.J., and M.A. Cole. 1999. Cycles of soil. John Wiley & Sons, Inc., New York, NY.'},{id:"B58",body:'Sundermeiser, A., R. Reeder, and R. Lal. 2005. Soil carbon sequestration – fundamentals. Ohio State University Extension Factsheet [online]. http://ohioline.osu.edu/aex-fact/0510.html (verified 23 July, 2012).'},{id:"B59",body:'United States Army Corps of Engineers (USACE). 2000. Grand prairie area demonstration project: Overview [online]. Available at http://www.mvm.usace.army.mil/grandprairie/overview/default.asp (verified 23 July, 2012).'},{id:"B60",body:'United States Department of Agriculture (USDA) Foreign Agricultural Service. (FAS). 2012. Production, supply and distribution [online]. Available at http://www.fas.usda.gov/psdonline/psdHome.aspx (verified 16 July, 2012).'},{id:"B61",body:'United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS). 2012. Crop Explorer: United States 2011 – area, yield, and production [online]. Available at http://www.nass.usda.gov/QuickStats/PullData_US.jsp (verified 15 July, 2012).'},{id:"B62",body:'United States Department of Agriculture (USDA) National Resources Conservation Service (NRCS). 2008. Web soil survey. Data from survey on November 12, 2008 [online]. Available at http://websoilsurvey.nrcs.usda.gov/app/WebSoilSUrvey.aspx (verified 23 July, 2012).'},{id:"B63",body:'Weil, R.R., and F. Magdoff. 2004. Significance of soil organic matter to soil quality and health. pp. 1-43. In F. Magdoff and R. R. Weil. (ed.) Soil organic matter in sustainable agriculture. CRC Press, Boca Raton, FL.'},{id:"B64",body:'West, T.O., and W.M. Post. 2002. Soil organic carbon sequestration rates by tillage and crop rotation: A global data analysis. Soil Sci. Soc. Am. J. 66:1930-1976.'},{id:"B65",body:'Witt, C., K.G. Cassman, D.C. Olk, U. Biker, S.P. Liboon, M.I. Samson, and J.C.G. Ottow. 2000. Crop rotation and residue management effects on carbon sequestration, nitrogen cycling, and productivity or irrigated rice systems. Plant Soil 225:265-278.'},{id:"B66",body:'Wolf, B., and G.H. Snyder. 2003. Sustainable soils: The place of organic matter in sustainable soils and their productivity. Food Products Press, New York.'},{id:"B67",body:'Xu, Y., W. Chen, and Q. Shen. 2007. Soil organic carbon and nitrogen pools impacted by long-term tillage and fertilization practices. Comm. Soil Sci. Plant Anal. 38:347-357.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Jill M. Motschenbacher",address:"jmotsche@email.uark.edu",affiliation:'
Department of Crop, Soil and Environmental Sciences, University of Arkansas, USA
'},{corresp:null,contributorFullName:"Kristofor R. Brye",address:null,affiliation:'
Department of Crop, Soil and Environmental Sciences, University of Arkansas, USA
'},{corresp:null,contributorFullName:"Merle M. Anders",address:null,affiliation:'
Department of Crop, Soil and Environmental Sciences, University of Arkansas, USA
'},{corresp:null,contributorFullName:"Edward E. Gbur",address:null,affiliation:'
Agricultural Statistics Laboratory, University of Arkansas, USA
'},{corresp:null,contributorFullName:"Nathan A. Slaton",address:null,affiliation:'
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'},{corresp:null,contributorFullName:"Michelle A. Evans-White",address:null,affiliation:'
Department of Biological Sciences, University of Arkansas, USA
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1. Introduction
Hepatocellular carcinoma (HCC) is the fifth most common cancer in males, the seventh in females, and the third leading cause of cancer-related deaths. Each year there are approximately 800,000 fatalities [1, 2, 3]. In developing countries, morbidity and mortality rates are 84% and 83%, respectively [4]. HCC typically occurs in the context of chronic hepatitis B virus (HBV) or hepatitis C virus (HCV) infection, accounting for 85% of all HCC cases globally [3]. Lower risk factors include non-alcoholic fatty liver disease (NAFLD) and chronic alcohol consumption [4].
Tumor evolution is a complex process implying many stages and involving many factors, such as genetic and chromosomal changes. During tumor development, the number, type, extent, and distribution of markers and variants are closely related to the occurrence, progression, invasion, and metastasis of HCC. Therefore, diagnosis and early detection are highly important in management and treatment because it is only possible to cure the disease when the tumor when it is detected at a small size.
Advances in the understanding of tumor biology, combined with the development of molecular methods in looking for new biomarkers in the early detection of the disease, their invasiveness, likelihood of metastasis and recurrence, has led to the discovery and use of several new markers in this disease. In this review, we discuss the results of the studies that we consider the most relevant, and in particular their diagnostic performance for the detection of HCC at an early stage.
2. Embryonic antigen
2.1 Alpha-fetoprotein (AFP)
Alpha-fetoprotein (AFP) is a large serum glycoprotein that is synthesized in the liver that occurs during fetal life is repressed during adulthood [5]. Therefore, AFP levels often diminish rapidly after birth and remain low throughout adulthood. Since AFP was discovered in the serum of HCC patients in 1964 [6], it has been regarded as the most useful serum protein for patients at risk for HCC [7, 8, 9]. However, the sensitivity and specificity of using AFP for early HCC detection are widely variable as elevated AFP levels are also observed in many other cancers [10]. In addition, AFP levels are below the detection limit in small liver tumors, while it can be above the detection limit when the tumor is large, producing an AFP-negative HCC. AFP is considered to have a screening role in HCC but its role is limited since it does not allow to distinguish between cancerous lesions and some other benign liver damage pathologies, hence causing a high proportion of false positives and false negatives. Patients with hepatitis still have high AFP level even without liver tumors. The positive predictive value of AFP for detecting HCC is 70% for people with hepatitis viruses and 94% for those without. Therefore, AFP is more effective in detecting HCC in cases without hepatitis viruses.
According to the 2010 recommendations of the American Association for the Study of Liver Diseases (AASLD) for the diagnosis and treatment of HCC, the effectiveness of AFP as a test to diagnose HCC was lower than expected. AFP is also increased in biliary carcinoma in the liver or metastases from colon cancer. Biliary cancer in the liver is also quite common in cirrhotic patients, although the incidence of this disease is lower than that of HCC. The fact that these two liver cancers are common in cirrhosis makes it necessary to identify accurately the disease. Because AFP may increase in many cases other than HCC, it is no longer recommended to be used in Europe and the Americas for its diagnosis. The current diagnosis of HCC is based on imaging and histopathology [11]. The Asia Pacific Association for the Study of the Liver (APASL) also stated that AFP alone is not recommended to diagnose HCC. When combined with other methods, the diagnosis threshold of AFP was 200 ng/ml (Table 1) [12].
AFP exists as three glycoforms, each of them having a different binding capability to lectin Lens culinaris agglutinin (LCA): AFP-L1 (non-binding fraction), AFP-L2 (weak binding fraction), and AFP-L3 (binding fraction). AFP-L1 is increased in early stages of liver disease progression, AFP-L2 has an intermediate affinity for lectin and is a major component during pregnancy because it is derived from the yolk sacs. AFP-L3 is only elevated in patients with HCC because it is solely produced by cancer cells, making it a specific biomarker for HCC [13, 14]. However, the drawback of AFP-L3 is that it can only be detected if AFP levels are >20 ng/ml.
AFP-L3 immunoassay sensitivity has been further improved by higher sensitivity analytical methods and advanced microfluidics-based separation science [15]. “Highly sensitive AFP-L3” (hs-AFP-L3) obtained significantly better results than conventional AFP-L3, even when patients had a single and/or small HCC tumor. The sensitivity and specificity of hs-AFP-L3 were 57% and 63.5%, and 40.4% and 81.1% for conventional AFP-L3 [16]. These results make hs-AFP-L3 a valuable biomarker for detecting early-stage HCC (Table 1).
3. Proteantigen
3.1 Glypican-3 (GPC3)
Glypican-3 (GPC3) is a member of the glycican family of heparan sulfate proteoglycans linked to cell membranes by glycosyl-phosphatidylinositol [17]. It is a fetal glycoprotein that exists on the cell surface to help regulate cell growth during pregnancy. GPC3 is associated with the malignant proliferation of cells but there are currently no studies to prove its association with healthy people and benign conditions. Quite a number of studies have proven the overexpression of GPC3 in malignant diseases such as breast cancer, ovarian cancer, or lung adenocarcinoma [18, 19]. With HCC, its expression is increased through the autocrine/paracrine regulator in conjunction with the Wnt signaling pathway [20]. Some studies have concluded that the sensitivity of GPC3 in HCC diagnosis ranges from 40 to 53%, which is interesting considering that in about 33% of cases, both AFP and DCP serum were within normal limits [21, 22]. GPC3 has been detected in HCC tumor but not in benign liver tissues, so it is likely a marker for early detection of HCC [23]. GPC3 expression does not depend on some clinical features such as tumor size, GPC3 sensitivity in early HCC diagnosis (size <3 cm) was 56% [23]. In a meta-analysis, the sensitivity and specificity of serum GPC3 to diagnose HCC were 55.2% and 84.2%, respectively [24]. A smaller analysis of the early-stage HCC group (BCLC 0 and A or TNM phase I) showed a sensitivity and specificity of GPC3 of 55.1% and 97%, respectively, which are higher than the those obtained with the AFP serum in the same study, that were 34.7% and 87.6%. Combining GPC3 and AFP increased the sensitivity to 76% for early-stage tumors [24]. In short, GPC3 might be a marker for HCC, especially in the early stages, but GPC3 expression also increases in some other malignancies, so the specificity for HCC diagnosis is not high. It can still increase diagnostic sensitivity when combined with other valuable serum markers (Table 1).
3.2 Heat shock protein 70 (HSP70)
Heat shock protein (HSP) is an antiapoptotic protein whose overexpression allows cell survival. It protects cells and stimulates the reparation of tissue damage. A study indicated the positive rate of HSP70 and HSP27 in HCC tissues at 56.3% and 61.9%, respectively [25]. There was a correlation between the stained intensity of HSP70 and tumor size, portal vein invasion, and tumor stage, while HSP27 was only associated with hepatitis B virus (HBV) related HCC. In addition, the overexpression of HSP70 and HSP27 in HCC tumors may lead to increased tumor growth and metastasis (Table 1) [26].
Data suggest that HSP70 can be used as a prognosis indicator for HCC. Its expression was detected in 282 of 392 HCC cases (71.9%), compared to 14 of 115 non-neoplastic liver tissues [27]. The sensitivity and specificity in the detection of HCC have been measured at 57.5% and 85%, respectively [28]. The expression of HSP70 is also correlated with the differentiation and apoptosis of tumor cells. HSP70 promotes cancer cell growth by stabilizing cyclin D1 and suppressing apoptosis in cancer cells by inhibiting the p53 pathway [29, 30]. This information makes HSP70 and HSP27 potential markers of HCC that should be further investigated.
3.3 Golgi protein 73 (GP73)
Golgi protein 73 (GP73) is a type II Golgi-specific membrane protein, which is normally expressed in epithelial cells of many human tissue types, but not hepatocytes [31]. A study showed that serum GP73 levels of patients with HBV-related HCC were significantly increased compared to patients with HBV and healthy adults [32, 33]. The sensitivity of diagnosis of HCC (76.9%) was significantly higher than that of AFP (48.6%), suggesting that GP73 can be an effective serum biomarker for the diagnosis of HCC [34]. The combination of GP73 and AFP further increased the sensitivity and specificity to 89.2% and 85.2%, respectively, with an AUC of 0.96 (Table 1).
FC-GP73 further improves the HCC diagnostic performance made with GP73 from 65 to 90 to 90–100%, respectively. Even when GP73 is at a very low level or absent, FC-GP73 is still detectable [35]. These are encouraging data but there is still a lot of work to be done regarding the correlation between GP73 and tumor size, stage, recurrence, and prognosis before this marker can be used.
3.4 Squamous cell carcinoma antigen (SCCA)
Squamous cell carcinoma antigen (SCCA) belongs to the high molecular weight protease inhibitor family found in the squamous and granular layers of the normal squamous epithelium. It consists of two different isomers, encoded by two highly homologous genes: SCCA1 being neutral, and SCCA2 acid [36]. SCCA2 has been detected in many malignancies such as cervical, lung, head and neck carcinoma, and it has been used as a valuable diagnostic biomarker in clinical practice [37].
Giannelli et al. showed that SCCA expression was higher in the HCC group than in the cirrhotic group. The sensitivity of SCCA is 84.2%, but the specificity is low at 48.9%. In the small tumor group (≤ 3 cm) the sensitivity and specificity of SCCA were 56.1% and 74.9% with a cut-off of 3.2 ng/ml. In their study of SCCA expression in cells, using immunohistochemistry, Guido et al. demonstrated that SCCA expression in cancerous tissues and dysplasia nodules was much higher than that of newly formed nodules in early HCC diagnosis [38]. SCCA was highly sensitive, but its specificity was quite low. Its expression in early HCC tissue and in dysplasia nodules makes SCCA a valuable complementary marker for HCC diagnosis. An alternative biomarker is an immune complex between SCCA and IgM, SCCA-IgM, whose expression increases in early HCC. The immune complex SCCA-IgM has a higher diagnostic performance than the free SCCA and is also more relevant since it is not found in the serum of healthy people. However, the detection rate of SCCA-IgM immune complex is 18% for chronic hepatitis, 26% for cirrhosis and 70% for HCC [39]. Its sensitivity and specificity for HCC diagnosis are 89% and 50% [40]. The concentration of SCCA-IgM immune complex is constantly increasing in patients with cirrhosis who tend to progress to HCC. Sensitivity and specificity were of higher value than AFP in the studies of Pontisso et al. [37].
Increased serum SCCA in patients with liver disease can be considered a valuable marker for early diagnosis of HCC. Especially the SCCA-IgM immune complex, which is highly sensitive. However, since its specificity is quite low, it must be combined with other markers such as serum AFP or DCP to increase its diagnostic value.
3.5 Osteopontin (OPN)
Osteopontin (OPN) is known as a conversion protein and is a glycophosphoprotein associated with integrin, which is overexpressed in many types of malignancies such as lung, breast, and colon cancers [41]. OPN usually manifests in biliary epithelial cells, astrocytes and Kupffer cells, but not in liver cells [42]. However, increased serum OPN expression has been reported in patients with HCC, but not in those with cirrhosis, chronic hepatitis, or healthy controls [43, 44]. In a meta-analysis, the sensitivity and specificity of OPN were 86% for all HCC stages [45]. Shang et al. suggested that serum OPN concentrations at the cut-off level of 91 ng/ml were more sensitive than that of AFP (74% versus 53%) in the diagnosis of HCC. Combining two imprints with an OPN cut-off of 156 ng/ml and an AFP cut-off of 20 ng/ml increased sensitivity and specificity (95% and 96%). The sensitivity and specificity of OPN were 75% and 62% for early HCC, which means the sensitivity was higher than that of AFP, but the specificity lower (46% and 93%). When combined with AFP at the cut-off of 91 ng/ml for OPNs, sensitivity increased to 83% and specificity decreased to 63% [45] (Table 1). Based on such findings, OPN can be considered an important marker in HCC diagnosis, especially for tumors in the early stages, and when combined with AFP to significantly increase sensitivity. However, studies with larger sample populations are needed to confirm its relevance.
3.6 Tumor-associated glycoprotein 72 (TAG-72)
Tumor-associated glycoprotein 72 (TAG-72) is a macro-molecular glycoprotein complex, which is rarely expressed in normal tissues, but overexpressed in the majority of human adenocarcinomas, including gastric, colon, and pancreatic cancer. TAG-72 expression is significantly increased in HCC tissues compared to normal liver tissues [46], and it is suspected of promoting tumor invasion and metastasis. A correlation between overexpression of TAG-72 and poor survival in patients with HCC has been observed [46]. This makes TAG-72 a potential prognosis marker for HCC, and anti-TAG-72 monoclonal antibody has been used for tumors clinical detection [47].
3.7 Zinc-α2-glycoprotein (ZAG)
Zinc-α2-glycoprotein (ZAG) is a member of the class I major histocompatibility complex (MHC-I) family. It is considered a new adipokine because of its strong amino acid sequence homology with lipid mobilizing factor (LMF). ZAG is downregulated in human obesity [48], but it is upregulated in different cancers such as breast, lung and prostate cancers, making it a potential biomarker for these. The serum proteome of the HCC, liver cirrhosis and healthy adult groups have been analyzed and it was found that the ZAG is overexpressed in the HCC patients suggesting a potential biomarker for the early detection of HCC [49].
3.8 Annexin A2
Annexin A2 is a calcium-dependent, phospholipid-binding protein found on the surface of endothelial cells and most epithelial cells [50, 51]. Annexin A2 serum concentrations in patients with HCC were often higher than those with benign liver disease, other malignant tumors, or healthy individuals [52, 53, 54]. High annexin A2 levels were observed in 83.2% of early-stage HCC and 78.4% of AFP-negative HCC patients [55]. Annexin A2 sensitivity and specificity were respectively measured at 83.2% and 67.5% in the detection of early-stage HCC, while HCC patients with normal AFP levels were 54.7% and 81.3%, respectively. The diagnostic performance of annexin A2 alone (AUC = 79%) was also greater than for AFP alone (AUC = 73%). As expected, the combination of annexin A2 and AFP further improved the overall diagnostic performance with a sensitivity of 87.4% and a specificity of 68.3%. This makes annexin A2 a potential independent biomarker for detecting early-stage HCC in patients with normal serum AFP.
4. Enzymes and isozymes
4.1 Des-γ-carboxyprothrombin (DCP)
Des-γ-carboxyprothrombin (DCP) or Prothrombin induced by vitamin K absence II (PIVKA II) is a prothrombin molecule which is synthesized in abnormally high amount in HCC. During malignant transformation in liver cells, vitamin K-dependent carboxylase system weakens [56]. In essence, this is a carboxylation defect that leads to increased DCP synthesis [57]. Serum DCP levels in patients with liver cancer have differed from normal individuals [58]. In a comparative study of cases of chronic hepatitis and liver cirrhosis, DCP showed a sensitivity of 72.7% and a specificity of 90.0%, equivalent to AFP [59]. The combination of these two markers improves HCC diagnosis with a sensitivity and a specificity of 74.2% and 87.2%, respectively [60]. Although DCP has proven to have great potential as a biomarker for early diagnosis of HCC, it needs to be verified by further studies, especially in combination with AFP. In a large multicentre study, the sensitivity of DCP was 56% for early HCC diagnosis. Combining DCP with AFP increased the sensitivity from 65–87% 3 months before HCC diagnosis, but the specificity decreased from 84–69% [61].
Although the diagnostic value of DCP has been studied in Asian countries, its assessments in Western countries, especially in Europe, are still limited. A case–control study to evaluate the performance of serum AFP and DCP concentrations for early HCC diagnosis was conducted in France [62]. The cut-off threshold for serum DCP was 42 mAU/ml and 5.5 ng/ml for AFP, resulting in DCP being better than AFP for early diagnosis of HCC with a sensitivity of 77% compared to a 61% one, and a specificity of 82% compared to a 50% one. The positive forecast value was 76% compared to 51%, and the negative forecast value was 83% compared to 62%. The combination of DCP and AFP improved diagnostic performance. These results further support the value of DCP as a marker for early HCC diagnosis. According to the 2010 recommendations of the Japan Society of Hepatology (JSH), the three biological markers AFP, AFP-L3 and DCP are checked by the state insurance for HCC screening, as a combination of two of the three biomarkers, or all three combined. These three markers help to increase sensitivity without reducing specificity in small liver cancer [63].
4.2 γ-Glutamyl transferase (GGT)
γ-Glutamyl transferase (GGT) is a membrane-binding enzyme, which appears in the development of liver cells during pregnancy, its concentration is high throughout pregnancy and decreases immediately after birth. The total GGT concentration increased in chronic liver diseases, HCC, and some extra-liver cancer diseases [63]. A study by Cui et al. on 90 patients with cirrhosis and 120 patients with HCC showed that the sensitivity of HS-GGT was 74%, irrespective of size, and 43.8% for small tumors (<3 cm) [64] (Table 1). The diagnostic value improves when combined with other biomarkers such as AFP, PIVKA II, or AFP-L3. This is a promising sign in the detection of small cancers and can be used in combination with AFP and AFP-L3.
4.3 Matrix metalloproteinases (MMPs)
Matrix metalloproteinase (MMP) is an enzyme belonging to the endopeptidase group, which helps regenerate tissue in various pathogenetic processes including tumor progression, and wound healing [65]. Kuo et al. showed that only cases of HBsAg-positive have high levels of MMP-2 expression [66], but the relationship between other markers of HBV and MMP was not clarified. Positive cases with HBeAg showed a high tendency for portal vein thrombosis along with high manifestations of MMP-7 and MMP-9. MMPs have a synergistic effect on HCC generation, proliferation and invasion, through ways that the study did not elucidate [67]. A significantly higher MMP-9/MMP-2 ratio was found in patients with advanced HCC compared to patients at an early stage [68]. The mRNA of MMP-14, MMP-15 and MMP-2 are highly expressed in most HCC cells suggesting an important role of MMPs in the growth, invasion, and metastasis of tumor cells. Selective inhibitors for these MMPs promise to be an effective mean of preventing the growth and metastasis of HCC [69].
4.4 Glutamine synthetase (GS)
Glutamine synthetase (GS) is an enzyme involved in catalyzing the synthesis of glutamine from glutamate and ammonia, it plays an important role in the function of ammonia metabolism and nitrogen balance of the liver [70]. Research by Haupt et al. demonstrated that GSmRNA increased its tissue and protein expression in the serum of HCC patients [71]. In addition, Osada et al. reported increasing GS expression correlated with cancer progression, suggesting GS can play a role in promoting HCC metastases [72].
4.5 Alpha L fucosidase (AFU)
Alpha L fucosidase (AFU) is a glycosidase responsible for hydrolysing fucoseglycoside bonds of glycoprotein and glycolipids and is found in all mammalian cell lysosomes and is involved in the degenerative reaction of a series of fucoglyco-containing fucoglyco complexes [73]. Serum AFU levels are constantly elevated in cirrhotic patients who tend to progress to HCC. Deugnier et al. found that serum AFU had greater sensitivity and specificity than AFP and that it can be considered a marker for HCC diagnosis. However, the cause of this increased serum AFU activity is still unknown. The most likely explanation is that increased serum AFU activity is a result of an increase in tumor protein synthesis that increases fucoses [74]. Measuring the activity of serum AFU regularly during follow-up of cirrhotic patients provides very useful clinical data in monitoring cirrhosis progression to HCC. Although an increased serum AFU activity was not correlated with tumor size and was common in cases of early HCC, the HCC tumor would appear within a few years in 82% of patients with liver fibrosis if serum AFU activity exceeds 700 nmol/ml/hour. Serum AFU activity increased in 85% of patients at least six months before HCC was detected by a diagnostic imaging method [75]. AFU activity was significantly increased in HCC patients compared with patients with other liver diseases or other cancers. AFU sensitivity is 81.5% and its specificity is 85.4% in HCC diagnosis [76] indicating a promising specific marker for HCC diagnosis.
5. Cytokines
Cytokines are a heterogeneous group of proteins that play roles of mediators in cellular reactions and activities. They are the product mediating and regulating immune processes of immune cells. Some cytokines also act as potential markers for early diagnosis and treatment of HCC.
5.1 Transforming growth factor-β1 (TGF-β1)
Transforming growth factor-β (TGF-β1) is a versatile growth factor associated with proliferation, cell differentiation, embryogenesis, vascular proliferation, invasion and immune activity. One study found that serum TGF-β1 levels increased in the HCC group compared to the group with non-malignant liver disease and the healthy group. With a cut-off of 800 pg./ml, the specificity of TGF-β1 HCC diagnostic serum is above 95%. Taking the same value as the serum AFP at the cut-off of 200 ng/ml, the sensitivity of TGF-β1 is 68%, which is superior to that of AFP (24%). Moreover, in patients with serum AFP within normal limits, increased TGF-β1 levels can be observed in 23% of cases [77]. It has been shown that TGF-β1 and TGF-β1 mRNA can be used as a marker to diagnose and predict HCC due to HBV with a sensitivity and specificity of 89.5% and 94.0% with a cutting level of TGF-β1 > 1.2 g/l [78]. TGF-β1 mediates various biological effects through signal paths and manifestations of TGF-β1 polymorphism may affect tumor susceptibility. The TGF-β1 signaling pathway can be considered as a target for HCC treatment. The subject is currently under study to confirm its role and promises to bring new cancer treatments.
5.2 Vascular endothelial growth factor (VEGF)
Vascular endothelial growth factor (VEGF) acts as an important factor in the process of tumor formation by forming new blood vessel systems that increase in size and promote invasion and metastasis. Studies have shown that angiogenesis is essential in tumor growth, including HCC, which is often characterized by the proliferation of blood vessels [79]. It has been demonstrated that VEGF expression in HCC tissues has a significantly higher incidence of portal vein thrombosis and a lower average survival time than when VEGF expression is not present [80]. In the study of Xiang et al., VEGF was associated with lymph node metastatic characteristics in HCC. In addition, VEGF expression is closely related to relapse and prognosis. Notably, several manifestations of the VEGF receptor are related to some of the clinical characteristics and prognosis of HCC [81]. Inactivation of VEGF165 increases the expression of the P53 gene that inhibits HCC development, invasion and metastasis.
5.3 Interleukin-8 (IL-8)
Interleukin-8 (IL-8) is a multifunctional CXC chemokine that is involved in the immune response of neutrophils in humans including kinetic phenomena, enzyme release and expression of surface adhesion of molecule. IL-8 also has a direct effect on tumor progression, including the proliferation of vascular endothelial cells and formation of new vessels. In addition, IL-8 increases the likelihood of metastases and new tumor formation in the liver [82]. A study showed that IL-8 serum concentrations increased in HCC patients compared to healthy subjects, it was positively correlated with tumor size (≥5 cm), portal vein thrombosis and advanced stage with lymph node metastases [83]. Therefore, it may be a biological marker that plays a useful role in HCC diagnosis and prognosis.
5.4 Tumor-specific growth factor (TSGF)
Malignant tumors have the ability to synthesize tumor-specific growth factors, releasing them into the capillaries surrounding the tumor and peripheral blood vessels during their development. Therefore, serum TSGF levels may be a marker of tumor survival. In one study, serum TSGF concentrations were used as a diagnostic marker for HCC with 82% sensitivity at 62 UI/ml [84]. Combined with other cancer markers, TSGF may yield higher diagnostic values with increased sensitivity. Theoretically, preeclampsia is highly expressed in many malignant tumors and HCC, but there are currently too few studies evaluating the role of TSGF in other malignancies to consider it as a potential factor. There are other markers, such as serum insulin-like growth factor-II (IGF-II), which can be used as diagnostic or prognostic markers for HCC. A cut-off of 4.1 mg/l of IGF-II obtained results of 63% sensitivity, 90% specificity and 70% accuracy in early HCC diagnosis with small tumor size. Moreover, the combination of IGF-II and AFP (cut-off value of 50 ng/ml) increases sensitivity up to 80% and accuracy up to 88% [85].
5.5 Hepatocyte growth factor (HGF)
Hepatocyte growth factor (HGF) is a multifunctional element produced in many organs in the body, it affects cell division, cell motility, intracellular invasion, and carcinogenesis [86]. In a study in Japan, serum HGF levels are increased significantly in the HCC group compared with cirrhosis, chronic hepatitis and healthy controls groups. With a cutting level of 0.6 ng/ml, its sensitivity can be up to 100% for any AFP or DCP concentration. The serum HGF concentration ≥ 1.0 ng/ml has a shorter shelf life, so it can be used as a prognostic marker for HCC [87]. The authors suggest that HGF causes proliferation and invasion of cancer cells through the expression of c-met receptors. In addition, increased HGF serum levels along with high expression of serum c-met protein after hepatectomy play an important role in predicting tumor recurrence and metastasis. This can be explained by the fact that HGF can increase the production and size of both normal and malignant liver cells after surgery, leading to tumor recurrence [88].
6. Circulating RNAs
6.1 AFP mRNA
AFP mRNA is a highly valuable marker only found in active cancer cells, which might be a sign of tumor metastasis. The non-recurrence time of HCC patients with high AFP mRNA expression after surgery was shorter than the group without this marker expression in liver cells (53% compared to 88% after 1 year; 37% compared to 60% after 2 years) [89]. In the advanced HCC stage, the AFP mRNA expression rate reaches 100%, and also acts as a predictor of recurrence after liver resection. However, the use of this marker in HCC diagnosis remains controversial, possibly due to the fact that it also manifests in many other malignancies and non-cancerous liver diseases [90]. Therefore, it could be used for diagnosis and prognosis when combined with other markers.
6.2 GGT mRNA
Gamma-glutamyl transferase mRNA (GGT mRNA) can be found in the blood and peripheral liver cells of healthy individuals, as well as in patients with benign liver disease, benign liver tumors or HCC. It has 3 types: A, B and C. Type A dominates in normal liver cases, non-cancerous liver diseases, benign tumors and secondary liver cancers, while type C is produced by the yolk during pregnancy. In contrast, type B predominates in HCC [91, 92, 93]. During malignant development, expression of GGT mRNA in liver tissues may change from type A to type B [93]. Patients with HCC and high type B expression will have a worse prognosis, with higher odds of a sooner and more serious relapse [94]. Therefore, hepatocellular expression of type B mRNA may be a valuable marker for HCC patients. As in liver tissues, peripheral blood type B expression has also been reported to be significantly higher in HCC patients than in healthy adults [91].
6.3 MicroRNA (miRNA)
MicroRNAs are small non-coding RNAs that inhibit or accelerate the translation process by attenuating or increasing the synthesis of target mRNAs or by binding to additional chains in the UTR region (3′-untranslated region). In recent years, the link between miRNA and tumor development has become a controversial issue. About 500 miRNA genes have been identified and contribute to control a number of cellular processes including proliferation, differentiation and apoptosis. In malignancy, the function of miRNA is determined to be carcinogenic and tumor suppressant [95]. miRNA can regulate many genes at the same time, they control the replication process and determine the characteristics of the cell. The variety in this functional role allows miRNA to be utilized as a diagnostic marker for early detection of cancer, risk assessment, prognosis and as a new therapeutic target.
Yamamoto et al. have used a global miRNA expression profile in mouse liver development and thus shown that miR-500 (miRNA) is a potential biomarker for HCC [95]. Their work showed that miR-500 is significantly associated with the regulation of liver development and thus is related to cirrhosis progression. The serum miR-21 levels were a valuable marker in distinguishing patients with HCC from those with chronic hepatitis with the sensitivity and specificity of 61.1% and 83.3%, respectively. Compared to the healthy group, the sensitivity and specificity were 87.3% and 92.0%, respectively. Both values are higher than serum AFP concentrations, which have been confirmed as a very valuable biological marker for HCC [96]. Serum miR-15b and miR-130b concentrations are relevant miRNA markers that are highly expressed in HCC. miR-130b has 87.7% sensitivity and 81.4% specificity. In contrast, while the sensitivity of miR-15b is high at 98.3%, its specificity is low at 15.3%. Because the sensitivity of these two factors is rather high, it can be used as a valuable marker in HCC screening and early diagnosis with low AFP levels [97].
A group of markers including seven miRNAs (miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801) has been shown to have a great diagnostic performance for HBV related HCC at an early stage [98]. Although its mechanism and signal path are still unknown, the expression of miRNA-29 may increase the susceptibility of cancer cells to apoptosis and reduce the expression of Mcl-1 and Bcl-2. Indeed, it has the ability to inhibit the formation and growth of cancer cells and is a potential marker in HCC prognosis and treatment [99]. MiR-122 is a specific miRNA found only in HCC, which concentration is inversely correlated with cancer growth and likelihood of invasion and metastasis. An analysis of miRNA markers revealed only tumor miR-21 expression and significantly higher serum miR-21 levels in HCC patients compared to those in chronic liver diseases and healthy control groups. Analysis of ROC curve between HCC and control group showed that sensitivity and specificity were 87.3% and 92% respectively, which is higher than that of serum AFP. Therefore, miR-21 is also a promising marker to support early HCC diagnosis [96].
Some of their features and expressions make miRNA particularly attractive as potential biomarkers. First, many miRNAs exhibit high stability and are easily detectable in peripheral blood of HCC patients. Secondly, miRNAs can be identified in urine, which will be a valuable non-invasive biological marker in detecting and managing HCC. The detection of the expression of some miRNAs in the urine (miR-625, miR-532, miR-618, miR-516-5P and miR-650) has been used for early detection of HCC [100]. However, more research is needed regarding miRNA before it can be used to detect HCC at an early stage.
6.4 Long non-coding RNA (lncRNA)
Like other cancers, HCC is characterized by a gradual accumulation of epigenetic changes. Among these changes, lncRNA has been found to play a significant role in the initiation and progression of HCC. Most lncRNAs express the characteristics of each species and the specific characteristics of the tumor. Increased or decreased expression of lncRNA has been found in cancerous tissues. Meanwhile, some lncRNA are found in urine, blood, and other body fluids. Moreover, the use of lncRNA as a marker for cancer pathology is superior to the coding RNA protein, due to the characteristic expression of lncRNA [101]. The sensitivity and specificity of lncRNA for HCC diagnosis found in some recent studies are quite high, while it has been demonstrated that JPX (just proximal to XIST) can have a sensitivity of up to 100% [102]. The 2-lncRNA signal has a high specificity of 90.62% but a low sensitivity of 60.65%, which could make it a potential marker to confirm an HCC diagnosis [103]. Recent findings suggest that lncRNA may be a potential marker for early diagnosis and monitoring of the risk of malignant progression in patients with chronic and highly specific chronic liver disease. These markers may contribute to the definitive HCC diagnosis without the need for histopathological diagnosis (Table 2).
miRNA/LncRNAs
Diagnostic value
AUC
Sensitivity
Specificity
Reference
miR-21
Differentiate HCC from patients with chronic hepatitis
P53 is an important protein in the P53 signaling pathway and mutation or loss of TP53 gene function leads to abnormal cell growth [104]. Notably, the mutation rate of TP53 varies by geographic area, reflecting the etiology and epidemiological changes of HCC [105]. Mutations in the TP53 gene, commonly found in sub-Saharan Africa and Southeast Asia, has the highest incidence of HBV infection and Aflatoxin B1 exposure. In these areas, the most common mutation is TP53 R249S, which is associated with an exposure factor of Aflatoxin B1 [106].
TP53 mutation was identified as one of the common molecular alterations in HCC, of which, the TP53 R249S mutation in exon 7 was found in HCC patients with a high incidence. Studies suggest that the TP53 R249S mutation may occur relatively early in areas associated with Aflatoxin exposure and chronic HBV infection [107]. The TP53 R249S mutation was an important factor in the carcinogenesis of HCC in Brazil, where Aflatoxin exposure is high [108]. In contrast, the TP53 R249S mutation may not play a role in causing HCC in Egypt, where HCV infection is common [109]. These findings suggest that TP53 mutations are involved in HCC pathogenesis in individuals with chronic HBV infection, especially in those exposed to high Aflatoxin B1.
Recent reports have shown that TP53 mutation can be used as a marker to predict HCC in high-risk groups. TP53 mutation has been shown to be associated with significantly higher relapse rates and lower disease-free survival rates [110]. It is also documented that TP53 mutation rate is about 30% and is associated with additional survival, non-recurrent survival and disease-free survival in HCC patients, with similar results observed in patients infected with HBV and HCV [111, 112]. However, a recent study showed that the TP53 mutation was only associated with a shorter survival time only in HBV-related HCC, while the R249S mutation was not related to the survival rate in the European patients with HCV-related HCC [113]. Growing evidence suggests that the stability of the TP53 mutation in tumors is important for its carcinogenic activities, decreasing the expression of the TP53 mutation that reduces malignant growth of cancer cells. Therefore, the TP53 mutation, especially at R249S position, can be considered as one of the early markers for HCC diagnosis and is an attractive therapy for cancer treatment.
7.2 hTERT gene mutation
The telomerase reverse transcriptase (hTERT) gene encodes an enzyme that maintains the telomeric DNA length and stabilizes the chromosomes [113]. hTERT is a major determinant of telomerase activity, which plays a key role in protecting cells from apoptosis and transforming into cancerous cells [114]. The reactivation of telomerase activity in cancer may be related to changes that occur during cancer development, including mutations and rearrangements of chromosomes [115].
The frequencies of hTERT mutations were observed in about 60% of HCC patients [116] but vary by geographical regions being the most common in Europe (59%) and less common in East Asia (20.7%) [117]. These data indicate that hTERT mutation is frequently associated with HCV-related HCC. hTERT-promoting mutations have been found with 6% of low-grade dysplasia nodules, 19% of advanced dysplasia nodules, 61% of early HCC and 42% of intermediate and advanced HCC [118]. Another study also found hTERT mutation in 57% of patients with chronic hepatitis and in 30% of those with early HCC [119]. Therefore, mutations in the hTERT promoter occur early in the course of malignant transformation and persists during tumor development. The regulation and expression of hTERT play an important role in the initiation and progression of HCC. hTERT mutation is one of the earliest gene mutations in cancer development and is also the most common gene mutation in HCC. Therefore, hTERT mutation is one of the most important markers in early diagnosis and may be a promising target for HCC treatment.
7.3 Mutations in ARID1A and ARID2 genes
ARID1A and ARID2 are two genes in the SWI/SNF complex (SWitch/sucrose non-fermentable) involved in chromosomal reconstruction. The mutation rate of the ARID1A and ARID2 genes found in 10% HCC, depending on the cause. ARID1A mutation is associated with alcohol consumption while ARID2 mutation is often associated with HCV infection [120]. Although the role of these mutations remains unknown, studies have shown that ARID1A and ARID2 genes are associated with the growth of cancer cells through affecting several signaling pathways such as PI3K/AKT, beta-catenin and p53 mutation [121] and are thus potential markers for early HCC detection.
8. DNA methylation
In HCC, methylation can occur in two ways: total methylation and partial methylation. Total methylation affects the structural function of the nucleus by promoting chromosome and genome instability, while partial methylation is associated with tumor suppressor genes [122]. Chronic hepatitis virus infections are the cause of DNA methylation aberrations in cancerous tissues. Although several DNA methyltransferase enzymes such as DNMT1, DNMT3A and DNMT3B have been shown to increase their expression in HCC related to hepatitis viruses, their mechanisms remain controversial and unclear [123].
p16 (CDKN2A), a tumor suppressor gene involved in cell cycle regulation, has been shown to be methylated and is related to clinical parameters in HCC [124]. A study has shown that the methylation levels of p16 gene increased in tissue samples from cirrhosis to HCC [125]. The methylation level of p16 gene is also associated with HBV infection, as the level of p16 methylation is higher in patients with HBV than those without HBV, the HBx gene being especially involved in the methylation of the p16 gene [126, 127]. A study on 64 HCC patients found that 77% of patients had p16 methylation and that methylation levels were correlated to serum AFP levels [128]. In a meta-analysis on 272 HCC tissue samples, the methylation rate of p16 gene was 58.5%, much higher than those with cirrhosis and chronic hepatitis [129]. Therefore, methylation in the p16 gene may serve as a promising molecular marker for HCC in patients with HBV infection.
Another potential marker for HCC prognosis is SOCS1 methylation. SOCS1 gene plays a role in modulating the JAK/STAT signaling pathway when methylation causes malignant cell proliferation. SOCS1 methylation correlates with tumor size and risk factors for HCC, it is more common in HCV and cirrhotic patients, but less common in HBV-infected groups. A study has shown that the methylation of SOCS1 gene in peripheral blood accounted for 38% in the HCC group, 20% in the cirrhotic group and 23% in the control group without liver disease. Expression of methylation of SOCS1 and RASSF1A genes in combination with serum AFP increased sensitivity to 86% and specificity to 75% for HCC diagnosis [130]. SOCS1 methylation is quite common in HCC, and is correlated with a number of clinical parameters and other serum biomarkers like AFP. Therefore, SOCS1 methylation in combination with serum AFP increases the sensitivity and specificity for early HCC diagnosis.
GSTP1 belongs to the Glutathione S-transferase family, which protects cells against carcinogens, regulates signaling pathways that control cell proliferation and cell death [131]. The methylation in the GSTP1 gene promoter was observed in prostate cancer, HCC and other malignancies. GSTP1 has been shown to have a high methylation rate in HCC related to HBV or HCV infection. Interestingly, methylation of the GSTP1 gene in HCC patients was 76.7% and those with high GSTP1 expression had a shorter survival time [132].
Detecting the methylation status of genes in serum provides a promising method for diagnosis of HCC. A study found aberrant methylation in the CCND2 gene in 39 out of 70 serum samples of HCC patients and methylation status was associated with a shorter disease-free survival time [133]. Yeo et al. showed that 17 out of 40 (42.5%) plasma samples of HCC patients had methylation in RASSF1A gene, and that methylation occurred mainly in patients with tumors ≥4 cm in size [134]. Methylation in RASSF1A in the serum of 85 HCC patients and found that 93% had methylation, it is associated with a shorter survival and disease stage [135]. The level of methylation in the RASSF1A gene of the HCC group is significantly higher compared to other liver disease groups and thus it is a promising independent marker for early diagnosis and prognosis of HCC [136].
9. Conclusion
A large number of markers have been studied and clinically applied for early diagnosis and monitoring of HCC treatment, of which serum AFP is a widely used with a controversial diagnostic threshold. A number of protein markers such as AFP-L3 and DCP are also being applied to support HCC diagnosis with higher sensitivity and specificity compared to AFP. However, the available marker is neither specific for solely HCC diagnosis nor provides great diagnostic performance for HCC and thus a combination of several serum protein markers can improve the early diagnosis rate. With the development of molecular technology, biomarkers based on miRNA and lncRNA expression, gene mutation (TP53, hTERT, ARID1A and ARID2) and DNA methylation have a great potential to improve the rate of HCC diagnosis at an early stage, as well as predicting progression, metastasis and tumor recurrence. In addition, with the development of current cell technology, cancer pathways and the expression of genes specific for HCC tumor may be important markers for early detection and new targets for the treatment of HCC.
Acknowledgments
This study was funded by the Vietnam National Foundation for Science and Technology Development (NAFOSTED; grant number 108.02-2017.15) to Hoang Van Tong. The funder has no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.
Competing interests
All authors have no conflicts of interest to declare.
\n',keywords:"Biomarkers, Hepatocellular Carcinoma, Diagnosis, Liver Cancer",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/77115.pdf",chapterXML:"https://mts.intechopen.com/source/xml/77115.xml",downloadPdfUrl:"/chapter/pdf-download/77115",previewPdfUrl:"/chapter/pdf-preview/77115",totalDownloads:133,totalViews:0,totalCrossrefCites:0,dateSubmitted:"May 2nd 2021",dateReviewed:"May 20th 2021",datePrePublished:"June 8th 2021",datePublished:null,dateFinished:"June 8th 2021",readingETA:"0",abstract:"Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, which is also often fatal. An early and accurate diagnosis is a decisive step towards the survival of the patients. Molecular biology improved significantly the prognosis of liver cancers through learned use of tumor markers like proteantigens, cytokines, enzymes, isoenzymes, circulating RNAs, gene mutations and methylations. Nevertheless, much improvement is still achievable and needed in this area, which is crucial in order to make an early diagnosis and monitor the progression of the disease. We present in this review what we believe to be the most relevant data regarding tissue and serum biomarkers related to HCC.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/77115",risUrl:"/chapter/ris/77115",signatures:"Hoang Van Tong, Pham Van Dung, Nguyen Thi Mong Diep and Nguyen Linh Toan",book:{id:"10787",type:"book",title:"Hepatocellular Carcinoma - Challenges and Opportunities of a Multidisciplinary Approach",subtitle:null,fullTitle:"Hepatocellular Carcinoma - Challenges and Opportunities of a Multidisciplinary Approach",slug:null,publishedDate:null,bookSignature:"Prof. Georgios Tsoulfas",coverURL:"https://cdn.intechopen.com/books/images_new/10787.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-83969-111-9",printIsbn:"978-1-83969-110-2",pdfIsbn:"978-1-83969-112-6",isAvailableForWebshopOrdering:!0,editors:[{id:"57412",title:"Prof.",name:"Georgios",middleName:null,surname:"Tsoulfas",slug:"georgios-tsoulfas",fullName:"Georgios Tsoulfas"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Embryonic antigen",level:"1"},{id:"sec_2_2",title:"2.1 Alpha-fetoprotein (AFP)",level:"2"},{id:"sec_3_2",title:"2.2 AFP heterogeneity",level:"2"},{id:"sec_5",title:"3. Proteantigen",level:"1"},{id:"sec_5_2",title:"3.1 Glypican-3 (GPC3)",level:"2"},{id:"sec_6_2",title:"3.2 Heat shock protein 70 (HSP70)",level:"2"},{id:"sec_7_2",title:"3.3 Golgi protein 73 (GP73)",level:"2"},{id:"sec_8_2",title:"3.4 Squamous cell carcinoma antigen (SCCA)",level:"2"},{id:"sec_9_2",title:"3.5 Osteopontin (OPN)",level:"2"},{id:"sec_10_2",title:"3.6 Tumor-associated glycoprotein 72 (TAG-72)",level:"2"},{id:"sec_11_2",title:"3.7 Zinc-α2-glycoprotein (ZAG)",level:"2"},{id:"sec_12_2",title:"3.8 Annexin A2",level:"2"},{id:"sec_14",title:"4. Enzymes and isozymes",level:"1"},{id:"sec_14_2",title:"4.1 Des-γ-carboxyprothrombin (DCP)",level:"2"},{id:"sec_15_2",title:"4.2 γ-Glutamyl transferase (GGT)",level:"2"},{id:"sec_16_2",title:"4.3 Matrix metalloproteinases (MMPs)",level:"2"},{id:"sec_17_2",title:"4.4 Glutamine synthetase (GS)",level:"2"},{id:"sec_18_2",title:"4.5 Alpha L fucosidase (AFU)",level:"2"},{id:"sec_20",title:"5. Cytokines",level:"1"},{id:"sec_20_2",title:"5.1 Transforming growth factor-β1 (TGF-β1)",level:"2"},{id:"sec_21_2",title:"5.2 Vascular endothelial growth factor (VEGF)",level:"2"},{id:"sec_22_2",title:"5.3 Interleukin-8 (IL-8)",level:"2"},{id:"sec_23_2",title:"5.4 Tumor-specific growth factor (TSGF)",level:"2"},{id:"sec_24_2",title:"5.5 Hepatocyte growth factor (HGF)",level:"2"},{id:"sec_26",title:"6. Circulating RNAs",level:"1"},{id:"sec_26_2",title:"6.1 AFP mRNA",level:"2"},{id:"sec_27_2",title:"6.2 GGT mRNA",level:"2"},{id:"sec_28_2",title:"6.3 MicroRNA (miRNA)",level:"2"},{id:"sec_29_2",title:"6.4 Long non-coding RNA (lncRNA)",level:"2"},{id:"sec_31",title:"7. Gene mutations",level:"1"},{id:"sec_31_2",title:"7.1 Mutations in TP53 gene",level:"2"},{id:"sec_32_2",title:"7.2 hTERT gene mutation",level:"2"},{id:"sec_33_2",title:"7.3 Mutations in ARID1A and ARID2 genes",level:"2"},{id:"sec_35",title:"8. DNA methylation",level:"1"},{id:"sec_36",title:"9. Conclusion",level:"1"},{id:"sec_37",title:"Acknowledgments",level:"1"},{id:"sec_37",title:"Competing interests",level:"1"}],chapterReferences:[{id:"B1",body:'Mittal S, El-Serag HB. Epidemiology of hepatocellular carcinoma: Consider the population. J Clin Gastroenterol 2013; 47 Suppl: S2-S6'},{id:"B2",body:'Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. 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Pathol Int 2007; 57: 328-336'},{id:"B128",body:'Lin Q , Chen L-b, Tang Y-m, et al. Promoter hypermethylation of p16 gene and DAPK gene in sera from hepatocellular carcinoma (HCC) patients. Chinese Journal of Cancer Research 2005; 17: 250-254'},{id:"B129",body:'Zang JJ, Xie F, Xu JF, et al. P16 gene hypermethylation and hepatocellular carcinoma: A systematic review and meta-analysis. World J Gastroenterol 2011; 17: 3043-3048'},{id:"B130",body:'Pasha HF, Mohamed RH, Radwan MI. RASSF1A and SOCS1 genes methylation status as a noninvasive marker for hepatocellular carcinoma. Cancer Biomark 2019; 24: 241-247'},{id:"B131",body:'Laborde E. Glutathione transferases as mediators of signaling pathways involved in cell proliferation and cell death. Cell Death Differ 2010; 17: 1373-1380'},{id:"B132",body:'Lee S, Lee HJ, Kim JH, et al. Aberrant CpG island hypermethylation along multistep hepatocarcinogenesis. Am J Pathol 2003; 163: 1371-1378'},{id:"B133",body:'Tsutsui M, Iizuka N, Moribe T, et al. Methylated cyclin D2 gene circulating in the blood as a prognosis predictor of hepatocellular carcinoma. Clin Chim Acta 2010; 411: 516-520'},{id:"B134",body:'Yeo W, Wong N, Wong WL, et al. High frequency of promoter hypermethylation of RASSF1A in tumor and plasma of patients with hepatocellular carcinoma. Liver Int 2005; 25: 266-272'},{id:"B135",body:'Chan KCA, Lai PBS, Mok TSK, et al. Quantitative analysis of circulating methylated DNA as a biomarker for hepatocellular carcinoma. Clinical Chemistry 2008; 54: 1528-1536'},{id:"B136",body:'Huang ZH, Hu Y, Hua D, et al. Quantitative analysis of multiple methylated genes in plasma for the diagnosis and prognosis of hepatocellular carcinoma. Exp Mol Pathol 2011; 91: 702-707'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Hoang Van Tong",address:"hoangvantong@vmmu.edu.vn",affiliation:'
Institute of Biomedicine and Pharmacy, Vietnam Military Medical University, Vietnam
Department of Pathophysiology, Vietnam Military Medical University, Vietnam
'},{corresp:null,contributorFullName:"Pham Van Dung",address:null,affiliation:'
Institute of Biomedicine and Pharmacy, Vietnam Military Medical University, Vietnam
Department of Pathophysiology, Vietnam Military Medical University, Vietnam
'}],corrections:null},book:{id:"10787",type:"book",title:"Hepatocellular Carcinoma - Challenges and Opportunities of a Multidisciplinary Approach",subtitle:null,fullTitle:"Hepatocellular Carcinoma - Challenges and Opportunities of a Multidisciplinary Approach",slug:null,publishedDate:null,bookSignature:"Prof. Georgios Tsoulfas",coverURL:"https://cdn.intechopen.com/books/images_new/10787.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-83969-111-9",printIsbn:"978-1-83969-110-2",pdfIsbn:"978-1-83969-112-6",isAvailableForWebshopOrdering:!0,editors:[{id:"57412",title:"Prof.",name:"Georgios",middleName:null,surname:"Tsoulfas",slug:"georgios-tsoulfas",fullName:"Georgios Tsoulfas"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},profile:{item:{id:"176128",title:"Associate Prof.",name:"Burçak",middleName:null,surname:"Karagüzel Kayaoğlu",email:"bkayaoglu@itu.edu.tr",fullName:"Burçak Karagüzel Kayaoğlu",slug:"burcak-karaguzel-kayaoglu",position:null,biography:null,institutionString:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",totalCites:0,totalChapterViews:"0",outsideEditionCount:0,totalAuthoredChapters:"1",totalEditedBooks:"0",personalWebsiteURL:null,twitterURL:null,linkedinURL:null,institution:{name:"Istanbul Technical University",institutionURL:null,country:{name:"Turkey"}}},booksEdited:[],chaptersAuthored:[{id:"49164",title:"Plasma Surface Treatments of Nonwovens",slug:"plasma-surface-treatments-of-nonwovens",abstract:"Plasma treatment has been used for surface activation and modification of textiles. The ionized, highly reactive species, such as ions, electrons, and radicals, in plasma modify the surface of the substrate material, and the composition of plasma depends on the gas used. Plasma technology is an environmentally friendly process and resource-efficient in nature. There is no solvent emission or wastewater in the process and drying processes with high energy and time consumption are not required. The textile applications of plasma include sterilization, wettability and hydrophobicity, dyeability enhancement, flame-retardant finishing, and antimicrobial properties. Plasma surface modification applied to fiber is a way to add value to a nonwoven fabric and enhance the functional performance of the final product. This chapter provides an overview of the plasma treatments of nonwovens that enhance their surface-related properties.",signatures:"Burçak Karagüzel Kayaoğlu",authors:[{id:"176128",title:"Associate Prof.",name:"Burçak",surname:"Karagüzel Kayaoğlu",fullName:"Burçak Karagüzel Kayaoğlu",slug:"burcak-karaguzel-kayaoglu",email:"bkayaoglu@itu.edu.tr"}],book:{id:"5062",title:"Non-woven Fabrics",slug:"non-woven-fabrics",productType:{id:"1",title:"Edited Volume"}}}],collaborators:[{id:"25460",title:"Prof.",name:"Kadir",surname:"Bilisik",slug:"kadir-bilisik",fullName:"Kadir Bilisik",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"1988-1991: PhD received from Leeds University / UK\r\n1991-1994: Post-Doc received from North Carolina State University at Raleigh / USA\r\n1994-1999: Associate Prof. worked in Ege University\r\n1999-2002: Senior Engineer worked in 3TEX INC. In North Carolina / USA\r\n2002-Present: Head and Prof. worked in Erciyes University",institutionString:null,institution:{name:"Erciyes University",institutionURL:null,country:{name:"Turkey"}}},{id:"28025",title:"Dr.",name:"Abbas",surname:"Milani",slug:"abbas-milani",fullName:"Abbas Milani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of British Columbia",institutionURL:null,country:{name:"Canada"}}},{id:"152908",title:"Prof.",name:"Ryohei",surname:"Sasaki",slug:"ryohei-sasaki",fullName:"Ryohei Sasaki",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Kobe University",institutionURL:null,country:{name:"Japan"}}},{id:"175795",title:"Associate Prof.",name:"Radostina",surname:"Angelova",slug:"radostina-angelova",fullName:"Radostina Angelova",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"175839",title:"Ph.D.",name:"Nesrin",surname:"Sahbaz Karaduman",slug:"nesrin-sahbaz-karaduman",fullName:"Nesrin Sahbaz Karaduman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/175839/images/16934_n.jpg",biography:"2010-2013: PhD received from Erciyes University / Turkey \n2014-Present: Assistant Prof. worked in Yozgat Bozok University / Department of Materials and Energy/ Hemp Research Institute",institutionString:null,institution:null},{id:"175840",title:"BSc.",name:"Nedim Erman",surname:"Bilisik",slug:"nedim-erman-bilisik",fullName:"Nedim Erman Bilisik",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"175893",title:"Dr.",name:"Izabella",surname:"Krucinska",slug:"izabella-krucinska",fullName:"Izabella Krucinska",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"176199",title:"Mr.",name:"Masoud",surname:"Haghi Kashani",slug:"masoud-haghi-kashani",fullName:"Masoud Haghi Kashani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"177114",title:"Dr.",name:"Bipin",surname:"Kumar",slug:"bipin-kumar",fullName:"Bipin Kumar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/177114/images/system/177114.jpg",biography:"Dr. Bipin Kumar graduated from the Indian Institute of Technology (IIT) Delhi, India, with a Ph.D. in Textile Engineering in 2013. Currently, he is an assistant professor in the Department of Textile Technology at IIT Delhi. Prior to joining IIT Delhi, he was a research assistant professor (2016–2017) at the Hong Kong Polytechnic University. He also served as a cultural ambassador (2014–2016) to the United States at the University of California Davis via the prestigious Fulbright Fellowship program. \n\nHis main research focuses on smart fibrous/polymeric materials and related fabric structures. He has more than forty publications in leading refereed SCI journals of materials, textiles, and medical fields, seven patents, three authored books, and many other academic publications. He has been awarded several prestigious awards including the Entrepreneur Faculty Award (IITDAA, 2020), IEI Young Engineer Award (Institute of Engineers, 2019), Teaching Excellence Award (IIT Delhi, 2018), DST INSPIRE Faculty Award 2016 (DST, 2016), Award for Excellence in Postdoctoral Research (UC Davis, 2016), and many more. He holds editorial membership at several international refereed journals including Journal of Engineered Fibers and Fabrics and Fabrics, American Association of Textile Chemists and Colorists Journal of Research, Fibres & Textiles in Eastern Europe, Advance Research in Textile Engineering, Current Trends in Fashion Technology & Textile Engineering and Journal of Textile Engineering & Fashion Technology. \n\nDr. Kumar’s research team launched their first commercial product, KAWACH Mask, in May 2020 at the time of the COVID-19 emergency. He is leading two successful start-ups at IIT Delhi, ETEX and SWATRIC, to commercialize several textile innovations for engineering and medical applications, including KAWACH masks, antiviral T-shirts, anti-radiation garments, Indian flags, E-textiles, anxiety garments, and more.",institutionString:"Indian Institute of Technology Delhi",institution:{name:"Indian Institute of Technology Delhi",institutionURL:null,country:{name:"India"}}},{id:"177453",title:"Dr.",name:"Hiroaki",surname:"Akasaka",slug:"hiroaki-akasaka",fullName:"Hiroaki Akasaka",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null}]},generic:{page:{slug:"types-of-publications",title:"Types of publications",intro:"
IntechOpen publishes different types of publications
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EDITED VOLUME
\\n\\n
IntechOpen Edited Volumes are integrated collections of chapters about particular topics that present new areas of research or novel syntheses of existing research and, as such, represent perspectives from various authors.
\\n\\n
Edited Volumes can be comprised of different types of chapters:
\\n\\n
RESEARCH CHAPTER – A research chapter reports the results of original research thus contributing to the body of knowledge in a particular area of study.
\\n\\n
REVIEW CHAPTER – A review chapter analyzes or examines research previously published by other scientists, rather than reporting new findings thus summarizing the current state of understanding on a topic.
\\n\\n
CASE STUDY – A case study involves an in-depth, and detailed examination of a particular topic.
\\n\\n
PERSPECTIVE CHAPTER – A perspective chapter offers a new point of view on existing problems, fundamental concepts, or common opinions on a specific topic. Perspective chapters can propose or support new hypotheses, or discuss the significance of newly achieved innovations. Perspective chapters can focus on current advances and future directions on a topic and include both original data and personal opinion.
\\n\\n
INTRODUCTORY CHAPTER – An introductory chapter states the purpose and goals of the book. The introductory chapter is written by the Academic Editor.
\\n\\n
MONOGRAPHS
\\n\\n
Monographs is a self-contained work on a particular subject, or an aspect of it, written by one or more authors. Monographs usually have between 130 and 500 pages.
\\n\\n
TYPES OF MONOGRAPHS:
\\n\\n
Single or multiple author manuscript
\\n\\n
COMPACTS
\\n\\n
Compacts provide a mid-length publishing format that bridges the gap between journal articles, book chapters, and monographs, and cover content across all scientific disciplines.
\\n\\n
Compacts are the preferred publishing option for brief research reports on new topics, in-depth case studies, dissertations, or essays exploring new ideas, issues, or broader topics on the research subject. Compacts usually have between 50 and 130 pages.
\\n\\n
CONFERENCE PROCEEDINGS
\\n\\n
Collection of papers presented at conferences, workshops, symposiums, or scientific courses, published in book format
IntechOpen Edited Volumes are integrated collections of chapters about particular topics that present new areas of research or novel syntheses of existing research and, as such, represent perspectives from various authors.
\n\n
Edited Volumes can be comprised of different types of chapters:
\n\n
RESEARCH CHAPTER – A research chapter reports the results of original research thus contributing to the body of knowledge in a particular area of study.
\n\n
REVIEW CHAPTER – A review chapter analyzes or examines research previously published by other scientists, rather than reporting new findings thus summarizing the current state of understanding on a topic.
\n\n
CASE STUDY – A case study involves an in-depth, and detailed examination of a particular topic.
\n\n
PERSPECTIVE CHAPTER – A perspective chapter offers a new point of view on existing problems, fundamental concepts, or common opinions on a specific topic. Perspective chapters can propose or support new hypotheses, or discuss the significance of newly achieved innovations. Perspective chapters can focus on current advances and future directions on a topic and include both original data and personal opinion.
\n\n
INTRODUCTORY CHAPTER – An introductory chapter states the purpose and goals of the book. The introductory chapter is written by the Academic Editor.
\n\n
MONOGRAPHS
\n\n
Monographs is a self-contained work on a particular subject, or an aspect of it, written by one or more authors. Monographs usually have between 130 and 500 pages.
\n\n
TYPES OF MONOGRAPHS:
\n\n
Single or multiple author manuscript
\n\n
COMPACTS
\n\n
Compacts provide a mid-length publishing format that bridges the gap between journal articles, book chapters, and monographs, and cover content across all scientific disciplines.
\n\n
Compacts are the preferred publishing option for brief research reports on new topics, in-depth case studies, dissertations, or essays exploring new ideas, issues, or broader topics on the research subject. Compacts usually have between 50 and 130 pages.
\n\n
CONFERENCE PROCEEDINGS
\n\n
Collection of papers presented at conferences, workshops, symposiums, or scientific courses, published in book format
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He first worked as a consultant at Vodafone-Spain. From 2004 to 2011, he was a Research Assistant with the Communications Engineering Department at the University of Málaga. In 2011, he became an Assistant Professor in the same department. From 2012 to 2015, he was with Ericsson Spain, where he was working on geo-location\ntools for third generation mobile networks. Since 2015, he is a Marie-Curie fellow at the Denmark Technical University. 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The vacuum thermal evaporation technique, electron beam evaporation, pulsed-layer deposition, direct current/radio frequency magnetron sputtering, and chemical route deposition systems will be discussed in detail.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Asim Jilani, Mohamed Shaaban Abdel-wahab and Ahmed Hosny\nHammad",authors:[{id:"192377",title:"Dr.",name:"Asim",middleName:null,surname:"Jilani",slug:"asim-jilani",fullName:"Asim Jilani"},{id:"192972",title:"Dr.",name:"M.Sh",middleName:null,surname:"Abdel-Wahab",slug:"m.sh-abdel-wahab",fullName:"M.Sh Abdel-Wahab"},{id:"192973",title:"Dr.",name:"Ahmed",middleName:"H",surname:"Hammad",slug:"ahmed-hammad",fullName:"Ahmed Hammad"}]},{id:"53225",doi:"10.5772/66396",title:"Radio Frequency Magnetron Sputter Deposition as a Tool for Surface Modification of Medical Implants",slug:"radio-frequency-magnetron-sputter-deposition-as-a-tool-for-surface-modification-of-medical-implants",totalDownloads:2252,totalCrossrefCites:8,totalDimensionsCites:28,abstract:"The resent advances in radio frequency (RF)‐magnetron sputtering of hydroxyapatite films are reviewed and challenges posed. The principles underlying RF‐magnetron sputtering used to prepare calcium phosphate‐based, mainly hydroxyapatite coatings, are discussed in this chapter. The fundamental characteristic of the RF‐magnetron sputtering is an energy input into the growing film. In order to tailor the film properties, one has to adjust the energy input into the substrate depending on the desired film properties. The effect of different deposition control parameters, such as deposition time, substrate temperature, and substrate biasing on the hydroxyapatite (HA) film properties is discussed.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Roman Surmenev, Alina Vladescu, Maria Surmeneva, Anna Ivanova,\nMariana Braic, Irina Grubova and Cosmin Mihai Cotrut",authors:[{id:"193921",title:"Dr.",name:"Alina",middleName:null,surname:"Vladescu",slug:"alina-vladescu",fullName:"Alina Vladescu"},{id:"193922",title:"Prof.",name:"Roman",middleName:null,surname:"Surmenev",slug:"roman-surmenev",fullName:"Roman Surmenev"},{id:"193923",title:"Dr.",name:"Maria",middleName:null,surname:"Surmeneva",slug:"maria-surmeneva",fullName:"Maria Surmeneva"},{id:"193948",title:"Dr.",name:"Mariana",middleName:null,surname:"Braic",slug:"mariana-braic",fullName:"Mariana Braic"},{id:"194047",title:"Ms.",name:"Anna",middleName:null,surname:"Ivanova",slug:"anna-ivanova",fullName:"Anna Ivanova"},{id:"194048",title:"BSc.",name:"Irina",middleName:null,surname:"Grubova",slug:"irina-grubova",fullName:"Irina Grubova"},{id:"196398",title:"Prof.",name:"Cosmin Mihai",middleName:null,surname:"Cotrut",slug:"cosmin-mihai-cotrut",fullName:"Cosmin Mihai Cotrut"}]},{id:"53792",doi:"10.5772/67085",title:"Silver-Based Low-Emissivity Coating Technology for Energy- Saving Window Applications",slug:"silver-based-low-emissivity-coating-technology-for-energy-saving-window-applications",totalDownloads:3132,totalCrossrefCites:7,totalDimensionsCites:13,abstract:"Low-emissivity (low-E) technology is a unique and cost-effective solution to save energy in buildings for different climates. Its development combines advances in materials science, vacuum deposition, and optical design. In this chapter, we will review the fundamentals of energy saving window coatings, the history of its application, and the materials used. The current low-E coating technologies are overviewed, especially silver-based low-E technologies, which comprise more than 90% of the overall low-E market today. Further, the advanced understanding of generating high-quality silver thin films is discussed, which is at the heart of silver-based low-E product technology development. How the silver thin film electrical, optical, and emissivity properties are influenced by their microstructure, thickness, and by the materials on neighboring layers will be discussed from a theoretical and an experimental perspective.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Guowen Ding and César Clavero",authors:[{id:"195240",title:"Dr.",name:"Guowen",middleName:null,surname:"Ding",slug:"guowen-ding",fullName:"Guowen Ding"},{id:"197064",title:"Dr.",name:"Cesar",middleName:null,surname:"Clavero",slug:"cesar-clavero",fullName:"Cesar Clavero"}]},{id:"52951",doi:"10.5772/66125",title:"Chemical Solution Deposition Technique of Thin-Film Ceramic Electrolytes for Solid Oxide Fuel Cells",slug:"chemical-solution-deposition-technique-of-thin-film-ceramic-electrolytes-for-solid-oxide-fuel-cells",totalDownloads:2392,totalCrossrefCites:7,totalDimensionsCites:10,abstract:"Chemical solution deposition (CSD) technique is recently gaining momentum for the fabrication of electrolyte materials for solid oxide fuel cells (SOFCs) due to its cost-effectiveness, high yield, and simplicity of the process requirements. The advanced vacuum deposition techniques such as sputtering, atomic layer deposition (ALD), pulsed laser deposition (PLD), metallo-organic chemical vapor deposition (MOCVD) are lacking in scalability and cost-effectiveness. CSD technique includes a variety of approaches such as sol-gel process, chelate process, and metallo-organic decomposition. The present chapter discusses briefly about the evolution of CSD method and its subsequent entry to the field of SOFCs, various solution methods associated with different chemical compositions, film deposition techniques, chemical reactions, heat treatment strategies, nucleation and growth kinetics, associated defects, etc. Examples are cited to bring out the history dating back to the discovery of amorphous zirconia film through the successful fabrication of the crystalline fluorite-type films such as yttria-stabilized zirconia (YSZ), scandia-doped ceria (SDC), and crystalline perovskite-type films such as yttria-doped barium zirconate (BZY) and yttria-doped barium cerate (BCY), to name a few.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Mridula Biswas and Pei-Chen Su",authors:[{id:"193015",title:"Dr.",name:"Pei-Chen",middleName:null,surname:"Su",slug:"pei-chen-su",fullName:"Pei-Chen Su"},{id:"193328",title:"Dr.",name:"Mridula",middleName:null,surname:"Biswas",slug:"mridula-biswas",fullName:"Mridula Biswas"}]},{id:"53336",doi:"10.5772/66476",title:"Molecular Precursor Method for Fabricating p-Type Cu2O and Metallic Cu Thin Films",slug:"molecular-precursor-method-for-fabricating-p-type-cu2o-and-metallic-cu-thin-films",totalDownloads:2360,totalCrossrefCites:5,totalDimensionsCites:10,abstract:"Functional thin films are used in various fields of our life. Many different methods are used to fabricate these films including physical vapor deposition (PVD) and chemical processes. The chemical processes can be used to manufacture thin films in a relatively cheap way, as compared to PVD methods. This chapter summarizes the procedures of the molecular precursor method (MPM), a chemical process, for fabrication of both metal oxide semiconductor Cu2O and metallic Cu thin films by utilizing Cu(II) complexes in coating solutions. The MPM, recently developed and reported by the present authors, represents a facile procedure for thin film fabrication of various metal oxides or phosphates. This method pertinent to the coordination chemistry and materials science including nanoscience and nanotechnology has provided various thin films of high quality. The MPM is based on the design of metal complexes in coating solutions with excellent stability, homogeneity, miscibility, coatability, etc., which are practical advantages. The metal oxides and phosphates are useful as the electron and/or ion conductors, semiconductors, dielectric materials, etc. This chapter will describe the principle and recent achievement, mainly on fabricating the p-type Cu2O and metallic Cu thin films of the MPM.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Hiroki Nagai and Mitsunobu Sato",authors:[{id:"148259",title:"Prof.",name:"Mitsunobu",middleName:null,surname:"Sato",slug:"mitsunobu-sato",fullName:"Mitsunobu Sato"},{id:"148920",title:"Dr.",name:"Hiroki",middleName:null,surname:"Nagai",slug:"hiroki-nagai",fullName:"Hiroki Nagai"}]}],mostDownloadedChaptersLast30Days:[{id:"52684",title:"Advance Deposition Techniques for Thin Film and Coating",slug:"advance-deposition-techniques-for-thin-film-and-coating",totalDownloads:7563,totalCrossrefCites:31,totalDimensionsCites:58,abstract:"Thin films have a great impact on the modern era of technology. Thin films are considered as backbone for advanced applications in the various fields such as optical devices, environmental applications, telecommunications devices, energy storage devices, and so on . The crucial issue for all applications of thin films depends on their morphology and the stability. The morphology of the thin films strongly hinges on deposition techniques. Thin films can be deposited by the physical and chemical routes. In this chapter, we discuss some advance techniques and principles of thin-film depositions. The vacuum thermal evaporation technique, electron beam evaporation, pulsed-layer deposition, direct current/radio frequency magnetron sputtering, and chemical route deposition systems will be discussed in detail.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Asim Jilani, Mohamed Shaaban Abdel-wahab and Ahmed Hosny\nHammad",authors:[{id:"192377",title:"Dr.",name:"Asim",middleName:null,surname:"Jilani",slug:"asim-jilani",fullName:"Asim Jilani"},{id:"192972",title:"Dr.",name:"M.Sh",middleName:null,surname:"Abdel-Wahab",slug:"m.sh-abdel-wahab",fullName:"M.Sh Abdel-Wahab"},{id:"192973",title:"Dr.",name:"Ahmed",middleName:"H",surname:"Hammad",slug:"ahmed-hammad",fullName:"Ahmed Hammad"}]},{id:"53792",title:"Silver-Based Low-Emissivity Coating Technology for Energy- Saving Window Applications",slug:"silver-based-low-emissivity-coating-technology-for-energy-saving-window-applications",totalDownloads:3132,totalCrossrefCites:7,totalDimensionsCites:13,abstract:"Low-emissivity (low-E) technology is a unique and cost-effective solution to save energy in buildings for different climates. Its development combines advances in materials science, vacuum deposition, and optical design. In this chapter, we will review the fundamentals of energy saving window coatings, the history of its application, and the materials used. The current low-E coating technologies are overviewed, especially silver-based low-E technologies, which comprise more than 90% of the overall low-E market today. Further, the advanced understanding of generating high-quality silver thin films is discussed, which is at the heart of silver-based low-E product technology development. How the silver thin film electrical, optical, and emissivity properties are influenced by their microstructure, thickness, and by the materials on neighboring layers will be discussed from a theoretical and an experimental perspective.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Guowen Ding and César Clavero",authors:[{id:"195240",title:"Dr.",name:"Guowen",middleName:null,surname:"Ding",slug:"guowen-ding",fullName:"Guowen Ding"},{id:"197064",title:"Dr.",name:"Cesar",middleName:null,surname:"Clavero",slug:"cesar-clavero",fullName:"Cesar Clavero"}]},{id:"52908",title:"Smart Thermoresponsive Surfaces Based on pNIPAm Coatings and Laser Method for Biological Applications",slug:"smart-thermoresponsive-surfaces-based-on-pnipam-coatings-and-laser-method-for-biological-application",totalDownloads:1836,totalCrossrefCites:3,totalDimensionsCites:7,abstract:"Various applications within last decades such as bacterially resistant surfaces, soft robotics, drug delivery systems, sensors and tissue engineering are poised to feature the importance of the ability to control bio-interfacial interactions. An enhanced attention is dedicated to designing smart stimuli-responsive interfaces for DNA, drug delivery, protein and cell based applications. Within this context, the thermoresponsive materials, especially poly(N-isopropylacrylamide) (pNIPAm) have been intensively used in tissue engineering applications for a controlled detachment of proteins and cells with a minimum of invasive effect on protein and cell structural conformation. The properties of smart bio-interfaces can be controlled by its composition and polymer architecture. Therefore, appropriate methods for obtaining controlled coatings are necessary. Laser methods were successfully used in the last decades for obtaining controlled organic and inorganic coatings for various types of applications, from electronics to tissue engineering. Among these, Matrix-Assisted Pulsed Laser Evaporation (MAPLE) technique bring us a step forward to other laser methods by avoiding damage and photochemical decomposition of materials. In this chapter we describe materials and approaches used for design of smart bio-interfaces aimed at controlling protein and cells behavior in vitro, focusing MAPLE method for tuning coatings characteristics in relation with biological response.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Laurentiu Rusen, Valentina Dinca, Cosmin Mustaciosu, Madalina\nIcriverzi, Livia Elena Sima, Anca Bonciu, Simona Brajnicov, Natalia\nMihailescu, Nicoleta Dumitrescu, Alexandru I. Popovici, Anca\nRoseanu and Maria Dinescu",authors:[{id:"32241",title:"Dr.",name:"Maria",middleName:null,surname:"Dinescu",slug:"maria-dinescu",fullName:"Maria Dinescu"},{id:"176781",title:"Dr.",name:"Valentina",middleName:null,surname:"Dinca",slug:"valentina-dinca",fullName:"Valentina Dinca"},{id:"176783",title:"Dr.",name:"Laurentiu",middleName:null,surname:"Rusen",slug:"laurentiu-rusen",fullName:"Laurentiu Rusen"},{id:"177680",title:"B.Sc.",name:"Anca",middleName:"Florina",surname:"Bonciu",slug:"anca-bonciu",fullName:"Anca Bonciu"},{id:"193439",title:"Ph.D.",name:"Madalina",middleName:null,surname:"Icriverzi",slug:"madalina-icriverzi",fullName:"Madalina Icriverzi"},{id:"193441",title:"Dr.",name:"Livia Elena",middleName:null,surname:"Sima",slug:"livia-elena-sima",fullName:"Livia Elena Sima"},{id:"193442",title:"Ph.D.",name:"Simona",middleName:null,surname:"Brajnicov",slug:"simona-brajnicov",fullName:"Simona Brajnicov"},{id:"193443",title:"Ph.D.",name:"Nicoleta",middleName:"Luminita",surname:"Dumitrescu",slug:"nicoleta-dumitrescu",fullName:"Nicoleta Dumitrescu"},{id:"193444",title:"Dr.",name:"Cosmin",middleName:null,surname:"Mustaciosu",slug:"cosmin-mustaciosu",fullName:"Cosmin Mustaciosu"},{id:"193445",title:"Dr.",name:"Anca",middleName:null,surname:"Roseanu",slug:"anca-roseanu",fullName:"Anca Roseanu"},{id:"196184",title:"Prof.",name:"Natalia",middleName:null,surname:"Serban",slug:"natalia-serban",fullName:"Natalia Serban"},{id:"198275",title:"Ms.",name:"A.I.",middleName:null,surname:"Popovici",slug:"a.i.-popovici",fullName:"A.I. Popovici"}]},{id:"52951",title:"Chemical Solution Deposition Technique of Thin-Film Ceramic Electrolytes for Solid Oxide Fuel Cells",slug:"chemical-solution-deposition-technique-of-thin-film-ceramic-electrolytes-for-solid-oxide-fuel-cells",totalDownloads:2392,totalCrossrefCites:7,totalDimensionsCites:10,abstract:"Chemical solution deposition (CSD) technique is recently gaining momentum for the fabrication of electrolyte materials for solid oxide fuel cells (SOFCs) due to its cost-effectiveness, high yield, and simplicity of the process requirements. The advanced vacuum deposition techniques such as sputtering, atomic layer deposition (ALD), pulsed laser deposition (PLD), metallo-organic chemical vapor deposition (MOCVD) are lacking in scalability and cost-effectiveness. CSD technique includes a variety of approaches such as sol-gel process, chelate process, and metallo-organic decomposition. The present chapter discusses briefly about the evolution of CSD method and its subsequent entry to the field of SOFCs, various solution methods associated with different chemical compositions, film deposition techniques, chemical reactions, heat treatment strategies, nucleation and growth kinetics, associated defects, etc. Examples are cited to bring out the history dating back to the discovery of amorphous zirconia film through the successful fabrication of the crystalline fluorite-type films such as yttria-stabilized zirconia (YSZ), scandia-doped ceria (SDC), and crystalline perovskite-type films such as yttria-doped barium zirconate (BZY) and yttria-doped barium cerate (BCY), to name a few.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Mridula Biswas and Pei-Chen Su",authors:[{id:"193015",title:"Dr.",name:"Pei-Chen",middleName:null,surname:"Su",slug:"pei-chen-su",fullName:"Pei-Chen Su"},{id:"193328",title:"Dr.",name:"Mridula",middleName:null,surname:"Biswas",slug:"mridula-biswas",fullName:"Mridula Biswas"}]},{id:"53122",title:"Anomalous Rashba Effect of Bi Thin Film Studied by Spin-Resolved ARPES",slug:"anomalous-rashba-effect-of-bi-thin-film-studied-by-spin-resolved-arpes",totalDownloads:2099,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The Rashba effect is a momentum‐dependent splitting of spin bands in two‐dimensional systems such as surface, interface and heterostructure. The effect is caused by broken space‐inversion symmetry and spin‐orbit coupling and allows to manipulate and generate the spin by the electric fields, that is, without the magnetic field. It means that the devices applied to the Rashba effect have many advantages. Bismuth is known as a promising candidate to investigate the surface Rashba effect, and the spin structure of Bi surface has also been intensively discussed. However, it is unclear to what extent the so far believed simple vortical spin structure is adequate. To understand the surface properties of the Rashba system is particularly important when utilizing the Rashba effect to the spintronic devices, since it is desirable to control the spin polarization when developing new types of devices. In this chapter, we report that the surface spin states of the Bi thin film exhibit unusual characteristics unlike the conventional Rashba splitting by using a spin‐ and angle‐resolved photoemission spectroscopy measurement.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Akari Takayama",authors:[{id:"192655",title:"Dr.",name:"Akari",middleName:null,surname:"Takayama",slug:"akari-takayama",fullName:"Akari Takayama"}]}],onlineFirstChaptersFilter:{topicId:"955",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:288,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 24th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:9,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",slug:"ana-isabel-flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",slug:"christian-palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. 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She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. 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Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"255360",title:"Dr.",name:"Usama",middleName:null,surname:"Ahmad",slug:"usama-ahmad",fullName:"Usama Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255360/images/system/255360.png",biography:"Dr. Usama Ahmad holds a specialization in Pharmaceutics from Amity University, Lucknow, India. He received his Ph.D. degree from Integral University. Currently, he’s working as an Assistant Professor of Pharmaceutics in the Faculty of Pharmacy, Integral University. From 2013 to 2014 he worked on a research project funded by SERB-DST, Government of India. He has a rich publication record with more than 32 original articles published in reputed journals, 3 edited books, 5 book chapters, and a number of scientific articles published in ‘Ingredients South Asia Magazine’ and ‘QualPharma Magazine’. He is a member of the American Association for Cancer Research, International Association for the Study of Lung Cancer, and the British Society for Nanomedicine. Dr. Ahmad’s research focus is on the development of nanoformulations to facilitate the delivery of drugs that aim to provide practical solutions to current healthcare problems.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}},{id:"226275",title:"Ph.D.",name:"Metin",middleName:null,surname:"Budak",slug:"metin-budak",fullName:"Metin Budak",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226275/images/system/226275.jfif",biography:"Metin Budak, MSc, PhD is an Assistant Professor at Trakya University, Faculty of Medicine. He has been Head of the Molecular Research Lab at Prof. Mirko Tos Ear and Hearing Research Center since 2018. His specializations are biophysics, epigenetics, genetics, and methylation mechanisms. He has published around 25 peer-reviewed papers, 2 book chapters, and 28 abstracts. He is a member of the Clinical Research Ethics Committee and Quantification and Consideration Committee of Medicine Faculty. His research area is the role of methylation during gene transcription, chromatin packages DNA within the cell and DNA repair, replication, recombination, and gene transcription. His research focuses on how the cell overcomes chromatin structure and methylation to allow access to the underlying DNA and enable normal cellular function.",institutionString:"Trakya University",institution:{name:"Trakya University",country:{name:"Turkey"}}},{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",biography:"Anca Pantea Stoian is a specialist in diabetes, nutrition, and metabolic diseases as well as health food hygiene. She also has competency in general ultrasonography.\n\nShe is an associate professor in the Diabetes, Nutrition and Metabolic Diseases Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. She has been chief of the Hygiene Department, Faculty of Dentistry, at the same university since 2019. Her interests include micro and macrovascular complications in diabetes and new therapies. Her research activities focus on nutritional intervention in chronic pathology, as well as cardio-renal-metabolic risk assessment, and diabetes in cancer. She is currently engaged in developing new therapies and technological tools for screening, prevention, and patient education in diabetes. \n\nShe is a member of the European Association for the Study of Diabetes, Cardiometabolic Academy, CEDA, Romanian Society of Diabetes, Nutrition and Metabolic Diseases, Romanian Diabetes Federation, and Association for Renal Metabolic and Nutrition studies. She has authored or co-authored 160 papers in national and international peer-reviewed journals.",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",country:{name:"Romania"}}},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279792/images/system/279792.jpg",biography:"Graduate and master in Biology from the University of Coimbra.\n\nI am a research fellow at the Macroalgae Laboratory Unit, in the MARE-UC – Marine and Environmental Sciences Centre of the University of Coimbra. My principal function is the collection, extraction and purification of macroalgae compounds, chemical and bioactive characterization of the compounds and algae extracts and development of new methodologies in marine biotechnology area. \nI am associated in two projects: one consists on discovery of natural compounds for oncobiology. The other project is the about the natural compounds/products for agricultural area.\n\nPublications:\nCotas, J.; Figueirinha, A.; Pereira, L.; Batista, T. 2018. An analysis of the effects of salinity on Fucus ceranoides (Ochrophyta, Phaeophyceae), in the Mondego River (Portugal). Journal of Oceanology and Limnology. in press. DOI: 10.1007/s00343-019-8111-3",institutionString:"Faculty of Sciences and Technology of University of Coimbra",institution:null},{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279788/images/system/279788.jpg",biography:"Leonel Pereira has an undergraduate degree in Biology, a Ph.D. in Biology (specialty in Cell Biology), and a Habilitation degree in Biosciences (specialization in Biotechnology) from the Faculty of Science and Technology, University of Coimbra, Portugal, where he is currently a professor. In addition to teaching at this university, he is an integrated researcher at the Marine and Environmental Sciences Center (MARE), Portugal. His interests include marine biodiversity (algae), marine biotechnology (algae bioactive compounds), and marine ecology (environmental assessment). Since 2008, he has been the author and editor of the electronic publication MACOI – Portuguese Seaweeds Website (www.seaweeds.uc.pt). He is also a member of the editorial boards of several scientific journals. Dr. Pereira has edited or authored more than 20 books, 100 journal articles, and 45 book chapters. He has given more than 100 lectures and oral communications at various national and international scientific events. He is the coordinator of several national and international research projects. In 1998, he received the Francisco de Holanda Award (Honorable Mention) and, more recently, the Mar Rei D. Carlos award (18th edition). He is also a winner of the 2016 CHOICE Award for an outstanding academic title for his book Edible Seaweeds of the World. In 2020, Dr. Pereira received an Honorable Mention for the Impact of International Publications from the Web of Science",institutionString:"University of Coimbra",institution:{name:"University of Coimbra",country:{name:"Portugal"}}},{id:"61946",title:"Dr.",name:"Carol",middleName:null,surname:"Bernstein",slug:"carol-bernstein",fullName:"Carol Bernstein",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/61946/images/system/61946.jpg",biography:"Carol Bernstein received her PhD in Genetics from the University of California (Davis). She was a faculty member at the University of Arizona College of Medicine for 43 years, retiring in 2011. Her research interests focus on DNA damage and its underlying role in sex, aging and in the early steps of initiation and progression to cancer. In her research, she had used organisms including bacteriophage T4, Neurospora crassa, Schizosaccharomyces pombe and mice, as well as human cells and tissues. She authored or co-authored more than 140 scientific publications, including articles in major peer reviewed journals, book chapters, invited reviews and one book.",institutionString:"University of Arizona",institution:{name:"University of Arizona",country:{name:"United States of America"}}},{id:"182258",title:"Dr.",name:"Ademar",middleName:"Pereira",surname:"Serra",slug:"ademar-serra",fullName:"Ademar Serra",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/182258/images/system/182258.jpeg",biography:"Dr. Serra studied Agronomy on Universidade Federal de Mato Grosso do Sul (UFMS) (2005). He received master degree in Agronomy, Crop Science (Soil fertility and plant nutrition) (2007) by Universidade Federal da Grande Dourados (UFGD), and PhD in agronomy (Soil fertility and plant nutrition) (2011) from Universidade Federal da Grande Dourados / Escola Superior de Agricultura Luiz de Queiroz (UFGD/ESALQ-USP). Dr. Serra is currently working at Brazilian Agricultural Research Corporation (EMBRAPA). His research focus is on mineral nutrition of plants, crop science and soil science. Dr. Serra\\'s current projects are soil organic matter, soil phosphorus fractions, compositional nutrient diagnosis (CND) and isometric log ratio (ilr) transformation in compositional data analysis.",institutionString:"Brazilian Agricultural Research Corporation",institution:{name:"Brazilian Agricultural Research Corporation",country:{name:"Brazil"}}}]}},subseries:{item:{id:"41",type:"subseries",title:"Water Science",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection",scope:"
\r\n\tWater is not only a crucial substance needed for biological life on Earth, but it is also a basic requirement for the existence and development of the human society. Owing to the importance of water to life on Earth, early researchers conducted numerous studies and analyses on the liquid form of water from the perspectives of chemistry, physics, earth science, and biology, and concluded that Earth is a "water polo". Water covers approximately 71% of Earth's surface. However, 97.2% of this water is seawater, 21.5% is icebergs and glaciers, and only 0.65% is freshwater that can be used directly by humans. As a result, the amount of water reserves available for human consumption is limited. The development, utilization, and protection of freshwater resources has become the focus of water science research for the continued improvement of human livelihoods and society.
\r\n
\r\n\tWater exists as solid, liquid, and gas within Earth’s atmosphere, lithosphere, and biosphere. Liquid water is used for a variety of purposes besides drinking, including power generation, ecology, landscaping, and shipping. Because water is involved in various environmental hydrological processes as well as numerous aspects of the economy and human society, the study of various phenomena in the hydrosphere, the laws governing their occurrence and development, the relationship between the hydrosphere and other spheres of Earth, and the relationship between water and social development, are all part of water science. Knowledge systems for water science are improving continuously. Water science has become a specialized field concerned with the identification of its physical, chemical, and biological properties. In addition, it reveals the laws of water distribution, movement, and circulation, and proposes methods and tools for water development, utilization, planning, management, and protection. Currently, the field of water science covers research related to topics such as hydrology, water resources and water environment. It also includes research on water related issues such as safety, engineering, economy, law, culture, information, and education.
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