",isbn:null,printIsbn:null,pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"f86a9f720cc3ac0f1c385d0367ea89b9",bookSignature:"Dr. Fiaz Ahmad and Prof. Muhammad Sultan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11624.jpg",keywords:"Agricultural Waste, Reuse, Reduction, Soil Health, Recycling, Agriculture and Environment, Modelling and Simulation, Agro-Industrial Waste, Bioresource Processing, Processing and Management, Crop Residue, Forest Waste",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 8th 2022",dateEndSecondStepPublish:"May 6th 2022",dateEndThirdStepPublish:"July 5th 2022",dateEndFourthStepPublish:"September 23rd 2022",dateEndFifthStepPublish:"November 22nd 2022",remainingDaysToSecondStep:"11 days",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Fiaz Ahmad is a researcher in the field of Agricultural Engineering with fifteen years of field and academic experience, currently in charge of the Agricultural Machinery Design Laboratory at Bahauddin Zakariya University. He applied for two patents at the national level.",coeditorOneBiosketch:"A renowned researcher in the field of Agricultural Engineering with 14 years of academic experience at Bahauddin Zakariya University. Winner of various prestigious fellowships, awards, and research grants. Published 250+ articles along with several books and chapters. Guest editor of seven ISI-SCI journals for publishers like SAGE, MDPI, and Frontiers.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"338219",title:"Dr.",name:"Fiaz",middleName:null,surname:"Ahmad",slug:"fiaz-ahmad",fullName:"Fiaz Ahmad",profilePictureURL:"https://mts.intechopen.com/storage/users/338219/images/system/338219.png",biography:"Dr. Fiaz Ahmad is an assistant professor and lecturer at the Department of Agricultural Engineering, Bahauddin Zakariya University, Multan, Pakistan. He obtained his Ph.D. in Agricultural Bioenvironmental and Energy Engineering from Nanjing Agriculture University, China, in 2015, and completed his postdoctorate in Agricultural Engineering from Jiangsu University, Zhenjiang, China, in 2020. He was awarded a fellowship from the Higher Education Commission of Pakistan for Ph.D. studies and from the Chinese Government for post-doctoral studies. He earned a BSc and MSc (Hons) in Agricultural Engineering from the University of Agriculture, Faisalabad, Pakistan, in 2004 and 2007, respectively. He is the author of more than fifty journal and conference articles. He has supervised six master’s students to date, and is currently supervising six master and two doctoral students. Dr. Ahmad has completed three research projects with his research interest focusing on the design of agricultural machinery, agricultural waste management, artificial intelligence (AI), and agricultural bioenvironment.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}}],coeditorOne:{id:"199381",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sultan",slug:"muhammad-sultan",fullName:"Muhammad Sultan",profilePictureURL:"https://mts.intechopen.com/storage/users/199381/images/system/199381.png",biography:"Muhammad Sultan is an Assistant Professor at the Department of Agricultural\r\nEngineering, Bahauddin Zakariya University, Multan (Pakistan). He completed his Ph.D.\r\nand Postdoc from Kyushu University (Japan) in the field of Energy & Environmental\r\nEngineering. He was an awardee of MEXT and JASSO fellowships (from the Japanese\r\nGovernment) during Ph.D. and Postdoc studies, respectively. He also did a Postdoc as\r\na Canadian Queen Elizabeth Advance Scholar at Simon Fraser University (Canada) in\r\nthe field of Mechatronic Systems Engineering. He worked for Kyushu University\r\nInternational Institute for Carbon-Neutral Energy Research (WPI-I2CNER) for two years.\r\nCurrently, he is working on 4 research projects funded by the Higher Education\r\nCommission (HEC) of Pakistan. He has completed six projects in past in the field of\r\nagricultural engineering. He has supervised 10+ M.Eng. and Ph.D. thesis and 10+\r\nstudents are currently working under his supervision. He has published 120+ journal\r\narticles, 100+ conference articles, 13 book chapters, and 6 books. He is serving as guest\r\neditor for the journals like Sustainability (MDPI), Agriculture (MDPI), Energies (MDPI),\r\nAdvances in Mechanical Engineering (SAGE), Frontiers in Mechanical Engineering, and\r\nEvergreen Journal of Kyushu University. His research is focused on developing energy-\r\nefficient temperature and humidity control systems for agricultural storage, greenhouse,\r\nlivestock, and poultry applications. 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1. Introduction
Climate is the biggest abiotical factor influencing the whole vegetation. At climate changing conditions adaptation ability of vegetation changes to grow in certain territory. Competitive abilities of plants are changing showing through new plant and weed biological qualities.
Global warming and climate change refer to an increase in average global temperatures. Global warming is primarily caused by increases in "greenhouse" gases (GHG). A warming planet thus leads to climate changes which can adversely affect weather in different ways. Some of the prominent indicators for a global warming are: temperature over land, snow cover and glaciers on hills, ocean heat content, sea ice, sea level, sea surface temperature, temperature over ocean, humidity, tropospheric temperature. Global warming in today’s scenario is threat to the survival of mankind [55]. Climate change inspired by global warming could lead to change of natural climatic zones, i.e. Tundra would disappear, Taiga would decrease essentially, Mediterranean climate zone would decrease and move to north, deserts and Arid world zones would move 400-800 km north to populous subtropical areas, main agricultural zones would move to north areas with low-fertile and worse soils [56, 57]. Global warming is closely associated as well with a broad spectrum of other climate changes, such as increases in the frequency of intense rainfall, decreases in snow cover and sea ice, more frequent and intense heat waves, rising sea levels, and widespread ocean acidification [55].
"The damage that climate change is causing and that will get worse if we fail to act goes beyond the hundreds of thousands of lives, homes and businesses lost, ecosystems destroyed, species driven to extinction, infrastructure smashed and people inconvenienced." – David Suzuki
Suzuki D. BrainyQuote.com, XploreInc, 2014. Available from http://www.brainyquote.com/quotes/quotes/d/davidsuzuk471841.html
Seasons of the years are constantly attended by the increase of marginal air conditions. Many researchers agree that anthropogenic activity is reason for climate change and it induced changes of the nature [1]. Agriculture and forestry take important place in Lithuanian national economy, therefore it is actual to adjust those sectors to climate change for mitigating consequences [2]. The constant competition between agricultural plants and weeds is seen in agro-ecosystems when the yields minimize. Alongside with other factors its progress can be explained by the plant resistance to abiotical factors. Different sensitivity of various varieties and their adaptability to the human activity may govern their relationship in agro-ecosystems. Thus, the adaptability of different abiotical factors for both agricultural plants and weeds should be estimated [3]. Weed spreading regularities are significantly dependent on weed ability to adapt, that is to adapt to changeable factors of environment.
Analogous weed chemical composition to agricultural plants induces competition in agrophytocenoses for growth factors. Weeds occupied place where agricultural plants could grow [4]. Adaptation possibility of separate plant species is different and can vary their competition as environment conditions change. It can cause serious agricultural problems. Undesirable change of plant species follows when environment conditions vary in ecosystems. Usually weeds signify by higher plasticity [5].
Biological invasions and climate warming are two major threats to the world’s biodiversity. To date, their impacts have largely been considered independently, despite indications that climate warming may increase the success of many invasive alien species [50].
The climate system is a complex, interactive system consisting of the atmosphere, land surface, snow and ice, oceans and other bodies of water, and living things. Climate is usually described in terms of the mean and variability of temperature, precipitation and wind over a period of time, ranging from months to millions of years (the classical period is 30 years) [6]. Observations of the climate system are based on direct measurements and remote sensing from satellites and other platforms. Global-scale observations from the instrumental era began in the mid-19th century for temperature and other variables. Paleoclimate reconstructions extended some records back hundreds to millions of years [7].
Changes in the atmospheric abundance of greenhouse gases and aerosols, in solar radiation and in land surface properties alter the energy balance of the climate system [8]. Global GHG emissions due to human activities have grown since pre-industrial times, with an increase of 70% between 1970 and 2004 (Figure 1). Annual CO2 emissions from fossil fuel combustion and cement production were 8.3 GtC12 yr-1 averaged over 2002-2011 and were 9.5 GtC yr-1 in 2011, 54% more than the level in 1990. Annual net CO2 emissions from anthropogenic land use change were 0.9 GtC yr-1 on average during 2002 to 2011 [7]. The global atmospheric concentration of carbon dioxide has increased from a pre-industrial value of about 280 ppm to 379 ppm in 2005 (Figure 2). The annual carbon dioxide concentration growth rate was larger during the last 10 years (1995-2005 average: 1.9 ppm per year), than it has been during 1960-2005 (average: 1.4 ppm per year) although there is year-to-year variability in growth rates [8]. In 2011 the concentrations of CO2 were 391 ppm, and exceeded the pre-industrial levels by about 40% [7].
Figure 1.
a) Global annual emissions of anthropogenic GHGs from 1970 to 2004. (b) Share of different anthropogenic GHGs in total emissions in 2004 in terms of carbon dioxide equivalents (CO2-eq). (c) Share of different sectors in total anthropogenic GHG emissions in 2004 in terms of CO2-eq (Forestry includes deforestation). Source: Climate Change 2007: Synthesis Report [9]
Figure 2.
Atmospheric concentrations of carbon dioxide over the last 10,000 years (large panels) and since 1750 (inset panels). Measurements are shown from ice cores (symbols with different colours for different studies) and atmospheric samples (red lines). The corresponding radiative forcings are shown on the right hand axes of the large panels. Source: IPCC, 2007: Summary for Policymakers [8]
The great part of GHG emissions locally, i.e. in Lithuania evaluating separate sectors of economy, is generated from energy supply objects and transport (Figure 3). It is in accordance with other developed industrial countries. As well it is forecasted increase of CO2 emissions till 2030 in all sectors of economy in Lithuania (Figure 3). Lithuania together with other modern world countries work solving global climate change problems. In Lithuania annual GHG emission terms of carbon dioxide equivalents (CO2-eq) covered about 4-5 tons per inhabitant and is one of the lowest in European countries where annual GHG of CO2-eq is about 3-15 tons per inhabitant [10].
Figure 3.
Present and forecasted share of anthropogenic GHGs in total emission in terms of carbon dioxide equivalent (CO2-eq) in Lithuania. Source: Ministry of Environment of the Republic of Lithuania [10]
Global warming is the increase of the average temperature of the Earth\'s near-surface air and the oceans since the mid-twentieth century and its projected continuation. Global mean surface temperature anomaly relative to 1961–1990 is presented in figure 4. Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decade since 1850 [7]. The warmest eleven years from twelve records in the world since 1850 were stated in the period of 1995-2006 [8].
Figure 4.
Global mean surface temperature anomaly relative to 1961–1990. Source: Climate Change 2007: The Physical Science Basis [8, 11, 12]
In Lithuania there was registered unique climate expression – even seven warm winters successively in the period of 1988/1989 – 1994/1995. Such long period of anomalously warm winters in the Baltic region were not registered during last 200 years [13]. Climate changes in Lithuania manifest through increasing air temperatures and precipitation during winter and slightly increase of air temperatures and decrease of precipitation during summer time [14].
Dynamics of average air temperature in Lithuania during 1961–2006 is presented in figure 5. The results from three locations, i.e. Klaipėda, Kaunas and Vilnius, showed increasing calculated trend-lines (dotted lines) and actual air temperature variation (solid lines).
Lithuanian average year air temperature in 1991–2006 increased by 0.7-1.0 °C relatively to 1961-1990 (Figure 6). That shows fast local climate warming in Lithuania. Climate warming tendencies are the most expressed in North and West Lithuania. Therefore, the last 16 year (1991-2006) average air temperature in Lithuania overcame the limit of 6°C.
Figure 5.
Average year air temperature (°C) change dynamics linear trends (dotted lines) in Lithuania during 1961–2006. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]
Figure 6.
Lithuanian average year air temperature (°C) in 1961–1990. The air temperature differences between 1961-1990 and 1991-2006 are shown by isolines. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]
During the second half of the 20th century and early part of the 21st century, global average surface temperature increased and sea level rose. Over the same period, the amount of snow cover in the Northern Hemisphere decreased (Figure 7). If radiative forcing was to be stabilised in 2100 at A1B levels, thermal expansion alone would lead to 0.3 to 0.8 m of sea level rise by 2300 (relatively to 1980–1999) [8].
The best estimates and likely ranges for global average surface air warming for six SRES emissions marker scenarios are shown in figure 8. Including uncertainties in the future greenhouse gas concentrations and climate sensitivity, the IPCC, scientific intergovernmental body set up by the World Meteorological Organization (WMO) and by the United Nations Environment Programme (UNEP), anticipates a warming of 1.1°C to 6.4°C by the end of the 21st century, relatively to 1980–1999 [8].
The globally averaged combined land and ocean surface temperature data show a warming of 0.85°C, over the period of 1880 to 2012. The total increase between the average of the 1850–1900 and the 2003–2012 periods is 0.78°C. For the longest period when calculation of regional trends is sufficiently complete (1901 to 2012), almost the entire globe has experienced surface warming [7]. If radiative forcing was to be stabilised in 2100 at B1or A1B levels (Figure 8), a further increase in global average temperature of about 0.5°C would be still expected, mostly by 2200. Thermal expansion would continue for many centuries, due to the time required to transport heat into the deep ocean [8].
Figure 7.
Changes in global average temperature, global average sea level and Northern Hemisphere snow cover. Source: Climate Change 2007: The Physical Science Basis, Summary for Policymakers, IPCC [8]
Figure 8.
Global warming: estimations of past and future global warming. Source: Climate Change 2007: The Physical Science Basis, Summary for Policymakers, IPCC [8]
Over the last two decades, the Greenland and Antarctic ice sheets have been losing mass, glaciers have continued to shrink almost worldwide, and Arctic sea ice and Northern Hemisphere spring snow cover have continued to decrease in extent [7]. Analogous to global tendencies, due to warming climate, day number with snow cover became more unstable and is being decreasing in Lithuania. Day number with snow cover during 1991-2006 relatively to 1961-1990 averagely decreased by 4-10 days (Figure 9). However, during winter emerging maximal snow cover thick increased by 0.8-2.0 cm. It is connected with last year’s increase of cold season precipitation amount and more often heavy snowing [10].
Figure 9.
Average number of days with snow cover in Klaipėda, Kaunas and Vilnius, Lithuania during 1961-1990 and 1991-2006. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]
Projected global average surface warming for 2020-2029 and the end of the 21st century (2090–2099) relatively to 1980–1999 are shown in figure 10. Projected warming in the 21st century shows scenario independent geographical patterns similar to those observed over the past several decades. Warming is expected to be the greatest over land and at the highest northern latitudes, and the least over the Southern Ocean and parts of the North Atlantic Ocean (Figure 10) [8].
Figure 10.
Projected changes in mean surface temperature by the late 21st century according to the A1B climate change scenario. All values for the period 2020-2029 and 2090–2099 are shown relatively to the mean temperature values for the period of 1980–1999. Source: Climate Change 2007: The Physical Science Basis, Summary for Policymakers, IPCC [8]
2. Material and methods
Lithuanian territory situated between 53o54’N and 56o27’N latitude, 20o56’E and 26o51’E longitude [53] occupies intermediate geographical position between west European oceanic climate and Eurasian continental climate. Cold air masses transfered from Arctic induce decrease of air temperatures which is reason of spring and early autumn frosts and of hard frost in winter time. Warm air masses from tropics are seldom which form thaws during winter and clear hot days during summer. Climate of the Lithuanian territory forms in different radiation and circulation conditions. Differences in these conditions hardly cross the boundaries of microclimatic differences; therefore, Lithuania belongs to western region of the Atlantic Ocean continental climatic area [45, 52] with average annual precipitation of 675 mm (572-907 mm) and temperature of 6-7oC [53, 54].
Phytotron vegetative pot experiments. The plastic pots (capacity of 5 L) substrata of turf (pH 6.0-6.5) were used. Till the emergence of white goosefoot Chenopodium album L. and one week after, pots were kept in a greenhouse, and then moved to the phytotron for 2 weeks. The emerged weeds were thinned out to 25 seedlings per pot. Results were evaluated after 21 days from weed emergence. Length of sprouts was measured (mm) and weed biomass (g per pot) was established oven-dried at 65oC.
Investigated weed genus white goosefoot Chenopodium album L. is widely spread in Europe, Asia and belongs to cosmopolitan group of plants. C. album is spread in agricultural lands and set–aside all over the world [15, 16]. White goosefoot C. album is annual hardly exterminated weed because one plant can give about 100,000 or till 200,000 seeds that germinate not all at once [15, 17].
2.1. Complex effect of CO2 and temperature
The experimental factor was the environment of contrasting carbon dioxide (CO2) concentrations and temperature level combinations.
Four levels of CO2 concentration:
350 ppm (control treatment)
700 ppm
1500 ppm
3000 ppm
Two levels of temperature regimes:
21oC/17oC (control treatment)
25oC/21oC
CO2 concentration, temperature regimes and their combinations were tested in the Phytotron vegetative pot experiments.
Concentration of CO2 was regulated using CO2 cylinder-reservoir controlled by CO2 measurer “CO2RT-5” (produced by Regin, Sweden). Photoperiod 16/8 h was achieved using high-pressure sodium (HPS) lamps SON-T Agro (Philips). The level of background radiation (PAR) made 170 micro-mol m-2 s-1. PAR was measured with RF-100 Radiometer-Photometer with G.PAR-100 detector cell (produced by Sonopan, Poland).
2.2. Effect of UV-B radiation
Six levels of UV–B radiation (wavelength 290-320 nm) were tested:
0 kJ m-2 d-1(control treatment)
1 kJ m-2 d-1
3 kJ m-2 d-1
5 kJ m-2 d-1
7 kJ m-2 d-1
9 kJ m-2d-1
To generate the chosen UV–B radiation Medical lamps “Philips TL 40W/12 RS” UV–B were used.
2.3. Effect of ozone
Four levels of ozone concentrations were tested:
0 µg m-3 (control treatment)
120µg m-3
240 µg m-3
360 µg m-3
The selected ozone concentration was reached using the ozone generator OSR-8 (Ozone Solutions, Inc.) 5 days per week, 7 hours per day. Ozone concentration was measured by the mobile ozone measuring equipment OMC-1108 (Ozone Solutions, Inc.).
2.4. Complex effect of UV-B radiation and ozone
Combination influence of two levels of ozone concentrations 120 µg m-3 and 360 µg m-3 with two levels of UV–B radiation: 3 kJ m-2d-1and 9 kJ m-2 d-1was tested.
Experimental schema of UV–B radiation and ozone combinations is as follows:
CT – control treatment, the plants were not exposed to either ozone or UV-B.
O3+O3 – plants exposed to 120 µg m-3 ozone concentration and later to the supplemental 360 µg m-3 ozone concentration.
O3+UVB – plants exposed to 120 µg m-3 ozone concentration, and later to the supplemental 9 kJ m-2 d-1 UV-B radiation.
UVB+UVB – plants exposed to 3 kJ m-2 d-1 UV-B radiation and later to the supplemental 9 kJ m-2 d-1 UV-B radiation.
UVB+O3 – plants exposed to 3 kJ m-2 d-1 UV-B radiation, and later to the supplemental 360 µg m-3 ozone concentration.
CT+O3 – plants exposed to 360 µg m-3 ozone concentration.
CT+UVB-plants exposed to 9 kJ m-2 d-1 UV-B radiation.
2.5. Complex effect of ozone and temperature
Experimental photoperiod is 14/10 h. Ozone impact duration is 12 days.
Three levels of ozone concentrations:
20 µg m-3 (control treatment)
40 µg m-3
80 µg m-3
Two levels of temperature regimes:
21oC/14oC (control treatment)
25oC/16oC
2.6. Complex effect of UV-B radiation and temperature
Experimental photoperiod is 14/10 h. Impact duration is 8 days.
Three levels of UV–B radiation:
0 kJ m-2 d-1 (control treatment)
2 kJ m-2 d-1
4 kJ m-2 d-1
Two levels of temperature regimes:
21oC/14oC (control treatment)
25oC/16oC
The experiments were conducted in three replications [18].
Data analysis. The collected data of the experiments were analysed by means of ANOVA. The treatment effects were tested for significance using the Sigma Stat software package [19] and the Selekcija software package [20].
3. Auto-ecological adaptability of weeds
Weeds are plants growing in undesirable places (i.e. crops and etc.) by human and competing with cultural plants for the growth factors and elements. Cultural plants can be counted as weeds if they are growing in crops of other cultural plants, for example, rye in wheat and etc. Autoecology is the branch of ecology which deals with individual species and their reactions to environmental factors. Adaptivity is the ability to react to change; adaptability allows the plant (weed) to function despite changes in the environment.
3.1. Complex effect of CO2 and temperature
During the past decades the climate change and environment pollution became the important factors influencing the plant growth, development and productivity. The anthropogenic activity constantly changes the abiotical factors that surround us. The increasing air temperature, carbon dioxide, ozone, UV-B radiation and etc. are the factors constantly felt by the plants and their ability to adapt to the changing situation secures their productivity and agro-ecosystem stability [3].
Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system [7]. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. Climate-carbon cycle coupling is expected to add carbon dioxide to the atmosphere as the climate system warms, but the magnitude of this feedback is uncertain. Based on current understanding of climate-carbon cycle feedback, model studies suggest that to stabilise at 450 ppm carbon dioxide could require that cumulative emissions over the 21st century would be reduced from the average of approximately 670 GtC (2460 GtCO2) to approximately 490 GtC (1800 GtCO2). Similarly, to stabilise at 1000 ppm, this feedback could require that cumulative emissions would be reduced from the model average of approximately 1415 GtC (5190 GtCO2) to approximately 1100 GtC (4030 GtCO2) [6, 8]. Depending on the scenario, about 15 to 40% of emitted CO2 will remain in the atmosphere longer than 1,000 years [7]. This could result in the global climate change. Plants react to the increased concentration of CO2, therefore this can trigger the processes of plant biomass accumulation [21].
Carbon dioxide as the carbon source used to synthesize the plant biomass is a very important abiotical factor in agriculture. Estimating the influence of CO2 concentration for the growth of white goosefoot Chenopodium album L., the control treatment was compared with 350 ppm CO2. Gradually CO2 concentration was increased up to 700 ppm and 1500 ppm and it maximized the growth of white goosefoot and its biomass accumulation on the regular basis. When CO2 concentration was increased up to 3000 ppm, the growth of C. album was reduced but still remained greater than CO2 concentration in the control treatment (Figure 11). This means, that C. album can successfully adapt to the twice as great CO2 concentrations, but it reaches the limit of the maximum growth. Other researchers [51] estimated also more intensive growth of other crop weed – Parthenium hysterophorus L. (whitetop weed) under a climate change scenario involving an elevated atmospheric CO2 (550 µmol mol-1) concentration. P. hysterophorus plants grew significantly taller (52%) and produced more biomass (55%) than under the ambient atmospheric CO2 concentration (380 µmol mol-1) [51].
The increasing concentration of atmospheric CO2 is observed to increase plant photosynthesis and plant growth, which drives an increase of carbon storage in terrestrial ecosystems. However, plant growth is constrained by the availability of anthropogenic reactive nitrogen (Nr) in soils. This means that in some nitrogen-poor ecosystems, insufficient Nr availability will limit carbon sinks, while the deposition of Nr may instead alleviate this limitation and enable larger carbon sinks [22].
Figure 11.
Chenopodium album L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm) under different CO2 concentrations [23]
In addition to land use and climate-induced vegetation changes, CO2 affects vegetation forcing indirectly, reducing transpiration from plants as stomata open less with increasing CO2, resulting in localized atmospheric drying and warming [22, 24].
Figure 12.
Chenopodium album L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm) under different combinations of temperature regimes and CO2 concentrations [23]
Continuing experiment under controlled phytotron conditions, complex impact of actual and forecasted CO2 and temperature to the growth of white goosefoot C. album were tested (Figure 12). Increase of temperature to forecasted 25oC/21oC initiates growth of white goosefoot more quickly and accumulates its biomass more intensively. But the increase of CO2 concentration up to 700 ppm at this forecasted temperature starts to inhibit the growth of white goosefoot and its roots (Figure 12). It was established that the most favourable conditions for C. album early growth were at higher temperature regime 25oC/21oC with both CO2 concentrations. However, for the root growth initiation, especially, optimal conditions were with lower – 350 ppm – CO2 concentration (Figure 12). Higher CO2 concentration 700 ppm with actual lower temperature regime 21oC/17oC showed the negative influence on early growth of C. album.
3.2. Effect of UV-B radiation
The shorter are waves of the radiation, the greater is the effect of the ultraviolet radiation on living organisms [25, 26]. Molecule alternations and damages inevitably alter other processes: activity of genes, metabolism, intensity of photosynthesis which, consequently, influence the growth of the plant [27]. The reduction of the photosynthesis intensity due to the impact of UV-B radiation is related to slight conductance of stomata and the quantity of photosynthetic pigments [28]. Height and biomass of the majority of plant species have a tendency to reduce due to the UV-B radiation [28-30].
Experimental data showed that low UV-B radiation of 0, 1 and 3 kJ m-2 d-1 had a positive effect on early growth of Chenopodium album white goosefoot (Figure 13). C. album can accumulate up to 30% of biomass in excess in the background of 1 kJ m-2 d-1 UV-B radiation with reference to the control treatment. Increasing the intensity of UV-B radiation, the length of the Chenopodium album L. over-ground part was systemically decreasing. Consequently, as UV-B radiation constantly increased up to 9 kJ m-2 d-1, the length of C. album over-ground part starting from 3 kJ m-2 d-1 gradually decreased by 28%. The over-ground part biomass of the C. album was decreasing respectively when increasing the UV-B radiation. The least over-ground part and root biomass of C. album were accumulated at the 9 kJ m-2d-1 UV-B radiation. Gradually increasing UV-B radiation till 9 kJ m-2d-1 C. album biomass decreased till 2 times compared it to the control treatment 0 kJ m-2 d-1 (Figure 13).
Figure 13.
The above-ground and root biomass from a pot (g) and seedling length (mm) of Chenopodium album L. white goosefoot under different UV–B radiation (kJ m-2 d-1) levels [31]
3.3. Effect of ozone
When the ozone layer in the stratosphere becomes thinner, the ozone concentration at the soil surface increases. Ozone concentration at the soil surface is also insecure to the plant development [3]. The ozone gas acts as strong oxidator in the plant cells and destabilizes the vital functions [32]. Short impact of ozone may cause various injuries to leaves, moreover, under the long-term continuous influence plants become less, the crop decreases, leaves are injured [33, 34]. Ozone adds to quicker senescence of plant leaves and their early fall. These processes are determined by the increase of free radicals in the plant cells [35, 36].
Evaluating the effect of ozone concentration on C. album white goosefoot growth, it has been established that the increasing ozone concentration had no statistically reliable impact on C. album growth, however, the tendency of over-ground part length (p=0.074) and air-dry biomass (p=0.958) decreasing was observed (Figure 14). The sprout height decreased by 15.4%, 16.8% and 2.0% in ozone concentration of 120 µg m-3, 240 µg m-3 and 360 µg m-3 accordingly, compared it with the control treatment. C. album white goosefoot have lost 20.3%, 5.2% and 21.1% their sprout air-dry biomass at ozone concentration of 120 µg m-3, 240 µg m-3 and 360 µg m-3 in respond to control treatment of 0 µg m-3 of ozone, respectively.
Plants are known to suffer damage due to exposure to levels of ozone (O3) above about 40 ppb [22, 37]. It is established that surface ozone detrimentally affects plant productivity [38]. Tropospheric ozone can also affect the natural uptake of CO2 by decreasing plant productivity [22].
Figure 14.
The Chenopodium album L. white goosefoot air-dry biomass and length of the over-ground part under the influence of ozone [31]
3.4. Complex effect of UV-B radiation and ozone
Ozone layer absorbs the greatest part of UV rays radiated by the Sun and other space bodies and protects plants and live organisms from their negative impact. Ozone depletion would increase the amount of ultraviolet light reaching the surface damaging terrestrial and marine ecosystems [22]. Since the beginning of the eight decade of the XX century the rapid breaking of the ozone layer in the stratosphere has been noticed as well as the increase of the intensity of UV radiation.
Ozone O3 formed in the troposphere as a result of NOx and volatile organic compound emissions reduces plant productivity, and therefore reduces CO2 uptake from the atmosphere [22]. The depletion of the ozone layer is induced by the pollutants containing chlorine and bromine ions released into the environment [39]. The thickness of the ozone layer has the greatest impact on the flow of the UV-B radiation [25, 26].
During the complex research (Table 1) the negative impact of ozone and UV-B radiation on white goosefoot C. album growth increased in comparison to the impact of ozone (Figure 14) and UV-B (Figure 13) when effecting separately. C. album is unable to adapt to the increasing UV-B radiation and the intensifying complex impact of ozone and UV-B.
Treatment
Over-ground plant part
Root
After the first action
After the second action
Sprout length, mm
Sprout length, mm
Green biomass, g pot-1
Air-dry biomass, g pot-1
Green biomass, g pot-1
Air-dry biomass, g pot-1
#CT
44.17
48.38
54.04
12.37
10.19
1.77
O3+O3
50.33*
54.74 **
38.27*
11.50
10.60
1.90
O3+UVB
51.00*
51.90*
46.69
10.82
12.73
1.98
UVB+UVB
47.53
47.98
45.83
12.10
9.60
1.75
UVB+O3
51.13*
52.20*
35.58*
10.26
11.43
1.81
CT+O3
49.63*
56.12**
37.84*
10.01
10.34
1.90
CT+UVB
51.83**
53.72*
50.11
12.92
14.86
2.07
P
0.017
0.001
0.024
0.398
0.071
0.820
Table 1.
Chenopodium album L. white goosefoot biomass and length of the over-ground part after the exposure to both ozone and UV-B radiation [31]
Note. #CT – control treatment; significant differences from control treatment (#CT) at * P < 0.05 and **-at P < 0.01
3.5. Complex effect of ozone and temperature
Continuing research of ozone concentration, impact on white goosefoot Chenopodium album growth, complex effect of ozone concentration 20, 40 and 80µg m-3 and of actual and forecasted climate temperature regimes were evaluated (Figure 15). Increase of the ozone concentration from 20 µg m-3, increased accumulation of C. album sprout air-dry biomass by 74% at 40 µg m-3 and by 68% at 80 µg m-3 and root air-dry biomass by 280% at 40 µg m-3 and by 200% at 80 µg m-3 in the actual climate temperature conditions 21°C/14°C. At forecasted climate higher temperature (25°C/16°C), the rising ozone concentration from 20 to 40 and 80µg m-3 increased the accumulation of C. album sprout air-dry biomass by 27-33% and root air-dry biomass by 23-50%, accordingly. Investigated ozone concentration and temperature regimes complex had no significant effect on C. album plant height (Figure 15). It was established that C. album is adapted to the actual and forecasted climate temperature and ozone concentration variations till 80 µg m-3 of ozone in the environment. Increasing ozone concentration further till 120, 240 and 360 µg m-3, there was observed negative effect on C. album growth and abilities to adapt to higher ozone concentration were not determined (Figure 14).
The sprout root ratio of air-dry biomass changing concentration of ozone at different levels of temperatures showed, that C. album root growth was 3.5-5.8 times more intensive at forecasted than at actual climate temperature regimes (Lithuanian conditions). At actual climate temperature under ozone concentration of 20, 40 and 80 µg m-3 white goosefoot C. album sprout root ratio of air-dry biomass covered 39.8, 24.8 and 33.5 and at forecasted climate temperature covered 6.9, 7.1 and 6.1, accordingly.
Figure 15.
The influence of ozone on Chenopodium album L. white goosefoot growth at actual and forecasted climate temperature [40]
3.6. Complex effect of UV-B radiation and temperature
At changing climate conditions competitive abilities of plants are changing showing through new weed biological qualities. Increase of weed ability of over-wintering for weed species that during winter time traditionally were frosting at conventionally colder climate conditions [41, 42]. It was established that during winter time in winter wheat crop annual weeds, even some summer annual ones, had increased adaptivity of successful surviving winter frosts and accumulated higher one plant average mass by 5-6% during winter time; especially when the weather is favourable for prolonged development of weeds even at low density of perennial weeds in the crop [42-44]. Even short-time brief changes of meteorological conditions in crop during vegetation are inducing mechanism of plant/weed adaptivity. Namely, weed seed rain in the crop regularly intensified with increase of temperature and sunlight duration and vice versa [45, 46]. Under heavily polluted or dark cloudy skies, plant productivity may decline as the diffuse effect is insufficient to offset decreased surface irradiance [47]. Plants need a certain amount of UV-B radiation. They stimulate biochemical processes and inhibit to fast plant growing and slow accumulation of air-dry biomass [48]. Due to UV-B radiation height and air-dry biomass of many plant genus decrease [28, 29]. The intensity of UV-B radiation is determined by the seasson, day and night period and meteorological conditions. According to the data of Kaunas meteorological station and Palanga avia-meteorological station, the average UV-B radiation doses during clear summer days reach 2.1–2.5 kJ m-2 d-1 [49].
UV-B radiation
Over-ground part
Root
Over-ground part and root ratio
Height cm
Green mass g
Air-dry mass g
Green mass g
Air-dry mass g
Green mass
Air-dry mass
Actual climate temperature 21°C/14°C
0 kJ m-2 d-1
7.10
28.27
1.89
2.35
0.25
12.0
7.6
2 kJ m-2 d-1
5.53**
11.63**
1.01*
1.12*
0.13*
10.4
7.8
4 kJ m-2 d-1
6.31**
5.02**
0.53**
0.88*
0.09*
5.7
5.9
P
0.001
0.001
0.002
0.040
0.013
–
–
Forecasted climate temperature 25°C/16°C
0 kJ m-2 d-1
21.36
68.89
6.05
2.92
0.54
23.6
11.2
2 kJ m-2 d-1
14.47**
34.73**
3.22**
1.89
0.28**
18.4
11.5
4 kJ m-2 d-1
12.22**
15.38**
1.63**
0.94*
0.16**
16.4
10.2
P
0.001
0.001
0.001
0.017
0.002
–
–
Table 2.
The influence of UV-B radiation on white goosefoot C. album growth at actual and forecasted climate temperature [40]
Note. * – significant differences from the control treatment (0 kJ m-2 d-1) at P < 0.05 and ** – at P < 0.01.
The next experiment increasing UV-B radiation intensity till 4 kJ m-2 d-1 showed significant negative influence on white goosefoot C. album development already at UV-B radiation 2 kJ m-2 d-1 at both-actual 21°C/14°C and forecasting 25°C/16°C climate temperature regimes (Table 2).The over-ground green biomass of C. album effected by UV-B radiation of 4 kJ m-2 d-1decreased 5.6 and 4.5 times at actual and forecasted climate temperature respectively compared it with the control treatment (UV-B radiation 0 kJ m-2 d-1), while root green biomass decreased 2.7 and 3.1 times, accordingly. C. album over-ground part and root air-dry biomass accumulation decreased nearly twice (1.9 times) already at UV-B radiation 2 kJ m-2 d-1 at both temperature regimes and declined till 3.6-3.7 and 2.8-3.4 times at UV-B radiation 4 kJ m-2 d-1, accordingly. Increasing intensity of UV-B radiation, C. album height growth inhibited significantly as well. The highest evaluated UV-B radiation in the experiment decreased plant height by 11% at actual climate temperature and by 43% at forecasted warmer climate temperature. Received data of experiment confirmed that C. album is sensitive to UV-B radiation in actual colder and forecasted warmer temperature regimes. C. album plant over-ground part and root green and air-dry biomass ratio with increase of UV-B radiation regularly decreased. It could be result of plant protection mechanism activation intensifying transpiration process.
4. Conclusions
Plant ability to survive under unfavourable conditions depends upon the intensity and character of the unfavourable factors. Abiotical factors of low intensity influencing plants induce weed growth, however, weed growth is regularly smothered as their intensity increases.
Increase of CO2 concentration positively affected the early growth of white goosefoot Chenopodium album L. and reached the optimum at 1500 ppm. Higher temperature regime 25oC/21oC compared with 21oC/17oC compounded more favourable conditions for C. album early growth at both – 350 ppm and 700 ppm – CO2 concentrations. White goosefoot successfully adapts even to several times increased concentration of CO2.
Minor UV-B radiation concentrations 1-3 kJ m-2 d-1 induced C. album growth; however, the increasing UV-B radiation (5-9 kJ m-2 d-1) reliably decreased both the length of the over-ground part and the biomass of white goosefoot.
Increasing ozone concentration to 120, 240 and 360 µg m-3 had a tendency to suppress C. album growth by 2-14% of its sprout length and by 5-17% of its accumulated air-dry biomass. However, complex investigation of ozone and temperature showed that C. album is adapted to actual and forecasted climate temperature and ozone concentration variations till 80 µg m-3 of the environment.
Complex investigation of UV-B radiation and temperature showed significantly negative influence on C. album growth and biomass accumulation already at UV-B radiation 2 kJ m-2 d-1 of both actual 21°C/14°C and forecast 25°C/16°C climate temperature regimes.
Joint action of ozone and UV-B radiation on C. album growth increased negative effect relatively to separate impact of ozone and UV-B. White goosefoot in early growth stage is unable to adapt to increasing UV-B radiation (>3 kJ m-2 d-1) and the intensifying complex impact of ozone and UV-B.
The experimental results suggest that in long-term (more than 30 years) time period weeds are well adapted to changing climate conditions and will become more competitive in temperate climate zone. For successful weed control in the crop of agricultural plants present weed control methods and strategy should be reviewed and improved adapting them to threats of global warming and climate change.
Acknowledgments
The Lithuanian State Science and Studies Foundation as a part of the research project "Complex effect of anthropogenic climate and environment changes on the forest and agro ecosystem flora" supported this research.
We would like to thank Vilma Pilipavičienė for the manuscript English reviewing linguistically.
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Introduction",level:"1"},{id:"sec_2",title:"2. Material and methods",level:"1"},{id:"sec_2_2",title:"2.1. Complex effect of CO2 and temperature",level:"2"},{id:"sec_3_2",title:"2.2. Effect of UV-B radiation",level:"2"},{id:"sec_4_2",title:"2.3. Effect of ozone",level:"2"},{id:"sec_5_2",title:"2.4. Complex effect of UV-B radiation and ozone",level:"2"},{id:"sec_6_2",title:"2.5. Complex effect of ozone and temperature",level:"2"},{id:"sec_7_2",title:"2.6. Complex effect of UV-B radiation and temperature",level:"2"},{id:"sec_9",title:"3. Auto-ecological adaptability of weeds",level:"1"},{id:"sec_9_2",title:"3.1. Complex effect of CO2 and temperature",level:"2"},{id:"sec_10_2",title:"3.2. Effect of UV-B radiation",level:"2"},{id:"sec_11_2",title:"3.3. Effect of ozone",level:"2"},{id:"sec_12_2",title:"3.4. Complex effect of UV-B radiation and ozone",level:"2"},{id:"sec_13_2",title:"3.5. Complex effect of ozone and temperature",level:"2"},{id:"sec_14_2",title:"3.6. 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Chemosphere 2001; 42(8) 945-953.'},{id:"B33",body:'Krupa S.V., Grunghoge L., Jager H.J., Nosal M., Legge A.H., Hanawald K. Ambient ozone and adverse crop response: a unified view of cause and effect. Environmental Pollution 1995; 99 398-405.'},{id:"B34",body:'Reddy K.R., Hodges H.F. Climate change and global Crop Productivity. CABI Publishing. 2000. 472 p.'},{id:"B35",body:'Farage P.K., Long S.P., Lechner E.G., Baker N.R. The sequence of changes within the photosynthetic aparatus of wheat following shortterm exposure to ozone. Plant Physiology 1991; 95 529-535.'},{id:"B36",body:'Fumagalli I., Gimeno B.S., Velissariou D., de Temmermand L., Millse G. Evidence of ozone-induced adverse effects on crops in the Mediterranean region. Atmospheric Environment 2001; 35(14) 2583-2587.'},{id:"B37",body:'Ashmore M.R. Assessing the future global impacts of ozone on vegetation. Plant Cell and Environment 2005; 28 949-964.'},{id:"B38",body:'Fishman J., Creilson J.K., Parker P.A., Ainsworth E.A., Vining G.G., Szarka J., Booker F.L., Xu X. An investigation of widespread ozone damage to the soybean crop in the upper Midwest determined from ground-based and satellite measurements. Atmospheric Environment 2010; 44 2248-2256.'},{id:"B39",body:'Rozema J., van de Staaij J., Bjorn L. O., Caldwell M. UV–B as an environmental factor in plant life: stress and regulation. Trends in Ecology & Evolution 1997; 12 22-28.'},{id:"B40",body:'Romaneckienė R., Pilipavičius V., Romaneckas K. The influence of ozone and UV-B radiation on fat-hen (Chenopodium album L.) growth in different temperature conditions. Žemdirbystė-Agriculture 2008; 95(4) 122-132.'},{id:"B41",body:'Pilipavičius V., Romaneckas K., Gudauskienė A. Weed Seedling Over-Wintering and Vegetation Dynamics in Organically Grown Winter Wheat Spelt Crop under Climate Changing Conditions. 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Journal of Food, Agriculture & Environment 2010; 8(2) 456-459.'},{id:"B45",body:'Pilipavičius V. Weed seed rain dynamics and ecological control ability in agrophytocenosis. In: Herbicides-Advances in Research. Edited by Price A. J. and Kelton J. A. Rijeka: InTech. 2013. p. 51-83. Available from http://cdn.intechopen.com/pdfs-wm/43456.pdf (accessed 12 May 2014)'},{id:"B46",body:'Pilipavičius V. Piktžolių sėklų byrėjimo priklausomumas nuo meteorologinių faktorių / Dependence of Weed Seed Falling on Meteorological Factors, Precipitation and Sunlight Duration. Vagos 2002; 53(6) 17-21.'},{id:"B47",body:'UNEP, 2011: Integrated assessment of black carbon and tropospheric ozone: Summary for decision makers. United Nations Environment Programme and World Meteorological Association. 2011. 38 p.'},{id:"B48",body:'Wei G., Zheng Y., Slusser J.R., Heisler G.M. Impact of enhanced ultraviolet – B radiation on growth and leaf photosynthetic reaction of soybean (Glicine max). 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Vilnius: Mokslo ir enciklopedijų leidybos institutas; 2007. Vol.12. 47-57.'},{id:"B54",body:'Pilipavičius V., Grigaliūnas A. Lithuanian Organic Agriculture in the Context of European Union. In: Organic Agriculture towards Sustainability. Edited by Pilipavičius V. Rijeka: InTech. 2014. p. 89-121. DOI: 10.5772/58352. Available from: http://cdn.intechopen.com/pdfs-wm/46459.pdf (accessed 30 May 2014)'},{id:"B55",body:'Singh B.R., Singh O. Study of Impacts of Global Warming on Climate Change: Rise in Sea Level and Disaster Frequency. In: Global Warming-Impacts and Future Perspective. Edited by Singh B.R. Rijeka: InTech. 2012. p. 93-118. DOI: 10.5772/50464. Available from: http://www.intechopen.com/books/global-warming-impacts-and-future-perspective/study-of-impacts-of-global-warming-on-climate-change-rise-in-sea-level-and-disaster-frequency (accessed 19 June 2014)'},{id:"B56",body:'Lazauskas P., Pilipavičius V. Agroekologija / Agroecology. Lietuvos žemės ūkio universitetas. Akademija [i.e.Klaipėda]: IDP Solutions. 2008. 140 p.'},{id:"B57",body:'Heinrich D., Hergt M. Ekologijos atlasas. Vilnius: Alma littera. 2000. 279 p.'}],footnotes:[{id:"fn1",explanation:"Suzuki D. BrainyQuote.com, XploreInc, 2014. Available from http://www.brainyquote.com/quotes/quotes/d/davidsuzuk471841.html"}],contributors:[{corresp:"yes",contributorFullName:"Vytautas Pilipavičius",address:"vytautas.pilipavicius@asu.lt",affiliation:'
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1. Introduction
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The unceasing increase in incidences of colorectal cancer (CRC) in recent decades has led to a rise in the number of medical tests being carried out; in the case at hand, colonoscopies. Specialists consequently have a greater amount of work, and find themselves overwhelmed. As a result of this problem, numerous investigations have been conducted in recent years focussing on developing tools to help with diagnoses, thereby supporting specialists. Development of algorithms for the automatic analysis of colonoscopy imaging requires preliminary pre-processing of the images in order to rectify the multiple factors that detract from their quality.
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The objective of this chapter is to shed light on the most common problems encountered in colonoscopic imaging, while also providing the most frequentlys-used solutions among the scientific community. The aim is to thusly supply useful information in order to develop automatic algorithms, which may then be implanted in robots that automate tasks currently requiring manual interaction.
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2. What is a colonoscopy?
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A colonoscopy is a method of reference for diagnosing and treating colonic diseases; essential to both colorectal screening and monitoring. This exploration enables the large intestine to be viewed in its entirety, to extract biopsies and to remove tumours.
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It has been proven that carrying out this procedure reduces the colon cancer mortality rate. Before undergoing the procedure, it is necessary for the patient to have been through a preparation phase, so that there is no solid waste in the colon. The procedure is performed by inserting a colonoscope—a flexible tube with a camera at the end—into the anus (see \nFigure 1\n). In some cases, a sedative is used so as to carry out the procedure without causing discomfort. It is the best means of detecting CRC since it enables localisation and, in the majority of cases, immediate extraction.
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Figure 1.
Colonoscope. Source: goo.gl/6qtSW9.
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3. Main problems of colonoscopies
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The principal difficulties in obtaining colonoscopy imaging are described below; which, in many cases, are the result of the equipment used or the environmental difficulties.
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\nBlack mask: this is due to the fact that the lenses used in the colonoscopy image capturing system have a black frame around the edge. In many cases, the mask is used to convey information, either pertaining to the patient or the test being carried out. This black frame hinders the development of digital image processing algorithms since it creates false borders, as well as covering a larger area for analysis that would not yield useful information. For these reasons, applying different techniques to eliminate its effects becomes necessary. In \nFigure 2\n, the black mask in colonoscopy imaging can be observed.
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Figure 2.
Black mask.
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\nGhost colours: the problem of ghost colours (see \nFigure 3\n) is linked to a lack of synchronisation of the colour channels. Its appearance is due to the fact that most colonoscopy equipment uses monochromatic cameras, in which the components R, G, and B are obtained at different times. This causes a reduction in the quality of the image, making the subsequent development of PDI algorithms difficult.
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Figure 3.
Ghost colours.
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\nInterlacing: interlacing allows twice the number of frames per second to be taken without consuming additional bandwidth. It is used in standard formats such as the National Television System Committee (NTSC) or phase alternating line (PAL), and shows half of the horizontal lines in each iteration. Each frame is divided into two fields: the first contains odd-numbered lines and the second field the even-numbered lines. Due to the phenomenon of the persistence of the human eye, the brain mixes both iterations of the interlaced frame, identifying it as one image. The effects of interlacing cause the appearance of false outlines in the images (see \nFigure 4\n), which make the development of algorithms more complicated. Therefore, it is necessary to implement techniques to reduce its occurrence.
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Figure 4.
Effects of interlacing.
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\nSpecular highlights: specular highlights (see \nFigure 5\n) are points of high intensity in the image due to the illumination of shiny objects. When a source of light is shone directly on an object, the light is reflected and captured by the camera. This process generates heavily saturated areas in the image, which can lead to unwanted outlines, making it subsequently difficult to process the image. This effect is extremely important in the detection of polyps, which are generally rounded and similar to tumours. Due to their shape, they reflect light and generate specular highlights when illuminated, which can lead to a malfunction of the developed algorithms.
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Figure 5.
Specular highlights.
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\nUneven lighting: the variations in the intensity and direction of lighting are decisive in the appearance of objects in digital images. The illumination of the colon in a colonoscopy is variable, which, because of the colon’s three-dimensional shape, causes shadows to appear, accentuating or diminishing certain aspects of the image. Varying degrees of illumination on the same object cause differing representations of the object, rendering said variability of lighting unwanted. In the literature, there are numerous publications that address this problem. In \nFigure 6\n, an example of uneven lighting in colonoscopic imaging is shown in order to facilitate its detection.
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Figure 6.
Uneven lighting.
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4. What is the pre-processing of colonoscopic images?
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Every image capturing process is affected in some way by factors that reduce the quality of the image to some degree. Colonoscopic imaging is no exception, so it is necessary to implement techniques that help to improve the quality and thereby obtain a better visual representation.
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Any technique whose objective is to contrast, highlight, accentuate or remove unwanted effects from the image is considered a method of improvement. This is a process of vital importance in medical imaging, in which the limitations of the image capturing system—in the case at hand, colonoscopies—cause unwanted effects which need to be removed. It is crucial to point out that by improving imaging:
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No new information is added to the image; the image is only highlighted so as to be used more efficiently by the algorithms that are to be developed.
There is no exact criterion for quantifying the degree of improvement; in many cases, it is based on subjective opinions and/or on the result obtained by the developed algorithms.
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Below is an outline of the applicability of pre-processing colonoscopic imagery in robots which may be able to automate tasks that are vital in a colonoscopy.
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5. Applicability of pre-processing colonoscopic imagery in robots
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Faced with the growing number of diagnostic tests for colon cancer being carried out, it has become necessary to rely on support tools for medical diagnoses. These tools support the specialist by providing objective data, thereby enabling more accurate diagnoses.
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The main functions that endoscopists require are related to the automatic detection of polyps and the evaluation of the quality of the test being carried out.
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In the case of detecting polyps, having tools available that enable their automatic detection will mean a reduction in the number of missed tumours, which, in many cases, lead to interval cancers. Interval cancers are those that appear between two scheduled diagnostic tests and, in most cases, are due to a polyp or tumour that was not detected by the specialist during the procedure. In this context, publications such as [1–3] have made important contributions to the scientific community.
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Moreover, the quality evaluation of the procedure is a necessity, since many of the metrics are currently based on the specialist’s interpretation and are therefore subjective, impeding correct comparison among different health centres with the intention of improving the process. The European Guidelines for Quality Assurance in Colorectal Screening and Diagnosis [4] provide a series of metrics that evaluate different aspects of the colonoscopy. In this regard, publications such as [5–8] make valuable contributions to the scientific community.
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All research studies focused on the development of automated tools for the assistance of medical diagnoses share the need for the availability of an image pre-processing system. The availability of tools to improve the quality of the images is a necessity, as can be observed in investigation [9].
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All the methods for pre-processing imagery outlined in this chapter will be able to be implanted in robots and colonoscopies in such a way as to enable the development of various automated tools, which allows for significant higher reliability of colonoscopies.
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6. Pre-processing colonoscopic imagery
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Here, we describe the most frequently used techniques in the scientific community for removing the most common discrepancies in colonoscopic imagery. Solutions that have been proposed in the literature are outlined, and the most appropriate focus for each point has also been proposed.
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6.1. Removal of black borders
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In the literature, there are three tendencies for black border removal: the restoration of the image, the use of thresholding and cropping of the black mask. Following is a brief explanation of each method.
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Removal of the black mask through restoring the image: this involves replacing the pixels of the black mask using the median value of the pixels in a certain vicinity. This focus has been used in investigation [9], obtaining satisfactory results.
Removal of the black mask using thresholding: a threshold is set to detect the real frame of the image, removing the black mask. In many occasions, this focus does not manage to completely remove the black mask, leaving residual lines, which makes it necessary to apply techniques such as the Hough transform [10] to remove them. This technique was used in investigation [11].
Removal of the black mask through cropping the image: this is the simplest focus, in which an area of the image is selected and the rest is removed. This method involves obtaining a smaller image but maintaining the maximum amount of information possible from the original image, running the risk of losing valuable information.
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In this section, a suggestion for an alternative focus for the removal of black borders is presented. Depending on the model of colonoscope used, the black borders that are generated vary (see \nFigure 7\n), which makes pre-processing difficult. In many cases, the borders are used to provide information about either the patient or the procedure being carried out (see \nFigure 7(b)\n). This frame makes the development of PDI algorithms difficult, since it generates false borders, as well as entailing a greater area to be analysed that does not provide useful information. Due to these reasons, it is necessary to apply different techniques to remove their effects.
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Figure 7.
Black masks with different characteristics: (a) Black mask in the corners. (b) Circular black mask and with information. (c) Black mask bordering the image.
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There are various literary references to methods addressing this problem: reconstructing the borders by restoring them [9], the use of thresholding for their detection [11] and the cropping of the black mask. In this pre-processing design, a method combining the existing solutions was chosen. This technique involves detecting the black mask using thresholding, as well as cropping and reconstructing. \nFigure 8\n shows the process in which this task is carried out.
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Figure 8.
Removal of black borders.
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The following is a description of the steps to remove the black borders using the proposed method:
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\nConversion to Hue, Saturation, Value: in order to address the automatic detection of the black mask in colonoscopic images, it is necessary to convert them from the RGB colour model (the original colour model for colonoscopic imagery) to the HSV colour model. This is due to the fact that the RGB model makes certain colour specification difficult, whereas this is one of the HSV model’s strengths. Thanks to this, the thresholding described in the next step is made much more simple.
\nChannel V thresholding: once the conversion from the RGB colour model to HSV is complete, the image is ready for thresholding. Thresholding offers a wide range of intensity values from which to choose, allowing us to define among them those objects that we want to be detected automatically. In this chapter, channel V thresholding is proposed, in which values of 0.03 and lower are attributed to the black mask. This method enables the separation of useful content in the colonoscopic image from the black borders. This process can be observed in \nFigure 9\n, in which \nFigure 9(a)\n shows the process of Channel V thresholding and \nFigure 9(b)\n presents the result generated.
Depending on the model of colonoscope used to capture the images, the black borders may be different. This is a problem, since when thresholding is carried out to detect the black borders, the information shown in the borders will remain visible over the image. In order to remove it, an additional step is necessary which involves making a morphological opening by using a size-5 disk structure to the detected black mask. In this way, all the information shown on the black border is removed, leaving it clean. This process can be observed in \nFigure 10\n, in which \nFigure 10(a)\n shows the detected black mask with leftover information and \nFigure 10(b)\n shows the result of the morphological opening for its removal.
Once the thresholding of the image is complete, it is possible to proceed to the removal of the black borders.
\nBlack border removal: the process of black border removal comprises two steps: cropping and reconstructing. The following is a detailed description of both:
\nDetection of the upper central point not belonging to the black mask: starting from the pixel in position (max(X)/2.1) searching southwards, the first pixel does not belong to the black mask.
\nDetection of the lower central point not belonging to the black mask:\n starting from the pixel in position (max(X)/2.max(Y)) searching northwards, the first pixel does not belong to the black mask.
\nDetection of the centre-left point not pertaining to the black mask: starting from the pixel in position (1.max(Y)/2) searching eastwards, the first pixel does not belong to the black mask.
\nDetection of the centre-right point not pertaining to the black mask: starting from the pixel in position (max(X).max(Y)/2) searching westwards, the first pixel does not belong to the black mask.
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Once the four positions of the sought pixels have been obtained, a rectangle is generated whi ch contains them and will be what determines the dimensions of the image with the black borders cropped out. \nFigure 11\n shows a visual example of this process. The next step in removing the black borders is the reconstruction of the leftover black borders. This process is addressed in the following section.
\nReconstruction of the remnants of the black mask: in \nFigure 11\n it can be seen that the final area of the image highlighted in orange still contains remnants of the black borders. The final task for their removal is to reconstruct them. In order to do so, a restoration is applied which aims to replace the pixels of the black mask by the median value of the pixels in a certain vicinity. This operation is carried out repeatedly until the difference between the values of the neighbouring pixels used in the reconstruction falls below a predetermined amount.
\nImage without black borders: having performed all the procedures designed for black border removal, we will obtain an image with reduced dimensions and the reconstructed black borders. The result obtained can be seen in \nFigure 12\n, in which \nFigure 12(a)\n shows the original image without editing, and \nFigure 12(b)\n provides the result obtained through this process.
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Figure 9.
Thresholding for the detection of black borders: (a) Channel V thresholding highlighted in red. (b) Result of thresholding.
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Figure 10.
Thresholding for the detection of black borders: (a) Black borders with information highlighted in red. (b) Result of the morphological opening.
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Figure 11.
Process of cropping the black borders.
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Figure 12.
Result of black border removal: (a) Original image with black borders. (b) Result of black border removal.
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6.2. Removal of specular highlights
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There are numerous methods to detect specular highlights. The following is a brief summary of the most important of these:
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Park et al. [12] propose the detection of specular highlights using a search of saturated areas and small regions with high contrast. The saturated areas are detected by applying adaptive thresholding to the image’s intensity histogram. The value of the threshold is predetermined as the region that surrounds the maximum value of the histogram. The smaller regions with high contrast are detected using the method proposed in Ref. [13], which applies a top-hat filter followed by a reconstruction and erosion operation by a size-5 disk structure.
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Bernal et al. [9] assume that the specular pixel intensity value is greater than that of the non-specular pixels in their vicinity. Furthermore, they indicate that non-specular pixels which neighbour specular pixels will have higher intensity values than non-specular pixels far from the reflective areas. The detection of specular highlights is carried out by the subtraction of the original image and their median. Once this has been done, specular highlights can be detected through the use of thresholding.
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Gross et al. [14] detect specular highlights based on the space of HSV colour. Specular highlights show a high saturation and low brightness, which makes their detection simple.
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The method put forward in Ref. [15] for the detection of specular highlights uses two different colour spaces. In the first, it is necessary to observe the borders generated by the changes in texture and specular highlights. In the second, only the borders generated by the textures need to be seen. Subtraction of these two colour spaces enables the detection of specular highlights. This method has been used in investigation [16] with satisfactory results. Therein, the detection of specular highlights based on low saturation of the colour of the highlights is suggested.
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Having shown the techniques used in various studies for the removal of specular highlights, the method for their elimination is proposed. \nFigure 13\n shows the steps for a better understanding. A description of each of the modules that comprise them follows.
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Figure 13.
System for the removal of specular highlights.
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\nConversion to greyscale: in order to commence the process of specular highlight removal, it is necessary to convert the borderless image from the original colour model (RGB) to greyscale. This operation is necessary for subsequent detection of specular highlights, which is described in the next step.
\nDetection of specular highlights: the method used for the detection of specular highlights has been proposed by the authors of the study [9]. To this end, a system comprising four blocks has been designed, which is shown in \nFigure 14\n. In the following steps, there is a detailed description of the process for specular highlight removal proposed for this investigation.
\nCalculation of the threshold value (U): to detect specular highlighting automatically, it is vital to affix a threshold value (U) which distinguishes between normal values in the image and specular highlighting. To this end, the median value of the original image (μ) is calculated on a greyscale, which is then multiplied by a weight (W) which, by default, has a value of 0.3. In this way, the value required for addressing the next phase in the detection of specular highlights is calculated.
\nSubtraction of the original image in greyscale and the threshold value: once the threshold value (U) has been calculated, the subtraction of the original image in greyscale with the threshold value (U) is performed. In this way, a matrix equal in dimensions to that of the image in greyscale is obtained, in which values above 0.75 belong to specular highlighting.
\nThresholding: having calculated the matrix with the values pertaining to the subtraction between the original image in greyscale and the threshold value (U), a binary mask will be generated in which values surpassing the threshold (U) are given a value of 1, and everything else a value of 0, thereby obtaining an image that only shows the positions of the specular highlighting that has been detected.
\nMask with specular highlights: as a result of this process, a mask is obtained which will be used in the next step and will deal with the reconstruction of the highlighting.
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\nReconstruction of the image: once the dilation of the specular highlighting mask has been carried out, we can begin to reconstruct the regions of the image indicated by the mask through the following steps:
The damaged section is filled in using information from the rest of the image.
The structure of the area surrounding the deteriorated part is filled in towards its centre, extending the lines that reach the border.
The numerous regions that are generated inside the damaged area from the extension of the contour lines are filled in with the colour of the corresponding bordering region.
Finally, the small details are coloured in to maintain uniformity.
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Figure 14.
Detection of specular highlights. μ Represents the median value of the image without black borders and W denotes the multiplication factor (0.3 by default).
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The algorithm repeatedly carries out steps 2 and 3 until the desired quality is achieved. Having carried out this process, an image free of specular highlights is obtained. The result is highly effective, as shown in \nFigure 15\n.
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Figure 15.
Removal of specular highlights.
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6.3. Lighting normalisation
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In the scientific literature, there are numerous publications that deal with uneven lighting in imaging. A brief summary of the most relevant works, as well as a proposal for an alternative to normalise lighting in colonoscopic imagery illumination is presented. Investigation [17] presents a contrast operator built by means of two primitives involving Weber’s law, and, in doing so, achieving an improvement in the contrast of the image. On the other hand, study [16] carries out a reduction of the effects of uneven lighting through the local normalisation of the image’s brightness. For this, each pixel is divided by the maximum value of its vicinity. In this publication, vicinity was considered 13 × 13 pixels. Finally, in investigation [14], an equalisation of the background of the image in greyscale was carried out, thereby strengthening the contrast of the different structures, as well as removing the lighting variation in the image.
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The following procedure is proposed to solve the issue of homogenous lighting in colonoscopic imagery. The proposed design is shown in \nFigure 16\n, offering a complete description of the blocks comprising it; i.e. obtaining the subtraction value, subtracting the image with the subtraction value and the image with normalised lighting.
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Figure 16.
Illumination normalisation.
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\nObtaining the subtraction value: in order to achieve a more uniform illumination in the images, it is a fundamental requirement to calculate a subtraction value for each of the windows into which the image has been divided (20 × 20 pixels). This value is obtained by calculating the median value of each channel inside the said window and multiplying it by a weight (0.3 by default).
\nSubtraction from the window with the subtraction value: once the subtraction values of the different channels have been calculated, these are subtracted from the corresponding channel of the window. In this way, the effects of the peaks of intensity that the uneven lighting causes are mitigated.
\nImage with normalised lighting: as an output of the lighting normalisation module, an image is obtained with a range of much more uniform colour intensities, which aids its subsequent analysis. Following this previous step, the colonoscopic images are ready to be used for quality evaluation algorithms for the preparation of the colon, using the BBPS, and automatic polyp detection. In \nFigure 17\n, it is possible to observe the result obtained through the normalisation of lighting. \nFigure 17(a)\n shows an image without lighting normalisation and \nFigure 17(b)\n shows the result obtained through this process.
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Figure 17.
Result of lighting normalisation: (a) Image with neither black borders nor specular highlighting. (b) Result of lighting normalisation.
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6.4. Removal of interlacing effects
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The adverse effects of interlacing are habitual in the use of videos, or in the extraction of images from video frames. The removal of these aspects has been addressed in numerous investigations, which achieve very accurate results. Below, the most relevant publications that propose a solution to this problem are shown.
\n
Studies [18–20] address the removal of the effects of interlacing through deinterlacing. The procedure is based on obtaining one in every two horizontal lines, decreasing the vertical size of the image. To maintain the size proportion of the original image, they apply vertical redimensioning by a factor of 0.5.
\n
\n\nFigure 18\n shows the results of applying these techniques for removing interlacing effects. As can be observed, the obtained result is very good, achieving high effectiveness.
\n
Figure 18.
Removal of the effects of interlacing.
\n
\n
\n
6.5. Removal of ghost colours
\n
This problem has been addressed in the literature, in study [21], where channel equalisation is proposed, as is carrying out an estimation and compensation of the movements of the camera. Channel equalisation aims to obtain a histogram with a more uniform distribution, i.e. the same number of pixels should exist for each level of grey in the histogram of a monochrome image. The estimation and compensation of the movements of the camera are obtained through the use of the movement vectors from MPEG video standard. These enable an estimate of the deviation affecting each colour channel in obtaining the image, allowing the errors produced to be corrected. This same solution has been addressed in study [22]. The application of this technique corrects the effect very accurately, failing solely in images of very low initial quality. The result obtained using this solution is shown in \nFigure 19\n.
\n
Figure 19.
Removal of ghost colours.
\n
\n
\n
\n
7. Conclusion
\n
The benefits derived from the tools described in the present chapter are in the improvement of colonoscopic images. Specifically:
\n
The scientific community is provided with information about the origin and characteristics of the most prevalent artefacts that corrupt colonoscopic images, thus allowing for their identification, detection and removal.
The techniques that have to be applied to the images in order to increase their quality are described, as well as the methodology that has to be used to apply them.
The scientific community is also given a useful guide to a system of medical diagnosis aid based on colonoscopic images, thus allowing to offer tools better suited to the needs of the patients.
\n
Since the systems to aid diagnosis are constantly on the rise nowadays and are likely to be in the immediate future, we consider the current chapter is undoubtedly necessary to the specialist in the area.
\n
\n\n',keywords:"colonoscopy, medical image pre-processing, specular reflections, inhomogeneous illumination, black borders, interlacing",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/54473.pdf",chapterXML:"https://mts.intechopen.com/source/xml/54473.xml",downloadPdfUrl:"/chapter/pdf-download/54473",previewPdfUrl:"/chapter/pdf-preview/54473",totalDownloads:1242,totalViews:228,totalCrossrefCites:4,dateSubmitted:"October 24th 2016",dateReviewed:"February 10th 2017",datePrePublished:"December 20th 2017",datePublished:"January 4th 2018",dateFinished:"March 18th 2017",readingETA:"0",abstract:"Colorrectal cancer is the third most frequently diagnosed cancer worldwide. The American Cancer Society estimates that there will be almost 100,000 new patients diagnosed with colorectal cancer and that around 50,000 people will die as a consequence of this in 2016. The increase of life expectancy and the increment of the number of diagnostic tests conducted have had a great impact on the amount of cancers being detected. Among other diagnostic tools, colonoscopy is the most prevalent. In order to help endoscopists cope with the increasing amount of tests that have to be carried out, there exists a need to develop automated tools that aid diagnosis. The characteristics of the colon make pre-processing essential to eliminate artefacts that degrade the quality of exploratory images. The goal of this chapter is to describe the most common issues of colonoscopic imagery as well the existing methods for their optimal detection and correction.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/54473",risUrl:"/chapter/ris/54473",signatures:"Alain Sánchez-González and Begoña García-Zapirain Soto",book:{id:"5798",type:"book",title:"Surgical Robotics",subtitle:null,fullTitle:"Surgical Robotics",slug:"surgical-robotics",publishedDate:"January 4th 2018",bookSignature:"Serdar Küçük",coverURL:"https://cdn.intechopen.com/books/images_new/5798.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-953-51-3720-7",printIsbn:"978-953-51-3719-1",pdfIsbn:"978-953-51-3977-5",isAvailableForWebshopOrdering:!0,editors:[{id:"5424",title:"Dr.",name:"Serdar",middleName:null,surname:"Küçük",slug:"serdar-kucuk",fullName:"Serdar Küçük"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"104709",title:"Prof.",name:"Begona",middleName:null,surname:"Garcia Zapirain",fullName:"Begona Garcia Zapirain",slug:"begona-garcia-zapirain",email:"mbgarciazapi@deusto.es",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Deusto",institutionURL:null,country:{name:"Spain"}}},{id:"199214",title:"Ph.D. Student",name:"Alain",middleName:null,surname:"Sánchez González",fullName:"Alain Sánchez González",slug:"alain-sanchez-gonzalez",email:"sanchez.alain@deusto.es",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Deusto",institutionURL:null,country:{name:"Spain"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. What is a colonoscopy?",level:"1"},{id:"sec_3",title:"3. Main problems of colonoscopies",level:"1"},{id:"sec_4",title:"4. What is the pre-processing of colonoscopic images?",level:"1"},{id:"sec_5",title:"5. Applicability of pre-processing colonoscopic imagery in robots",level:"1"},{id:"sec_6",title:"6. Pre-processing colonoscopic imagery",level:"1"},{id:"sec_6_2",title:"6.1. Removal of black borders",level:"2"},{id:"sec_7_2",title:"6.2. Removal of specular highlights",level:"2"},{id:"sec_8_2",title:"6.3. Lighting normalisation",level:"2"},{id:"sec_9_2",title:"6.4. Removal of interlacing effects",level:"2"},{id:"sec_10_2",title:"6.5. Removal of ghost colours",level:"2"},{id:"sec_12",title:"7. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'\nS.-H. Bae and K.-J. Yoon, Polyp detection via imbalanced learning and discriminative feature learning, IEEE Trans Med. Imaging., vol. 34, no. 11, pp. 2379-2393, 2015\n'},{id:"B2",body:'\nJ. Bernal, F. J. Sánchez, G. Fernández-Esparrach, D. Gil, C. Rodríguez, and F. Vilariño, WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians, Comput. Med. Imaging Graph, vol. 43, pp. 99-111, 2015\n'},{id:"B3",body:'\nL. Alexandre, N. Nobre, J. Casteleiro, and others, Color and position versus texture fea- tures for endoscopic polyp detection, International Conference on BioMedical Engineering and Informatics, 2008. BMEI 2008, Sanya, China. vol. 2, pp. 38-42, 2008\n'},{id:"B4",body:'\nS. P. Halloran, G. Launoy, and M. Zappa, European guidelines for quality assurance in colorectal cancer screening and diagnosis, Endoscopy, vol. 10, pp. 0032-1309791, 2012\n'},{id:"B5",body:'\nN. F. Fayad and C. J. Kahi, colonoscopy quality assessment, Gastrointest. Endosc. Clin. N. Am., vol. 25, no. 2, pp. 373-386, 2015\n'},{id:"B6",body:'\nJ. Oh et al., Measuring objective quality of colonoscopy, IEEE Trans. Biomed. Eng., vol. 56, no. 9, pp. 2190-2196, 2009\n'},{id:"B7",body:'\nM. F. Kaminski et al., Quality indicators for colonoscopy and the risk of interval cancer, N. Engl. J. Med., vol. 362, no. 19, pp. 1795-1803, 2010\n'},{id:"B8",body:'\nS. Hwang, J. Oh, W. Tavanapong, J. Wong, and P. C. de Groen, Stool detection in colo- noscopy videos, in Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, Vancouver Convention and Exhibition Centre,Vancouver, BC, Canada. pp. 3004-3007, 2008\n'},{id:"B9",body:'\nJ. Bernal, J. Sánchez, and F. Vilarino, Impact of image preprocessing methods on polyp localization in colonoscopy frames, in Engineering in Medicine and Biology Society (EMBC), 2013. 35th Annual International Conference of the IEEE, Osaka International Convention Center, in Osaka, Japan. pp. 7350-7354, 2013\n'},{id:"B10",body:'\nR. O. Duda and P. E. Hart, Use of the Hough transformation to detect lines and curves in pictures, Commun. ACM, vol. 15, no. 1, pp. 11-15, 1972\n'},{id:"B11",body:'\nH. C. Wang, W. M. Chen, Y. P. Lin, and W. C. Shen, Tumor detecting in colonoscopic narrow-band imaging data, presented at the 2012 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), New Taipei City, Taiwan. pp. 564-568, 2012\n'},{id:"B12",body:'\nS. Y. Park, D. Sargent, I. Spofford, K. G. Vosburgh, and Y. A-Rahim, A colon video analysis framework for polyp detection, IEEE Trans. Biomed. Eng., vol. 59, no. 5, pp. 1408-1418, 2012\n'},{id:"B13",body:'\nD. S. Bright and E. B. Steel, Two-dimensional top hat filter for extracting spots and spheres from digital images, J. Microsc., vol. 146, no. 2, pp. 191-200, 1987\n'},{id:"B14",body:'\nS. Gross, S. Palm, J. J. Tischendorf, A. Behrens, C. Trautwein, and T. Aach, Automated classi cation of colon polyps in endoscopic image data, in SPIE Medical Imaging, Orlando, Florida, United States. pp. 83150W-83150W, 2012\n'},{id:"B15",body:'\nT. Gevers, Re ectance-based classi cation of color edges, in Computer Vision, 2003. Proceedings of Ninth IEEE International Conference, Washington, DC, USA. pp. 856-861, 2003\n'},{id:"B16",body:'\nT. Stehle et al., Classi cation of colon polyps in NBI endoscopy using vascularization features, in SPIE Medical Imaging, Lake Buena Vista, Florida, United States. pp. 72602S-72602S, 2009\n'},{id:"B17",body:'\nE. A. Rivas Araiza, J. D. Mendiola Santibañez, G. Herrera Ruiz, C. A. González Gutiérrez, M. Trejo Perea, and G. J. Ríos Moreno, Mejora de Contraste y Compensación en Cambios de la Iluminación, Comput. Sist., vol. 10, no. 4, 2007\n'},{id:"B18",body:'\nBernal, J., Sánchez, J., Vilariño, F.: Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions. In: Proceedings of the XXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica, Madrid, Spain\n'},{id:"B19",body:'\nJ. Bernal, J. Sánchez, and F. Vilarino, A region segmentation method for colonoscopy images using a model of polyp appearance, in Pa ern Recognition and Image Analysis, Springer, pp. 134-142, 2011\n'},{id:"B20",body:'\nJ. Bernal, J. Sánchez, and F. Vilarino, Towards automatic polyp detection with a polyp appearance model, Pattern Recognit., vol. 45, no. 9, pp. 3166-3182, 2012\n'},{id:"B21",body:'\nR. Dahyot, F. Vilariño, and G. Lacey, Improving the quality of color colonoscopy videos, J. Image Video Process, vol. 2008, p. 15, 2008\n'},{id:"B22",body:'\nM. Arnold, S. Ameling, A. Ghosh, and G. Lacey, Quality Improvement of Endoscopy Videos, in Proceedings of the 8th IASTED International Conference on Biomedical Engineering, Innsbruck, Austria, 2011\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Alain Sánchez-González",address:"sanchez.alain@deusto.es",affiliation:'
DeustoTech-LIFE Unit, University of Deusto, Biscay, Spain
DeustoTech-LIFE Unit, University of Deusto, Biscay, Spain
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This chapter mentions all clinical trial studies that have been done to evaluate probiotic efficacy with a focus on gastrointestinal diseases.",book:{id:"5193",slug:"probiotics-and-prebiotics-in-human-nutrition-and-health",title:"Probiotics and Prebiotics in Human Nutrition and Health",fullTitle:"Probiotics and Prebiotics in Human Nutrition and Health"},signatures:"Amirreza Khalighi, Reza Behdani and Shabnam Kouhestani",authors:[{id:"179560",title:"Dr.",name:"Amirreza",middleName:null,surname:"Khalighi",slug:"amirreza-khalighi",fullName:"Amirreza Khalighi"},{id:"185238",title:"Dr.",name:"Reza",middleName:null,surname:"Behdani",slug:"reza-behdani",fullName:"Reza Behdani"},{id:"185239",title:"Dr.",name:"Shabnam",middleName:null,surname:"Kouhestani",slug:"shabnam-kouhestani",fullName:"Shabnam Kouhestani"}]}],mostDownloadedChaptersLast30Days:[{id:"50992",title:"Probiotics: A Comprehensive Review of Their Classification, Mode of Action and Role in Human Nutrition",slug:"probiotics-a-comprehensive-review-of-their-classification-mode-of-action-and-role-in-human-nutrition",totalDownloads:5325,totalCrossrefCites:14,totalDimensionsCites:26,abstract:"Probiotics are live microorganisms that live in gastrointestinal (GI) tract and are beneficial for their hosts and prevent certain diseases. In this chapter, after a complete introduction to probiotics, definition, mechanism of action, and their classification, currently used organisms will be discussed in detail. Moreover, different kinds of nutritional synthetic products of probiotics along with their safety and drug interaction will be noticed. This chapter mentions all clinical trial studies that have been done to evaluate probiotic efficacy with a focus on gastrointestinal diseases.",book:{id:"5193",slug:"probiotics-and-prebiotics-in-human-nutrition-and-health",title:"Probiotics and Prebiotics in Human Nutrition and Health",fullTitle:"Probiotics and Prebiotics in Human Nutrition and Health"},signatures:"Amirreza Khalighi, Reza Behdani and Shabnam Kouhestani",authors:[{id:"179560",title:"Dr.",name:"Amirreza",middleName:null,surname:"Khalighi",slug:"amirreza-khalighi",fullName:"Amirreza Khalighi"},{id:"185238",title:"Dr.",name:"Reza",middleName:null,surname:"Behdani",slug:"reza-behdani",fullName:"Reza Behdani"},{id:"185239",title:"Dr.",name:"Shabnam",middleName:null,surname:"Kouhestani",slug:"shabnam-kouhestani",fullName:"Shabnam Kouhestani"}]},{id:"51065",title:"Role of the Biofilms in Wastewater Treatment",slug:"role-of-the-biofilms-in-wastewater-treatment",totalDownloads:6759,totalCrossrefCites:24,totalDimensionsCites:55,abstract:"Biological wastewater treatment systems play an important role in improving water quality and human health. This chapter thus briefly discusses different biological methods, specially biofilm technologies, the development of biofilms on different filter media, factors affecting their development as well as their structure and function. It also tackles various conventional and modern molecular techniques for detailed exploration of the composition, diversity and dynamics of biofilms. These data are crucial to improve the performance, robustness and stability of biofilm-based wastewater treatment technologies.",book:{id:"5197",slug:"microbial-biofilms-importance-and-applications",title:"Microbial Biofilms",fullTitle:"Microbial Biofilms - Importance and Applications"},signatures:"Shama Sehar and Iffat Naz",authors:[{id:"180364",title:"Dr.",name:"Iffat",middleName:null,surname:"Naz",slug:"iffat-naz",fullName:"Iffat Naz"},{id:"183345",title:"Dr.",name:"Shama",middleName:null,surname:"Sehar",slug:"shama-sehar",fullName:"Shama Sehar"}]},{id:"50610",title:"Antimicrobial Effect of Probiotics against Common Pathogens",slug:"antimicrobial-effect-of-probiotics-against-common-pathogens",totalDownloads:4708,totalCrossrefCites:24,totalDimensionsCites:31,abstract:"The antimicrobial or antagonistic activity of probiotics is an important property that includes the production of antimicrobial compounds, competitive exclusion of pathogens, enhancement of the intestinal barrier function and others. There are many methods to ascertain probiotic properties, including various in vitro and in vivo methods. The in vivo methods include various modifications of the spot‐on lawn assay, agar well diffusion assay (AWDA), co‐culturing methods, usage of cell lines and others. In many cases in vitro antagonist activity is observed, but in real settings it is not observed. The in vivo methods mainly used are animal models; however, their use is being restricted according to the European legislation OJ L136. The justification of animal models is also questionable as the results of studies on animals do not predict the same results for humans. The use of replacement alternative methods, for example incorporating human cells and tissues, avoids such confounding variables. Most important studies are double‐blinded randomized clinical trials; however, these studies are difficult to perform as it is not easy to achieve uniform conditions. There is a clear need for more elaborate assays that would better represent the complex interactions between the probiotics and the final host. This complex situation is a challenge for scientists.",book:{id:"5193",slug:"probiotics-and-prebiotics-in-human-nutrition-and-health",title:"Probiotics and Prebiotics in Human Nutrition and Health",fullTitle:"Probiotics and Prebiotics in Human Nutrition and Health"},signatures:"Sabina Fijan",authors:[{id:"179312",title:"Prof.",name:"Sabina",middleName:null,surname:"Fijan",slug:"sabina-fijan",fullName:"Sabina Fijan"}]},{id:"68305",title:"Introductory Chapter: Alginates - A General Overview",slug:"introductory-chapter-alginates-a-general-overview",totalDownloads:1437,totalCrossrefCites:14,totalDimensionsCites:29,abstract:null,book:{id:"8019",slug:"alginates-recent-uses-of-this-natural-polymer",title:"Alginates",fullTitle:"Alginates - Recent Uses of This Natural Polymer"},signatures:"Leonel Pereira and João Cotas",authors:[{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira"},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas"}]},{id:"55889",title:"The Physiology of Mycobacterium tuberculosis in the Context of Drug Resistance: A System Biology Perspective",slug:"the-physiology-of-mycobacterium-tuberculosis-in-the-context-of-drug-resistance-a-system-biology-pers",totalDownloads:1539,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis (Mtb), is the main cause of death due to an infectious disease. After more than 100 years of the discovery of Mtb, clinicians still face difficulties finding an effective treatment for the increasing number of drug-resistant cases. The difficulties in the clinical setting can be related to the slow pace at which the understanding of the physiology of this bacterium has occurred. Mtb is distinct from other microorganisms not only due to its slow growth and difficulties to study in the laboratory, but also due to its inherent physiology such as its complex cell envelope and its metabolic pathways. Understanding the physiology of drug susceptible and resistant Mtb strains is crucial for the design of an effective chemotherapy against TB. This chapter will review the mycobacterial cell envelope and major physiological pathways together with recent discoveries in Mtb drug resistance through different “omics” disciplines.",book:{id:"5853",slug:"mycobacterium-research-and-development",title:"Mycobacterium",fullTitle:"Mycobacterium - Research and Development"},signatures:"Luisa Maria Nieto, Carolina Mehaffy and Karen M. Dobos",authors:[{id:"198240",title:"Dr.",name:"Carolina",middleName:null,surname:"Mehaffy",slug:"carolina-mehaffy",fullName:"Carolina Mehaffy"},{id:"221619",title:"Dr.",name:"Luisa",middleName:null,surname:"Nieto",slug:"luisa-nieto",fullName:"Luisa Nieto"}]}],onlineFirstChaptersFilter:{topicId:"895",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81375",title:"Environmental Persistence of SARS-CoV-2 and Disinfection of Work Surfaces in View of Pandemic Outbreak of COVID-19",slug:"environmental-persistence-of-sars-cov-2-and-disinfection-of-work-surfaces-in-view-of-pandemic-outbre",totalDownloads:22,totalDimensionsCites:0,doi:"10.5772/intechopen.104520",abstract:"Coronavirus disease 2019 (COVID-19) is primarily a respiratory illness, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The pandemic outbreak of SARS-CoV-2 across the world has been responsible for high morbidity and mortality, which emphasizes the role of the environment on virus persistence and propagation to the human population. Since environmental factors may play important roles in viral outbreaks, and the severity of the resulting diseases, it is essential to take into account the role of the environment in the COVID-19 pandemic. The SARS-CoV-2 may survive outside the human body from a few hours to a few days, depending upon environmental conditions, probably due to the relatively fragile envelope of the virus. The shedding and persistence of SARS-CoV-2 in the environment on animate and inanimate objects contributes to the risk of indirect transmission of the virus to healthy individuals, emphasizing the importance of various disinfectants in reducing the viral load on environmental surface and subsequently control of SARS-CoV-2 in the human population.",book:{id:"11006",title:"Disinfection of Viruses",coverURL:"https://cdn.intechopen.com/books/images_new/11006.jpg"},signatures:"Koushlesh Ranjan"},{id:"81019",title:"Physical Inactivation of SARS-CoV-2 and Other Coronaviruses: A Review",slug:"physical-inactivation-of-sars-cov-2-and-other-coronaviruses-a-review",totalDownloads:34,totalDimensionsCites:0,doi:"10.5772/intechopen.103161",abstract:"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the ongoing pandemic of Coronavirus Disease 2019 (COVID-19). Other members of the enveloped RNA virus family Coronaviridae have been responsible for a variety of human diseases and economically important animal diseases. Disinfection of air, environmental surfaces, and solutions is part of infection prevention and control (IPAC) for such viruses and their associated diseases. This article reviews the literature on physical inactivation (disinfection) approaches for SARS-CoV-2 and other coronaviruses. Data for thermal (heat) inactivation, gamma irradiation, and ultraviolet light in the C range (UVC) irradiation have been reviewed. As expected, the susceptibilities of different members of the Coronaviridae to these physical inactivation approaches are similar. This implies that knowledge gained for SARS-CoV-2 should be applicable also to its emerging mutational variants and to other future emerging coronaviruses. The information is applicable to a variety of disinfection applications, including IPAC, inactivation of live virus for vaccine or laboratory analytical use, and waste stream disinfection.",book:{id:"11006",title:"Disinfection of Viruses",coverURL:"https://cdn.intechopen.com/books/images_new/11006.jpg"},signatures:"Raymond W. Nims and Mark Plavsic"},{id:"80772",title:"Variability and Relative Order of Susceptibility of Non-Enveloped Viruses to Chemical Inactivation",slug:"variability-and-relative-order-of-susceptibility-of-non-enveloped-viruses-to-chemical-inactivation",totalDownloads:22,totalDimensionsCites:0,doi:"10.5772/intechopen.102727",abstract:"Viruses exhibit a marked variation in their susceptibilities to chemical and physical inactivation. Identifying a trend within these variations, if possible, could be valuable in the establishment of an effective and efficient infection control or risk mitigation strategy. It has been observed that non-enveloped viruses are generally less susceptible than enveloped viruses and that smaller sized viruses seem less susceptible than larger viruses. A theory of a “hierarchy” of pathogen susceptibility has been proposed and widely referenced. This concept provides a useful general guide for predicting the susceptibility of a newly emerged pathogen. It also serves as a theoretical basis for implementing a limited scale viral inactivation study that is to be extrapolated onto many other viruses. The hierarchy concept should be interpreted with caution since the actual viral inactivation efficacy may, in some cases, be different from the general prediction. The actual efficacy is dependent on the type of chemistry and application conditions. The order of susceptibility is not always fixed; and viruses within the same family or even the same genus may exhibit drastic differences. This chapter reviews viral inactivation data for several commonly used chemistries against non-enveloped viruses, highlighting the cases wherein the order of susceptibility varied or even flipped. Possible underlying mechanisms are also discussed.",book:{id:"11006",title:"Disinfection of Viruses",coverURL:"https://cdn.intechopen.com/books/images_new/11006.jpg"},signatures:"Sifang Steve Zhou"},{id:"80523",title:"Predicted and Measured Virucidal Efficacies of Microbicides for Emerging and Re-emerging Viruses Associated with WHO Priority Diseases",slug:"predicted-and-measured-virucidal-efficacies-of-microbicides-for-emerging-and-re-emerging-viruses-ass",totalDownloads:38,totalDimensionsCites:0,doi:"10.5772/intechopen.102365",abstract:"The World Health Organization has updated its list of priority diseases for 2021 to currently include the following: Ebola virus disease and Marburg virus disease (Filoviridae), Nipah and henipaviral diseases (Paramyxoviridae), Lassa fever (Arenaviridae), Rift Valley fever and Crimean-Congo hemorrhagic fever (Bunyaviridae), Zika (Flaviviridae), COVID-19 (SARS-CoV-2) including Delta, Omicron, and other variants of concern, Middle East respiratory syndrome, severe acute respiratory syndrome (Coronaviridae), and the always present “disease X,” which is a term used for the next emerging pathogen of concern that is not known about today. In this chapter, we review the virucidal efficacy data for microbicides (disinfectants and antiseptics, also known as surface and hand hygiene agents or collectively hygiene agents) for the viruses associated with these diseases. As these diseases are each caused by lipid-enveloped viruses, the susceptibilities of the viruses to virucidal agents are informed by the known hierarchy of susceptibility of pathogens to microbicides. The unique susceptibility of lipid-enveloped viruses to most classes of microbicides is based on the common mechanism of action of envelope-disrupting microbicides. Empirical data supporting this principle and the mitigational role of targeted hygiene in infection prevention and control (IPAC) discussed are presented.",book:{id:"11006",title:"Disinfection of Viruses",coverURL:"https://cdn.intechopen.com/books/images_new/11006.jpg"},signatures:"M. Khalid Ijaz, Raymond W. Nims, Todd A. Cutts, Julie McKinney and Charles P. Gerba"},{id:"79842",title:"Antiviral Coatings as Continuously Active Disinfectants",slug:"antiviral-coatings-as-continuously-active-disinfectants",totalDownloads:81,totalDimensionsCites:0,doi:"10.5772/intechopen.101752",abstract:"Antimicrobial surfaces and coatings have been available for many decades and have largely been designed to kill or prevent the growth of bacteria and fungi. Antiviral coatings have become of particular interest more recently during the COVID-19 pandemic as they are designed to act as continuously active disinfectants. The most studied antiviral coatings have been metal-based or are comprised of silane quaternary ammonium formulations. Copper and silver interact directly with proteins and nucleic acids, and influence the production of reactive free radicals. Titanium dioxide acts as a photocatalyst in the presence of water and oxygen to produce free radicals in the presence of UV light or visible light when alloyed with copper or silver. Silane quaternary ammonium formulations can be applied to surfaces using sprays or wipes, and are particularly effective against enveloped viruses. Continuously active disinfectants offer an extra barrier against fomite-mediated transmission of respiratory and enteric viruses to reduce exposure between routine disinfection and cleaning events. To take advantage of this technology, testing methods need to be standardized and the benefits quantified in terms of reduction of virus transmission.",book:{id:"11006",title:"Disinfection of Viruses",coverURL:"https://cdn.intechopen.com/books/images_new/11006.jpg"},signatures:"Luisa A. Ikner and Charles P. Gerba"},{id:"79247",title:"Hybrid Hydrogen Peroxide for Viral Disinfection",slug:"hybrid-hydrogen-peroxide-for-viral-disinfection",totalDownloads:124,totalDimensionsCites:0,doi:"10.5772/intechopen.100237",abstract:"Decontamination is often necessary in facilities with sensitive spaces where pathogen elimination is critical. Historically, high concentration vaporized hydrogen peroxide technologies have been applied in these areas for pathogen disinfection. While effective, these high concentration solutions come with inherent risks to human health and safety. Alternatively, one recent innovation is a hybrid hydrogen peroxide system which combines a 7% hydrogen peroxide solution with a calibrated fogging device that delivers a mixture of vaporous and micro aerosolized particles, significantly lowering the risk of exposure to high-concentration hazardous chemicals. Studies performed with this technology demonstrate high level pathogen decontamination across a variety of tested pathogens and substrates. This chapter will cover a brief history of hydrogen peroxide technologies and their application processes; examine the correlations between viral inactivation, viral disinfection, and biological indicators for validation; demonstrate the necessity of dwell time for optimal efficacy; discuss the effects of viral disinfectant use on laboratory surfaces; and examine various studies, including virologic work performed in Biosafety Level 3 facilities and good laboratory practice (GLP) data performed by EPA-approved laboratories. This chapter will provide readers a deeper understanding of essential components and considerations when implementing hydrogen peroxide systems for viral decontamination.",book:{id:"11006",title:"Disinfection of Viruses",coverURL:"https://cdn.intechopen.com/books/images_new/11006.jpg"},signatures:"Meaghan Hislop, Frances Grinstead and John R. Henneman"}],onlineFirstChaptersTotal:8},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:8,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:286,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:105,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:9,numberOfPublishedChapters:101,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:11,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,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:9,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:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188",scope:"This series will provide a comprehensive overview of recent research trends in various Infectious Diseases (as per the most recent Baltimore classification). Topics will include general overviews of infections, immunopathology, diagnosis, treatment, epidemiology, etiology, and current clinical recommendations for managing infectious diseases. Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"May 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,annualVolume:11410,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},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,annualVolume:11411,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. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. 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. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,annualVolume:11413,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. 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Novel computational algorithms for image analysis, scene understanding, biometrics, deep learning and their software or hardware implementations for natural and medical images, robotics, VR/AR, applications are some research directions relevant to this topic.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",keywords:"Image Analysis, Scene Understanding, Biometrics, Deep Learning, Software Implementation, Hardware Implementation, Natural Images, Medical Images, Robotics, VR/AR"},{id:"25",title:"Evolutionary Computation",scope:"Evolutionary computing is a paradigm that has grown dramatically in recent years. This group of bio-inspired metaheuristics solves multiple optimization problems by applying the metaphor of natural selection. It so far has solved problems such as resource allocation, routing, schedule planning, and engineering design. Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. 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Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. 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Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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