",isbn:"978-1-80355-607-9",printIsbn:"978-1-80355-606-2",pdfIsbn:"978-1-80355-608-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"6cf0b844f6881c758c61cca10dc8b134",bookSignature:"Associate Prof. Gülşen Akın Evingür and Dr. Önder Pekcan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11830.jpg",keywords:"Elasticity, Toughness, Modulus, Compression, Extension, Optical Properties, Swelling, Drying, Diffusion, Release, Transmission Loss, Sound Absorption Coefficient",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 5th 2022",dateEndSecondStepPublish:"May 3rd 2022",dateEndThirdStepPublish:"July 2nd 2022",dateEndFourthStepPublish:"September 20th 2022",dateEndFifthStepPublish:"November 19th 2022",remainingDaysToSecondStep:"15 days",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Evingür is a researcher in polymer composites and a lecturer at a maritime university. She has edited 2 books and has had 5 chapters published in international books, and 3 international and 5 national projects, respectively.",coeditorOneBiosketch:"Prof. Pekcan received their Ph.D. from the University of Wyoming, United States of America, in 1974. He has more than 362 SCI articles, 26 chapters, and 10 projects and is a member Science Academy in Turkey.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"180256",title:"Associate Prof.",name:"Gülşen",middleName:null,surname:"Akın Evingür",slug:"gulsen-akin-evingur",fullName:"Gülşen Akın Evingür",profilePictureURL:"https://mts.intechopen.com/storage/users/180256/images/system/180256.jpeg",biography:"Gülşen Akın Evingür graduated from Physics Department at the Yıldız Technical University (YTU, İstanbul, Turkey) in 1996. She completed her Master of Science degree in 2002 at the same department. The titled of her thesis was 'Electrical Properties of Polystyrene”. She received her PhD from Physics Engineering at İstanbul Technical University in 2011. The title of the thesis was 'Phase Transitions in Composite Gels”. She worked as an Assistant Professor between 2011 and 2018, and she is currently working as an Assosciate Professor at Pîrî Reis University, Istanbul, Turkey. She has been engaged in various academic studies in the fields of composites and their mechanical, optical, electrical, and acoustic properties. She has authored more than 60 SCI articles, 92 proceedings in national and international journals, respectively. 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He became Associate Professor at Hacettepe University in 1979. \nHe visited ICTP Trieste, Italy as Visiting Scientist between June and August 1980. Between 1980 and 1981 he was a Visiting Scientist at the Technical University of Gdansk, Poland. \nHe worked as Visiting Professor at the Department of Chemistry, University of Toronto, Canada between 1981 and 1988. \nHe was appointed as full Professor at the Department of Physics, Istanbul Technical University, Turkey and worked there between 1988 and 2005. \nHe became an Elected Member of the Turkish Academy of Sciences (TÜBA) in January 1995. \nHe became the Dean of School of Arts and Sciences at the Istanbul Technical University in 1997. \nHe received the Science Award from the Scientific and Technological Research Council of Turkey (TÜBİTAK) in 1998. 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In the last few years Prof. Pekcan’s work covers mostly the area of biopolymers and nanocomposites.",institutionString:"Kadir Has University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Kadir Has University",institutionURL:null,country:{name:"Turkey"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"14",title:"Materials Science",slug:"materials-science"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"185543",firstName:"Maja",lastName:"Bozicevic",middleName:null,title:"Dr.",imageUrl:"https://mts.intechopen.com/storage/users/185543/images/4748_n.jpeg",email:"maja.b@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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1. Introduction
Population growth and increased demand for food have led humanity to look for new ways to increase food production. Energy, which is an essential input in agriculture, has been considered as a feasible option to increase food productivity and enhance food security. As a result, agriculture has become energy-intensive to meet increased food and biofuel demand [1].
After the green revolution, the introduction of high yield varieties and intensive crop management practices has increased the use of energy manifolds in both developing and developed countries [2, 3].
It is anticipated that energy input for crop production will increase further mainly due to population and economic growth, climate change, degrading quality of soils, and shortage of labor [4, 5]. On the other hand, intensive use of energy in crop production is posing many threats to agriculture sustainability, human health, and sustainability of the environment. Sometimes to get maximum returns farmers make overuse of energy inputs. This has led to increased energy used in crop production at a faster rate compared to other sectors. Escape of traditional practices in agriculture, technological advancements in Agri-machinery, and increased application rate of fertilizer is also responsible for increased use of energy in crop production. It is also ascribed to the introduction of high yielding varieties, and excessive use of biocides and chemical fertilizer. In addition to this diesel fuel consumption has also increased due to farm mechanization and pumping of underground water. Finally, scarcity of cultivable lands and irrigation water increased the human population, and the desire for improved living standards has also contributed to the intensive use of energy in agriculture. Both agriculture and the environment are dependent on each other and the efficient use of energy is a basic requirement for sustainable agriculture [6, 7]. Sustainable development of agriculture is dependent on high energy use efficiency with low energy use in crop production. Thus, increasing energy use efficiency in crop production is important for food security and environmental sustainability. Keeping in view the multiple interactions of agriculture with the environment, analysis of the consumption of energy (both operational and embodied) in the agriculture system is urgently needed to fight both environmental issues stemming from agriculture and climate change impacts on agriculture.
1.1 Environmental implications of input energy use in agriculture
Agriculture contributes 24% of global Greenhouse gases emission, and agricultural activities are considered a significant source of pollution [8, 9]. It is estimated that GHG emission from agriculture has doubled in the last 50 years, they could increase by another 30% by 2050 [10]. Increasing use of energy inputs in agriculture is associated with numerous environmental problems such as loss of biodiversity, pollution of the aquatic environment by chemical fertilizers and pesticides, and high consumption of non-renewable energy resources. Among all other energy inputs used in crop production, diesel fuel and fertilizers have the highest share of energy consumption [11, 12]. Studies have found that fertilizer and pesticides are among the most substantial secondary sources of CO2 emissions [8]. According to an intergovernmental panel on climate change [13]. Direct and indirect consumption of fossil fuels for crop production leads to the emission of carbon dioxide (CO2), nitrous oxide (NO2), and methane (CH4). Climate Change resulting from greenhouse gasses is the most important environmental challenges in today’s world [13]. A significant portion of these greenhouse gases is produced by agriculture. About 10–12% of all anthropogenic GHG emissions are contributed by agricultural greenhouse gasses emission [14].
The major use of commercial energy in agriculture is during the production and operation of agricultural machinery. Most of the agricultural operations like, land preparation, irrigation, fertilization, spraying, and harvesting are performed using fossil fuels. The combustion of fossil fuels in agricultural machinery releases CO2 into the atmosphere.
Excessive or over-use of fertilizers leads to loss of nutrient elements, which are main contributors to non-point source pollution from agriculture, degradation of water and soil quality, decrease in the quality of agricultural products, and increase in air emissions. Due to losses incurred by pest attacks, the use of pesticides is increasing at a higher rate. There is a 4.4% average annual growth in the use of agrochemicals worldwide [15]. This increased use of pesticides is causing air, water, and soil pollution. The increasing use of pesticides in agriculture is becoming the main environmental hazard and a major contributor to agriculture pollution. Additionally, agriculture is thought to be the major contributor of N2O by indirect and direct sources [16]. The food production system is under increasing pressure due to consistent population growth and climate change; by an increase in demand for food security while protecting the natural resources by minimizing the environmental footprints [17].
Both sustainable environment and sustainable agriculture are dependent on each other. Environmental factors have a significant contribution to agriculture; agriculture, as compared to other sectors, is more dependent on the natural environment. Agriculture is the source of food and fiber for the human being and vital for human existence; as a result, sustainable agriculture development is not just related to economic development but also human survival. Therefore, efficient use of energy is one of the conditions for sustainable agriculture [18].
1.2 Energy efficiency in agriculture
Efficient use of energy inputs helps to increase production and productivity, profitability and competitiveness of agriculture, and sustainable rural living. Higher energy use efficiency will promote sustainable agriculture by minimizing environmental problems and preventing the destruction of natural resources. The use of renewable energy sources and increase in efficiency of energy can also make a significant contribution in achieving sustainable energy development goals [19]. Currently, the world is focused to develop a production system that maintains high levels of output while minimizing the input of fossil energy and as a result, helps to reduce greenhouse gas emissions. To combat global warming, reducing emissions of greenhouse gases by minimizing the direct and indirect use of fossil fuels for crop production is a vital strategy. Energy efficiency is an essential element for achieving sustainable agricultural development. This is also important for increasing economic returns, preserving fossil fuel reserves, and sustainable agricultural production. Therefore, environmental impact assessments, energy analysis, and GHG emission assessments are important components.
2. Wheat production in Pakistan
Wheat (Triticum aestivum L.) is an important winter crop in Pakistan. Wheat significantly contributes to the livelihood and food security of the population in Pakistan, as well as at the global and regional levels. It meets about 1/5th of the daily calorie and protein requirement of human beings [20] and it constitutes 65% of staple food consumption in Pakistan. It contributes 1.7% to the national GDP of Pakistan and 8,7% to agriculture value addition. Wheat was cultivated on 8,25 Million hectares in 2019–2020 and the area under wheat has slightly decreased in the past five years. Over the years, wheat yield per acre has been stagnant or little change has been seen due to declined under-ground water table, soil degradation, environmental pollution, etc. delayed sowings, low germination rate, insect-pest infestation, and low crop stand has lowered the production efficiency of wheat. A further decline in wheat yield in recent years can be attributed to locust attacks. Keeping in view increasing population and government policies (increased support price from 1400/40 kg to 1650/40 kg before the wheat season in 2020), it is projected that farmer will divert their resource towards wheat to get maximum output from a limited quantity of arable land. The limited supply of labor on one hand and incentives for higher productivity on other hand will lead to increased use of energy in wheat production. In Pakistan, winter wheat is grown both irrigated and drylands. During winter availability of canal water is almost negligible and irrigated wheat is irrigated with groundwater. However, sustainability productivity of wheat crop is under threat due to over-exploitation of underground water. Moreover, a substantial amount of diesel fuel is used to pump water from underground, leading to significant consumption of diesel fuel energy in wheat production. On the other hand, water is a scarce resource and the water table is depleting rapidly in Pakistan. These both issues are posing a great threat to the environmental sustainability of Pakistan, as Pakistan is among the 10 most climate affected countries in the world. The worsening energy and water issue in Pakistan needs the urgent attention of policymakers.
2.1 Input energy use in wheat production
There’s substantial use of energy in wheat production both directly and indirectly. In operations like tillage, planting, and harvesting there’s a direct use of energy, while energy is indirectly used in inputs such weedicides, fertilizers, and agriculture machinery (Figure 1).
Figure 1.
System boundaries of wheat production system in Pakistan.
2.1.1 Human labor
Human labor is the most important source of the energy in agriculture, although the introduction of machines has reduced human labor in the industry in the field activities, human labor is still playing its key role. In agricultural activities, human labor is used almost at every step, from manual work on the farm, driving agricultural machinery, maintenance, fertilizer and pesticide application, irrigation, and harvesting to management. In developing countries, human power constitutes 73% of the total energy use on farms [21]. Maybe in the future with full mechanization of farms, the use of human labor will be reduced, but some scientists believe that organic and modern agriculture needs more manual work for weeding and harvesting [22, 23]. There are different estimates for the energy output of human labor on farms. The main physical activities in wheat production are driving a tractor, manual sowing, manual fertilization and spraying, harvesting, and transportation. In this study, human labor work was calculated based on the information provided by the wheat farmers on the number of hours spent in each operation. The energy equivalent of human labor is muscle power used in the field operations of crop production. The energy equivalent of human labor is 1.96 MJ/h determined from literature (Table 1). Labor energy consumption can be determined by multiplying total hours of human activity by the energy coefficients of workers. In Pakistan, where still mechanization of the farms is not so common, there is ample use of human labor in the farm operations. On average 178.45 hours of human labor is used in one hectare of wheat production.
Quantity of inputs used in wheat production in Pakistan and their energy equivalents.
2.1.2 Seed
Seed is mostly provided by seed producers and private seed companies; however, some farmers also use seeds from their farms. Wheat is planted either by seed drill or manually by spreading, the amount of seed also varies according to the sowing method. On average, 134.19 kg/ha wheat seed is used in Pakistan. Energy equivalents of the seed are the energy used in the preparation of wheat seed. Energy inputs of seed can be calculated by multiplying the quantity of seed used per hectare with its energy equivalents (8.65 MJ/kg).
2.1.3 Farm machinery
The embedded energy necessary to manufacture machinery for crop production is a tertiary input that typically has a minor impact on the total energy. Farrell et al. [24] reported that machinery accounted for only 1.7% of the total energy associated with corn production. Therefore, energy use in machinery is not included in the estimation of energy used in wheat production.
2.1.4 Fossil fuels
Diesel fuel is the main fuel used in farm machinery and water pump for different crop operations. Consumption of the fuel is dependent on several factors like climate, crop, soil, rolling assistance, and speed. In dry and warm climate use of diesel is more for irrigation than other operations, while in dry farming system diesel is mainly used in tillage and sowing as compared to irrigation. The energy output of diesel fuel was calculated by multiplying liter/ha with fuel equivalent of energy per liter. Energy equivalents of diesel fuel are 44.83 MJ/L. The average diesel fuel use is 39.98 liter/ha in wheat production.
2.1.5 Fertilizer chemical and pesticides
Soil nutrients are the most important obstacle to crop productivity. Fertilizers are used by farmers to increase soil nutrients and resultant growth. Chemical, organic, and biological fertilizers are used in crop production, but just chemical fertilizers are believed to increase the yield more than any other fertilizer. Nitrogen is the main mineral fertilizer being used in crop production. Nitrogen fertilizer is energy-intensive, on the other hand, phosphate and potash do not need high energy. Chemical and chemical fertilizers energy equivalents mean the energy consumption for production, packing, and distribution of the material. On average 177.68 kg per hectare of nitrogen nutrients, 130.17 kg phosphate nutrients, and 37.36 kg potash are used in wheat production in Pakistan. Additionally, 1.60 kg per hectare of herbicides are used in wheat production for weed management.
2.1.6 Water for irrigation
While dry-land wheat is dependent on rains, but irrigated wheat requires irrigation water throughout the production process. On average 8483.07 m3 of irrigation water is used in one hectare of wheat. The energy equivalents of the water for irrigation input is the indirect energy of irrigation consists of the energy consumed for manufacturing the material for the dams, canals, pipes, pumps, and equipment as well as the energy for constructing the walls and building the on-farm irrigation system. The energy equivalent of the irrigation was estimated to be 0.014 MJ/m3.
2.2 Energy balances in wheat production
Energy consumption in wheat production includes; labor, embodied energy in seed, chemical and fertilizers, diesel, and water for irrigation. Except water for irrigation all other input energies are same for rainfed (dry land) wheat. There’s a wide variation of input energy (Table 2), which shows high level of mismanagement in usage of energy resources among some wheat producers. This also indicates that there is great scope for improving energy consumption efficiencies of wheat producers in both farming systems. On average total input energy consumption in irrigated wheat is 49,079.27 MJ ha−1 and 31421.59 MJ ha−1 for rainfed wheat. The higher use of input energy use in irrigated wheat can be attributed to irrigation energy. Highest share of energy consumption in irrigated wheat is from chemical fertilizer (31.33%), while farmyard manure contributes highest in total input energy consumption in rainfed wheat.
Energy Inputs
Irrigated
Rain-fed
Energy equivalents MJ ha−1
SD*
Energy equivalents MJ ha−1
SD*
Human labor
402.07
166.78
259.45
163.12
Seed
2157.54
193.91
2017.93
157.72
Diesel fuel
9435.13
2697.53
5155.56
1835.76
Water for irrigation
13578.13
7578.43
—
—
Chemicals
627.10
358.56
129.87
324.53
Farmyard manure
7518.00
10767.05
12837.32
12363.56
Nitrogen
13069.26
6998.60
9437.68
6374.82
Phosphate
1702.02
675.63
1474.07
1015.25
Potash
589.68
994.91
109.69
354.96
Yield (output)
50756.79
11715.46
34427.32
20161.36
Table 2.
Energy balance in both production systems.
Standard Deviation.
In fertilizers, nitrogen constitutes the highest share, 80.39% and 82.31%, in irrigated and rain-fed wheat, respectively. Highest share of nitrogen in total fertilizer consumption is also recorded in some other countries by [25, 26, 27]. Though, nitrogen fertilizer has played key role in enhancing the food production, at the same time excessive use of nitrogen has contributed to soil, water, and air pollution in many parts of the world. Sustainability of crop production is threatened by overuse of inorganic fertilizer which inflicts severely on soil health. The need for nitrogen can be reduced by fertilization management and integrating a legume in crop rotation. In order to reduce demand for inorganic fertilizer in medium term, soil fertility and organic matter contents can be increased by applying composts, chopped residues or other soil amendments. Almost, 55% of the farmers in Punjab (Pakistan) just use inorganic fertilizers, and 30% use combination of both organic and inorganic. Furthermore, farmers use more than recommended dose of fertilizer (Zulfiqar et al. 2017). So, adopting balanced use of fertilizer by wheat producers will reduce the use of nitrogen, as nitrogen has been found to be main difference between conventional and sustainable farming system (Pimentel et al. 2005). So, consumption of nitrogen with organic fertilizer and balanced use of fertilizer will reduce energy consumption in production system and improve its productivity.
Water for irrigation is the second largest consumer of energy in irrigated wheat. Diesel fuel is used for operating machinery in wheat production, it constitutes 19.25% of the total input energy consumption in irrigated and 16.4% in rain-fed. Börjesson and Tufvesson [28] found diesel as the main energy input after fertilizer in wheat, sugar beet, canola and maize. Particularly in irrigated land where diesel is also used for ground water pumping its use is higher (9435.13 MJ ha−1) than rain-fed (1835.76 MJ ha−1). Siddiqi and Wescoat [29] reported that ground water pumping consumes 61% of direct energy in Punjab. Pumping systems are mostly dependent on fossil fuels, almost 91% of the total installed pumps use diesel driven motors.
Furthermore, share of human labor (0.81%) with amount of 402.07 MJ ha-1 in the irrigated farming system is the least in total energy consumption, followed by chemicals and seed. In rain-fed wheat share of chemical (0.4%) in total energy consumption was negligible followed by human labor and seed. The average output energy in irrigated wheat was calculated as 50756.79 MJ ha-1, and 34427.32 MJ ha-1 for rain-fed wheat farming.
2.3 Energy indices
Energy ratio which is a relationship between input and output energy is often used as an index to measure energy efficiency in crop production. Energy ratio can also be used to determine subsistence of the system in isolated societies. If ratio is lower than one, it means system is losing energy and if it is higher than one it means system is earning energy. Energy efficiency for irrigated and rain-fed wheat production is estimated to be 1.03 and 1.09, respectively (Table 3). Irrigation can be the reason for difference between two production system, higher energy efficiency for rain-fed and comparatively low for irrigated. This suggests that an efficient irrigation system will improve energy ratio in irrigated wheat. For comparisons between two production system energy efficiency may not be very good approach, because difference in energy efficiency can be due to difference in energy input and yield. Ziaei et al. [30] said that energy productivity is comparatively a better parameter to show the difference between two production systems, as it calculates the ratio of production yield per kg into consumer energy. Estimates of energy productivity shows that, for each unit of input energy (MJ) consumed in wheat, 0.07 and 0.06 yield units are achieved in rain-fed and irrigated wheat production, respectively (Table 3). This again shows that, energy is more efficiently being used in rainfed production system. Specific energy was estimated to be 12.70 and 14.49 MJ kg−1 for rain-fed and irrigated wheat production (Table 3). Lower value of specific energy shows that less amount of energy is used for production of one yield unit, as it is reciprocation of energy productivity. As a result, rain-fed is superior to irrigated wheat production from specific energy perspective also. The net energy per hectare for rain-fed and irrigated wheat production was 3005.73 and 1677.52 MJ, respectively.
=Human Labor + Seed +Water for irrigation + Farmyard manure
Non-renewable energy (NRE)
MJ ha−1
16306.67
25423.19
=Tractor + Harvester +Diesel Fuel + Herbicides + Chemical fertilizers
Total energy input
MJ ha−1
31421.59
49079.27
=NRE + RE or = DE + IDE
Table 3.
Energy indices for wheat production in Pakistan.
The distribution of input energy according to renewable and non-renewable, direct and indirect forms is important for energy analysis. In both production systems, ratios of indirect and non-renewable energy are higher than direct and renewable energy. Higher share of non-renewable energy in irrigated wheat production is due to high dependence on fossil fuels. In other words, common use of diesel driven motor for ground water pumping and higher use of chemical fertilizer is the reason for share of non-renewable energy. Penetration of electricity driven irrigation systems, efficient water management, and balanced use of fertilizer will reduce share of the non-renewable energy in agricultural systems. Moreover, investment in renewable energy system such as solar, wind etc. will improve the situation. According to [31] improvement in energy efficiency and increase in amount of renewable energy in agricultural system is very important to achieve sustainable system of food production.
3. Efficiency analysis
Traditionally input–output ratios have been used to determine efficiency. Though, input–output ratios are also helpful in explaining efficiency of the system. However recently, researchers have started applying Data Envelopment Analysis (DEA) to analyze efficiency of farmers. DEA is generalization of single-input single-output technical efficiency measure of Farrel (1957) and use multiple-input multiple-output technique to evaluate the relative efficiency of peer units with respect to multiple performance measures [32, 33]. A decision-making unit called DMU are under evaluation in DEA. A DMU is considered as efficient when no other DMU can produce more output using an equal or lesser amount of inputs [34].
3.1 Efficiency estimates
An input-oriented DEA approach was used to determine technical, pure technical and scale efficiencies of wheat farmers in both production systems. Technical efficiency of all farmers was evaluated using CCR model, and BCC model was used to determine pure technical (PTE) and scale efficiency (SE). The results from CCR and BCC model for rain-fed wheat producers in Pakistan are presented in Figure 2. It can be seen from the figure that only about 18% rainfed farmers are technically efficient. This shows that there is a considerable inefficiency between wheat producers in the study area. From efficient farmers 17% are efficient in both technical and pure technical efficiency score; this means that these farmers are globally efficient and operating at most productive scale size, on the other hand the 22% farmers are only locally efficient farmers and they have disadvantageous scale size. Additionally, 14% and 36% of the farmers have pure technical and technical efficiency score less than 0.5.
Figure 2.
Percentage distribution of TE, PTE, and SE scores of wheat producers in rainfed production system.
Efficiency scores of irrigated wheat producers are demonstrated in Figure 3. About 34% irrigated farmers are technically efficient and 42% are pure technically efficient. Among efficient farmers 90% are globally efficient and 10% are locally efficient due to scale problem. Considering CCR model 7% farmers have efficiency scores between 0.9 to less than 1 and 19% have between 0.8 to less than 0.9. On the other hand, in BCC model 13% had scores between 0 to less than 1 and 16% had between 0.8 to less than 0.9. Less than one score of the pure technical efficiency means that producer is using more energy from different sources than required [35].
Figure 3.
Percentage distribution of TE, PTE, and SE scores of wheat producers in irrigated production system.
Table 4 presents the summarized statistics for technical efficiency, pure technical efficiency and scale efficiency for wheat producer of Pakistan. The results revealed that average technical efficiency of wheat producer in rain-fed production system was 0.62 and in irrigated it was 0.82. The pure technical efficiency and scale efficiency was 0.78 and 0.67, respectively in rain-fed, and 0.87 and 0.85 in irrigated wheat production system. The technical efficiency of irrigated wheat farmers varied between 0.12 to 1 which shows that all farmers did not have knowledge of right production techniques or they were not applying at the right time. The low average values of scale efficiency in both production systems imply that the average size of the wheat farms is not equal to optimal farm size. This mean if the inefficient wheat farmers operate at optimal scale size considerable saving of energy from different sources is possible without affecting the yield level.
Particular
Rain-fed
Irrigated
Mean
SD
Min
Max
Mean
SD
Min
Max
Technical Efficiency
0.629
0.291
0.126
1
0.825
0.179
0.224
1
Pure Technical Efficiency
0.782
0.222
0.35
1
0.879
0.141
0.420
1
Scale Efficiency
0.674
0.287
0.12
1
0.869
0.161
0.230
1
Table 4.
Average efficiency of rain-fed and irrigated wheat production in Pakistan.
3.2 Input use pattern of efficient and inefficient wheat producers
The amount of physical inputs and output for 10 efficient and inefficient farmers based on CCR model in both rain-fed and irrigated wheat production system are presented in Table 5. The efficient farmers use all inputs in less amount compared to inefficient farmers in irrigated production system. While in rain-fed production system except diesel and nitrogen use of all other inputs was low for efficient farmers than inefficient. Inefficient farmers in rain-fed production system use more human labor hours by 27.78%, seed by 1.92%, FYM by 48.5%, and phosphate by 7.14%. In irrigated production system, use of inputs by efficient farmers is lower than inefficient farmers by, 28.40% for human labor hour, 11.61% for diesel fuel, 34% for chemicals, 42.85% for nitrogen, 34.6% for phosphate, 59.97% for potash and 60% for water for irrigation. Looking at output it is evident that yield of efficient farmers is higher than inefficient farmers in both production systems.
Inputs/output (unit)
Rainfed
Irrigated
10 EF (1)
10 IF (2)
Difference (%) (2–1) *100/2
10 EF (1)
10 IF (2)
Difference (%) (2–1)*100/2
A. Inputs
Human Labor (h)
80.04
110.84
27.78
184.65
257.92
28.40
Seed (kg)
133.38
136
1.92
135.88
130.91
−3.79
Diesel (l)
89.16
65.94
−35.21
140.58
159.06
11.61
Farmyard manure (kg)
25,688
49,894
48.51
0
39,520
Herbicide (kg)
0.12
0
−0.12
1.70
2.59
34.36
Nitrogen (kg)
102.91
98.84
−4.11
148.2
259.35
42.85
Phosphate (kg)
80.27
86.45
7.14
104.97
160.55
34.61
Potash (kg)
12.33
0
−12.33
49.35
123.31
59.97
Water for irrigation
—
—
—
2187.43
3033.06
27.88
B. Output
Wheat (kg)
4004.64
592.92
−575.40
3946.32
2041.20
−93.33
Table 5.
Amount of input and output for 10 efficient and inefficient wheat producers.
EF = Efficient Farmers.
IF = Inefficient Farmers.
4. Conclusions
Energy security and environmental problems due to its use are the major concern for most of the developing world. Agriculture is among the largest energy consuming sectors; this chapter was an effort to estimate energy use in wheat production which is an important staple food in Pakistan. Data on quantity of different energy inputs used in wheat production was collected through field surveys. Energy consumption in wheat was calculated by multiplying amount of inputs with their energy equivalents drawn from literature. Energy indices which are important to interpret how energy is being used were also estimated. A non-parametric data envelopment analysis technique was used to identify efficient and inefficient farmers.
In Pakistan two different wheat production systems prevail (rain-fed and irrigated). So, all estimations were performed separately for both production systems. The results of the study showed that, FYM, fertilizer, and diesel fuel has the highest share in total input energy consumption in rain-fed wheat, while in irrigated wheat fertilizer, water for irrigation, and diesel were the main energy consuming inputs. In both production systems consumption of indirect and non-renewable energy resources was higher than direct and renewable energy resources. The results of the DEA analysis revealed that, 85% of the farmers in rain-fed wheat production and 65% in irrigated wheat production were technical efficient in Pakistan. Based on BCC model the estimate of target energy use showed that there is a great scope for energy savings from various input sources. If the optimum energy requirement levels are adopted by farmers, then it would lead to increase in energy efficiency. Comparison of 10 most efficient and no-efficient farmers revealed that input usage of inefficient farmers is comparatively higher than efficient ones with no difference in yield output and size. Based on result it could be said that there is dire need for dissemination of information about best agricultural practices and economic benefits of use of inputs at recommended levels. Adoption of better agriculture technologies is highly recommended as it will result in improvement in efficiency of use of diesel and human labor. Most of the wheat is cultivated manually and majority of the farmers apply flood irrigation leading to higher use of water and diesel fuel also. Efficient management of water for irrigation would improve energy efficiency and minimize environmental impacts.
Conflict of interest
The authors declare no conflict of interest.
\n',keywords:"energy use efficiency, input–output analysis, DEA, wheat, Pakistan",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/74465.pdf",chapterXML:"https://mts.intechopen.com/source/xml/74465.xml",downloadPdfUrl:"/chapter/pdf-download/74465",previewPdfUrl:"/chapter/pdf-preview/74465",totalDownloads:278,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:1,impactScore:0,impactScorePercentile:19,impactScoreQuartile:1,hasAltmetrics:1,dateSubmitted:"November 22nd 2020",dateReviewed:"November 30th 2020",datePrePublished:"December 16th 2020",datePublished:"May 11th 2022",dateFinished:"December 16th 2020",readingETA:"0",abstract:"Wheat is an important staple food in Pakistan and is grown in both irrigated and rainfed production systems. To meet increased demand, farmers have increased the use of input energy in wheat production. The intensive use of energy has many consequences for energy security and environmental sustainability. In this chapter, we have analyzed the energy use efficiency of wheat crop grown in two different production systems using data collected from wheat farmers of Punjab province of Pakistan through face-to-face interviews. Energy input–output analysis revealed that 49,079 MJ/ha input energy is used in irrigated wheat and 31,421 MJ/ha in rainfed wheat. The main difference between both production systems is because of irrigation water. Fertilizer has the highest share in total energy consumption followed by diesel fuel. Energy consumed per kilogram of wheat produced is less in rainfed wheat compared to irrigated. Similarly, energy efficiency values of rainfed wheat are better than irrigated wheat. Results of data envelopment analysis reveal that 38% of wheat farmers in rainfed systems and 62% in the irrigated system are using energy efficiently. The substantial difference between the energy use of inefficient and efficient indicates that there’s a significant potential to improve energy use efficiency in both systems.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/74465",risUrl:"/chapter/ris/74465",book:{id:"9670",slug:"current-trends-in-wheat-research"},signatures:"Muhammad Imran and Orhan Özçatalbaş",authors:[{id:"170206",title:"Prof.",name:"Dr. Orhan",middleName:null,surname:"Özçatalbaş",fullName:"Dr. Orhan Özçatalbaş",slug:"dr.-orhan-ozcatalbas",email:"orhan.ozca@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/170206/images/system/170206.png",institution:{name:"Akdeniz University",institutionURL:null,country:{name:"Turkey"}}},{id:"332065",title:"Assistant Prof.",name:"Muhammad",middleName:null,surname:"Imran",fullName:"Muhammad Imran",slug:"muhammad-imran",email:"maniuaf@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Veterinary and Animal Sciences",institutionURL:null,country:{name:"Pakistan"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 Environmental implications of input energy use in agriculture",level:"2"},{id:"sec_2_2",title:"1.2 Energy efficiency in agriculture",level:"2"},{id:"sec_4",title:"2. Wheat production in Pakistan",level:"1"},{id:"sec_4_2",title:"2.1 Input energy use in wheat production",level:"2"},{id:"sec_4_3",title:"Table 1.",level:"3"},{id:"sec_5_3",title:"2.1.2 Seed",level:"3"},{id:"sec_6_3",title:"2.1.3 Farm machinery",level:"3"},{id:"sec_7_3",title:"2.1.4 Fossil fuels",level:"3"},{id:"sec_8_3",title:"2.1.5 Fertilizer chemical and pesticides",level:"3"},{id:"sec_9_3",title:"2.1.6 Water for irrigation",level:"3"},{id:"sec_11_2",title:"2.2 Energy balances in wheat production",level:"2"},{id:"sec_12_2",title:"2.3 Energy indices",level:"2"},{id:"sec_14",title:"3. Efficiency analysis",level:"1"},{id:"sec_14_2",title:"3.1 Efficiency estimates",level:"2"},{id:"sec_15_2",title:"3.2 Input use pattern of efficient and inefficient wheat producers",level:"2"},{id:"sec_17",title:"4. Conclusions",level:"1"},{id:"sec_21",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Yuan S, Peng S, Wang B, Man J. Evaluation of the energy budget and energy use efficiency in wheat production under various crop management practices in China. Energy 160 (2018) 184-191. 10.1016/j.energy.2018.07.006.'},{id:"B2",body:'Evenson RE, Gollin D. Assessing the impact of the green revolution, 1960 to 2000. Science 2003; 300:758-62.'},{id:"B3",body:'Kazemi H, Kamkar B, Lakzaei S, Badsar M, Shahbyki M. Energy flow analysis for rice production in different geographical regions of Iran. Energy 2015;84: 390-6.'},{id:"B4",body:'Maraseni T, Chen G, Banhazi T, Bundschuh J, Yusuf T. 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Department of Economics and Business Management, University of Veterinary and Animal Sciences, Pakistan
Department of Agricultural Economics, Akdeniz University, Turkey
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1. Introduction
The Society of Nuclear Medicine and Molecular Imaging has defined molecular imaging as “the visualisation, characterisation, and measurement of biological processes at the molecular and cellular levels in humans and other living systems. This PET-CT imaging is based on two important software aspects two-dimensional (2D) or three-dimensional (3D) imaging techniques which are useful for the evaluation of various pathologies. The basis here is that the newer PET-CT machines are having more 3D software which is capable of better resolution. The use of the positron emission tomography (PET) by using the 18F-fluoro-2-deoxy-D-glucose as the radiotracer forms the basis of the modern imaging newer concepts leading to the personalised medicine.
The development of the PET instrumentation is based on the early development in the radioisotope manufacture in the radiochemistry. This was in the 1970s, where the Ter-Pogossian and colleagues [1] has mentioned the different compounds in the article in Scientific American which are 15O, 13N, 11C, or 18F. Along with this the FDG was also one of the compounds which was developed in first half of the 1970s at the Hospital of the University of Pennsylvania (PENN) by the Martin Reivich, David Kuhl, and Abass Alavi and also at the Brookhaven National Laboratory (BNL) [2]. The first PET center in PENN was established in August 1976, and FDG was used as the radiotracer. This was the first of the machine with the low-energy gamma photons and this was later modified into the high-energy collimators which are capable of the positron emission photons. And thus, the first whole-body image was acquired with a dual-head rectilinear scanner comprising of the high-energy collimators. This PET III scanner was shifted to the University of the Pennsylvania (Figure 1) [3, 4, 5, 6].
Figure 1.
The PET gantry showing the patient surrounding the gantry with scintillators surrounding the patient. The activated gamma camera with gamma rays passing through this ray.
2. Positron emission tomography technology
2.1 PET annihilation
The first use of the PET in the imaging was done by the use of the various short-lived positron-emitting isotopes like 11C, 13N, 15O, and 18F which are being produced as generator-produced gallium 68 (68Ga) and rubidium 82 (82Rb). The production of these isotopes is done by the use of the proton irradiation of the various natural or enriched targets, and all these will be having the various production equation, half-lives, and also the various properties of the positron-emitting radionuclides. The positron emission is the process which is also the beta plus decay (b1 decay), also known as the isobaric decay process in which the proton will be converted into a neutron by releasing a positron and a neutrino. And this decay process is made up of the proton-rich radionuclides. The use of the positron decay will be resulting in the formation of the element which will be having the atomic number which will be less by one unit. This process is known as the nuclear transmutation where there will be the conversion of one isotope or the element into the another. Thus, the isobaric decay process will be representing the mass number of the daughter nuclei which will be the same, but the atomic number will be changing.
Here the process in which the proton-rich radionuclides will be converting into the stable nuclei by the isobaric decaying of the element resulting into the positron emission or electron capture. There will be the proton rich nuclide which are capable of the absorption of the inner shell electron where there will be the conversion of the proton into the neutron. This is the process where the insufficient energy will be having difference with the element as well as the prospective daughter. The minimum energy difference here is if less than 1.022 MeV, the positron emission is not possible. The electron capture here will be in the usual decay mode. The positron emission is common in the lower atomic-weight nuclei made up of the 11C, 13N, 15O, and 18F, and the electron capture is seen in iodine 123.
The positron is capable of the moving into the very short distance and is seen as Positron energy 1 neutrino energy with the 5-transition energy of the 1.022 MeV. During this process the electron clouds due to the various surrounding materials will be retarding the energy, this along with the electron system will be forming the positronium which is the unstable system made up of the electron and a positron. These components will annihilate each other within the fraction of the second like 125 picoseconds to produce the various annihilation photons having energy equivalent of 511 keV. This is the energy which will be equivalent to the combined mass of the electron and a positron, and this is emitted in opposite directions most of the times at 180 degrees to each other (Figure 2).
Figure 2.
This showing the principle of the positron emission where the beta decay causing the positron electron annihilation at 180 degree.
These annihilation photons which are being emitted at 180 are being detected by PET detectors by the principle of electronic collimation. The arrival of the annihilation photons here is based on the very small timing of the window which is usually the 3–15 nanoseconds. This process will be resulting into the process of the coincidence detection in PET. These detection at 180 is resulting in the formation of the line of the response which is the straight line drawn between the 2 detectors, and this process is the line of response (LOR) or coincidence line. The common availability of the various detectors having the faster timing decay, along with the high light output, and also the higher stopping power. The use of the PET scanners having the time-of-flight (TOF) capability thus it will be resulting the principle of which relies on measuring the arrival time difference of the 2 annihilation photons. The pinpoint emission point is also seen along the LOR. The ultimate use of the TOF will result in the better contrast PET images having the better sensitivity [7]. The TOF position will be resulting the along the LOR is clearly defined and resulting into the various coincidence time resolution.
2.2 PET-scan
These scanners are made up of the various many small detectors which are usually placed in adjacent rings around the patient. The clinical state-of-the-art PET system was having a ring diameter of 60–90 cm with the extent of 10–25 cm and made up to 25,000 detectors. The single PET detector is made up of the very high-density scintillator crystal (eg, BGO, lutetium yttrium orthosilicate [LSO], or lutetium yttrium orthosilicate [LYSO]) which are capable of converting the photons striking on the detector into light. The scintillator is usually optically coupled to a device, of which the photo multiplier tube (PMT) is the commonly seen where the light will be converted into an amplified electric signal (Figure 3). These signals arising from the single detector will be added the coincidence circuit and this will be added as the PET event identified by the detection time. These various photons which are being detected within these various coincidence windows are documented as the coincidence events which will be attached to the LOR having the various 2 detectors, and all these events will be rejected.
Figure 3.
Image showing the blocks of the scintillating crystals which will be showing the multiple bocks of the PMTs, and each block of the scintillation crystal are made up of the 4 PMTs.
Majority of these PET systems will be acquiring the data over a given time frame and these events will be tagged with the LOR position and also at the time point of detection.
The tomographic single slice is being reconstructed independently by only accepting LOR within the given slice. These independent reconstructions are being obtained by using the various lead or tungsten collimating rings in between crystal rings and these inter-ring coincidences can be prevented. This process of the imaging is called 2D PET. The higher sensitivity of the inter-ring coincidences will be resulting into the 3D PET. Usually the 2D PET is preferred over 3D PET as it is easier to have simple data for handling and various image reconstruction algorithms. But due to the various technological development having the better iterative reconstruction algorithms the sensitivity from 3D PET is now more preferred in the various clinical PET systems. The various 511-keV photons from the various annihilation events are being detected in the PET system which are within the coincidence window, and these are being referred as the random coincidences. These random coincidences in LOR will define the width of the coincidence window and also the various event rates in the detectors which will be defining the LOR. These will result in the various random coincidences being modelled by the various coincidence effects.
2.3 Developments in PET instrumentation
Due to the various quantitation of the smaller lesions due to the increased image contrast and along the various partial volume effects. These limitations of the PET reconstructed spatial resolution of close to the 5 mm will be resulting in various partial volume effects. This spatial resolution is based on the various size of the detector crystals, where the spatial resolution can be improved with the use of the smaller crystals. In the older versions of the conventional PET designs, the light output from a particular crystal is being shared by the use of the several PMTs. These improvements in spatial resolution will have the direct electronic readout of the light emitted by a given crystal. These features will be seen in the PET photon-counting detector designs [8] and also in PET detectors where the silicon photomultiplier detectors are being developed and also used for PET/MR imaging [9].
The modern PET systems are made up of the TOF capabilities which will be having the biggest advantage of better image contrast, resolution with the improved noise which will be further reduced by the better localization of the annihilation position. The TOF resolution is directly related to the with the growth in the technology the signal-to-noise ratio in the new detector designs will be having better TOF resolution. The improvements in signal-to-noise ratios will be reducing the less activity as well as the scan time in each patient. There is the potential reduction in the patient dose or PET scan time which will be increasing the PET scanner sensitivity, and this is based on the advancements and improvements of the various PET detector.
2.4 PET radionuclides
FDG production 18F is produced in a cyclotron by the process of the nuclear reaction between oxygen 18 (18O)-enriched water which is being bombarded with protons by the releasing of the neutron. In the 68Ga, the germanium 68 which will be bound to the generator will result into another daughter isotope.
The half-life of 110 minutes is the ideal one for the clinical use and this will be used for the synthesis which can be used for hours. The very low positron energy (640 keV) will be resulting in the very short tissue range (2.3 mm) causing the higher resolution and low radiation dose. The 18F synthesis for the higher radioactive material will be having the advantages over the short-lived radioisotopes and also for the plasma analysis which will be needed for the quantification as well as for the evaluation.
2.5 The FDG concept
The basis of the tumour metabolism is that they consume more energy in the form of the glucose as this is the most commonly used metabolite, this happens by the process of the increased glycolysis which is also known as Warburg effect. This is the principle which is being used in the PET when FDG is used as a radiotracer. The FDG is a radiolabelled glucose analogue in which the 20-hydroxyl group is being substituted by 18F.
Many factors will be having an impact on the glycolysis of the tumour cells like the histologic type, the tumour grading, the tumour cell proliferation and most important is the tumour vasculature all these factors are important for the delivery of glucose and oxygen to the tissues [10]. The less amount of the oxygenation will result in the tumour hypoxia, and this is being explained on the basis of the tumours with the lower partial pressure of oxygen in comparison to the normal tissues. The tumour hypoxia will also be based on the principle of the solid tumours. The detection of the hypoxic regions means more malignant potential with bad prognosis and resistance to the therapy [11].
The increased glucose and also the hyperinsulinism will be resulting in the less amount of the FDG uptake in the tumours based on the uptake of FDG and glucose which will be competing with each other. This is the reason that the at least 4–6 hours fasting is needed before the FDG injection which will reduce insulin levels and will be facilitating the better background ratio. For the evaluation of the various pathologies the blood glucose levels have to be within normal range, 150–200 mg/dL. If the sugar levels are more than these values, then the PET-CT should be rescheduled unless and until it is stabilised to normal levels. The reason for this is that the insulin-induced hypoglycaemia will show the less tumour uptake and also facilitates the normal physiological uptake in the muscles and fat, causing the significant reduction of the tumour-to background ratio.
The normal uptake which appears more prominent in the brain and the heart due to increased glycolysis. In the cerebral parenchyma it will be more uniform in the cortex and basal ganglia, and corresponding lesser uptake in white matter and in the cerebrospinal fluid. The myocardial uptake is significantly variable can be very high, low, or absent also. This pattern is seen in the left ventricle; however, the right ventricle and atria uptake are not very high (Figure 4). The prolonged fasting of the 18 hours or more and a the low-carbohydrate-high-fat diet will result in the change of the metabolism like glucose to free fatty acids, this will result into the varied uptake due to the temporal and geographic diversities of the decreased glycolytic activity. The normal physiologic uptake in the various organs like the liver, spleen, and bone marrow are usually homogenous and low; on contrary the bone marrow will be showing significant uptake in following conditions like systemic inflammation, prolonged bleeding, or associated therapeutic interventions with chemotherapy or bone marrow stimulants. With this pattern of the uptake the different types of the skeletal metastases or associated malignant bone marrow infiltration; and this will result in the skeletal metastases.
Figure 4.
This PET-CT images (a–c) showing the normal mild physiological uptake, image (d) showing the physiological uptake in the bowel loops in the whole body scan.
Another important aspect of is that the glandular tissue of the breasts. The two areas of the physiological uptake will be giving the incidental findings especially related to the deserve special mention, namely, the thyroid gland and the gastrointestinal tract. The pattern of the uptake like the diffuse or focal uptake will be seen as in goitrous glands or thyroiditis. The closest differentials will be the malignancies or premalignant findings in as many as 33% of patients and should be further examined [12]. The Physiologic uptake in the bowel will be variable, resulting from the mild to the diffuse intense and focal uptake; more subtle in the caecum and rectosigmoid and also the patients undergoing treatment with metformin The exact cause of the intestinal uptake is not fully completely understood. The various factors which will be impacted are metabolically active mucosa, luminal contents, or glycolytic bacteria.
3. PET imaging applications
The clinical role of the correlative imaging will be used for various applications. And with the commercially available radiopharmaceuticals which are being used more commonly in various oncology [13], cardiology [14], neurology, and psychiatry [15, 16]. As discussed previously, the inner component of the PET/MR imaging design will be showing similarities of the MR head coil, PET detector ring, and MR magnet tunnel. Simultaneously acquired MR images, PET, and fused combined PET/MR images after intravenous injection of 370 MBq of FDG are shown. This tracer can be recorded for the 20 minutes at steady state till 2 hours. The earliest form of the image registration will be restricted to the various applications of the brain for the various brain tissues with the satisfactory model [17, 18]. Thus, the PET-CT is more useful for the neuroimaging applications and now one of the well-established imaging modalities. This also has the important role in the evaluation of the various central nervous system disorders like epilepsy, Alzheimer’s and Parkinson’s disease, head injury, and inoperable brain tumours [19, 20, 21].
The use of the various radiotracers for the assessment of the tumour metabolism and also the various physiological alteration involved in various diseases, and these are having significant impact on the PET/CT role as the emerging modality in the field of molecular imaging. The various oncological applications are being used for the evaluation of the [13, 22] various conditions in the central nervous system disorders, orthopaedic infections, and inflammatory disorders, and also for the evaluation and metastatic follow up of various pathologies.
PET imaging of radiolabelled nanoparticles has created lot of curiosity in the field of the molecular imaging. The size criteria’s for the nanoparticles is related to the size range of the few to several hundred nanometres. Lot of advantages of the nanoparticles are there as the newer molecular imaging agents, which are not being limited by the ease of the physical properties and also for the surface functionalisation [23, 24]. Physically the nanoparticles will be having the larger surface area-to-volume ratio. These are capable of getting attached to the various targets which will be used as the targeting agents for the various diagnostic, and therapeutic purposes. These are the agents which will be providing the more specific binding receptor capacity with higher specificity and affinity which is more important for the more precise detection and the evaluation of the various disease markers. Another important property is that it will be having the longer half-life as compared to the free drug molecules resulting in the significantly enhanced bioavailability.
The important aspect is the important characteristics of the radioisotopes which are the imaging characteristics of isotopes; the decay half-life of the radioisotope; the isotope availability; and the reliability of the radiolabelling of the radioisotope. The lesser positron energy with the high branching ratio of β+ decay will be having the different characteristics for PET imaging. The use of the isotopes having the high positron energy will be travelling for the longer distance for the positron annihilating and will have the significant loss of the spatial resolution. The isotopes which are having the very low positron efficiency, will have the lower atoms undergoing the β+ decay as compared to the overall atoms which will be requiring the very long scan times and also the very noisy images [25].
The nanomaterial use in the biomedical engineering can be able to understand the better “absorption, distribution, metabolism, and excretion” (ADME) pattern for the materials which can strike the balance between the nanoparticle-induced benefits and also the long-term toxicity due to nanoparticle exposure [26, 27, 28]. As we all know that the PET imaging is having significant advantage of higher sensitivity and also the ability for the quantitative analysis of the whole-body imaging and due to this property the more precise biodistribution of nanoparticles can be done. Thus, the PET imaging can be able to monitor the various nanoparticles in the non-invasive manner. The labelling of the nanoparticles coordinating with the radiometal, and the chelator is more preferred option. There is also the alternative method of the evaluation.
3.1 Radiolabeled nanoparticles for molecular imaging
The nanoparticles are having the two important advantages. Different and multiple modalities can be useful for the various modalities to get integrated in the single nanoparticle platform. We all know at this point that every imaging modality is having the advantages and disadvantages. PET imaging resolution is very much sensitive upto the picomolar level and quantitative >1 mm which is very low. The magnetic resonance imaging (MRI) is having the submillimetre-level spatial resolution still having significantly low sensitivity. The use of the optical imaging is highly sensitive and easily accessible. But due to the scatter of light there is the limitation of the penetration depth and also the spatial resolution. With this the combination of the different imaging modalities will be complimentary to each other and will have better imaging quality. The nanomaterials due to its functionalization they can be prevented to get attacked by the immune system and can have longer circulation time. The multiple targeting ligands are being conjugated to a single nanoparticle which will be providing the significant enhanced receptor binding affinity by the polyvalency effect [29].
3.2 Special imaging techniques
This technique was described by Weissman and Carrau [30]. By this method of the puffing the cheeks, the oral vestibule is being filled with air, creating the negative contrast separating the buccal and labial mucosa from the gingival mucosa, and due to this both the mucosal surfaces can be evaluated separately. In this procedure the buccinators muscle, the pterygomandibular raphe, and the retromolar trigone are also seen better. The mucosal pliability is also being affected due to the trismus. So, during the FDG PET/CT acquisition if there is focal area of the uptake of FDG in the oral cavity then the use of the puffed-cheek maneuvere, should be done which will take around 4 minutes. Patient is asked to close the mouth and fully puff the cheeks while breathing through the nose during this 3- to 4-minute PET/CT acquisition. The puffed cheek scanning time is very short and can result into the more increased salivation and associated attenuation effects [31, 32]. This technique will lead to the better localisation and demonstration of the extent of a tumour of the oral cavity. Chang and colleagues [33] demonstrated that the puffed cheek maneuvere on FDG PET/CT is more useful for the evaluation of the oral cancers and their extent as seen in the FDG PET/CT. This study has shown that the localised or extended oral cancers of puffed cheek FDG PET/CT and conventional FDG PET/CT was 95.2% and 54.5%, respectively. FDG PET/CT delineated more oral cancers as compared to our routine conventional FDG PET/CT and also for the preoperative evaluation of the tumour thickness. The dental artefacts are significantly reduced by 70% in the puffed-cheek FDG PET/CT.
3.3 Open-mouth technique
Method is described by Henrot and colleagues [34]. In this technique the routine conventional whole-body FDG PET/CT done from the supraorbital margin to mid-thigh (Figure 5). After this the patient has to open the mouth. 50-mL syringe is put in between the teeth to for the correct immobilisation. The PET-CT is acquired during quiet respiration. PET/CT scan is again acquired from the orbitomeatal line to the clavicular fossa, with one field of view (15 cm, 3.5 minutes) and totally taking upto 3–4 minutes. The important indication of these is the evaluation of the tumour of the oral cavity and also the oropharynx which sometimes are difficult for the evaluation of the dental artefact. Cistaro and colleagues [32] have demonstrated that this technique is more useful in the evaluation of the oral carcinomas. With this the tumour localization, tumour extent, and surrounding structure involvement can be seen in this open-mouth view as compared with the closed mouth view.
Figure 5.
This is the puff cheek technique which is very important for the evaluation of the small nodular lesion seen in the left buccal mucosa. CT image (A) showing nodule, (B and C) are the PET images and (C) image is the fused image showing nodular lesion with the significant uptake.
Modified Valsalva maneuvere is used for the evaluation of the location and extent of a hypopharyngeal tumour as there will be the opposition of the mucosal surfaces and also for the evaluation of the nasopharynx when the pharyngeal recesses are collapsed. This maneuvere is done by asking the patient to utter the word “e” uniformly for at least 10 seconds and during this time the patient should hold breath for at least 10 seconds. It is advisable to instruct the patient before so that no artefacts can be seen. This technique is done from the hyoid bone to the trachea.
The phonation is indicated to differentiate between the true and false vocal cords which are needed to evaluate the precise location of the laryngeal tumour and its margins for the quiet respiration during the examination. With this the true vocal cords can be seen opposing and cannot be able to distinguish from each other as performed during the apnoea. Still, they can be abducted and not visible when the acquisition is performed during quiet respiration [34]. These techniques along with the modified Valsalva and phonation techniques are mostly used for the CT acquisition. The performing hybrid PET/CT along with this two maneuvere is difficult as the PET acquisition for one field of view requires a minimum time duration of 2–3 minutes The use of the spot and the various maneuvere will be leading to the better delineation of the hot spots [35]. Ter-Pogossian [1] showed that it will take 3 minutes to perform modified Valsalva or phonation technique for this period. There are many motion artefacts and due to this the coregistration of CT and PET images is very difficult.
3.4 Optimization of patient preparation
The Optimization of scan protocol will lead to the decrease in the physiologic uptake of FDG in the head and neck region. The voluntary or involuntary tongue movement or sucking actions will cause in the significant increase in the pharyngeal muscles uptake [36]. The increased uptake in the base of the tongue and anterior part of the floor of the mouth is due to the increased uptake in the genioglossus muscle in the supine position due to its role of preventing the tongue to fall posteriorly and causing obstruction of the airway especially in the rest and also during the [37]. The other false uptake can be due to the activity post injection like talking and movement this is due to the increased laryngeal muscle activity [38]. The other areas of the uptake will be seen in the various muscles like lateral pterygoid, and masseter and this is also possible due to the long wait time [39]. Mid-morning is better time for the evaluation to prevent the supine position related FDG uptake in the muscles at the base of the tongue and anterior part of the mouth floor. FDG uptake in the brown fat and neck muscle can be difficult to differentiate between the supraclavicular lymph nodes and can be masked [40]. Ter-Pogossian [1] silent suggested not to have the liquid intake 30 minutes before the injection and also during the waiting time between FDG injection and whole-body scanning to avoid FDG uptake by the tongue and vocal muscles. Before the scan, all metal objects 7(eg, necklaces, earrings, and prosthesis) should be removed to prevent the metal attenuation artefacts. Cistaro and colleagues [32] showed the optimization of patient preparation in patients with HNC. With this technique there will be less FDG uptake in the muscles of base of tongue and floor of the mouth can be achieved. FDG, is not tumour-specific and various image interpretation pitfalls may occur because of false-positive and -negative causes of FDG uptake. The use of certain premedication, such as propranolol and diazepam, will result in the decrease physiologic FDG uptake in the brown fat and muscle.
3.5 Precision medicine
National Institutes of Health (NIH) has defined precision medicine as “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” This concept will be more useful for the doctors and researchers for evaluation of the various treatment options and other prevention aspects for the various diseases. Thus, leading to the various focus is on identifying different approach including the genetic, environmental, and lifestyle factors. The current therapy paradigm of “one-size-fits-all” approach, in which disease treatment and prevention strategies are developed.
3.6 Biomarker for precision diagnostics
A good and ideal biomarker for patient selection is very important for the evaluation of the novel therapeutic agent. Due to this there has to be companion diagnostic predictive markers, and these are being developed for the selection of the right patients. Tirapazamine (TPZ) is the benzothiazine series hypoxia-selective antitumor agent. PET/CT with fluorine-18-labelled fluoromisonidazole (18F-FMISO) or 18F fluoroazomycin arabinoside (FAZA) which is the hypoxic agent can be used with the TPZ [41, 42] as a diagnostic marker. PET/CT for the evaluation of the oestrogen receptor (ER) expression for the management and also with hormonal therapies for the various neuroendocrine tumour patients like the 68Ga DOTATATE PET/CT, before the initiation of the therapeutic management with 177LuDOTATATE [43]. The use of the 68GaPSMA PET/CT before therapy with 177Lu-PSMA therapy can also be evaluated [44]. Thus, there are more precise and the important new PET radiopharmaceuticals having the specific molecular targets, and also for the therapy along with these agents.
3.7 Tumour heterogeneity
The important aspect of the precision medicine use in the oncology is the tumour heterogeneity, but it is still challenging due to various reasons and most important one is the heterogenous presentation of the tumour. The heterogeneity of the tumour can be again sub classified as the (1) intertumoral heterogeneity: In this category the patient will be having different tumours or lesions which looks similar histologically but may be differing in the molecular variants as well as the malignant potential; (2) on contrary the intratumor heterogeneity: where the tumour will have the different functional capabilities in the tumour heterogeneity. The application of the spatial heterogeneity of subclones in a primary lesion or metastasis will be providing a bigger challenge for precision medicine as sequencing a portion of the tumour may miss important therapeutically relevant information. Lesions may be at locations who will get the tissue biopsy practically impossible. The end result of the clones can change with selective pressure from a targeted therapy leading to the of mutagenic activity of radiation and chemotherapy. Usually, the patient prognosis is poor when biomarkers found in the primary tumour, and metastatic lesions are varied. Thus, precision medicine will be requiring the different intratumor and intertumoral heterogeneity in the patient. The PET/CT is capable of the providing the different intratumor pattern of the heterogeneity along with the interpatient intertumoral heterogeneities. By this the evaluation of the whole-body can be done for the primary as well as metastatic lesion at one time. With the availability of the newer PET radiotracers, it will be possible for the evaluation of the intratumor and intertumoral heterogeneity. PET with 18F-FES can evaluate the regional ER expression [45] and this is having the advantage to overcome the different errors which will be arising the from disease heterogeneity. The use of the PET can also be able to measure the delivery and also the binding of oestrogen in vivo in correlation of the ER expression for the multiple tumour sites. The 18F-FES uptake in the tumour can be correlating with the ER expression corresponding to the various radioligand binding sites [45] the radiotracer uptake is directly related with the tamoxifen and aromatase inhibitor treatment [46, 47, 48]. Here the FES-PET is more important for the assessment of tumour heterogeneity of ER expression [49]. One of the recent study the role of the 18F-FES PET/CT can change the plan of the management upto the 48.5% of patients. For the detection of the ER status in the metastasis group (n 5 27), there will be significant increase in the 18F-FES PET/CT which has shown the significant increase in the metastatic lesions in 11 patients; absent in the 13 patients, and the rest of the 3 patients will be having both the 18F-FES positive and negative lesions. The 18F-FES PET/CT results has shown the better management plans in 16 patients (48.5%, 16/33) [50]. Another example is radiation therapy delivery which is significantly based on the heterogeneity of tumour hypoxia which is based on 18F-FMISO PET/CT [51]. The concentration of the 18F-FMISO in this gross tumour volume (GTV) is based on the hypoxia levels in the tumour. The 18F-FMISO PET/CT-guided intensity modulated radiotherapy (IMRT) for 10 patients in the diagnosed head and neck cancers which will be achieved 84 Gy to the GTV(h) and 70 Gy to the GTV, these can be done without exceeding the normal tissue tolerance levels. Investigators also attempted to deliver 105 Gy to the GTV(h) for 2 patients and were successful in 1, with normal tissue sparing.
3.8 Therapy assessment
The use of the various current therapy evaluations showing the anatomic changes, and these are the not sensitive biomarkers for the novel and targeted therapies. The basis here is the identification of the therapy resistance which needs to be evaluated early for the delivery of the precision medicine. The role of the PET/CT is important for the delivering precision medicine. Thus PET/CT is useful for the evaluation of the early therapy assessment along with the biology of the tumours or molecular subtypes, therapy selection, timing of early therapy assessment PET/CT, and for the performing PET/CT in a standardised manner.
4. Methionine
Methionine is the commonly used amino acid tracer, which is used in PET imaging of brain tumours, due to the low physiologic uptake of MET in brain. This is being used as it is very convenient for the radiochemical production, which will be allowing the rapid synthesis leading to the higher radiochemical yield [52]. The significant increased uptake of methionine is to be correlated with both cellular proliferation [53] and micro vessel count [54] in gliomas. Post injection, MET uptake in the brain is low and, in combination with high tumour uptake, leading to the very higher detection rate and also the good lesion delineation [55]. The normal biodistribution of the MET uptake is lower in the cerebral cortex, cerebellum, basal ganglia, and thalamus. Moderate amount of the accumulation is seen in pituitary and glandular system (parotid and salivary glands).
5. Choline
Prostate cancer is one of the most common malignancies in men and the incidence of prostate cancer increases directly with age. This tumour is showing the biologic behaviour, from a clinically silent, intraprostatic tumour to an aggressive malignancy, and resulting into the more sensitivity. Early identification is more helpful for the benefit of therapeutic decision-making [56, 57]. Prostate cancer cells are showing the significant increased phosphocholine levels along with the elevated turnover of the cell membrane phospholipid, namely phosphatidylcholine [58]. Choline imported into the cell which is again phosphorylated by choline kinase in the first step of the Kennedy cycle. The role of the choline kinase is more in the prostate cancers, and due to this the prostate cancers will have more carbon-11 choline concentrations in the cells [59]. The important characteristic of the CHO faster blood clearance (5 min) and also the significantly faster uptake in the prostate tissue (3–5 min), this will be resulting into early excretion in the urine. The longer half-life of fluorine-18 (110 min) allows transportation of 18F-fluorocholine to centres without a cyclotron [60], although 18F-choline has a higher urinary excretion than CHO [60].
6. Radiotracer advances
Due to the technical developments various new radiotracers are in pipeline for the more precise use of these in various cancers, which is capable of the evaluation of the cell proliferation, metastasis to different organs, hypoxia in various tumours, focussed receptor status, tumour antigen levels, and various therapeutic response.
18F-fluorothymidine (18F-FLT) is being used as the cell proliferation marker which will be used for the better quantification of tumour growth and also for the metastatic work up and also for the treatment response evaluation [61, 62]. 18F-Fluoromisonidazole (FMISO), is the important hypoxia biomarker for the evaluation of the degree of hypoxia in a tumour which can be used to see the aggressiveness of the tumour and also the response to management. This will introduce the various endothelial cells which are being activated by tumour-induced angiogenesis which can be used as an indicator of the local as well as the distant metastasis. The use of the 18F-galacto-arginine-glycine-aspartic acid tripeptide, having the capacity to bind the primary tumours as well as the metastatic lesions. 68Ga-PSMA, is being widely used as the radiotracer of choice with significant low FDG avidities. Thus, this PSMA is showing in the pathologies which are showing the low uptake. The use of the 18F-Fluciclovine, is the analog used for the various pathologies. The use of the 18F-Choline PET/CT is being used as the radiotracer of choice for the leptomeningeal metastasis detection.
The radiotracers which will be targeting the various hormone receptors and HER2 are the newer development, and they are having significantly increased efficacy. The use of the 18F-16α-fluoroestradiol (FES) as an substrate of oestrogen receptors is seen widely and can be seen as the source of the ER expression and the pharmacodynamic marker in the ER-directed therapy [63]. The use of the 68Ga-NOTA-RM26, is seen as the ER expression for the improvement in the sensitivity and specificity of breast cancer diagnosis which is seen as close to the 100 and 90.9%, respectively, in the proliferating phase of the menstruating cycles patients. Clinically HER2 status is determined by immunohistochemical or fluorescence in situ hybridization testing of biopsy samples. New PET tracers like the 89Zr-trastuzumab and 89Zr-pertuzumab are being used for the quantification of the HER2 expression of the primary tumour and metastases simultaneously which shows the promising results.
7. PET radiomics
Radiomics is the newer concept of using the various disease characteristics in which the various parameters/features can be taken in the region of interest like the mathematical algorithms. Non-invasive image-derived biomarkers are also generated from PET radiomics based on the pixels, their associated parameters, and their positions [64, 65, 66]. Since the MRI has significantly high sensitivity then the PET- and MRI combination will have better spectrum of features for the building of the predictive models.
8. Summary
The relevance of PET scan is the important aspect of the various techniques which can be used for the various clinical applications. The different protocols need to be set for the different conditions to have the better sensitivity of that particular pathologies. The use of different radiotracers also needs to be explained in detail for the evaluation on the lines of the precision medicine. The various clinical applications are based on the different techniques used as well as the different radiotracers used. The sensitivity of these are based on the using of the optimal parameters for the evaluation of the different tumours or the pathologies. Thus this chapter redefines the important aspects of the both techniques as well as the clinical applications.
\n',keywords:"molecular imaging, PET, CT, radiotracer, fluorodeoxyglucose FDG, photo multiplier tube PMT, uptake",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/81213.pdf",chapterXML:"https://mts.intechopen.com/source/xml/81213.xml",downloadPdfUrl:"/chapter/pdf-download/81213",previewPdfUrl:"/chapter/pdf-preview/81213",totalDownloads:15,totalViews:0,totalCrossrefCites:0,dateSubmitted:"October 15th 2021",dateReviewed:"February 28th 2022",datePrePublished:"April 11th 2022",datePublished:"May 18th 2022",dateFinished:"April 11th 2022",readingETA:"0",abstract:"PET-CT is an important imaging modality which is well established in the recent years. The role of the molecular imaging in the evaluation of the various pathologies has been increased due to the various technological advances, radiotracer advances and also in the research. This chapter is emphasised to give the broader and better overview of the PET-CT imaging which will be used for various applications in broader fields. These advanced imaging techniques will form the basis of the different clinical applications of the PET-CT. Thus, there will have more precise applications in various pathologies which will increase the sensitivity and specificity of the different disease processes. The understanding of the basic techniques is important before being used in various pathologies. The techniques can be routine or special like the puff cheek technique for the better evaluation of the oral malignancies. The newer concept of the dual time point imaging which is being used to differentiate between the various infective and inflammatory lesions from the malignant pathologies. This chapter emphasises the use of the various techniques for various focussed clinical applications.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/81213",risUrl:"/chapter/ris/81213",signatures:"Sikandar Shaikh",book:{id:"10871",type:"book",title:"Computed-Tomography (CT) Scan",subtitle:null,fullTitle:"Computed-Tomography (CT) Scan",slug:"computed-tomography-ct-scan",publishedDate:"May 18th 2022",bookSignature:"Reda R. Gharieb",coverURL:"https://cdn.intechopen.com/books/images_new/10871.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-80355-118-0",printIsbn:"978-1-80355-117-3",pdfIsbn:"978-1-80355-119-7",isAvailableForWebshopOrdering:!0,editors:[{id:"225387",title:"Prof.",name:"Reda R.",middleName:"R.",surname:"Gharieb",slug:"reda-r.-gharieb",fullName:"Reda R. Gharieb"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"427919",title:"Dr.",name:"Sikandar",middleName:null,surname:"Shaikh",fullName:"Sikandar Shaikh",slug:"sikandar-shaikh",email:"idrsikandar@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Positron emission tomography technology",level:"1"},{id:"sec_2_2",title:"2.1 PET annihilation",level:"2"},{id:"sec_3_2",title:"2.2 PET-scan",level:"2"},{id:"sec_4_2",title:"2.3 Developments in PET instrumentation",level:"2"},{id:"sec_5_2",title:"2.4 PET radionuclides",level:"2"},{id:"sec_6_2",title:"2.5 The FDG concept",level:"2"},{id:"sec_8",title:"3. PET imaging applications",level:"1"},{id:"sec_8_2",title:"3.1 Radiolabeled nanoparticles for molecular imaging",level:"2"},{id:"sec_9_2",title:"3.2 Special imaging techniques",level:"2"},{id:"sec_10_2",title:"3.3 Open-mouth technique",level:"2"},{id:"sec_11_2",title:"3.4 Optimization of patient preparation",level:"2"},{id:"sec_12_2",title:"3.5 Precision medicine",level:"2"},{id:"sec_13_2",title:"3.6 Biomarker for precision diagnostics",level:"2"},{id:"sec_14_2",title:"3.7 Tumour heterogeneity",level:"2"},{id:"sec_15_2",title:"3.8 Therapy assessment",level:"2"},{id:"sec_17",title:"4. Methionine",level:"1"},{id:"sec_18",title:"5. Choline",level:"1"},{id:"sec_19",title:"6. Radiotracer advances",level:"1"},{id:"sec_20",title:"7. PET radiomics",level:"1"},{id:"sec_21",title:"8. Summary",level:"1"}],chapterReferences:[{id:"B1",body:'Ter-Pogossian MM, Raichle ME, Sobel BE. Positron emission tomography. 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Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis. npj Breast Cancer. 2018;4:24. DOI: 10.1038/s41523-018-0078-2'},{id:"B66",body:'Moscoso A, Ruibal A, Dominguez-Prado I, Fernandez-Ferreiro A, Herranz M, Albaina L, et al. Texture analysis of high-resolution dedicated breast 18F-FDG PET images correlates with immunohistochemical factors and subtype of breast cancer. European Journal of Nuclear Medicine and Molecular Imaging. 2018;45:196-206. DOI: 10.1007/s00259-017-3830-1'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Sikandar Shaikh",address:"idrsikandar@gmail.com",affiliation:'
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\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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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. This series is intended for doctors, engineers, and scientists involved in biomedical engineering or those wanting to start working in this field.",coverUrl:"https://cdn.intechopen.com/series/covers/7.jpg",latestPublicationDate:"May 7th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:3,numberOfPublishedChapters:96,numberOfPublishedBooks:12,editor:{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. 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. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:null,institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda",middleName:"R.",surname:"Gharieb",fullName:"Reda Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. 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. Osma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDv7QAG/Profile_Picture_1626602531691",institutionString:null,institution:{name:"Universidad de Los Andes",institutionURL:null,country:{name:"Colombia"}}},{id:"69697",title:"Dr.",name:"Mani T.",middleName:null,surname:"Valarmathi",fullName:"Mani T. Valarmathi",profilePictureURL:"https://mts.intechopen.com/storage/users/69697/images/system/69697.jpg",institutionString:"Religen Inc. | A Life Science Company, United States of America",institution:null},{id:"205081",title:"Dr.",name:"Marco",middleName:"Vinícius",surname:"Chaud",fullName:"Marco Chaud",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDGeQAO/Profile_Picture_1622624307737",institutionString:null,institution:{name:"Universidade de Sorocaba",institutionURL:null,country:{name:"Brazil"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/243197",hash:"",query:{},params:{id:"243197"},fullPath:"/profiles/243197",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()