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The World Health Organization (WHO) declared COVID-19 (novel coronavirus) as a global pandemic in the middle of March 2020, after the disease spread to more than 150 countries and territories leading to tens of thousands of cases within a couple of months. To date, there are no effective pharmaceutical treatments available. As well as that, the novel vaccines have not yet been approved as establishing their efficacy will take time. This study aims to summarize the evidence regarding corticosteroids such as dexamethasone for the treatment of COVID-19. Electronic searches were conducted on 7 September 2020 on Google Scholar database, MEDLINE and PubMed. A further search was conducted on the World Health Organization's COVID-19 research article database. The findings of recent investigations that proved, both, the in vitro and in vivo activity of corticosteroids against COVID-19 and other coronavirus-related pneumonia were discussed. Low doses of corticosteroids (dexamethasone) could reduce the mortality in patients with severe COVID-19 disease; however, they had no effect on the mortality rate of those patients with a mild form of the condition. Moreover, the liberal use of corticosteroids was not advocated for, as high doses of the drug can cause more harm than good.

Nutrients are required for plant growth and development, absence or shortage of this could limit crop productivity. However, the misappropriate application of nutrients could cause environmental challenges like greenhouse gas emission, global warming, and climate change. Nutrient dynamics also seem to be affected by climate change as all the processes in which nutrients are taken up, transferred, and cycled over time in an ecosystem are linked with climatic factors directly or indirectly. Many biogeochemical models including APSIM (Agricultural Production Systems Simulator), CropSyst, CERES-EGC, DayCent, DNDC (DeNitrification DeComposition), DSSAT (Decision Support System for Agrotechnology Transfer), EPIC (Environmental Policy Integrated Climate), PaSim, RothC (Rothamsted Carbon Model), and STICS (SimulateurmulTIdisciplinaire pour les Cultures Standard, or multidisciplinary simulator for standard crops) can be used to study the nutrients dynamics which includes uptake from the soil, assimilation, and remobilization in plants. This chapter presents the application of different biogeochemical models to simulate nutrients dynamics, mainly Carbon (C), Nitrogen (N), and Phosphorus (P). Soil organic carbon (SOC) dynamics and loss of N as nitrous oxide (N2O) emission is also discussed by using models like APSIM and DNDC. Finally, life cycle assessment (LCA) is presented as a valuable tool to study environmental impacts associated with all steps of nutrients distribution among different systems. In conclusion, process-based biogeochemical cycles are valuable tools that can be used to study and manage nutrients in soil-crop system under changing climate.

Production of crops and climatic changes are internally linked with each other in several features because changes in climatic conditions are the key reason for abiotic as well as biotic stresses, that have adversative influences on the farming systems at local, regional, and global levels. The yields of major agronomic crops are being negatively impacted by climatic changes in several aspects like disparities in rainfall pattern and intensity, mean temperature, heat waves, changes in weeds infestation, disease causing microorganisms, and pest attack during all growing seasons in major cropping systems. Heat and water shortage stress disturb the crop yield in various ways as response of crop towards these impacts of climatic variables vary. Higher temperature frequently causes a reduction in crop production by reason of the fact that, they generally happen in combination with drought. Crop phenology is negatively affected due to climate change. Yield and yield components are more sensitive under drought condition in comparison to higher temperature in all cropping systems. In this chapter, we summarize the impact of climate change and stresses produced due to climate change on crop production.

Cotton fiber quality is a complex trait which is influenced by environmental stresses. Breeding alone is not found up to the mark to get the desired fiber quality. Combination of approaches to bring all fiber quality traits through gene pyramiding can only be attained by genetic modification followed by breeding. Genetic modification is increasingly being used in biotechnology. Improved cotton fiber quality is always preferred by the textile industry. Researchers are working hard to reveal genes involved in controlling various fiber characteristics; resultantly several genes have been identified. Studies determined the effects of variation in expression of fiber-related genes transcription factors, and genes expressing phytohormones can have its impact on altering the fiber quality. Introduction of single gene cannot impart the desired results, but combination of fiber-related genes and transcription factor controlling gene expression can be useful strategy for fiber improvement. This chapter highlights the structure and composition of fiber at various developmental stages and also the impact of transgene in improving fiber traits.

Abiotic stress is a problem of grave concern for the growth and productivity of plants in modern times. Abiotic stresses, such as drought, salinity, extreme temperatures and extreme radiation, are responsible for huge crop losses globally. Plants face a combination of different abiotic stresses under field conditions that are lethal to plant growth and production. Exposure of plants to biotic and abiotic stress induces a disruption in plant metabolism implying physiological costs and thus leads to a reduction in fitness and, ultimately, in productivity. Abiotic stress is one of the most important features of and has a huge impact on growth, and consequently, it is responsible for severe losses in the field. The resulting growth reductions can reach more than 50% in most plant species. One of the physiological processes greatly affected by these stresses in plants is photosynthesis. The decline in photosynthetic capacity of plants due to these stresses is directly associated with reduction in yield. Application of nutrients to overcome nutrient stress positively affects plant growth, yield and quality. Transition/heavy metals such as zinc, manganese and copper are essential minerals for healthy plant growth. Micronutrients are essential for balanced nutrition in plants under abiotic stress conditions. The present chapter describes the role of macro- and micronutrients under stress conditions. In this chapter, we have discussed a variety of macro- and micronutrients which are beneficial for plant physiological development under stress conditions.

The use of nanotechnology in agriculture is increasing at a phenomenal rate. It is, therefore, necessary to appreciate and elucidate the role of nanoparticles (NPs) in plant growth and development. Silicon is regarded as a ‘quasi-essential’ element for plants and regulates a range of physiological processes including germination, vegetative growth, photosynthesis and stress tolerance. It is, therefore, of importance to assess the effects of silicon nanoparticles (SNPs) on these physiological processes, as SNPs are considered more efficient than their bulk particles due to their small size and high surface area and reactivity. The present chapter deals with the role of SNPs in plant growth, photosynthesis and stress tolerance. Additionally, potential toxic effects of NPs are presented.

Analysis of data is very important for accurate prediction. Particle Swarm Optimization (PSO) and Support Vector Machine (SVM) is used for load forcasting. Features are selected using PSO and redundant features are removed. Data is divided into training and testing data. Load forecasting is done by using SVM classifier. However, SVM classifier predicts short term load accurately and efficiently. Multiple time testing is done on data for checking accuracy of PSO. SVM shows efficient performance as compared to Principle Component Analysis (PCA).

Today global climate change and its impact on crop production is a major issue. Climatic factor such as temperature has been closely linked to agricultural production. According to the international panel on climate change (IPCC) these changes are very rapidly affecting crop productivity. To explore the future climate change impacts on wheat yield in Pakistan, especially the rain fed region of Pothwar which is considered vulnerable to climate change, a wheat crop simulation study was conducted. The specific objectives of the study were to (a) simulate the impact of climate change using DSSAT on wheat yield in the Pothwar region using IPCC climate change scenario for Pakistan and (b) generate spatial maps of wheat yield and correlate with climatic factors. The crop simulation study assessed the impact of rise in maximum and minimum Temperature on the wheat yield. The CERES-Wheat which is a component of the Decision Support System for Agrotechnology Transfer (DSSAT) model was used to input soil, crop management practices and weather data. IPCC Fourth Assessment report B1 scenario for increasing temperature was used in the simulations. The simulated results were imported into ArcGIS to produce regional impact maps for visual assessment and spatial analysis under different climate change scenarios levels through an interface of ArcMap. The DSSAT model simulated results showed that the rise in maximum and minimum temperature decreased the wheat yields across the Pothwar region. The similar methodology could be adopted for different crops in other parts of the country for better mitigation of future food security.

Bioinformatics is an interdisciplinary science emerging from interaction of computer, statistics, biology and mathematics to analyze genome arrangement and contents, biological sequence data, predict the structure and function of macromolecules that use in interpreting and decoding plant genome. The broad amounts of data produced in life sciences resulted to the evolution and development of bioinformatics. Omics, bioinformatics and computational tools are very essential to understand genomics and the molecular systems that underlie several plant functions. Various new omic layers such as genome, hormonome, metabalome, interactome, and epigenome analysis have emerged by technological advances. Such integration of information enables and facilitates the identification of expression of gene which helps to interpret the relationship between phenotype and genotype, thus approving from genome to phenome system-wide analysis. Earlier biological research that used laboratories, plant clinics and field is now at In-silico or computers level (Computational). Bioinformatics develops software, algorithms, databases and tools of data analysis to make discoveries and infer the information. Application of various bioinformatics tools and databases enable analysis, storage, annotation, visualization and retrieval of outcomes to helps enhanced understanding in living system research. Thus it will help to improve the plant quality based on health care disease diagnosis. In this chapter we describe the bioinformatics approaches (databases and tools) in plant science and implication of next generation sequencing technology (NGS) on crop genetics.

Drought affects wheat crop adversely resulting in reduced growth and productivity. The physio-biochemical adaptations of wheat were studied using ten wheat genotypes namely V-4178, PDW-34, Chakwal-97, Shorawaki, 4098805, Baluchistan, Yecora-70, S-24, SARC-1 and Pasban-90 were sown in pots by using completely randomized design two factorial with three replications. Wheat genotypes were raised at two soil moisture levels i.e. soil moisture level maintained at 100 % field capacity and soil moisture level maintained at 40 % of field capacity. The effects of the two soil moisture levels were studied on wheat genotypes by considering the parameters photosynthetic rate (An), transpiration rate (E), stomatal conductance (gs), stomatal resistance (rs), leaf membrane stability index (LMSI), leaf succulence, relative water content (RWC), epicuticular wax, proline contents, chlorophyll content (SPAD), grain yield, biological yield and harvest index. Drought was considered responsible for the enhanced production of proline and epicuticular wax, reduced stomatal conductance, high stomatal resistance, low photosynthetic and transpiration rate in genotypes as a mechanism to bear the harsh conditions. Low harvest index, biological yield and grain yield were also recorded as a result of drought. Hence, it is concluded that the genotypes resistant to drought performed better under drought conditions due to better physio-biochemical adaptations.

A comprehensive overview of greenhouse gas (GHG) emissions of from different sectors across the globe is provide in this chapter. Particular attention is given to agriculture, forestry, and other land use (AFOLU). Since agricultural activities (cultivation of crops, management activities and rearing of livestock) result in production and emissions of GHG, quantification of GHG and its mitigation is addressed in this chapter. The suggested mitigation techniques include the use of bioenergy crops, fertilizer and manure management, conservation tillage, crop rotations, cover crops and cropping intensity, irrigation, erosion control, management of drained wetlands, lime amendments, residue management, biochar and biotechnology. Furthermore, quantification of GHG emissions is discussed using different process based models. These models could further be used as decision support tools under different scenarios to mitigate GHG emissions if calibrated and validated effectively.

Nitrogen is the most limiting element in the production of cereal crops after water hence leads plant nutrition. Since, nitrogen uptake and supply directly depends upon soil physical conditions, climate and plant genetic features, so N requirement could be varied by place to place. Crop simulation models can be complementary tools in field experiments to develop innovative crop management systems under continuous varying nitrogen regime. Data regarding total nitrogen, nitrogen uptake efficiency, nitrogen utilization efficiency and nitrogen utilization efficiency, drymatter accumulation at three phenological stages (Three leaf, Anthesis and Maturity), and yield parameters (Number of tillers, Biological yield, Thousand grain weight, Grain yield and Harvest index) were recorded. The present study revealed that different nitrogen rates and application methods have significant impact upon crop growth and development. Wheat crop responded well to nitrogen fertilizer. Maximum grain yield obtained for N100 when nitrogen was applied as split dose. Similarly, genotypes responded significantly to nitrogen fertilizers for grain production. Genotype NARC-2009 performed well under different nitrogen regime of rainfed zone of pothwar. APSIM model was parameterized using different agronomic parameters (days after sowing, biomass total nitrogen, root total nitrogen, grain yield and grain total nitrogen). The modeled nitrogen was satisfactory compared to observed nitrogen. The analysis of the modeling results depicted the strong dependency of the mineral nitrogen content upon plant nitrogen uptake and growth. By concluding APSIM model performed well under rainfed conditions of pothwar for modeling nitrogen use efficiency. Modeling approaches should be adopted by farmers and policy makers to get maximum crop production and eliminate extra nitrogen losses.

Earth life is greatly dependent on function and properties of water. A major threat to agricultural production is drought. Drought is a multidimensional stress and world spread problem that cause substantial losses by influencing the yield and production seriously. Tolerance to drought is a principal target for molecular strategies to crop enhancement. The plants ability to resist drought conditions is important for agricultural production globally. Current progress in responses to drought has been made in our comprehending of signal transduction, gene expression and transcriptional regulation in plants. Plants have developed a diverse variety of drought resistance mechanisms in front of water limiting conditions at physiological, metabolic and molecular level. Water uptake and development of healthier root, WUE, osmotic adjustment, and mineral nutrients also have important consequences on adaptation to drought. This chapter is organized around the concept of “drought tolerance in rice and maize crops”. Some innovative tactics are discussed. This chapter summarizes different aspects of crop breeding for drought tolerance and analyses how conventional breeding, genetics, biotechnology tools, micro arrays, MAS, QTL, bioinformatics and transgenic crops as well as mineral nutrients, plant growth regulations can participate to advancing the emancipation of drought-resistant rice and maize cultivars. We foresee the functional and genetic of drought resistance based on such premises. Novel opportunities for tailoring new genotypes will be generated ‘by design’. Harnessing the genomics-assisted breeding’s potential will need an integrated knowledge of physiological and molecular processes and a multidisciplinary approach influencing drought tolerance.

A project was executed to study genotype to phenotype relationships through QTL analysis in a recombinant inbred population of 77 lines and its integration in crop simulation modeling. RILs were generated from a cross between wheat cultivar Opata and SH-349. At two leaves stage drought was imposed using gravimetric method for drought maintenance at 40 % of field capacity and control was maintained at 100 % field capacity. At three phenological stages viz. jointing, flag leaf and anthesis; photosynthetic rate, stomatal conductance, transpiration rate, stomatal resistance were determined and chlorophyll content was measured. The RILs under study exhibited high phenotypic variation under drought stress. The physiological and phenological data was used to parameterize and validate Agricultural Production Systems Simulator (APSIM); a crop growth and development modeling tool. It was noted that APSIM predicted the phenology of all the 77 RILs with R2 value ranging from 0.72 to 0.98. The same mapping population was used for QTL mapping using computational approaches with observed data and simulated data from crop simulation model APSIM. In linkage group 1 a single QTL controlling 13 physiological traits and another QTL controlling a single trait for phenology was found. In linkage group 2 one QTL controlling 7 phenological traits was mapped. The QTLs which were mapped with real data were the same as with simulated data. This indicated that the simulated data with crop models under different environmental scenarios could be efficiently used for QTL mapping reducing the environmental contribution in G x E complex and suggesting the QTLs with more precision. Photosynthetic attributes of these RILs under drought stress at different phenological stages suggests complex physiological aspects critical for coping moisture stress and provides a strong basis for their utilization in wheat cultivar improvement for drought stress adaptation under changing climatic scenarios.

Wheat is sown over a wide range of sowing date in various cropping systems of rainfed and irrigated areas of Pakistan. This variation in sowing time is caused by various factors such as erratic rainfall in rainfed area, late planting or harvesting of preceding crop, lack or unavailability of farm machinery and inputs. At present the greatest challenge which is being faced by the agriculture sector is production of more food from less available water. Increasing water productivity of the crops can help in facing this challenge. For understanding the relationship between water and food, a sound knowledge of crop water productivity (CWP) is important. Dynamics of crop environment proved most important in rainfed areas for crop production. Therefore, to achieve higher CWP (crop water productivity) under changing climatic conditions, increasing WUE (water use efficiency) could be an option by adopting mitigation strategies. These measures might be, adopting good management practices like optimizing the sowing date on long-term basis using simulation modeling as decision support tool. In the present study, Soil and Water Assessment Tool (SWAT) model was parameterized and validated to study the relationship between yield and crop water productivity of rainfed wheat. For this study, field experiment was conducted at three locations using three wheat cultivars and two sowing dates. Crop water productivity was calculated by dividing the grain yield by evapotranspiration during crop growth cycle. Satellite based parameterization of study area for GIS mapping, topographic analysis, vegetation dynamics, land use, and soil mapping was done by using different software packages like ArcGIS 10.1, Erdas Imagine, QGIS, and Swat-CUP. The SWAT model was used to simulate the processes related to the soil-crop-atmosphere interaction in the present study and it showed significant potential to simulate CWP.

Phosphorus the macronutrient, a component of nucleic acid and helpful for grain developmental phases (reproductive growth) of crops. It is also component of energy carriers like ATP, ADP, NADPH and FADPH which provide energy for different physiological processes. Phosphorous plays an important role in the growth, development and yield of crops. However, P causes some environmental problems like eutrophication. The importance of the element necessitate its study through modeling and distribution under changing climate. Since P is present as organic and inorganic form but their fate is different in soils. The inorganic P accounts for 35–70 % while organic form of P accounts for 30–65 % of the total P but it is dominantly available as stabilized forms like diesters. The availability of this P depends upon mineralization processes by soil biota which has dependency upon soil moisture, temperature, physiochemical properties and soil pH. However, the transformation of organic p has strong influence on the availability of P in soil. Therefore, availability of P to crop is extremely complex and its needs to be evaluated using modeling approaches. The Phosphorus Use Efficiency (PUE) for crops might be increased by understanding P-dynamics which may be done by models. The understanding of P dynamics will help to optimized balance use of P. By monitoring P for longer period of time might increase P status of soil. The use of computer models will help to modify fertilizer application which can reduce use of P but will increase PUE. The effects of high temperature, elevated CO2 and drought on the availability of phosphorous, PUE and its dynamics could be modeled using dynamics models like APSIM, AEP or by using regression modeling approaches.

Rice feeds half of humanity. Global climate change has given rise to food security issues. Changes in temperature and rainfall may affect the yield of rice as its water requirement is higher than other crops. Though rice is adaptable to a variety of environments, seasonal rainfall variability, and even at times complete absence of rainfall, are major issues in rice growing areas. This chapter discusses problems in the rice growing areas and possible solutions. The need of the hour is to find new strategies and ways to exploit the genetic yield potential of rice. Water use efficiency improvement is vital for the crop so that it may be grown under water-limiting conditions. The crop may be improved by selection and breeding techniques as well as molecular and biotechnological techniques. Crop management for enhanced water use efficiency has great significance. Production systems such as the system of rice intensification (SRI), alternate wetting and drying irrigation (AWD), aerobic rice system (ARS), raised beds and ground cover rice production system (GCRPS) to enhance water use efficiency are beneficial. Incorporation of the C4 photosynthetic pathway into rice is another approach to increase rice yield for food security problems in future. The conversion of rice from C3 to C4 will enhance the yield of the crop. All these techniques can help tackle the problems of water scarcity and food security.