eChapters

Historical Development of Soil Science/Agriculture

Francis Bacon (1561-1624 A.D.): Found the water as nutrient of plants.

Van Helmont (1577-1644): Give the ideas about the role of soil as a simple source of water and minerals for the plants.

Abstract

Rural women play a vital role in farming system operations and contribute substantially in the physical aspect of farming, livestock management, postharvest and allied activities. Around 43% of the agricultural labour force of developing countries is composed of women dependency. India has achieved self sufficiency in agricultural production, but a considerable amount of production gets spoiled in every year due to inadequate post-harvest management, processing, infrastructure and skill. To uplift the livelihood and economic conditions of the rural women there is an urgent need to impart trainings for skill development regarding the value addition of horticultural crops. This offers tremendous opportunities for women occupation but also inculcate entrepreneurial characteristics in them. Trainings and skill development are useful for rural women as they can add more value to the seasonal fruits and vegetables and generate varieties of products namely Pickle, Murabbaa, Chutney, Jam, Sharbat etc. These efforts enhance their family income by around 30-40 thousands per annum as they fetch more prices of raw produce after processing. Moreover during peak production times glut only promote produce and profit loss. Instead of direct marketing of their produce they can do value addition of their produce and then sell them in market, it not only increases the value of their products but the prices also enhance by many folds. After giving training to rural women, they are motivated to go for self marketing of their produce at domestic and village level. Similar way these trainings can transform the life style and income level of farming families comprehensively.

Introduction 
Augmented energy demand as well as impacts of employment of fossil coals on human health and environment, stresses and imposes the need to lessen the use of conventional fuels or replace them. Equally, global warming has stretched to a distressing level due to many diverse anthropogenic actions leading to increased pollution. The alternate energy sources are desirable that might be the conspicuous and sustainable approach of enabling environmental remediation, besides meeting the global energy call (Grosser et al 2016, Kanchanasutha et al 2016). A potential solution is generation of Biofuels, either conventional biofuels produced from agricultural crops or advanced biofuels produced from wastes, inedible crops or forestry products (Sreedevi Sarsan et al 2021). Advanced biofuels production especially by the utilization of agricultural and animal wastes using new technologies and processes are gaining increased interest among researchers and general public all over the world. Food waste, municipal trash, animal waste and other wastes can all be utilised as feedstocks to create biogas, a clean and sustainable energy source and thus may be the ideal replacement for traditional energy sources. The raw biomass may be converted into fuel products like biogas by briquetting, gasification, and anaerobic digestion, among other processes (Deepanraj et al 2015). In comparison to landfills, incinerations, and composting processes, anaerobic digestion (AD) is suggested as an inexpensive and environmentally benign technique for the generation of renewable energy (Van Forest et al 2012; Nishio et al 2007; Capson-Tojo et al 2016; Xu, F et al 2018; Cha, M et al 2020). The production of energy-rich biogas and alleviation of issues related to the removal of organic waste are all achieved by anaerobic digestion (AD) of organic solids (Sonakya et al 2001). This is since AD is a highly energy-efficient and ecologically benign technique. In an atmosphere devoid of oxygen, the AD system uses anaerobic microbes to transform the naturally occurring substances in the biomass into biogas. The primary byproduct of AD, biogas, has a methane content of roughly 50-70% by volume and 30- 40% atmospheric carbon dioxide (CO2) when feedstocks are digested under anaerobic circumstances, with small levels of hydrogen sulphide (H2S) (0.1-3% v/v), humidity, and other trace pollutants also present (Sahota et al. 2018). The generation of biogas is known to be influenced by factors such as waste types, pretreatment procedures, the microorganisms or enzymes added, operation circumstances and design of the digestors (Mao et al 2015).

Introduction

Spectral signature: A spectral signature is the unique pattern of reflection and emission of a target at different wavelengths. This difference helps to classify remote sensing images based on the spectral signatures of different objects.

Electromagnetic (EM) spectrum: The EM spectrum is the range of all types of EM radiation. Some examples are visible light from a lamp, radio waves from a radio station, microwaves, infrared light, ultraviolet light, X-rays, and gamma rays.

Spectral response patterns: A spectral response pattern is the amount of energy that an object reflects or emits at different wavelengths. It shows how the object interacts with the EM radiation.

Acid soils are found in India in about 93 million hectares ( Table 1) and they occur in the Himalayan region, the great Indo-Gangetic and Brahmaputra plains, peninsular plateau and uplands and the coastal plains including island eco-systems under varying environmental conditions of landscape, geology, climate and vegetation. Conditions which are conducive for the formation of acid soils, such as high rainfall coupled with high temperature encouraging intense weathering and loss of alkali and alkaline earth metals with a simultaneous accumulation of iron and aluminium hydroxy compounds or the formation of free acidic substances in the humid forest foot hill regions, exist in some region or other in almost all the states in India.  A soil with pH less than 7.0 is deemed as an acid soil (Soil Survey Staff,1951). However, for characterization and classification, acid soils may be defined as those having pH less than 5.5 in 1:1 water extract (Soil Survey Staff, 1999).

Abstract

Most of the sorghum accessions are landraces, and much of the cultivated area of sorghum is under local land races. The local land races are highly adapted to specific environmental conditions and are useful sources of genetic variation. Under the present investigation one hundred and two local land races of sorghum collected from different geographical origins were evaluated during kharif 2010 and kharif 2011 in order to assess the genetic diversity. The analysis of variances showed highly significant differences among the accessions for all the characters studied.

Abstract

The genetic divergence among 249 germplasm lines of maize was assessed by D2statistics based on nine parameters at Agricultural Research Station, Karimnagar. The germplasm lines were grouped into eleven clusters. Clusters I and II were the largest clusters with 73 and 79 genotypes, respectively. The highest inter cluster distance was observed between cluster X and XI followed by cluster V and XI indicating more variability in the genetic makeup of inbreds included in these clusters. Cluster V showed highest mean values for grain yield/plant and ear length. Cluster XI had the lowest mean values for plant height and ear height and these two characters showed maximum contribution towards total divergence among different characters. Based on inter cluster distances, inter crossing among the genotypes belonging to cluster V, IX, X and XI has the chance of getting high yielding hybrids with higher heterosis.

Abstract

Genetic diversity of thirty two rice genotypes from different states of India was evaluated through Mahalanobis’s D2statistic under integrated fertilizer management for fourteen yield and quality characters. The genotypes were grouped in to seven different clusters. Cluster I had nine genotypes. Three genotypes each were included in cluster II, cluster IV and cluster VII, whereas six and seven genotypes in cluster III and cluster V, respectively while the cluster VI had only one genotype. The results revealed that the geographic diversity might not always be related to genetic diversity. Kernel length after cooking, days to maturity and kernel breadth contributed maximum towards divergence indicating their importance in choice of parents for the hybridization programme.

Ralstonia solanacearum is a phytopathogenic bacterium belong ing to the b subdivision of the Proteobacteria (Yabuuchi et al., 1995) having a wide geographical distribution ranging from tropical, subtropical and warm temperate regions (Liu et al., 2009). It has broad host range and infects around 54 plant families and 450 plant species (Hayward, 1991; Wicker et al., 2007). 

Early attempts to study the diversity present in the R. solanacearum species complex resulted in separate race and biovar systems. R. solanacearum has been phenotypically classified into 5 races based on the host range at the plant species level and into five biovars based on the metabolic profiles related to the ability to reduce three disaccharides and three hexose alcohols (Wicker et al., 2007).

Abstract
Understanding genetic diversity is essential for achieving genetic improvement and conservation of grain legumes. These crops serve as important pulses grown and consumed all over the world, especially in Africa, South East Asia and America. Legumes serve as a good source of carbohydrates, oil, fibre and proteins. Grain legumes are a major source of food and nutrition globally. However, it has not been possible to enhance gain legume production to the required level, primarily due to the narrow genetic base of most of the legume crops, coupled with changing climatic conditions. Most grain legumes are lacking in desired plant ideotypes and resistance sources for various biotic and abiotic stresses. The genetic diversity conserved in gene banks globally is a major resource for crop breeding programs, but it
is utilized only marginally. Therefore, in order to broaden the genetic base of grain legume crops and enhance the genetic gains made in improvement programs, conventional approaches and modern scientific tools should be integrated in a phased and carefully judged manner. The first phase should focus on the search for desired traits and the infusion of diversity into the cultivated gene pool through use of landraces and CWRs. The second phase should focus on the utilization of advanced selection tools, such as genomics, high-throughput precision phenotyping, and artificial intelligence, to exploit the hidden potential of the available genetic diversity; and the third phase should involve technologies such as mutational breeding, genome editing, and transgenic technologies to improve, modify any novel or alien traits that are not available in the entire crop gene pool. We presume that enrichment of the genetic diversity of cultivated grain legume gene pools, along with simultaneous improvements in their yield and plant type with the aid of advanced scientific tools, will enhance grain legume crop yields to the required level.
Keywords: Crop improvement, Genetic diversity, Genome editing, Legume, Phenotyping

Development of sophisticated procedures for the isolation, manipulation and expression of genetic materials is a field called genetic engineering. Genetic engineering has applications in both basic and applied research. In basic research, genetic engineering techniques are used to study the mechanisms of gene replication and expression in prokaryotes, eukaryotes and viruses. For applied research, genetic engineering used for development of microbial cultures capable of producing valuable products such as human insulins, growth hormones, interferons, vaccines, enzymes etc. The commercial application of genetic engineering is sometimes referred as Biotechnology. In broad sense, Biotechnology refers the use of living organisms to carry out defined chemical processes for industrial application.

The process of isolation, purification and replication of specific DNA fragment is called molecular cloning or gene cloning. Molecular cloning is the base of most of the genetic engineering procedures. The purpose of molecular cloning is to isolate large quantity of specific genes in pure form. Thus molecular cloning is very important in genetic engineering and can be divided into several steps depends on the purpose. The steps are as follows:

Introduction

One of the main environmental problems is the improper disposal of agricultural waste, which has a negative impact on ecosystems when it is carelessly dumped into the environment. According to the majority of publications, burning, dumping, or storing the untreated and unused agro-industrial waste in a landfill are the methods used for disposal (Neh, 2020). Untreated trash increases the amount of greenhouse gases released into the atmosphere, which in turn aggravates climate change in a number of ways. This has detrimental consequences on the climate in addition to releasing more unwanted gaseous byproducts (Toop et al., 2017). As a result, substantial interventions are needed to use agro-waste sustainably. This can be achieved through the development of bioproducts with added value and sustainable energy technologies. Increased garbage output worldwide has put more stress on the environment, causing harm to soil, air, and water resources (Rao and Rathod, 2018). These effects jeopardize population health and the long-term sustainability of ecosystems. According to Zeidabadi et al. (2018), the agriculture sector produces between 21 and 37 percent of greenhouse emissions. A sustainable development paradigm that advocates for significant changes to traditional agricultural production techniques and waste management has emerged in response to this new reality. According to Torres-león et al. (2018), agro-wastes contain high amounts of complex carbohydrates, proteins, fibers, polyphenolic components, bioactive substances, etc. Organic compound wastes can be used as a raw material for a variety of agricultural, food, and pharmaceutical products, even if they are hazardous to the environment (Uzodinma et al., 2007). Because of their high nutrient content, agro-residues are not seen as trash; rather, they are exploited as a source material for new goods. The cost-effectiveness of conversion procedures for the development of bioproducts can be increased by using efficient pre-treatment technologies for agro-waste biomass, as well as by utilizing its biochemical properties and sophisticated conversion processes (Yusuf, 2017). The bioconversion of agricultural waste into enzymes and other bioactive compounds for the pharmaceutical industry, vermicompost, organic fertilizers, and biofuels for the agriculture sector, as well as nutraceuticals and food products, is greatly aided by microbial biotechnology and nanotechnology (Beltrán-Ramírez et al., 2019: Samborska et al., 2019). In the food and healthcare sectors, nanotechnology is being studied more and more because of its numerous potential uses. As previously indicated, the increased bioavailability and quantities of bioactive compounds significantly improve the potential for targeted delivery of bioactive compounds to particular tissues or organs. Nano-structured materials’ distinctive qualities and vast surface area make them potentially revolutionary for the food industry. Although the potential advantages of nanotechnology for society at large have been well acknowledged, food science has only lately started to investigate its uses (Del Rio Osorio et al., 2021).

Introduction
Genetic engineering is the process of modifying an organism’s genome, frequently to add or eliminate desired features. This field is developing quickly and has many uses in biological sciences, the agricultural sector and medicine. Gene therapy is a medical application of genetic engineering that corrects or replaces malfunctioning genes using beneficial ones to alleviate genetic illnesses. It is used in gene therapy and medicine to treat hereditary illnesses by introducing therapeutic genes into the body or fixing defective genes. Generating genetically modified organisms (GMOs) in agriculture as crops enhanced to withstand pests or environmental conditions also depends significantly on it. Over the last 10 to 20 years, genetically modified organisms (GMOs) have been incorporated into the system of agriculture and products for the consumer sector. This developed in the USA but has since spread to poorer nations. Since genetic engineering was discovered, its ability to alter the genetic material of living things’ DNA has been identified. The debates have taken place worldwide but have gained the most traction in the European Union due to mistrust in scientists, regulatory bodies and technology decisions. The genetic hinders can potentially enter a new cell through bacteria or viruses. Transgenic plants are those created using transformation techniques (such as Agrobacterium-mediated transformation or direct gene transfer) that insert specific foreign nucleotide or gene sequence regions into their genome (Grifths et al. 2005).
Agrobacterium rhizogenes and A. tumefaciens are common vectors used in plant-to-plant gene transfer. The desired gene inserted into the bacteria’s DNA will be transferred to the plants by the bacteria when they infect them with an individual plasmid in the soil. Vector transmission of genes is a natural environmental alteration, the favored modification technique. A curious field at the intersection of biotechnology and genomics is the field of genetic engineering. To put it bluntly, it’s the process of modifying an organism’s DNA to introduce new or altered features. Altering the DNA is a technique that allows for inserting, deleting or modifying particular genes to modify property or add new functions. Genetic engineering has many valuable and significant applications. It is used in agriculture to produce crops with better nutrient content and increased resilience to pests, diseases and environmental stress. According to studies, tissue-specific, promoters-especially stress-inducible promoters, which limit transgene expression to the stress period-improve the phenotypes of transgenic plants when compared to constitutive promoters (Shavrukov et al., 2016). Biotechnology also involves genetic engineering in producing illicit substances, enzymatic agents and bioenergy.

Technologiocal intervention is essential for improving pulse productivity through introduction of suitable high yielding varieties (Masood Ali and Shiv Kumar 2009). This is only possible through: (i) development of high yielding varieties with multiple resistance/tolerance to major diseases like mung bean yellow mosaic virus (MYMV), powdery mildew (PM) and Cercospora in mung bean and urdbean; (ii) development of varieties having resistance and tolerance to pre-harvest sprouting in mung bean, (iii) development of efficient plant type with high biomass and harvest index, (iv) development of varieties suited for intercropping system, (v) broadening genetic base of developed varieties, (vi) development of 50-55 days varieties of mung bean having 1 tonne/ha productivity and resistance to YMV for summer cultivation, (vii) development of high yielding and early maturity varieties of peas having resistance to powdery mildew, (viii) developing rajmash genotypes resistant to bean common mosaic virus and sclerotia rot, tolerant to high/low temperature and shattering resistance are important ones for increasing production through varieties intervention (AICRP MuLLaRP, http://iipr.res.in/mullarp).

Genetic purity is the vital determinant in continuing the genetic integrity in seed from generation to generation. This is the basis of variety purity maintenance. The genetic purity depends upon the purity of the seeds planted. The genetic purity of the seeds planted must exceed or equal to the final product purity standards required as the purity generally decreases with subsequent generations of propagation. The improved varieties loose their identity and healthiness unless properly maintained. Maintenance selection can prevent the seed quality deterioration.

Millets are the staple food cropsacross the globe. The ability to thrive in harsh conditions established them as most suitable for current climate adversaries. The nutritional richness of millet reminded the need for adding them to our food basket.Despite possessing several desirable traits their cultivation is limited to a few pockets across the globe.Though significant progress has been achieved by conventional and transgenic breeding programs inmillets, there is a need for rapid improvement to meet the current needs.In order to accelerate the pace of breeding efforts, several molecular biology and biotechnology tools are being deployed by plant breeders. In the meantime, genome editing techniques like CRISPR, TALENS, ZFNs, Base and Prime editing have revolutionized the methods of genome engineering among which CRISPR has emerged as the most rapid, convenient and effective mechanism. The availability ofwhole genome sequence information, identified candidate genesfor various traits and successful transformation methods of millets promoted the application of CRISPR and resulted in the improvement of several traits. Initially, its application has been limited due to the restricted policies across the globe but the gradual change in the policies promoted genome editing across several parts of the globe. Thus, the application of genome editing for millet crop improvement can bring back those ancient grains to our food basket.

Modern plant genomics generates highly complex and high-dimensional datasets that require advanced computational approaches for effective analysis. This chapter explores the application of artificial intelligence to plant genomic data analysis. Machine learning and deep learning techniques are discussed for identifying complex patterns, classifying genomic information, predicting phenotypes and supporting genomic selection. Convolutional neural networks, long short-term memory networks and transformer models are considered for analyzing genomic sequences and relationships. The chapter presents an AI-based framework integrating data processing, model development and prediction while highlighting the challenges associated with genomic data heterogeneity and dimensionality. It emphasizes the potential of AI for improving genomic research and plant improvement strategies