eChapters

Introduction
Maize (Zea mays L.) is the second most widely crop grown globally after wheat, with 205 million hectares under cultivation. The area cultivated under maize is steadily increasing and expected to overtake that of wheat by 2030 (Erenstein et al., 2022). With production exceeding 1.2 billion metric tons, maize surpasses the production of other highly cultivated cereals like wheat and rice mainly due to its higher yields (Erenstein et al., 2022). Maize is cultivated in the Americas, Africa, and Asia, for multiple end-uses (Nuss and Tanumihardjo, 2010). It is a staple food in several countries across Africa and Latin America, and in a few countries in Asia, with an overall contribution of 15-20% of daily calorific needs (Shiferaw et al., 2011).
The global maize yield tripled from the 1960s with the average yield rising from 2 tons/ha to the current 5.8 tons/ha, mainly due to the adoption of highyielding hybrid cultivars and complementary input use (Erenstein et al., 2022). Maize is naturally an outcrossing species and inbreeding is unnatural. When maize is subjected to inbreeding and the resulting inbred lines from genetically distant backgrounds are crossed, hybrid vigor or heterosis is realized (Springer and Stupar, 2007). Hence, the development of the homozygous inbred lines is a very important step in hybrid maize breeding.
In the well-evolved maize breeding programs, the germplasm is well characterized into different heterotic groups where the hybrids developed by crossing inbred lines from different heterotic groups exhibit high heterosis (Ertiro et al., 2017a; Sang et al., 2022). For the development of inbred lines, maize breeders develop F1 populations by crossing two inbred lines within the same heterotic group (Prigge et al., 2011; Sang et al., 2022). Inbred lines are developed from the F1 population by recurrent self-pollination for 6-8 generations; this can take up to 3-4 years or even more, depending on the availability of off-season nurseries for generation advancement. The resulting inbred lines are highly homozygous (~98-99%), but not 100% homozygous. The doubled haploid (DH) technology emerged as a viable alternative to the time-consuming and resourceintensive recurrent selfing method to produce 100% homozygous inbred lines in just two crop seasons (Prasanna et al., 2012; Chaikam et al., 2019a).
In addition to significantly reducing the time taken to develop homozygous lines, the use of DH lines in maize breeding offers several other benefits: a) As DH lines are completely homozygous at all loci, they are stable and do not show further inbreeding depression; b) DH lines are also best suited for evaluating distinctness, uniformity and stability (DUS) criteria, thereby better facilitating plant variety registration and intellectual property protection (Röber et al., 2005); c) The use of DH lines facilitates selections on completely homozygous lines which is more reliable and effective compared to selections on segregating families with different levels of heterozygosity (Chaikam et al., 2019a); d) Use of DH lines also simplifies breeding operations like planting, managing the nurseries, seed shipments, record keeping, etc. as selfing nurseries spread over several generations are replaced by just two generations for DH line development (Prasanna, 2012; Röber et al.,

Introduction
Plant being sessile are subjected to a myriad of biotic and abiotic stresses that impede growth and resulting significant losses in crop productivity globally (Bhat et al., 2019; Ganie & Reddy, 2021). In this context, there is an immediate need to develop high yielding climate-resilient crop varieties for ensuring food security in the face of increasing population growth. Although conventional breeding has achieved notable success in the development of high-yielding crop varieties (Bhat et al., 2020), but this approach is slow to maintain pace with ever increasing population. In this regard, more recent approach of genomics-assisted breeding (GAB) has emerged as a pivotal approach to develop the high-yielding climate resilient crop varieties (Bhat et al. 2021). Although, low-throughput sequencebased markers like simple sequence repeats (SSRs) have been extensively utilized in molecular breeding programs, but they have the limitations of reduced genomic coverage and high cost (Varshney et al., 2014; Zargar et al., 2015). In this context, the emergence of second-generation DNA marker systems has provided higher genomic coverage and low cost in marker-assisted breeding. For example, recent advancements in next-generation sequencing (NGS) and genotyping platforms have substantially enhanced marker density and genomic coverage while reducing costs (Przewieslik-Allen et al., 2019); thus rendering them commercially available for both model and non-model crop species (Huang & Han, 2014; Rasheed et al., 2017). These high-throughput genotyping platforms provides millions of DNA polymorphisms (Bassi et al., 2016; Ganal et al., 2012), thereby enhancing gene mapping resolution and prediction accuracy in genomic selection (GS) (Robertsen et al., 2019; Yu et al., 2019). Most of the agriculturally important crop traits, such as yield, quality, and stress tolerance, possess complex inheritance i.e., governed by multiple genes with minor effect on trait of interest as well as are highly influenced by genotype-by-environment (G × E) interactions (Voss-Fels & Snowdon, 2016). The conventional linkage mapping approach has elucidated the genetic basis of agriculturally important complex traits but this approach involves the use of bi-parental mapping populations which are constrained by the limited genetic diversity, low resolution, and restricted recombination events (Brachi et al., 2011; Collard et al., 2005). Consequently, the genome-wide association study (GWAS) has emerged as a powerful approach for dissecting the genetic basis of complex quantitative traits in crop plants, resulting higher resolution and allelic diversity (Varshney et al., 2020; Zhu et al., 2008). Moreover, owing to the availability of cost-effective and high-density genotyping platforms, has allowed the routine use of GS in the crop breeding which is more recent approach of GAB (Crossa et al., 2017). In recent years, the advent of next-generation sequencing (NGS)-based genotyping techniques has significantly allowed the genotyping of extensive germplasm collections, enabling comprehensive GWAS and GS analyses (Annicchiarico et al., 2017; Zargar et al., 2015). Nonetheless, the predominant limitations impeding the utilization of SNPs in the GWAS and GS approaches encompass their inherently biallelic nature, the occurrence of rare alleles, and the prevalence of linkage drag (Voss-Fels & Snowdon, 2016; Wray et al., 2013). In

Introduction
A breeding value is essentially the additive effect of a trait of interest that can be passed on stably to offspring. In artificial selection, the breeding values of the genotypes are determined. Hence, the key question is how to quantify the breeding value of a genotype for a phenotypic trait of interest that is part of a breeding program. As part of the process of breeding livestock, the estimated breeding value (EBV) is predicted based on a model that relates the phenotype over a population of genotypes with their pedigree information by using the best linear unbiased prediction (BLUP). Nevertheless, this method is not feasible for populations with no pedigree information or a complex population structure, which is typically the case in plant breeding when there are no pedigree records. With genomic selection (GS), this problem is addressed by determining the genomic estimated breeding value (GEBV), which addresses the problem by using genome-wide markers and combining them with various machine learning approaches in order to estimate the breeding value (Meuwissen et al. 2001). It is for this reason that the GS models are developed in a training population that is both genotyped and phenotype. GS model that has been created can be used for predicting phenotypic traits in unseen genotypes as well as for genotype selection in another population, called the breeding population (testing population) that has genotyped data only. The GS procedure described here can be applied to predict phenotypic traits for inbred as well as hybrid populations. As a result of this procedure, GS cuts in half the time it would take for a breeding cycle to be completed in order to develop new cultivars. All GS approaches rely on a method that is statistical in nature as they use a mathematical relationship between genotypic and phenotypic data in order to predict genotypes values.
Genetic improvement of crops has been a cornerstone of agricultural development, making a significant contribution to the food security and economic growth of the global economy. Plant breeding poses a great deal of challenge when it comes to selecting the best individuals. The use of visual selection has not yielded the desired genetic gain compared to the results derived from the estimation of breeding values.

Introduction
The early human beings undertook extensive exploration of wild species in different plant species before selection followed by domestication for food and other purposes. The identification and selection of innumerable wild plant species and their domestication formed an integral part of early agriculture. Thus the organized cultivation of plant species is the result of selection in and among numerous wild species followed by domestication. It started around 9000-11000 years ago and has given birth to agriculture. The evolution of numerous human civilisations/settlements across the globe is largely shaped by agriculture. Selection continued during domestication which has led to the improvement in the wild plant species and transformed wild plant species into cultivated crop plants. Subsequently, the crop plants were differentiated into distinct landraces depending on morphological features, adaptation, economic use, etc. across different continents on Earth. Selection by humans and/or by nature is a continuous and dynamic process and will continue in future as well. However, a deep understanding of genetic diversity in crop species is essential for successful selection by human beings (Naqvi et al., 2022). The objective of the selection and domestication were dynamic and varied depending on cultural, social, economic and climatic factors. In general, the major objective of selection was to increase yield and bring desirable changes in valuable traits of economic importance. The significance of selection has increased over the years and will continue to increase in future as well. The procedure and methods followed while selecting traits or genotypes of economic importance have led to the birth of a new discipline, plant breeding. In the early years, plant breeding was more of an art than a science. As science progressed, the increased understanding of the genetics of traits complemented plant breeding with scientific back-up. Subsequently, genetics has become the basis of selection, the essence of plant breeding.
Globally, the demand for food, fodder, fuel, energy etc. is increasing continuously and increased crop production is considered as the most viable and sustainable answer or solution. The major driving force for increased demand is the growing population. However, the challenges to increasing crop production are also many namely, the decreasing arable land for agriculture, changing climate (increased extreme temperatures and altered rainfall patterns etc.), decreasing natural resources like water and energy etc. (Razzaq et al., 2021). Further, global warming also impacts the overall agricultural production across crops adversely. In this scenario, the role of plant breeding is vital to sustain higher crop production on a sustainable basis. The responsibility of plant breeders also increases in terms of the development of new, high-yielding, stress (biotic and abiotic) tolerant, high-quality and higher resource use efficient genotypes continually. Historically, conventional/traditional plant breeding has made significant progress in several crops in terms of increasing production, productivity, stress tolerance, nutritional value, etc. Conventional plant breeding relied fundamentally on extensive evaluation of available germplasm for a range of traits of economic importance and utilization of genetic diversity found in the landraces and closely related species (primary and secondary gene pools) (Prohens, 2011; Mangal et al., 2024). The success in conventional plant breeding largely depends on the expertise of breeders while undertaking phenotypic selection. It mainly involved selection within broad genetic base germplasm like landraces, open-pollinated varieties, exploration of wild and related species, and their evaluation for traits of interest, followed by hybridization and cyclical selection (Hallauer and Carena, 2009). The

Introduction
Chromosome engineering has emerged as a revolutionary approach, offering immense potential for genetic improvement by manipulating the structure and composition of chromosomes. Using genome engineering technologies, it is possible to introduce desirable traits into plants, such as disease resistance, increased yield, and enhanced nutritional content. To sustain the current standard of living, agriculture must yield significant increase in production (Gerland et al. 2014). Novel cutting-edge techniques developed for chromosome engineering hold great promise for addressing the challenges faced by modern agriculture, including climate change and food security. Engineering ability to precisely modify the genetic makeup of plants, chromosome engineering opens new avenues for creating novel cultivars with improved characteristics. While classical breeding has been successful in developing improved cultivars, it has its limitations. The process is time-consuming and often relies on probability to bring desired genetic changes. Since genes are organized into chromosomes, one important step to solve this issue is the development of novel genetic tools for chromosome reorganization and manipulation. When (Sears 1956) used X-ray irradiation to introduce foreign chromosome segments into the wheat chromosomes to transfer new traits, it was the beginning of plant chromosome engineering. Since then, plant chromosome engineering has evolved.
Applying methods such as chemicals and X-rays, induced mutagenesis was essential to the Green Revolution. Induction of polyploidy yielded more vigor and benefits like larger and higher-quality fruits (Osborn et al. 2003). Insect resistant and herbicide resistant transgenic crops successfully contributed to enhanced food production with less input into the farms. Genome editing enables precise modifications to increase disease resistance and stress tolerance (Ma et al. 2015). Considering practical features of chromosome engineering, this article discusses the use of induced mutagenesis, polyploidy induction, transgenesis, and genome editing, as the practical tools. The purpose of this chapter is to provide an in-depth analysis of chromosome engineering, exploring its scope, historical milestones, techniques, and its contributions to genetic diversity improvement and crop improvement. It also highlights the importance of efficient delivery techniques to overcome constraints such as off-target effects and concerns about genetically modified organisms (GMOs).

Introduction
In the ever-evolving landscape of agriculture, the intersection of science and technology continually reshapes the way we approach crop improvement. Among the most revolutionary advancements in recent years is the advent of genome editing technologies. These powerful tools offer unprecedented precision and efficiency in modifying the genetic makeup of plants, holding immense promise for revolutionizing the field of plant breeding. Genome editing plays a crucial role in plant breeding by enabling plant breeders to make precise and targeted changes to the DNA of crops, offering significant advantages over conventional breeding methods. Besides, crop improvement, these new breeding tools shorten the time needed to introduce desirable traits into crops, from decades to just a few years. They have revolutionized plant breeding by providing breeders with the ability to efficiently create crops that are more resilient, better adapted, and can produce higher yields with fewer resources, ultimately contributing to sustainable food production and addressing the challenges posed by climate change and population growth.
This comprehensive review aims to explore the transformative potential of genome editing technologies in genetic improvement of crop plants. The review will commence by elucidating the underlying mechanisms of genome editing technologies, offering insights into the molecular machinery that drives precise DNA modifications mediated by ZFNs, TALENs, CRISPR/Cas, base editing, prime editing and other new variants of CRISPR/Cas systems, highlighting their respective strengths and limitations. From enhancing crop productivity and quality to conferring resistance against biotic and abiotic stresses, these technologies offer a versatile toolkit for addressing pressing agricultural challenges. Case studies and examples from recent research will illuminate the successes and potential pitfalls of employing genome editing in crop improvement efforts. Besides, the regulatory and ethical considerations surrounding the deployment of genome editing in agriculture will be addressed. In conclusion, this comprehensive review seeks to provide a holistic perspective on harnessing genome editing technologies in plant breeding. By elucidating the scientific principles, applications, regulatory challenges, and ethical considerations, we hope to facilitate informed discourse and decision-making surrounding the integration of these transformative tools into agricultural practices. As we stand at the precipice of a new era in crop improvement, embracing the potential of genome editing holds the promise of unlocking sustainable solutions to global food security challenges.

Introduction
Eversince green revolution was introduced in 1960’s, the Indian agriculture has taken a series of transformations that resulted in paradigm shift from tradition farming to precision agriculture with an intend to address a wide array of challenges including burgeoning population, shrinking farm land, restricted water availability, imbalanced crop nutrition, multi-nutrient deficiencies, crop yield barriers and decline in soil organic matter. Agricultural scientists were looking for alternative strategy to tideover the bundle constraints with a single stop solution. Nanotechnology deals with atom-by-atom manipulations to evolve processes and products precised to overcome the farming challenges altogether that hardly possible to achieve by the traditional systems. Nanotechnology applications in agriculture include diagnostic devices for early detection of plant diseases (Chen and Hu, 2013), nano-agricultural inputs such as nano-fertilizer (Subramanian et al., 2015; yuvaraj and Subramanian., 2018; Nongbet et al., 2022; Verma et al., 2022; Mohanraj et al., 2024), nano-herbicides (Abigail and Chidhambaram, 2017; Forini et al., 2022) and nano-insecticides (Wang et al., 2022), nano-seed science, plant health management (Subramanian et al., 2016), nano-food systems (Anusuya et al., 2016; Jincy et al., 2017; Jan et al., 2023) besides environmental remediation (Rajkishore et al., 2023).
Even though the nanotechnology is being exploited in wide array of disciplines such as energy, environment, electronics, health sciences and few areas in agricultural sciences, the literature on the application of nanotechnology in plant breeding and genetics is scanty. Nanotechnology is a key component in the creation of genetically enhanced crops (Servin et al., 2015) with an increase crop yield or disease resistance (Kerry et al., 2017). Using genetic engineering or plant breeding, nano-enabled approach aids in the development of resilient and better plant genotypes (Patel et al., 2014). Plant breeding and genetic modification to create better crops frequently utilise nanotech-derived devices (nano sensors and nanoparticles) (Kumar and arora, 2020). Nanobiotechnology is to better understand the biology of various crops and the breeders may be able to increase agricultural yields or nutritional value (Sah et al., 2014). Atomically altered seeds, plant cells with silica beaks, hormone and antibiotic delivery in plants, particle farming, and iron seeding are a few examples. (Prasanna et al., 2018; Jha et al., 2013). Particle farming is the process of cultivating plants in predetermined soils to produce nanoparticles for industrial purposes. Plant production and growth are negatively impacted by abiotic stress. Salinity and drought are the two abiotic stressors that affect plants the most widely (Lavania et al., 2015; Zhao et al., 2017). Nano-enabled crop improvement can be achieved through four important aspects such as (1) genome editing, (2) genetic engineering, (3) abiotic and biotic stress management and (4) plant performance.

Introduction
The science of epigenomics has emerged as a key area of research across numerous biological disciplines. Epigenomics is the analysis of epigenetic changes occuring across many genes in a cell or entire organism, whereas the concept of epigenetics focuses on processes that regulate how and when certain genes are turned on and turned off. Understanding on the science of epigenetics can be traced back to the early hypothesis proposed by Aristotle to disprove the theory of preformation. Waddington’s initial conceptualization of epigenetics as a “conceptual tool” to integrate genetics and embryology established a foundational framework for subsequent research. Over time, advancements in molecular biology, developmental biology and evolutionary biology have since profoundly expanded and refined our understanding of epigenetics. Waddington further progressed in the 20th century with his introduction of the “Epigenetic Landscape” model (Baedke, 2013), marking a crucial milestone in the evolution of epigenetic theory.
In modern times, epigenetics refers to the study of heritable changes in gene expression or cellular phenotype that do not involve alterations to the underlying DNA sequence. Recent genetic and biochemical research has improved the understanding of various epigenetic regulation by three mechanisms including DNA methylation, histone modifications and non-coding RNA regulations. These mechanisms induce changes in chromatin conformation (active-open or repressiveclosed), which influences the gene expression that results in gene activation or gene silencing (Fig.1).
The transition between open and closed chromatin states, along with interactions among various epigenetic mechanisms, is essential to maintain optimal cellular function in diverse cell types, tissues and in response to varying developmental or environmental stimuli (Allis and Jenuwein, 2016).
Extensive studies in Arabidopsis led to a profound understanding of epigenetic mechanisms in plant growth and development. Later, intensive investigations was

Introduction
Detailed understanding of the gene structure and functions are achieved in respect of the genes present in the nuclear genome. The knowledge of the gene functions is being applied in plant genetics and plant breeding. The different kinds of genetic variants are well captured and explained in crop improvement programmes. The organelle genomes, namely, chloroplast and mitochondria that are present outside the nucleus have not received much attention to understand this organization, structure, functions and in utilizing their genetic endowments in many of the plant development and functions. The organelle genomes present in the cytoplasm are providing cytoplasmic effect, cytonuclear and inter genome interactions that impact plant development, plant fertility and agronomic traits expression. It is estimated that 80% of the metabolites are affected by the variations in organelle genomes. The organelle genome also influences and regulates the activity of nuclear genes. The The chloroplast genome encodes proteins that are central to plant photosynthetic activity for plant photosynthesis producing sugar and mitochondria genomes as the energy powerhouse for the cells and they are very essential to provide support to the plant functions and biomass production that is converted to the crop yield. Together, the organelle genomes have disproportionate effects on the nuclear gene functions.
These two organelle genomes that exist outside the nuclear genomes, active in synthesizing food and energy for cell functions, are not as much considered and relied upon by the plant breeders although they are basic biological machineries. This chapter on the organelle genomes is designed to present the structure and genetic endowments and functioning of the chloroplast and mitochondrial

Introduction
Currently, about 350,000 species of flowering plants have been described under global flora, but only a few of them have been rigorously screened for plant breeding parameters and systematic research accomplished in terms of varietal development. According to the Great Medical Encyclopaedia, medicinal plants are those used as a source of raw material for preparation of medicinal products of natural origin. Medicinal and aromatic plants occupy a pivotal position in the socio cultural, health care and spiritual arena of rural people of India. Medicinal plants contribute significantly to the rural livelihoods for their sustenance and income generation. Medicinal and aromatic plants are being used since ancient time for the treatment of many diseases in traditional and recognized systems of healthcare and for therapeutic, fragrance and flavoring products in pharmaceutical and cosmetic industries besides as sources of natural dye, fat, essential oil, biopesticide, resin, protein, vitamin, condiment, spice, timber, fiber and other useful substances. Medicinal and aromatic plants-based livelihood systems are often mediated by the market forces and/ related directly to employment and income of the poor people.
Based on the research work carried out by International Development Research Centre (IDRC) in South Asia, MAP and other biodiversity-based livelihoods can not only become poverty alleviating but also been made socially equitable and gender balanced. According to the World Health Organization, 80% of people from developing countries depend mainly on traditional medicine for primary health care. India is one of the worlds’ richest sources of medicinal plants comprising of nearly 45,000 species, of which nearly 100 species find major commercial use as per the statistics of National Medicinal Plant Board, New Delhi. In 2017, the estimated global market value of herbal medicine and herbal supplements was in the region of $107 billion (Yao et al, 2019), and not surprisingly, the substantial demand and consumption of these products have resulted in shortages, and in some cases even the exhaustion, of several medicinal plant resources, leading to habitat destruction and the loss of genetic diversity.
Plant secondary metabolites specific to each medicinal herb are derived from the precursors obtained from the primary metabolic processes related to one plant species or related group of species. These metabolites protect plants against plants being eaten by herbivores or being infected by microbial pathogens. They serve as attractants for pollinators and as agents of plant-plant competition and plant microbe symbioses. The rise of chemical taxa of medicinal and aromatic plants can be considered as consequence of biochemical and metabolic processes mostly under genetic control. It is assumed that differentiation of cell is mostly manifested in chemo-differentiation at a molecular level and the fundamental differences of protein present in an organism, between different enzyme systems. Moreover, the identity of a medicinal plant is attributed to the dissimilarities in their metabolic profiling intra specific chemical adaptations influenced by the ecological and geographical conditions. This discrete chemical difference is known as poly chemism that occur in autogamous species like medicinal and aromatic plants

Introduction
The 2022 edition of the United Nation’s global forest sector outlook for 2050 presented an update on the current patterns of wood consumption, its rising tendency, and projected future demand of primary processed wood to total 3.1 billion cubic meters of round wood equivalents (FAO, 2022). In addition, up to 199 million m³ would be required to substitute for non-renewable materials. Planted forests contributed around 46 percent to the global industrial round wood supply in 2020. However, globally the supply of wood from planted forests is always lower than the actual demand. Increasing population, urbanisation, economic development and consumption pattern are some of the major driving causes behind the demand in growth of wood and wood products. Wood security is defined as long-term availability of wood and wood products (sawn wood, veneer, plywood, particleboard, pulp, wood fuel and other primary wood products) for domestic and industrial requirements. The deficiency in the wood supply chain will continue to increase, and when the world population touches 9.4 to 10.2 billion, a 22 to 34% increase, the demand-supply imbalance will also increase. This supply gap would result in a shift in consumption patterns and lead to increase in environmentally harmful products such as petroleum-based plastics. Hence to meet the basic wood demand in 2050, at world level an additional 33 million ha of highly productive plantation forest would need to be established to meet the industrial round wood demand (FAO, 2022).
New demands for forest ecosystem continue to surge based on the Sustainable Development Goals, and mitigation of climate change related issues, water and other goods and services. Along with policy measures to directly act on existing forest resources conservation, increase in tree plantations with management interventions to increase productivity is necessary to fulfil the wood supply demands (McMaho and Jackson, 2019). Globally, the area under plantation forestry is on the rise (McEwan et al. 2020). Numerous studies (Silva et al. 2019; Carle et al. 2020; Pinnschmidt et al. 2023), highlight that plantation forests increasingly fulfil the ecological services provided by natural forests. Particularly, short rotation exotic trees with high productivity have found a niche in high-intensity industrial plantations, driving the expansion of the pulp and paper industry into a

Introduction
Based on the mode of reproduction, plants are broadly classified into sexually propagated and asexually propagated crops and some of the agricultural crops and a large number of horticultural crops are asexually propagated. The most important asexually propagated crops cultivated on a global basis are potato (Solanum tuberosum), cassava (Manihot esculenta), sweet potato (Ipomoea batatas), sugarcane (Saccharum spp), yam (Dioscorea spp.), taro (Colocasia esculenta), banana (Musa paradisiaca), etc. In sexually propagated crops, seeds are the primary propagules and it is produced by the fertilization of male and female gametes. Whereas, asexual reproduction or clonal reproduction covers all those modes of multiplication of plants where normal gamete formation and fertilization do not take place and vegetative propagules are the means of reproduction. Since sexual reproduction involves meiosis, segregation and recombination, the creation of variation is a continuous process which is inevitable in these crops. On the other hand, in asexual propagation, progenies are identical to the parent clones and they are genetically similar without any variation and they reproduce via mitosis.
Characteristics of asexually propagated crops
• Majority of the asexually propagated crops are perennials, e.g., sugarcane, fruit trees, etc. The annual crops are mostly tuber crops, e.g., potato, cassava, sweet potato, etc.
• Many of these crops show reduced flowering and seed set, and some varieties of these crops do not flower at all. But many of these crops flower regularly and show satisfactory seed set.
• They are invariably cross-pollinated and highly heterozygous and show severe inbreeding depression.
• A vast majority of asexually propagated crops are either polyploids. eg., sugarcane, potato, sweet potato, etc., or have polyploid species or varieties.
• Many cultivated crops are interspecific hybrids, ex., banana, sugarcane, etc.
• These crops consist of a large number of clones, that is, progeny derived from a single plant through asexual reproduction. Thus, each variety of an asexually propagated crop is a clone.

Introduction
The most extensive diversity is found in the realms of plants and insects, encompassing over 1 million arthropod taxa, primarily comprising insects, which have been comprehensively described, along with more than 350,000 plant taxa. Notably, a substantial portion of the described insect species serve as either pollinators or herbivores. Over millions of years, insects and plants have coevolved, constantly adjusting and adapting to each other’s characteristics. Plants have developed numerous morphological and biochemical features to withstand damage from insects, while in response, insects have evolved a range of defensive and adaptive mechanisms. These mechanisms include behavioural, morphological, physiological, biochemical, and genetic traits, enabling them to either tolerate or adapt to the defensive traits of plants (Schmelz et al., 2006; Wu et al., 2007; Howe & Jander, 2008; War et al., 2018). Plant defenses against insect pests can be broadly categorized into two main types: antibiosis and antixenosis resistance. Antibiosis involves the direct impact of plant defensive traits on insect growth, development, and survival. In contrast, antixenosis defense relies on morphological or chemical factors that alter insect behaviour, deterring them from feeding and laying eggs on the plant. The trichomes, spines, cuticles, thorns, and lignified cell walls, are the morphological traits of defense that directly protect plants from insect pests. The biochemical defense mechanisms are typically activated in response to insect attacks and are characterized by their dynamic nature (War et al., 2018). Plant volatiles serve a significant function in the indirect defense of plants against insect herbivores. They accomplish this by either deterring the insect pests or by luring the pests’ natural adversaries. Among the various attributes associated with plant defense, chemical barriers, whether they are induced by stress or present constitutively, along with the nutritional composition of the plant, are regarded as particularly crucial for impeding insect growth and development (Peters & Constabel, 2002; War et al., 2019).
Chemical resistance entails the production of secondary metabolites, whether inherently present (constitutive) or induced as a response to a threat, to fortify the plant’s defense mechanisms (Figure 1). Constitutive defense metabolites, initially stored in an inactive state, referred to as phytoanticipins, become activated when herbivores attack. This activation is facilitated by the enzyme ß-glucosidase, which subsequently triggers the release of various aglycone metabolites possessing biocidal properties (Morant et al., 2008). Metabolites that are induced in response to herbivore activity are referred to as phytoalexins. These compounds encompass a variety of substances such as isoflavonoids, terpenoids, alkaloids, and more. They are recognized for their capacity to influence the growth and viability of herbivorous organisms (Walling, 2000). Furthermore, a notable role in imparting host-plant

Introduction
Loss of arable land due to population expansion, urbanization and climate change have substantially impacted agricultural production, driving the need to exploit advanced techniques for enhancing sustainable crop production (Bren d’Amour et al. 2017). The yield and productivity of plants are influenced by both their genotype and the growing environment, which govern the performance indices or phenotype (Reynolds et al. 2020). Conventional plant breeding plays a crucial role in ensuring food and nutritional security for the ever-growing global population by harnessing genetic diversity and selecting plants with superior agronomic traits (Singh et al. 2019). However, identifying plants with superior agronomic traits and novel genes (quantitative trait loci or QTLs) through conventional breeding is akin to finding a needle in a haystack (Bohra et al. 2022). Furthermore, the conventional breeding approach is time-consuming and often associated with linkage drag due to extensive inter-crossing/hybridization among elite, wild, and common landraces (Beaver and Osorno 2009). Despite these challenges, classical breeding does develop new plant varieties with improved traits that can withstand climate extremes. Nevertheless, the duration of breeding cycles required to successfully complete the breeding program remains a major bottleneck, taking around 7-9 years to develop an improved variety (Pratap et al 2021).
Efforts have been made to revamp conventional breeding techniques by exploiting molecular markers (Ribaut et al. 2010). These markers effectively capture genetic variations across large populations at an early plant developmental stage. Additionally, the use of molecular markers in plant breeding significantly reduces the time required to screen plant genotypes with desired traits. Otherwise, achieving this task would take 2-3 years (Amiteye et al. 2021). Molecular marker-based techniques, such as marker-assisted selection (MAS), markertrait association (MTA), and genome- wide association studies (GWAS), have become routine tools. They help predict and develop genetic models for plants containing desired traits (Bohra et al. 2020). Furthermore, plant breeders have successfully integrated these molecular markers with genomics, phenomics, transcriptomics, proteomics, metabolomics, and epigenomics approaches (Malik

Introduction
The integration of bioinformatics into plant breeding has been shaped by several key milestones over the past few decades. Concepts like Breeding 4.0 (Wallace et al.,2018) and, 5G Breeding (Varshney et al., 2020) have gained global prominence, strengthened by the availability of extensive omics data. The advent of DNA sequencing technologies marked a key milestone in this field, catalyzing numerous genome sequencing projects worldwide such as Arabidopsis, rice, tomato, maize, wheat, etc. Next-generation sequencing (NGS) platforms, such as Illumina, PacBio, and Oxford Nanopore, have enabled rapid sequencing of entire plant genomes, facilitating the identification of genetic variations, including single nucleotide polymorphisms (SNPs), insertions, deletions, and structural variants (Deschamps & Campbell, 2010; Fuentes-Pardo et al.,2017). These advancements have significantly improved comparative genomics, enabling researchers to compare the genetic makeup of different plant species or varieties and identify genes associated with agronomic traits, such as yield, disease resistance, and environmental stress tolerance (Khan et al., 2024). As a result, these developments have revolutionized plant genetic research and crop improvement strategies, providing unprecedented opportunities to enhance agricultural productivity (Bellare et al., 2018; Shendure and Ji, 2008).
Bioinformatics has revolutionized plant biology by combining computational and statistical tools to analyze genomes, transcriptomes, proteomes, and metabolomes facilitating insights into genome structure, function, and evolution (Yadav et al., 2015; Saha et al., 2023; Roychowdhury et al., 2023). Genomics, emerged in the 1980s primarily focussing on mapping and sequencing genomes and there after laid the groundwork for functional genomics, which systematically explored gene functions (Hieter and Boguski, 1997; (Jackson et al., 2011). Further, advances in sequencing technologies, such as long-read platforms, have enabled detailed analyses of structural variants in crop genomes, crucial for identifying agronomic traits.
The large volumes of genomic sequence data have allowed researchers to identify genetic markers for crop improvement and candidate genes for trait development. However, the full potential of these genomic sequencing efforts depends on assigning functions to the thousands of genes with unknown roles. Model organisms such as humans, mice, Arabidopsis, rice, tomato, Medicago, and wheat have been instrumental in advancing genomic investigations (Bult, 2006). A notable example is the model organism Arabidopsis thaliana, which has provided a foundation for exploring fundamental biological phenomena using resources such as the TAIR database (Lamesch et al., 2012). Leveraging advanced bioinformatics techniques, researchers have enhanced crop productivity, mitigated diseases, and optimized resource management in agriculture. Advanced approaches like genome-wide association studies (GWAS) and transcriptome analysis continue to refine the understanding of genetic underpinnings, revolutionizing modern agricultural strategies (Mai et al., 2023).

Introduction
Crop breeding programmes are under increasing pressure for developing cultivars that possess the ability to adapt to diverse environments while maintaining higher quality and quantity, in response to the escalating worldwide demand for food. The primary goal of plant or crop breeding is to attain genetic enhancement, leading to the creation of new varieties that demonstrate higher yield and superior quality. Hence, the central aim of crop breeding initiatives is to develop novel cultivars that demonstrate improved resistance against fungal, bacterial, insect, or viral pathogens, alongside increased tolerance to abiotic stresses such as drought low temperature, salinity, dehydration, and heavy metal toxicity. Additionally these breeding efforts aim to improve quality attributes, including taste, size shape, colour, and cooking convenience (Lenaerts et al., 2019). The ability to anticipate emergent phenotypes resulting from genetic or environmental disruptions necessitates the utilization of methodologies capable of identifying metabolic pathways or canopy structures suitable for change. The insilico tools have the potential to guide breeding endeavours aimed at developing novel germplasm that exhibits robust adaptation to diverse environmental conditions. The precise simulation of organisms in a computational environment is a current and effective approach to enhance prediction abilities. Significant progress has been made in the field of predictive medicine through the implementation of community projects that utilize integrative, multi-scale modeling techniques. However, there are a lot of crop models that are just geographically and temporally restricted, which limits their ability to go beyond the data that is now available and, consequently, leads to insufficient forecasts regarding crop reactions in novel circumstances. The plant community has launched or continued a coordinated endeavour focused on the development of a virtual plant modelling through consolidative and multi-scale mapping, models and simulations (Marshall-Colon et al., 2017).

Introduction
Recent scientific findings highlight the escalating threats to global agricultural production due to climate change. The surge in extreme weather events, amplified by erratic precipitation patterns, alongside diminishing soil fertility and declining plant productivity, has led to an upsurge in disease and pest pressures. This amalgamation of factors has propelled a distressing trend of crop failures on a global scale. Over the last century, the average global temperature has already risen by 0.74°C, and projections suggest this rise could accelerate dramatically, reaching an alarming 2.6–4.8°C by the close of this century. This impending temperature escalation from climate change endangers agricultural output, thereby posing a signifi cant risk to the world’s food security. Presently, a staggering 794.6 million individuals face undernourishment, with nutrition-related issues contributing to a staggering 45% of deaths in children under fi ve years of age. The situation is particularly dire in developing regions, where 779.9 million people grapple with undernourishment. The repercussions of reduced agricultural production extend beyond hunger; they encompass potential food shortages and infl ationary pressures, predominantly affecting populations in low-income regions. These adverse consequences underscore the imperative of addressing these challenges. While advancements in crop breeding have led to incremental genetic gains in major agricultural crops, the pace of progress remains inadequate to meet the mounting global food demands. It is evident that enhancing the rate of genetic gain through innovative breeding programs is vital. This endeavor holds the potential to expedite the development of crop varieties resilient to changing climates and endowed with higher nutrient densities. Such cultivars are essential for ensuring sustainable food production and bolstering food security for our burgeoning population.

Aquaculture is practiced in the majority of countries worldwide, however the significance of water quality standards remains largely unknown to farmers and new aqua entrepreneurs. They may achieve maximum fish production with minimal input costs if they are trained and stay up to date on water quality management in the aquatic ecosystem. The water quality categorised into three main of metrics as physical, chemical, and biological parameters. Dissolved oxygen (DO), biochemical oxygen demand (BOD), free carbon dioxide (CO2), pH, temperature, total dissolved solids (TDS), turbidity, ammonia, nitrite, nitrate, alkalinity, bacterial density primary productivity (chl a), plankton population, etc. play a significant role for fish production. However, even small variations in certain physical and chemical parameters—particularly pH, temperature, and dissolved oxygen (DO)—can cause stress in the animals, which may manifest as physiological changes, reduced reproductive capability, and altered behavior. Water parameters such as alkalinity and hardness are relatively stable, whereas others like pH, dissolved oxygen (DO), and temperature fluctuate regularly. Proper maintenance and monitoring of these water quality parameters in aquatic environments support fish health and enhance fish production. On the other hand, variability in dissolved ammonia, nitrites, and nutrients like nitrate significantly affects aquaculture production. It has also been observed that high feeding rates in aquafarms create eutrophic conditions in water bodies, leading to substantial algal blooms. These blooms are responsible for die-offs, and as a result, ammonia levels in the ponds rise rapidly. The environmental factors responsible for generating high ammoniacal concentrations may also lead to increased nitrite concentration in aquafarm. Both ammonia and nitrite are directly toxic or sublethal cultured aqua animals, leading to reduced resistance to diseases. In aquaculture system, ammonia is produced through the ammonification process, which occurs when organic matter is broken down by the microbial community. However, this decomposition also reduces dissolved oxygen levels in the system. Low dissolved oxygen surges the toxicity of ammonia to cultured animals. Ionized ammonia (NH4 +) and hydroxide ions occurs in equilibrium with unionized aqueous ammonia solution. The unionized form of ammonia (NH3) is toxic

Water colour is consequences of the plankton, humus, metal ions (iron and manganese), weeds and peat materials, presence in water. Iron oxides cause reddish color whereas Manganese oxides causes brown or brackish colour in water. Water colour of an aquatic body also indicates the density of planktons. Brownish colouration without any foul smell is an indication of good growth of zooplankton. Phytoplankton or algae are usually green in colour and these green alage in large quantities turn the green color of water. Water color suggests plankton or other aquatic life growth, clear and transparent colour of water indicates low and poor growth of plankton. Brownish green to greenish brown colour of water indicates well for aquaculture.
Principle
Natural waters colour comprising yellow-brownish in appearance. It has been observed that potassium chloroplatinate (K2PtCl2) tinted with small amounts of CoCl2 yield colours that are very much like the natural colours of water. 1 mg/L of Pt (K2PtCl6) produces a standard 1 unit of colour. The intensity of colour increases as pH rises. For this reason recording pH together with colour is advisable.

pH is defined as the negative logarithm of hydrogen ion concentration. The amount of the acidic gas CO2 significantly affects the pH of natural water body. Fish have usually blood pH levels of 7.4, but little deviation has been observed, perhaps 7.0 to 8.5pH range is more suitable for the growth and reproduction of the fish. However, pH range 4.0 to 6.5 and 9.0 to 11.0 cause fish death in water pH less than 4.0known as acidic death point or even more than 11.0 known as alkaline death point. The pH of fresh water more fluctuating as compare to sea water due to release and consumption of CO2 and O2 respectively by bacterial oxidation and respiration. However, the pH of marine water often constant at 7.8-8.3 due to presence of buffer like HCO3-, CO2 -, CO3-2 etc.
Principle
The estimation of hydrogen (H+) ion activity through sensing electrode. Electrode composed of a narrow glass bulb with fixed concentration of HCI solution inside it. A wire made of an Ag-AgCI placed in to the bulb which work as electrode to fix voltage. Potential difference forms between the solution in the glass bulb and the sample solution when the electrode immersed into solution.

The Secchi disc is named after its Italian inventor Pietro Angelo Secchi. Transparency is a water-quality characteristic of lakes and reservoirs and can be measured quickly and easily using simple equipment. This characteristic varies with the combined effects of colour and turbidity. Some variation may also occur with light intensity and with the apparatus used.
Procedure
1. Morning (early) or afternoon (late) is suitable time to check transparency
2. Lower the Secchi disc and observed the depth at which it just disappears from view (L1)
3. Then further lift up slowly till it just reappears (L2).

Principle
The estimation of all solids, including dissolved, volatile, and suspended solids, is called total solids (TS). The residue that remains after the unfiltered sample evaporates between 103 and 105°C can be used to estimate total solids. Total dissolved solids (TDS) and Total suspended solids (TSS) are its two constituent components. After heating to 550°C, each fraction is separated once more into fixed solids and volatile suspended solids (VSS). The percentage of ash that remains is called fixed solids, while VSS is the organic proportion that was lost as CO2.
Apparatus
1. Ceramic or platinum evaporating dishes 100 mL volume.
2. Dessicator contain CuSO4.5H2O. Desiccator, provided with a desiccant containing a colour indicator of moisture (CuSO4.5H2O).
3. Analytical balance
4. Hot air oven
Procedure
1. Take a clean evaporating beaker or dish of required volume and dry it at hot air oven at 103 to 105oC for 1h, then cool and store it in a desiccator until needed. Immediately weigh before use. Note » the initial weight (Wi) in mg.
2. Take 250-300 ml or required volume of unfiltered well mixed sample in it (beaker or dish).
3. Place it in hot air oven at 103 to 105 oC for 2 h.
4. Cool it in a desiccator and take the final weight (Wf) in mg.
5. Replication the above process until a constant weight is achieved

Pure water is a poor conductor of electricity. Water may carry electricity fairly well when it contains electrolytes such as Acids, bases and salts. Electrolytes in the solution dissociates with cations and anions and pass on electrical conductivity. Hence, more electrolytes concentration in water, more its electrical conductance. The following ions are crucial for adding conductivity to water.
i) Cations: Mg 2+,Ca2+, Na+ and K+
ii) Anions: Cl-, S4
-, CO3
-, HCO3
-and NO3
-
In the International System of units (SI) the reciprocal of ohm is the Siemens (S) and conductivity is reported as millisiemens per meter (mS/m). 1 mS/m = 10 µS/cm = 10 µmhos/cm and 1 µS/cm = 1 µmhos/cm Principle
The quantity and kind of ions present in a solution affect conductivity, which is a numerical representation of a water sample’s capacity to conduct electricity. Since the majority of dissolved inorganic compounds in water are ionised, they add to conductance. The definition of conductance G is the reciprocal of resistance R.

Pure water is a poor conductor of electricity. Water may carry electricity fairly well when it contains electrolytes such as Acids, bases and salts. Electrolytes in the solution dissociates with cations and anions and pass on electrical conductivity. Hence, more electrolytes concentration in water, more its electrical conductance. The following ions are crucial for adding conductivity to water.
i) Cations: Mg 2+,Ca2+, Na+ and K+
ii) Anions: Cl-, S4
-, CO3
-, HCO3
-and NO3
-
In the International System of units (SI) the reciprocal of ohm is the Siemens (S) and conductivity is reported as millisiemens per meter (mS/m). 1 mS/m = 10 µS/cm = 10 µmhos/cm and 1 µS/cm = 1 µmhos/cm Principle
The quantity and kind of ions present in a solution affect conductivity, which is a numerical representation of a water sample’s capacity to conduct electricity. Since the majority of dissolved inorganic compounds in water are ionised, they add to conductance. The definition of conductance G is the reciprocal of resistance R.

The total amount of salts dissolved in water is known as salinity. Salinity of water is denoted as ppt, g/L, psu. Salinity of different water has been classified as Freshwater 0-0.5 ppt, Brackish water 0.5-30ppt and Marine water > 300 ppt.
Reagents
1. Silver nitrate (AgNO3) (0.1N): Dissolve 4.25 g silver nitrate in distilled water and make the total volume 250 ml by shaking.
2. Potassium chromate (K2CrO4) indicator (5%): Dissolve 2.5 g potassium chromate in distilled water and make the total volume 50 ml by shaking.
Procedure
1. Salinity in estuarine and coastal water can be estimated by this method.
2. Take 10 ml of water sample in a 50 ml conical flask.
3. Add 3-4 drops of potassium nitrate indicator solution to it.
4. Titrate against 0.1N Silver nitrate till the yellow colour changes to brick red.

The decreased ability of water to transmit light which is caused by suspended particulate matter ranging in size from colloidal to coarse dispersions is refers as turbidity.
Principle
Turbidity is measured by its effect on the transmission of light, which is termed as Turbidimetry or by its effect on the scattering of light, which is termed as Nephelometry. Turbidimeter can be used for sample with moderate turbidity and Nephelometer for samples with low Turbidity. Higher the intensity of scattered light higher the turbidity.
1 mg SiO2/L = 1 unit of turbidity

Dissolved oxygen (DO) refers to oxygen gas that is dissolved in water. Fish are able to absorb oxygen directly from the water into their bloodstream using gills. There are three main sources of oxygen in the aquatic environment: 1) direct diffusion from the atmosphere; 2) wind and wave action; and 3) photosynthesis. Oxygen depletion refers to low levels of DO and may result in fish mortality. A concentration of 5 mg/L DO is recommended for optimum fish health. Sensitivity to low levels of dissolved oxygen is species specific, however, most species of fish are distressed when DO falls to 2-4 mg/L. Mortality usually occurs at concentrations less than 2 mg/L. If fishes gulfing on the water surface and also show the low swimming in the water it indicates deficiency of dissolved oxygen in pond.

The biochemical oxygen demand is a chemical procedure for determining the amount of dissolved oxygen needed by aerobic organisms in a water body to break the organic materials present in the given water sample at certain temperature over a specific period of time. BOD of water or polluted water is the amount of oxygen required for the biological decomposition of dissolved organic matter to occur under standard condition at a standardized time and temperature. Usually, the time is taken as 5 days and the temperature is 20°C. microbes
C6H12O6 + 6O2 ¾¾¾¾®CO2 + H2O
Principle
The test measures the molecular oxygen utilized during a specified incubation period for the biochemical degradation of organic material (carbonaceous demand) and the oxygen used to oxidize inorganic material such as sulfides and ferrous ion. It also may measure the amount of oxygen used to oxidize reduced forms of nitrogen (nitrogenous demand).
Procedure
Fill two BOD bottles with sample (or diluted sample); the bottles should be completely filled.

Free carbon dioxide in the water accumulates due to microbial activity and respiration of organisms. Surface waters normally contain less than 10 mg free CO2 per litre while some groundwater may easily exceed that concentration up to 30 to 50 mg/L.
Principle
Free CO2 reacts with sodium carbonate to form sodium bicarbonate, or with sodium hydroxide to form sodium carbonate. Completion of reaction is indicated by the development of the pink colour characteristics of phenolphthalein indicator at the equivalence pH of 8.3.
Analysis of Water and Effluents
CO2 + N2CO3 + H2O = 2NaHCO3
CO2 + 2 NaOH = N2CO3 + H2O
Reagents
1. Standard sodium hydroxide titrant (0.05N): Dissolve 40g of NaOH in boiled CO2 free distilled water and make up the volume to 1 litre. Filter the solution through a sintered glass filter to remove any Na2CO3, the concentration of solution is 1N NaOH. Store it in in glass bottle.
2. Phenolphthalein indicator

Chemical oxygen demand (COD) is measurement of oxygen demand of waste in terms of the total quantity of oxygen required for oxidation of the waste to carbon dioxide and water. This test is based on the fact that all the organic compounds, with few exceptions, can be oxidized The test is based on the fact that all organic compounds, with a few exceptions, can be oxidized by the action of strong oxidizing agents under acid conditions. Organic matter + Oxidizing agent = CO2 + H2O. The major advantage of COD test is the short time required for evaluation. The determination can be made in about 3 hours rather than the 5-days required for the measurement of BOD
Principle
The oxidizing agents like potassium permanganate and potassium dichromate is usually used to determine COD. Potassium permanganate is selective in the reaction like it reacts with carbonaceous on the other hand it shows nonreactive with nitrogenous matter. Estimating of COD with any method, oxidizing agent must be present to ensure that organic matter is oxidized completely. The organic matter and oxidisable inorganic substances present in water or wastewater get oxidised completely by standard potassium dichromate (K2Cr2O7) in the presence of H2SO4 to produce CO2 + H2O.The excess K2Cr2O7 remaining after the reaction is titrated with ferrous ammonium sulphate [Fe(NH4)2 (SO4)2]. The dichromate consumed gives the 02 required for oxidation of the organic matter.

Principle
Alkalinity of a water sample is can be determined by titrating with standard sulphuric acid. Titration to pH 8.3 or de-colourization of phenolphthalein indicator will indicate complete neutralization of OH and ½ of CO3 while to pH 4.5 or sharp change from yellow to pink of methyl orange indicator, that will indicate total alkalinity (complete neutralization of OH, CO3, HCO3)
Chemicals
1. Phenoplthalein indicator
2. Methyl orange indicator
3. Sodium carbonate, Na2CO3
4. Sodium hydroxide, NaOH
5. Sulphuric acid, H2SO4
Reagents
1. Phenolphthalein indicator: Dissolve 0.5 g in 500 ml 95% ethyl alcohol.
2. Methyl orange indicator: Dissolve 0.5 g of methyl orange in 100 ml of water and dilute to 1000 ml in deionized or distilled water (CO2 free deionized or distilled water should be use).
3. Standard Sulphuric acid, H2SO4 (0.02N): to prepare 0.1N H2SO4 take 3 ml conc. H2SO4 and dilute it in to 1000 ml of deionized or distilled water. Standardise it against standard Na2CO3.
4. Sodium carbonate, Na2CO3 (0.05 N): Take 7g standard Sodium carbonate (Na2CO3) dry at 250 oC for 4 hr and cool in desicator then weigh 5.3 g and transfer it a 1000 ml volumetric flask after that fill to mark with distilled water. Solution should be use within 1 week.

Common elements of natural water that significantly contribute to its hardness include calcium and magnesium ions of these elements leached from rocks. Water hardness reduces the utility of water for domestic use. Calcium hardness sometimes may be helpful because it provides a coating in the pipes which protects them against corrosion.
Principle
When calcium and magnesium are present in the water, EDTA reacts with calcium first. EDTA can be used to directly measure calcium when the pH is raised to a point where magnesium hydroxide is mostly precipitated and an indicator that only combines with calcium is employed. At a pH of 12 to 13, several indicators change colour to indicate that all of the Ca has been incorporated by the EDTA. The variations between an aliquot titrated at pH 10 and one titrated at pH 12 or 13 are what define the amount of magnesium.

Hardness is the total soluble Ca and Mg Salts (in same cases Fe salts). It includes sulphates and chlorides along with carbonate, bicarbonate and hydroxide salts. Soft water: 0-100 mg/L, Hard water: 100 - 300 mg/L, Very hard water: > 300 mg/L CaCO3. Total hardness should be 50- 300 mg/L. Very hard water causes osmoregulatory stress to fish. Hardness below 50 mg/L reduces growth of plankton.
Reagents
1. 10.01M EDTA solution: Dissolve 3.72 g disodium salt of EDTA in distilled water and make the volume 1L by shaking.
2. Eriochrome Black T (EBT) Indicator: Add 0.2 g dry Eriochrome powder to 50 ml of triethyl amine. Add 5 ml absolute alcohol and shake it.
3. Ammonium chloride-Ammonium hydroxide buffer solution: Dissolve 17.5g ammonium chloride (NH4Cl) in 142 ml of ammonia solution (NH4OH). Add distilled water to make the volume 250 ml.
Procedure
1. Take 50ml water sample in a 250 ml conical flask.
2. Add 2 ml buffer solution and 5 drops of EBT indicator.
3. Wine-red colour will appear.
4. Titrate against 0.01M EDTA till the colour changes into bright greenish blue.

Principle
Chloride ion is determined by Mohr’s method, titration with standard silver nitrate solution in which silver chloride is precipitated first. The end of titration is indicated by formation of red silver chromate from excess AgNO3 and potassium chromate used as an indicator in neutral to slightly alkaline solution.
AgNO3 +Cl- ? AgCl+NO3
2AgNO3+ K2CrO4 ? Ag2CrO4+2KNO3 (Reddish Brown)
Reagents
1. Standard Silver nitrate 0.0141N : Take 1.189 g and dissolved it in 500 ml distilled water.
2. Sodium chloride 0.014N: Dissolve 0.28 g sodium chloride in 500 ml of distilled water.
3. Potassium Chromate indicator
Procedure
1. Take 50 ml sample in a 100 ml conical flask
2. Adjust its pH in between 7.0 and 8.0 either with alkali or acid solution. Otherwise, AgOH is formed at high pH level or CrO4 -2 at low pH level.
3. Add 1 ml of potassium chromate (K2CrO4) colour turn to light yellow.
4. Titrate with standard silver nitrate (AgNO3) solution till colour change from light yellow to brick red colour.
5. Note the volume of AgNO3 added (A)
6. For better accuracy, titrate distilled water in the same manner
7. Note the volume of silver nitrate added for distilled water (B)

Fish excrete Ammonia, is a byproduct from protein metabolism and bacteria break down organic waste such as discarded food, faeces, dead planktons, sewage, and so on. When ammonia is unionized form (NH3) is extremely dangerous; yet when ammonia ionized form (NH4 +) it is harmless; both forms are known as total ammonia. Fish suffering from ammonia toxicity often”become lethargic and frequently emerge near the surface gasping for oxygen. common effects of ammonia in the range >0.1mg/l include Gill damage, breakdown of mucous-producing membranes, “sub-lethal” effects like reduced growth, poor (FC) feed conversion, and reduced disease resistance at concentrations lower than lethal concentrations, osmoregulatory imbalance, and kidney failure.
Principle
When Ammonia react with alkaline Nessler reagent (K2HgI4 or 2KI + HgI2) it produces a yellowish-brown coloured compound. Pretreatment with ZnSO4 and NaOH precipitates Ca, Mg, Fe and sulphide, which form turbidity and apparent colour. Addition of ethylene diamine tetraacetic acid, EDTA (before nessler’s reagent) or Rochelle salt solution prevents precipitation of residual Ca and Mg in presence of the alkaline Nesslers’s reagent.

Nitrite (NO2-) is formed in waters by oxidation of ammonia compounds (by aerobic nitrifying bacteria, e.g. Nitrosomonas) or by reduction of nitrate (by facultative anaerobic denitrifying bacteria, e.g. Pseudomonas). Such oxidation and reduction may occur in wastewater treatment plants, water distribution system, and natural waters. As an intermediate stage in nitrogen cycle, it is unstable. Very high nitrite levels are usually associated with waters having unsatisfactory microbiological activity.
Principle (Colorimetric method)
When nitrite (NO2 -) as nitrous acid (HNO2) mixes with sulfanilamide in an acidic environment (pH 2-2.5), a diazonium salt is created. This salt then combines with N-(1-naphthyl)-ethylenediamine dihydrochloride (NED dihydrochloride) to make a vivid pinkish red azo-dye. The amount of nitrite in the sample directly correlates with the colour that is created. At 543 nm, the colour follows Beer’s law up to 180 µg/L with a 1 cm light path. By diluting a sample, a higher nitrite concentration can be determined. Sulfanilamide + HNO2 + HCl ? Diazonium salt + H2O.
Diazonium salt + NED-dihydrochloride ? Red colouredazo dye

The most oxidizable form of nitrogen is nitrate nitrogen (NO3 -N), which is found in minimal amounts in surface waters but can reach considerable concentrations in some aquifers. An essential plant nutrient, nitrate also contributes to eutrophication in receiving water bodies.
Principle
Nitrate reacts with phenol disulphonic acid and produces a nitro-derivative which in alkaline solution develops yellow colour due to rearrangement of its structure. The yellow colour follows Beer’s law and is proportional to the concentration of nitrate present in the sample. Ultraviolet (UV) technique measures the absorbance of nitrate at 220 nm, which is suitable for screening uncontaminated water (low in organic matter). A second measurement made at 275 nm, may be used to correct the nitrate value (because 275 nm is not absorbed by nitrate, but absorbed by other matter). The nitrate calibration curve follows Beer’s law up to 11mg NO3 -N /L.
Reagents
1. Stock nitrate solution (1ml=100 µg NO3 -N): Dry potassium nitrate (KNO3) in an oven at 105 oC for 24 h. Take 360.9 mg potassium nitrate and dissolve in distilled water and dilute to 500 ml. Preserve it with adding 1 ml of chloroform in per 500 ml stock nitrate solution. This solution will stable for at least 6 months.
2. Intermediate nitrate solution (1 ml = 10µg NO3 -N): Take 100 ml of stock nitrate solution and dilute it to 1000 ml of distilled water. This solution can be preserve by adding 2 ml of chloroform per 1000 ml. This Intermediate nitrate solution will stable for at least 6 months.
3. Hydrochloric acid (HCL) solution, 1N: Take 83 ml of hydrochloric acid and dilute it to 1000 ml of distilled water

Phosphorus is nearly exclusive found as phosphates in waters and wastewater and it categorised in to: a) orthophosphate, (b) organically bound phosphate and (c) condensed phosphates. Theses all three forms of phosphorus occur in solution, in the body of aquatic organisms through food chain. All the forms of phosphorous, whether dissolved or particulate are converted to inorganic forms (phosphate) after digestion of sample. Various methods use for the digestion of the sample including use of perchloric acid, H2SO4- K2SO4, H2SO4- HNO3 etc. The H2SO4- HNO3 digestion technique is discussed here.
Reagents
1. Phenolphthalein indicator
2. Conc. sulphuric acid (H2SO4)
3. Conc. nitric acid (HNO3)
4. Sodium hydroxide (NaOH), 1 N: Dissolve take 40 g of NaOH in 1000 ml of distilled water
Procedure
Digestion
1. Take 50 ml of sample in a Kjeldahl flask
2. Add 1 ml H2SO4 and 5 ml HNO3
3. Once the HNO completely removed, digest the sample on a hot plate until the volume approaches 5 ml. Then, keep heating the solution until it loses colour (you may also heat it in a beaker covered with a watch glass to prevent excessive evaporation).

Sulfate can have harmful effects on aquatic life in freshwaters, sulfate cause osmotic stress or specific ion toxicity in aquatic organisms, especially in soft waters where Ca2+ and Mg2+ concentrations are low. Egg fertilization and early embryonic development were the most sensitive developmental stages of whitefish to sulfate (Karjalainen et al., 2021).
Sulphate (SO4 2-) may be estimated by either turbidimetric or gravimetric methods (APHA, 1995)
1. Turbidimetric method is more applicable in the range of 1- 40 mg Sulphate (SO4 2-)/ L
2. Gravimetric method is suitable if the concentration of Sulphate (SO4 2-) is above 10 mg/ L
Turbidimetric Method (Range 1 - 40 mg/L of sulphate) Principle
Sulphate ion (SO4 2-) precipitated with barium chloride (BaCl2) in an acetic acid medium in order to form crystals of barium sulphate (BaSO4).
BaCl2 + SO4 2-+ BaSO4 (precipitate)
The formation of these crystals is increased in the presence of an acetic acid solution containing sodium acetate, potassium nitrate, acetic acid and magnesium chloride. The suspended barium sulphate (BaSO4) is measured by spectrophotometer and concentration of sulphate (SO4 2-) is determined by comparison of the reading with a standard curve. Minimum detectable concentration is approximately 1 mg (SO4 2-) / L.

The total plate count (TPC) is also called the Bacterial plate count (BPC), aerobic plate count, standard plate count (SPC), total viable count (TVC) or mesophilic count represents the number of colony forming units (CFU) per g (or per mL) of growing microorganisms such as bacteria, yeast and mold on a nonspecific solid bacteriological growth medium under the specified conditions. Temperature, incubating time, medium type, and any other conditions used in the enumeration varies upon reference standards and laboratory objectives. Laboratories participating in the program choose their own routine conditions.
Principle
Usually direct count of too many bacteria in a sample is difficult but the bacterial colonies may be used as a measure of the bacterial cells in the known serially dilution and plated out on an agar surface in such a way that single isolated bacteria form visible isolated colonies. However, colony-forming unit might actually consist of a chain of bacteria rather than a single bacterium if the organism often develops various cell configurations, such chains. Furthermore, a portion of the bacteria might be grouped together. Thus, typically refer to the process of using the plate count technique as a means of estimating the number of colony forming units (CFUs) in that known solution. Then further this figure use to extrapolate the total amount of CFUs present in the original sample.

Laboratory pipettes are classified by their method of liquid transfer. There are two types of pipette one is plastic which is made up of polystyrene and are essentially disposable and second one is glass pipettes are very resistant to chemicals. Glass pipette can be used frequently by washing, sterilising and dry heat sterilisation is also available. Some of the common types of pipettes are using in laboratory such as serological, volumetric, micropipettes, multichannel, and Pasteur pipettes. Serological and graduated pipettes are used for transferring various volumes, while micropipettes and volumetric types of pipettes are only considered for precise measurement and transfer. Multichannel pipettes are used for dispensing into multiple wells, and Pasteur pipettes are simple for transferring small amounts.
1. Serological Pipettes
• Also known as graduated pipettes, made of glass or transparent polystyrene they are calibrated with markings to measure and dispense varying volumes.
• Appropriate for cell culture applications, transferring liquids and mixing.
2. Multichannel Pipettes
• It is design to transfer multiple samples at once, often used for 96 well plates or pcr tubes.
• It can be manual or automated, with multiple heads for faster dispensing.
3. Volumetric Pipettes
• It is designed to supply for single and particular volume of liquid.
• Marked by single graduation for an exact volume, such as 1, 5, 10, 25, and 50 mL.
• Used in chemical reactions and analysis where accuracy is crucial.

The entire world is now facing a crisis situation. The problems encountered to address the crisis are interactive with each other and there is no easy way to find solution. The world’s population is expected to increase by 70 per cent by the end of year 2050 and there is need to step up agricultural production for a hunger free world. Nearly 70 per cent of the fresh water is used in agriculture sector. The demand for water in agriculture sector can be judged by the fact that several thousands of litres of water is required to produce one kilogram of food grains. Whatever maybe the source from which water is drawn for agriculture, all the sources depend upon the precipitation for replenishment on continuous basis. The precipitation patterns are not consistent and are known for greater variability from season to season, year to year and from region to region. These inconsistencies are further increasing due to recent threat of climate change triggered by the atmospheric pollution. The atmospheric pollution due to increase of greenhouse gases in the atmosphere is responsible for rise in temperatures. The rise in temperature induced changes in global pressure and wind systems. The consequence effect of it is changes in rainfall patterns, frequent occurrence of extreme weather events like floods, droughts, heat waves, intensified cyclonic activity. Rise in temperatures is increasing evaporation of water and water requirement of crops as well. There is considerable increase of the chemicals in the agriculture sector in the form of fertilizers, pesticides, fungicides and weedicides how to increase crop production and protection of crops from biotic and abiotic stresses. Consequently, there is increased pollution of water resources which may adversely affect the availability of fresh water, which is essential and critical input in agriculture for increasing agricultural production. It calls for efficient utilization of water resources in agriculture. More concerted efforts are required immediately to:
• Improve water use efficiency in agriculture
• Reduce pollution of water resources
• Conservation of fresh water resources
• Reduce emissions in agriculture sector and
• Prevent dwindling of fresh water resources

Water is the most important natural resource that governs and exercises control on living organisms on earth besides supporting all human activities. The demand for water is almost increasing at exponential rate due to increase in population and industrialization. All sectors of agriculture including crop production, horticulture, animal husbandry, poultry and fi sheries primarily depend upon water. Water scarcity can cause all kinds of miseries. The water exists in all 3 different forms on earth. It exists as snow or ice in glaciers and ice caps, liquid water in rivers, lakes, streams, tanks, ponds and as groundwater storage. The water exists in all three different forms in the atmosphere. The clouds may contain fi ne ice particles, tiny water droplets and as well as water vapour. The air in atmosphere also contains water vapour. It is estimated that 97% of water is salt water and remaining 3% of water is pure and fresh water. Approximately two-thirds of the fresh water is trapped in glaciers and ice caps. Most of the fresh water (30%) exists as groundwater. About 0.7% of fresh water exists as soil water and 0.3% a fresh water accounts for surface water resources and water present in the atmosphere as water vapour, water drops and ice particles. The circulation of water between oceans, earth and atmosphere forms hydrologic cycle.
2.1. Hydrological Cycle
The hydrological cycle explains the continuous recirculation and transport of water between the atmosphere, oceans and earth. It is a very complex system that has many sub cycles associated with it. For example, the water from earth surface, oceans and water bodies get evaporated due to heat energy received from the sun in the form of incident solar radiation (Fig.2.1).

The major source of water supply on the earth is precipitation. The water received at the earth’s surface from the atmosphere either in solid or liquid form is called precipitation. The water received in solid form may be snow or hail. The precipitation is seasonal in character in many parts of the world. The precipitation may occur due to –
• Conventional physical process
• Orographic effect and
• Convergence of air masses
3.1. Conventional Physical Process
It occurs when the air on the surface of the earth and few metres above the surface of the earth is heated by absorbing long wave radiation emitted by the earth’s surface. As the air is heated, it becomes lighter. The water vapour formed due to evaporation from the soil surface or water bodies will mix with the air and the air will be moist. When the moist air gets heated it becomes lighter and rises vertically upwards. After reaching certain height, the air gets cooled enough to get saturated with water vapour. The moisture in the saturated air will condense on small solid particles to form tiny drops. These solid particles may be dust or smoke or solid particles suspended in the atmosphere and are called aerosols.

The soil consists of many solid particles of different sizes and is capable of absorbing and retaining water in the soil within certain limits when water is received through either from precipitation or by irrigation. The water that is held in the soil is called soil water (Fig.4.1). It can exist also in the form of water vapour as well. The crop production depends upon the soil water. All the water that is present in the soil may not be available for plants.
The water availability to the plants from the soil depends upon some physical properties of the soil as well as on the physical processes that govern the existence of water in the soil. Therefore, it is necessary to understand about the relationships that govern the water availability in the soil as explained in the following text-
4.1. Energy Concept of Soil Water
Soil water energy concept is all about potential energy, gravitational potential, osmatic potential, pressure potential energies.
4.1.1. Soil Water Energy: The total energy state of soil water is defined by its
equivalent potential energy as determined by various forces acting on the water per unit quantity. Different energies are involved including kinetic and potential energy.

The plants draw water from the soil for growth and development. The soil acts a reservoir for soil moisture (Fig.5.1). The basic aim of a soil water balance model is to quantify the manner in which the water supplied to the soil either through precipitation and irrigation is disposed off. In the process, the soil water balance models were found to be extremely useful to determine the amount of water utilized by the crop for evapotranspiration.
The concept of water balance was originally developed by Thornthwaite, an American geographer and it formed the basis for development of more scientifi c advances due to its wide range of applicability including
• Choice of crops/ cropping systems based on water availability
• Irrigation scheduling
• Optimisation of limited water resources for higher productivity
• Characterization of droughts and agricultural droughts
• Assessment of crop yield and pre harvest forecasting of crop yields
• Designing irrigation projects
• Development of water storage structures
There are quite a large number of water balance models available in literature nowadays. Several of these models may be applicable for regions where there are developed. There were considerable efforts to develop water balance models can be used by the crop on daily basis in case of different crops as well. The choice of a water balance model to a large extent depends on the availability of data required for running the model. It may not be possible to cover all models available in

The movement of water from soil to the crop canopy and leaves to provide water for transpiration and the effect of weather factors on transpiration is most important area of study. When the crop is just sown, there will be an only evaporation of water from the soil. After germination of seeds there will be emergence of seedlings. After the emergence of seedlings there will be formation of leaves. The small leaves start intercepting the incoming solar radiation and absorb some portion of solar energy, get heated and there will be evaporation turn off water from the stomata of the leaf. When water vapour escapes into the atmosphere through the stomata of leaf, the plant absorbs carbon dioxide which results in photosynthetic activity. During night time, there will not be any photosynthesis due to absence of sunlight. The plants use parts of the photosynthetic accumulate for its metabolic activity and the process is called maintenance respiration. The balance of the photosynthetic accumulate contributes to the expansion of leaves and increased dry matter accumulation in crop plans. The process of dry matter accumulation in plants is called crop growth. When the seedlings start growing, there will be formation of tillers or branches. When the leaves grow it reaches a stage when the crop will be completely shading the ground and the soil evaporation will be minimum and maximum amount of water is lost only through evapotranspiration (Fig.6.1).

It is estimated that the world requires nearly 70 per cent increase in agriculture production to meet the demand for food by the year 2050 based on current trends in population growth it can be achieved either by increasing land under cultivation (which is not possible), increasing the availability of more water for agriculture and efficient utilisation of available land and water resources. The best available option is to increase in productivity of unit of land for unit water. However, the availability of water for agriculture production cannot be presumed to be same year after year as the major source of water is precipitation more known for its uncertainty due to change in weather patterns from season to season and year to year all over the world. The element of uncertainty is increasing since the beginning of the present century due to climate change under the present circumstance, the crop production is practiced -
• In Irrigated Areas
• In Rainfed Areas
• Under Conserved Moisture Condition Without Any Source Of Irrigation
For increasing crop production under irrigated condition, it is necessary to identify crops and varieties that can produce more yield per unit of water even when there is some decrease in availability of water through irrigation. Therefore, the concept of water production function is used for evaluation of water use efficiency of the crops.

Stress is force per unit area. When matter is subjected to stress; it may undergo changes in size, shape and displacement. Plants are grown in open environment and are likely to experience stress due to environmental conditions or when subjected to pests and diseases. The stress experienced by plants due to environmental conditions is called abiotic stresses. These include stresses caused by weather factors and climatic conditions and include moisture stress and thermal stress. The plants may also experience stress due to strong winds, dryness and as well as humid conditions (Fig.8.1).
The plants are generally classified into three types depending upon the ability to cope up with moisture stress as exhibited by-
• Drought resistance
• Drought tolerance
• Drought adaptations
The moisture stress may be to shortage of Water Compared to its requirements for evapotranspiration and metabolic activities. The plants may also suffer moisture

Remote sensing involves measurement of the physical properties of a body without actual contact with it. It is based on the reflectance when the electromagnetic radiation is incident upon a body or surface. The spectral characteristics of the reflected radiation vary depending upon the nature and condition of the surface. In case of vegetation, it absorbs light and can reflect light in the visible range. The leaf pigments dominate the reflectance properties (Fig.9.1). The radiation bands within which the reflectance of electromagnetic radiation takes place are classified as follows-
Spectrum Wave Length (nm)
Visible 400-700
Near Infrared 701-1300
Middle infrared 1301-2500
Far infrared >3000

9.1. Vegetation Indices
The vegetation index is a mathematical expression that uses spectral imaging data to characterize the health and growth of the vegetation indices are calculated using data collected by remote sensors like Satellites. The vegetation indices have wide range of applications in agriculture and hydrology including
• Classification of vegetation
• Apex health of vegetation
• Changes in land cover
• Drought monitoring
• Estimation of soil moisture
• Evaluate crop growth, vigour, biomass and chlorophyll content
• Irrigation scheduling