eChapters

River restoration aims to rehabilitate degraded or altered river systems, enhancing ecological integrity, improving water quality, and increasing biodiversity. Despite its potential benefits, the process is complex and multifaceted, facing challenges across scientific, social, ecological, technical, and conceptual dimensions. Scientifically, there is limited understanding of how physical complexity influences key ecological processes, such as stream metabolism and contaminant degradation. Site-specific factors, altered sediment regimes, and invasive species further complicate recovery efforts, often hindering ecological restoration even when hydrological conditions are improved. Socially, restoration initiatives struggle due to a lack of public awareness and appreciation for the ecosystem services provided by healthy rivers. Economic paradigms frequently undervalue these benefits, leading to perceptions that restoration is non-essential. Additionally, many projects lack robust pre- and post-monitoring frameworks, which restricts the ability to evaluate success and adapt strategies. To achieve effective restoration, a shift in scientific approaches and enhanced public engagement are essential. River scientists must act as educators and advocates, clearly communicating the societal value of restored ecosystems. Addressing these interconnected challenges requires interdisciplinary collaboration, long-term monitoring, and a comprehensive understanding of ecological, social, and physical dynamics to yield meaningful and sustainable outcomes across various environments.

Large Ruminants Neurological examination of farm animals is an essential part of the physical examination, especially when there’s a suspicion of neurological disease. The examination begins with observing the animal’s gait and how it interacts with its surroundings. The main goal is to determine whether the neurological issue is primary (originating in the nervous system) or secondary (caused by something else) and to pinpoint where the problem is in the nervous system ( central nervous system -CNS or the peripheral nervous system –PNS ). When examining an animal, it is best to start with procedures that cause the least distress. Painful tests or more invasive checks should be done at the end of the examination.

Introduction India’s animal husbandry sector plays a vital role in the country’s economy and food security. It provides livelihood to millions of people, contributes significantly to the agricultural gross domestic product (GDP), and meets the nutritional needs of the population. The sector encompasses various aspects of livestock production, including dairy farming, poultry farming, sheep rearing, goat rearing, and piggery. Milk Production India is the world’s largest milk producer, with an annual production of 230.58 million tonnes in 2022-23. This represents an impressive growth rate of 3.83% over the previous year. The top five milk-producing states are Uttar Pradesh, Rajasthan, Madhya Pradesh, Gujarat, and Andhra Pradesh. Egg Production India is also the third-largest egg producer in the world, with an annual production of 138.38 billion eggs in 2022-23. Egg production has grown by 6.77% in the last year. The top five egg-producing states are Andhra Pradesh, Tamil Nadu, Telangana, West Bengal, and Karnataka. Meat Production India’s meat production in 2022-23 was 9.77 million tonnes, with an annual growth rate of 5.13%. The top five meat-producing states are Maharashtra, Uttar Pradesh, West Bengal,

Introduction Livestock is a global resource with significant benefits to society in the form of food, income, nutrients, employment, insurance, traction, clothing and others. Livestock sector of India holds among one of the largest globally. Around 20.5 million people depend on it on livestock for their livelihood. Livestock farming contributed 16% of small farm income households compared to an average of 14% for all rural households. provides livestock Livelihood for two thirds of the rural population. Furthermore, it provides employment to around 8.8% of the workforce population in India. India has huge livestock populations. The livestock sector contributes 4.11% GDP and 25.6% of total agricultural GDP. Livestock count Livestock farming plays an important role in the farmers’ economy. The farmers in India Maintaining a mixed farming system, i.e

Animals are exhibited in various ways and events like in fairs, judging shows, in circuses, in zoos and as performing animals. Some famous animal fairs in northern part of the country are Sonepur cattle fair of Bihar. It is the largest cattle fair of Asia, held on the confluence of holy river Ganges and Gandak annually on KartikPoornima in the month of November for the trade of animals such as Cattle, horses,goats,donkeys,camels,birds and elephants. Haathi Bazaar is the major attraction of SonepurMela. Nagaur cattle fair held during the months of January and February. It is the second biggest cattle fair in India. Pushkar Cattle Fair,popularly known as camel fair held for five-days between the months of October and November. Cattle shows are organized time to time where animals are judged for their different characteristics, selecting for their best type, possessing true breed characteristics, dairy conformation, good temperament, proper growth and development according to its age, with optimum condition of fleshing and free from defects. To take part in such shows animals are transported to different places. So, apart from knowledge of restraining methods, concept related to ageing, animal handling (flight zone, point of balance) animal behavioural consideration and welfare indicators are of much importance for transporting and presenting animals in any show. Some of

Livestock plays a pivotal role in sustaining the livelihood of millions of people worldwide, particularly in rural and semi-urban communities. Beyond providing food products such as milk, meat and eggs, livestock also contribute to income generation, draught power, manure for agriculture and socio-cultural functions in many regions. The health and productive performance of livestock animals are central to achieving the economic, nutritional and ecological goals of animal husbandry. Any compromise in animal health or productivity directly impacts farmers’ income, food security, and national agricultural output. Animal health is the foundation of productive and sustainable livestock farming. Good health ensures animals can grow, reproduce and perform at their genetic potential. Conversely, disease, poor nutrition and environmental stress can severely reduce productivity and increase mortality. Common health challenges in livestock include infectious diseases (bacterial, viral, and parasitic), metabolic disorders and management- related stress conditions. Moreover, zoonotic diseases—those transmissible to humans— are of growing concern in the context of public health and food

The Convention on Biotechnology has defined biotechnology as “any technological application that uses biological systems, living organisms or derivatives thereof, to make or modify products or process for specific use”. The global food requirement is increasing with growing population, so the productivity gap could be filled by improving genetic health. Animal breeding focuses on genetic improvement through biotechnological and genomic approaches. Genetic progress is influenced by the type of biotechnology such as selection accuracy, genetic interval, intensity of selection, genetic variance. It helps to improve animal production, treatment of genetic disorders, production of transgenic animals resistant to diseases, vaccine production and also to maintain genetic diversity for endangered species. Genomic selection is a type of marker assisted selection. It improves the genetic gain by decreasing genetic interval and improving reliability. These novel approaches have high potential in animal breeding, if executed judiciously may provide practical benefits to mankind. The magnitude of genetic improvement of livestock species

Introduction Care and management of calf • Begins before its birth. • Good dairy herds are raised rather than purchased. • Dam should be dried 6-8 weeks before expected calving and should be fed well. • Underfed dam will give weak and small calves. Steps of calf management 1.  Removal of mucous • Immediately after birth:  removal of mucous or phlegm from nostril, mouth, eyes & ears for normal breathing. • Rub and dry the calf with a dry cloth or gunny bag • If cow not licking: sprinkle a little common salt on calf’s body. • If calf does not start breathing: Provide artificial respiration by: • Compressing and relaxing the chest with hands • Swinging • Inserting twig in nostril 2.  Ligation of naval cord • Cutting of naval cord: ligate-2.5cm & cutting-1cm below.

Raising healthy and productive animals is a cornerstone of successful livestock farming. Whether the goal is milk production, meat, draught power or breeding, the foundation of a thriving animal enterprise lies in appropriate general management and feeding practices that consider the animal’s stage of growth, reproductive status and work requirements. Each class of animal—calves, heifers, pregnant and lactating females, dry animals, bulls and working animals—has unique physiological needs that must be addressed through specialized care and nutrition. Modern animal husbandry aims not just at higher productivity but also at ensuring animal welfare, sustainability and profitability. Scientific and stage-specific practices improve the animals' lifetime performance and reduce mortality, disease incidence and reproductive failure. In this context, proper rearing practices are not merely a routine, but a strategic necessity. The calf represents the future of the herd. Ensuring its survival, growth and development is crucial for long-term productivity

According to the World Health Organization (2005), total health means the physical, mental, emotional and social health of a person. In these days of turmoil and hustle-bustle of modern life, emotional health has become as important as physical and mental health of an individual. A man should be physically fit, mentally alert, emotionally matured and socially adjusted, to lead a well-balanced life. A man who is having sound physical and mental health will also have good emotional health which will lead to social health. It means that all these four components of health are interrelated.

Emotional health depends upon a man’s emotional wellbeing, which is based on our self-concept, and self-esteem, that is how we feel about ourselves and behavior which is appropriate and healthy. Emotionally healthy people can adjust to their environment and solve their problems effectively and efficiently and in this way, they get satisfaction and pleasure out of life. So, it is essential to study the mental and emotional health of an individual, as both mental and emotional health are interrelated. It means that a person who is mentally healthy will also be emotionally healthy. In the same way, one who has good emotional health will also have good mental health.

The purpose of technological advancement these days is to make our lives comfortable. But many of the new inventions have added more stress to our lives and have made our lives increasingly more complex and complicated. Even more needs and demands seem to be built into our daily lives. These demands have affected the mental health, wellness, and psychological well-being of people living in our society.

These days, many advances have been made in eradicating disease, poverty, and other problems that have plagued our society, with the strains of modern living. Insecurity, worry, unhappiness, etc., have increased and have made mental illness our number one health problem. Anxiety and tension have increased so much that one out of every ten persons in our society has started taking tranquilizing drugs in one form or another.

The cases of mental illnesses have also increased these days, as shown by the admission records of the mental hospitals. These conditions have given birth to many psychological problems that are related to mental health. In this chapter, we are going to study those problems.

Climate change affects horticultural crops through rising temperatures, irregular rainfall, extreme weather, altered carbon dioxide levels and changes in seasonal patterns. These conditions influence plant growth, flowering, fruit development, nutritional quality and geographical suitability. They also alter the development, survival, reproduction and distribution of horticultural insect pests. Warmer conditions may accelerate insect life cycles, increase the number of generations and intensify crop infestations. Changes in rainfall can either suppress pest activity or create favourable conditions for outbreaks. This chapter examines interactions among climate, horticultural crops and insect pests and highlights the need for proactive monitoring and climate-adaptive pest-management strategies to safeguard horticultural production.

Successful onion cultivation begins with vigorous, disease-free seedlings and their timely establishment in the field. Seed quality, nursery-bed preparation, growing medium, nutrition, irrigation, weed control and protection against pests and diseases determine seedling performance. This chapter explains conventional and modern nursery-management practices, including raised beds, plug trays, protected structures, soilless media, fertigation and climate-controlled production. It also discusses seedling selection, hardening, transplanting age, spacing and field establishment. Mechanized, robotic and precision transplanting systems are examined as solutions to labour shortages and uneven planting. Climate-resilient nurseries, sensors and automation can further improve transplant survival, resource efficiency, uniformity, productivity and sustainability.

Processing extends onion availability and transforms perishable bulbs into stable, marketable products such as dehydrated flakes, powder, paste and pickles. Onion is also rich in phenolic acids, flavonols, anthocyanins and organosulphur compounds associated with antioxidant, antimicrobial, anti-inflammatory and cardioprotective properties. This chapter explains processing operations, quality preservation and the commercial importance of value-added onion products. It also addresses the large quantities of peels, outer scales and trimmings generated during processing. These residues contain quercetin, polyphenols, dietary fibre and other useful compounds that can be recovered for functional foods, nutraceuticals, natural antioxidants, biofuels and biodegradable materials, supporting waste reduction and a circular bioeconomy.

Artificial intelligence and machine learning provide the technological foundation for intelligent agricultural applications. This chapter introduces supervised, unsupervised and reinforcement learning, model-development pipelines, feature engineering and evaluation metrics. It explains how algorithms can be selected and implemented for agricultural datasets that may be noisy, incomplete, variable or weakly labelled. Advanced topics include deep-learning architectures, transfer learning and model optimization. Practical considerations involving preprocessing, interpretability and deployment constraints are also discussed. Agricultural case studies illustrate AI applications in crop-yield prediction, plant-disease detection and environmental modelling. The chapter provides the technical foundation needed to design, evaluate and responsibly implement AI-driven agricultural solutions.

The Internet of Things supports continuous monitoring of soil, crops, weather and other field conditions through distributed sensors and connected devices. This chapter proposes an edge-cloud architecture designed to address scalability, heterogeneous data, communication latency and energy requirements. Edge nodes conduct local processing and anomaly detection, while cloud platforms provide storage and run advanced machine-learning models. Applications include crop-status evaluation, irrigation scheduling, pest and disease detection and yield forecasting. Explainable artificial intelligence improves transparency by helping users understand model recommendations. The integrated architecture can reduce response time compared with conventional centralized systems and provides a foundation for scalable, efficient and responsive next-generation smart-farming operations.

Decision Support Systems convert farm data into recommendations that improve livestock productivity, health and sustainability. This chapter explains data-driven, model-driven and knowledge-based systems and their principal components: data management, analytical models and user interfaces. Technologies such as IoT, artificial intelligence, machine learning and cloud computing support applications in feed optimization, disease prediction, reproductive management, milk production and animal-welfare monitoring. Dairy and poultry examples demonstrate how DSS can reduce operational costs and strengthen farm decisions. Implementation challenges include inadequate data quality, high costs, limited technical expertise and maintenance requirements. Future systems are expected to integrate blockchain, robotics, Edge AI and increasingly autonomous management technologies.

The growing integration of Large Language Models into healthcare, education, business and cybersecurity has created new opportunities while introducing significant security and privacy risks. This chapter provides a comprehensive examination of vulnerabilities across the LLM lifecycle, from training and inference to deployment and integration with external applications. It discusses threats including prompt injection, jailbreak attacks, model extraction, membership inference, privacy-attribute inference and adversarial prompting. Deployment environments introduce additional risks involving unauthorized API access, misconfiguration, insecure integrations, logging-related data leakage and supply-chain attacks. The chapter also considers availability and integrity threats, including denial-of-service attacks and attempts to manipulate or remove AI-generated content watermarks. Privacy protection mechanisms such as differential privacy, anonymization, de-identification and encryption are examined as potential safeguards. Legal and regulatory considerations are also addressed, including data protection requirements and organizational governance. Because LLM applications may process sensitive personal and business information, security cannot be treated as an isolated technical feature. The chapter emphasizes continuous monitoring, secure architecture, privacy-preserving techniques, access controls and responsible governance for trustworthy LLM deployment.

The rapid adoption of Large Language Models requires organizations to manage not only model performance but also ethical, regulatory, operational and lifecycle risks. This chapter presents an integrated perspective on governance, optimization and lifecycle management of LLMs. It examines governance principles based on fairness, accountability, transparency, human-centered design and responsible AI. Regulatory developments and policy gaps are considered alongside the challenges of auditing opaque models, controlling hallucinations and establishing accountability across organizations and jurisdictions. The chapter also explores optimization methods such as pruning, quantization, model compression, instruction tuning, LoRA and QLoRA to improve efficiency while maintaining useful capabilities. Lifecycle management extends from data collection and model design through training, evaluation, deployment, monitoring, updating and eventual decommissioning. Real-world cases demonstrate the importance of continuous testing, feedback, security controls and governance throughout the model lifecycle. Emerging threats, including prompt injection, data poisoning, misinformation, privacy leakage and malicious use, further emphasize the need for coordinated oversight. The chapter ultimately advocates a lifecycle-based governance framework combining technical optimization, regulatory compliance, ethical safeguards and continuous monitoring

Generative Artificial Intelligence (GenAI) is rapidly transforming education by changing how knowledge is created, delivered, assessed, and experienced. Unlike conventional digital technologies that primarily retrieve or process existing information, generative AI can produce new text, images, audio, code, explanations, questions, and other learning resources in response to user prompts. This chapter introduces the foundations of GenAI and traces its evolution within educational environments, from conventional digital learning systems to intelligent, adaptive, and personalized platforms. It examines the role of Large Language Models, Retrieval-Augmented Generation, Learning Management System integration, multimodal learning, adaptive assessment, and AI-supported instructional design. The chapter also considers evidence from educational implementations involving school, higher education, and other learner groups. Particular attention is given to student engagement, self-regulated learning, teacher productivity, accessibility, fairness, privacy, and governance. By establishing the technological and pedagogical foundations of GenAI, the chapter provides a framework for understanding its opportunities, limitations, and responsible integration into contemporary education

Educational content development traditionally requires substantial time and effort from teachers, instructional designers, and academic institutions. Generative AI is changing this process by enabling the rapid creation, adaptation, personalization, and transformation of learning materials. This chapter examines how GenAI can redesign educational content generation across different subjects, educational levels, and learner requirements. It explores automated lesson-plan generation, question-bank development, personalized learning materials, visual and interactive resources, simulations, and multimodal educational content. AI systems can generate explanations at different levels of complexity, create assessments aligned with learning outcomes, and adapt instructional materials to student performance. Such capabilities can support differentiated instruction, self-paced learning, and improved learner engagement while reducing repetitive preparation work for educators. The chapter also examines important challenges, including content accuracy, algorithmic bias, copyright, data privacy, academic integrity, and teacher readiness. Future possibilities include adaptive tutors, multimodal content generation, AI-supported curriculum design, and intelligent learning resources. Overall, the chapter emphasizes that GenAI should augment professional educational judgment rather than replace it.

Student engagement and creativity are essential components of meaningful learning, particularly when education moves beyond passive knowledge transmission toward active participation and experiential learning. Generative AI is enabling educators to create interactive games, dynamic stories, role-playing environments, virtual laboratories, and realistic simulations that respond to individual learners. This chapter explores the potential of AI-generated creative learning environments to increase motivation, participation, imagination, problem-solving, and higher-order thinking. AI-generated educational games can dynamically adjust difficulty, generate new tasks, track student progress, and provide personalized feedback. AI-supported storytelling allows learners to modify narratives, develop characters, create alternative endings, and become active co-creators of educational content. Simulations provide opportunities to experiment with realistic situations without the cost or risk associated with physical environments. Applications include science laboratories, healthcare training, business decision-making, historical role-play, emergency management, environmental planning, and engineering design. The chapter also examines challenges including bias, privacy, infrastructure limitations, overdependence on technology, and changing teacher roles. Overall, AI-generated creative environments can connect theoretical knowledge with authentic practice while supporting deeper engagement and creativity.

The growing adoption of Generative AI in education offers substantial benefits in personalization, content creation, assessment, tutoring, and administrative efficiency, but it also introduces significant ethical, legal, and pedagogical challenges. This chapter examines the principles and practices required for responsible application of GenAI across educational environments. It focuses on algorithmic bias, fairness, data privacy, academic integrity, intellectual property, transparency, accountability, and the digital divide. AI models trained on large datasets may reproduce historical stereotypes or generate inaccurate and discriminatory content, potentially affecting marginalized learners. The extensive collection and processing of student information also raises concerns about informed consent, data storage, security, and appropriate use. Generative AI challenges traditional concepts of authorship and academic integrity because students may use AI to produce essays, assignments, and other academic work. The chapter discusses institutional policies, ethical audits, transparent content moderation, teacher and student AI literacy, human oversight, and multi-stakeholder governance. International principles such as UNESCO and IEEE guidance are considered as foundations for responsible implementation. The chapter emphasizes that trustworthy educational AI must remain human-centered, transparent, inclusive, accountable, and continuously evaluated.

Teachers perform numerous instructional, administrative, assessment, and planning activities that can consume substantial amounts of professional time. Generative AI offers opportunities to reduce repetitive workload while enabling educators to devote greater attention to pedagogy, mentoring, creativity, and student relationships. This chapter examines how GenAI can empower teachers rather than replace them. AI tools can assist with lesson planning, differentiated instruction, question-bank creation, assessment rubrics, feedback generation, learning-material development, classroom analytics, and administrative documentation. Adaptive AI platforms can analyze learner performance and help teachers provide different levels of support, practice, and challenge according to individual needs. Generative AI can also expand teachers’ creative capacity by enabling the development of stories, gamified activities, simulations, multimodal resources, and inclusive learning pathways. The chapter considers teacher experiences and implementation cases, including AI-supported teacher education and multilingual content generation. At the same time, successful adoption depends on teacher AI literacy, professional development, institutional support, ethical awareness, and appropriate human oversight. The chapter presents teachers as co-creators and change agents who use AI strategically while retaining professional judgment, responsibility, and control over educational decisions.

Education has continuously evolved in response to technological, economic, and social change. Education 5.0 represents a further transformation toward human-centered, personalized, inclusive, creative, sustainable, and collaborative learning environments supported by intelligent technologies. This chapter examines the evolution from Education 1.0 through Education 4.0 and explains how Generative Intelligence contributes to the emerging Education 5.0 paradigm. Earlier models progressed from teacher-centered knowledge transmission to standardized education, digitally connected learning, and technology-enabled competency development. Education 5.0 extends this evolution by emphasizing meaningful collaboration between humans and intelligent systems rather than simple technology adoption. Generative AI can support personalized content, automated assessment, intelligent tutoring, adaptive learning pathways, multimodal resources, and immersive educational experiences. The chapter also considers the role of AI, IoT, AR/VR, robotics, big data, cloud technologies, and other digital systems in shaping future learning ecosystems. Importantly, Education 5.0 must address data privacy, algorithmic fairness, academic integrity, digital inequality, sustainability, and human control. The chapter presents Education 5.0 as a human-centered transformation in which technology supports creativity, inclusivity, lifelong learning, social responsibility, and sustainable development.

Evaluation is a systematic process of determining the merit, worth, effectiveness and value of a programme through the collection, analysis and interpretation of relevant information. In agricultural extension, evaluation provides a structured basis for understanding whether programmes are achieving their intended objectives and how their implementation can be improved. This chapter introduces the fundamental concepts, purposes, types and criteria of programme evaluation and explains its role in accountability, decision-making, learning and programme development. It discusses formative and summative evaluation and examines approaches such as objective-based, process-oriented, theory-based and participatory evaluation. The chapter also introduces important principles governing credible evaluation, including impartiality, independence, transparency, competency, participation and pragmatism. Particular attention is given to the role, competencies and credibility of evaluators. Theories of evaluation, programme theory, social science theory, Utilization-Focused Evaluation, Values-Engaged Evaluation, Empowerment Evaluation and Theory-Driven Evaluation are also examined, providing a theoretical foundation for evidence-based agricultural extension evaluation.

Hypothesis testing provides a statistical framework for making inferences about populations from sample observations obtained through random experiments. This chapter introduces the scientific logic underlying statistical hypotheses and explains the formulation of null and alternative hypotheses. It discusses one-tailed and two-tailed tests, levels of significance, Type I and Type II errors, sampling distributions, test statistics, critical regions, p-values, and decision-making. The chapter also explains statistical significance and the interpretation of test results. Applications of Student’s t-test and related procedures are illustrated through forestry and biological examples, enabling researchers to determine whether observed differences between means can reasonably be attributed to treatments rather than random sampling variation.

Sexual propagation through seeds is a fundamental method for producing horticultural crops, rootstocks, and planting material. This chapter explains seed structure, quality, viability, dormancy, germination, and factors affecting successful seedling establishment. Different types of seed dormancy and methods for overcoming dormancy are discussed, including scarification, stratification, chemical treatments, temperature management, and appropriate moisture conditions. Seed testing and quality considerations are important for obtaining uniform and healthy plants. The chapter also emphasizes the influence of temperature, oxygen, water, light, and substrate conditions on germination. Understanding seed biology enables students and growers to produce vigorous seedlings and establish reliable nursery and crop-production systems.

Successful orchard establishment requires careful planning of site, climate, soil, water, planting material, spacing, and crop architecture. This chapter explains principles of orchard planning and establishment, including site evaluation, land preparation, layout, pit preparation, planting systems, and selection of suitable cultivars and rootstocks. Traditional and modern planting systems, including high-density and ultra-high-density systems, are discussed in relation to light interception, productivity, mechanization, and efficient resource use. Proper orchard design also facilitates irrigation, fertigation, pruning, harvesting, and plant protection. The chapter emphasizes long-term planning because perennial horticultural crops remain productive for many years and early establishment decisions strongly influence future orchard performance.

Metabolic fingerprinting and profiling provide powerful approaches for investigating global biochemical changes within biological systems. This chapter explains the principles of metabolic fingerprinting and profiling and distinguishes between broad, untargeted characterization and targeted analysis of selected metabolites. It discusses experimental design, sample preparation, analytical platforms, data preprocessing, normalization, statistical analysis, and multivariate approaches used to identify meaningful metabolic patterns. Techniques such as principal component analysis and related statistical methods help reveal differences between biological conditions. The chapter highlights applications in disease investigation, agricultural research, environmental studies, food analysis, and biotechnology, while emphasizing the importance of reproducible analytical procedures and appropriate interpretation of complex metabolomic datasets.

Composting explains the biological decomposition of organic materials and its importance for soil fertility, nutrient recycling, and sustainable farm management. The chapter introduces stages and types of composting, including anaerobic, aerobic, and vermicomposting systems, and discusses physical, chemical, biological, economic, and social benefits. Major methods such as Indore, Coimbatore, Bangalore, NADEP, sugarcane trash composting, fermented mixed compost, and crop-residue composting are presented. Factors affecting decomposition, including carbon-to-nitrogen ratio, shredding, moisture, and temperature, are examined. The chapter concludes with vermicomposting, earthworm roles, materials, preparation, developmental phases, and essential conditions required for effective vermicompost production. with emphasis on practical farm-level management practice systems.

Orchids represent a premium segment of commercial floriculture because of their distinctive flowers, long vase life and high market value. This chapter introduces major commercial orchid groups, including Dendrobium, Cymbidium, Cattleya, Phalaenopsis and Paphiopedilum. It discusses botanical features, climate requirements, growing media, propagation, tissue culture, planting, nutrition, irrigation, shade management and greenhouse production. Important pests, diseases and physiological problems are covered along with harvesting, grading, storage and postharvest handling. The chapter also includes commercial standards and cultivar characteristics, making it useful for understanding the specialized management required for high-value orchid production and export-oriented floriculture.

Neurological examination in farm animals requires systematic assessment of behaviour, mental status, posture, gait, cranial nerve function, spinal reflexes and sensory responses. This chapter presents practical methods for localizing neurological lesions and characterizing abnormalities. Examination includes assessment of head position, coordination, proprioception, skin sensation, panniculus response, deep pain and various spinal reflexes. Cranial nerve tests such as menace response, pupillary light reflex and corneal reflex are also described. Abnormalities including head tilt, circling, ataxia, paresis and paralysis can provide valuable clues to lesion localization. The chapter emphasizes a structured neurological examination for accurate clinical assessment.

16.1 Introduction

Producing more crops, livestock, fish and forest products per unit of water use is an essence of water productivity and is highly essential for both food and environmental security. A variety of options exist for improving the productivity of water in agriculture through breeding, better management practices and supporting policies and institutions. It is imperative to identify a range of means to enhance water productivity in agriculture, assess their potential and the consequences of their adoption. The production systems to be considered can vary from purely rainfed to irrigated, and from dry zones to semi-humid monsoonal areas.

The productivity of water used in agriculture has almost doubled during 1961 to 2001, It is mainly due to increases in crop yields. Irrigated rice yields doubled and rain-fed wheat yields rose by 160% in that period, with little variation in water consumption per kilo of output. Globally, FAO estimates that water needs for food per capita halved from about 6 m³/day to less than 3 m³/day during 1961 to 2001 which is a significant saving and an equally significant gain for other water users.

According to an estimate, a 1% increase in water productivity in food production enables to save about 24 lit/day of water per head of population, while a 10% increase would equal current domestic water consumption. Importance of saving water in agriculture can be realised from the above observation.

Introduction

Nucleotide and protein sequences construct the core of Bioiformatics. These biological sequences form complex and very large datasets. Various Statistical techniques have been used for analysis and extraction of precise information form small as well as large biological datasets. Evolution and natural selection makes biological sequences redundant and statistically biased. Once the mechanisms involved in such biases have been characterized, their analysis and systematic investigation become valuable tools for use in predicting the properties of other biological sequences. This biased nature results in relative codon usage value among the synonymous codons or Relative Synonymous Codon Usage (RSCU) value. Codon usage variation within a single genome can be an important source of information about gene expression levels and events of horizontal gene transfer (Medigue et al., 1991). The analysis of codon usage patterns can be traced back to when first molecular sequence databases were being colleted (Grantham et al., 1981). In order to evaluate the codon and amino acid usage variation, multivariate analysis options like Correspondence Analysis, Principal Component Analysis, Cluster Analysis, Factor Analysis, Multidimensional Scaling and Eigenanalysis Ordination are available (Morrison et al., 1994). It is well established that codon usage by its nature is multivariate. These methods provide a low dimensional point representation of genes, where the proximity of gene specific points indicates (CoA) a similar codon usage of associated genes. Correspondence Analysis is an exploratory graphical approach that requires contingency tables and generates results in the form of tables, scattered plots and graphs. CoA can identify the major sources of variation in the dataset. The output from a CoA can be used to evaluate other aspects of genes, such as base composition, expressivity, aromaticity and location on the genome (Thiouse et al. 1997).

Introduction

A careful compilation and scrutiny of data of aquaculture variables is essential for appropriate statistical analysis and meaningful statistical inference and interpretation of results. In nature, many aquaculture variables are inter-related with each other and the changes in variables would often depend on different variables which are either correlated or independent. In some cases, the variables could also be intra-related over a period of time. For statistical analysis of data of aquaculture variables comprising of different physical growth variables like fish weight, body mass, length and bio-chemical growth variables like muscle protein, lipid, glycogen, protease etc. and variables like pond size, water and its quality, the environmental parameters, type of feed, chemicals used etc., appropriate statistical procedures of correlation and regression could be explored for statistical analysis, testing and interpretation of results. Different statistical procedures are used for analysis of aquaculture data with the objective of making an assessment of

Introduction

S tates/organizations/agencies with statuary powers constitute Legislation, which are directly or indirectly related to their basic needs, smooth functioning of targeted system and to facilitate the safe survival of present as well as future generations of human being under jurisdiction. Legislation is a Latin word and customary that include all law constituted or in the process of constitution by empowered statuary houses/persons/group of people. Such Law has been categorized as Bill, Act, Rules and Regulations etc. Policy is a multipurpose dynamic tool, which activates different levels of administrative mechanism to perform various assignments systematically according to legislation systems. It includes collection of important information and statistics along with usefulness and validity of prevailing system of law. It brings required changes based on authentic and evaluated proper information. Legislation and policy and appropriate administrative mechanism are linked to each other in circular sequence.

Constitution of legal documents and its success is totally linked with administrative mechanism presumed to implement it. Basically administrative mechanism for implementation of legislation and policy is the responsibility of state/government. To devise a good administrative mechanism to implement legislation successfully, is a complicated, dynamic and multidimensional process system which ensure the balance functioning of the different components with automatic feedback of the targeted output and effectiveness of the legislation system in place.

Crop Management Practices
DSIR/TPDU/TIF 056 and E-28-GO-GOI Research Scheme on “Documentation and Preservation of Agricultural Traditional Knowledge through Farmer Participatory Approach”

Medicinal Plants
DSIR/TPDU/TIF 056 and E-28-GO-GOI Research Scheme on “Documentation and Preservation of Agricultural Traditional Knowledge through Farmer Participatory Approach”

Introduction

Pesticide in broad term refers to “killer of pests” but is an agent used to control, prevent, destroy, repel and mitigate a pest. Pesticides are thus poisonous substances intentionally applied in situations, which harbour so-called pests. Agriculture including poultry and veterinary (i.e. raising of crops and protection of produce and storage), health (public places-hospitals, restaurants, gardens cinema halls etc.), transportation (shipment, air rail and road transport) are some areas where pesticides are used extensively as spot application, fumigation, aerial and field sprays, soil treatments etc. Plant protection comes to be recognized as an equally important factor of agriculture production as improved seeds, fertilizers and irrigation. Pesticides over time get accumulated in the environment and contaminate all systems i.e. air, water, soil, plants, animals and micro-organisms on being transported from one system to another leading to biomagnifications.

The fate of a pesticide in the environment and the entities, which come in contact, is depicted in the Fig. 1 reflecting the pollution and contamination. Pesticides during manufacturing, transportation, storage and actual use enter the biotic and abiotic components of the environment through air, water and soil and disturb the cohesion causing great disaster sometimes. Pollution is defined as undesirable change in physical, chemical and biological characteristics of air, land and water. This change may or will harmfully affect human life or that of desirable species, industrial process, living conditions and cultural assets. It may or will waste or deteriorate our raw material resources. Pollution increases burden of human society causing loss of resources through unnecessary wasteful exploitation, the cost of pollution abatement and deterioration of human health.

Quantitative heat production estimation is necessary to  know the net energy of feeds and fodders. In the case of ruminants approximately 8 per cent of the gross energy consumed is lost as methane, therefore it becomes necessary to know this important loss in terms of methane energy so as to assess the metabolisable energy of any particular feed. In human subjects, heat production studies are conducted to know the effect of planes of nutrition on basal metabolism as affected by different environmental conditions.

In the important laboratories of world, heat production and methane production studies were conducted by respiration chamber (open circuit and closed circuit), since in our country respiration chamber has been installed at IVRI, Izatnagar, Bareilly (U.P.) India, therefore, this technique is mentioned in brief in this chapter. Indirect calorimetry involving the use of face mask and Douglas bag is followed at present in our country at NDRI, Karnal (India) so as to study the basal metabolic rate (BMR), heat production in human subjects and animals, Krishna (1973). Some laboratories in the country are interested to study respiratory quotient at different levels of feeding in human subjects and animals. The methods of estimation of RQ (respiratory quotient) is expressed in detail in this chapter.

1. Country Profile
 
Trinidad & Tobago comprises two islands with Trinidad being by far the larger of the two. They have a combined land area of 5,130 sq. km with Trinidad being 4,825 square kilometer. Over 95 per cent of the population of 1.3 million lives in Trinidad. Tobago’s affairs are, for the most part, administered separately through the Tobago House of Assembly, and therefore, the description of it’s extension system is reported separately.

The CSO report (CSO, 2004) listed Trinidad as having approximately 18,142 farmers who are mostly male (85 per cent) and average age of 52 years. These farmers farm on 84,900 hectares of arable land. The majority of this land (72.5 per cent) is under crop cultivation. While most of this land is dedicated to Sugarcane production, tree crops and vegetable cultivation are also important commodities. The rest of the farmland is used for Livestock (10.6 per cent), mixed farming (16.3 per cent) and some small amount of fisheries production. The majority of farms (63 per cent) are less than 5 hectare in size with 22  per cent being less than 0.5 hectare. Agriculture is mainly rain- fed but increasing amounts of farmland are being irrigated. Trinidad has six months of dry season (January-June) and an annual rainfall of 2010.9 mm of rain.

INTRODUCTION

The debate on climate change is going on. From the report of the Inter Governmental Panel on climate change (IPCC), a premier organization set up in 1998 by the World Meteorological Organisation and United Nations Environment Programme, it is known that the average surface temperature has increased over the 20th century by about 0. 6ºC. The number may seem insignificant but it is an unprecedented rise. In the past 150 years, the 11 hottest years were witnessed. It says that 1990s was the warmest decade and 1998 the warmest year since 1861. Worse, the Artic is warming twice as rapidly as the rest of the world and there is a distinct possibility of the Greenland Ice Sheet collapsing altogether and pushing up sea levels by several metres. It is predicted that 2035 is the year when Himalayan glaciers may totally disappear causing catastrophic disruptions. Unfortunately, India is among the countries that will suffer the most serious consequences as a result of global warming. Following is the probable effect of global warming.

INTRODUCTION

Of an estimated 142 mha of net cultivated areas in India, about 67 % is rainfed and only 45 mha is irrigated. The NCA (1976) predicted that even when the full irrigation potential of the country is exploited by 2013 AD, over 50% of arable land would continue to remain rainfed in future. It is the rainfed belt where cultivation of 91 % coarse cereals (Sorghum, Pearl millet and Finger millet), 91% pulses (Chickpea and Pigeon pea), 80% oilseeds (Groundnut, Rapeseed, Mustard and Soybean) and 65% cotton have predominated. Even the crop that formed the backbone of green revolution such as rice and wheat, still have 50% and 19% area under rainfed condition, thus emphasing the importance of rainfed agriculture in India. Inadequate resource (soil and rain water) management coupled with traditional farming practices are responsible for subsistence farming. Monocropping, traditional crops and their varieties, low and imbalance nutrients and inadequate crop establishment, in past, had been the major cause for poor development of dryland agriculture in the eastern region.

INTRODUCTION

Integrated Pest Management (IPM) has been defined as a “system that, in the context of the environment and the population dynamics of the pest species, utilizes all suitable techniques and methods in as compatible manner as possible that maintain the pest populations at levels below those causing economic injury” (Glass 1975). The Inter society Consortium for Plant Protection (ICPP) has defined integrated pest management as “the use of multiple tactics in a compatible manner to maintain pest population at levels below those causing economic injury while providing protection against hazards to humans, domestic animals, plants and the environment”. The term ’integrated’ means it is a broad interdisciplinary approach taken using scientific principles of plant protection of variety of management strategies and tactics to fuse into a single system. The terms ‘pest’ means all biotic agents which adversely affect plant production. This includes insects, mites, nematodes, weeds, bacteria, fungi, viruses, parasitic seed plants and vertebrates. The term ‘management’ indicates to keep the pest population below some level based on economic criteria. It does not mean complete eradication of entire pest population.

INTRODUCTION

One of the most important changes in the global environment which affects the existence of all living things , is the climate change. The climate change globally and locally also changes the aquatic habitat which, in turn directly and indirectly affects the environment. Anyway, the changes in climate are certain to occur and may be inevitable. The only possible way is to analyze the situation and find out the reasons for such changes and take immediate steps to minimize the impact of these climate changes. Global warming has eventually become synonymous with climate change because almost all the variables of the ecosystem are influenced directly or indirectly at different levels.

Aquatic environment is extremely diverse and influenced by the climate changes to a large extent both locally and globally. The changes in the ocean and its life are well studied at different levels with all possible details compared to the freshwater habitats. Unlike agriculture and animal husbandry, the vast majority of the fish production still comes from the natural habitat or the wild collections. Agriculture and animal husbandry usually focus on few important species but for fisheries, all the species of fishes including most of the aquatic living organisms are commercially important. The media (water) in which the aquatic organisms dwell, is much more important to all living organisms of the earth and so the influence by climate changes on water becomes very much relevant in the present situation. Freshwater habitats are limited and are much more complex to investigate in respect of climate changes due to the variability and diverse micro and macro level interactions. A holistic approach to deal with all these problems has not got much attention both globally and locally even though , it is the need of the hour to address the issues of impact of climate changes in the aquatic environment.

11.1 Introduction

The application of greenhouse in agriculture is vast. Greenhouses are used for growing flowers, vegetables, fruits, transplants and varieties of certain crops in a controlled environment which is appropriate for the plants. The edible flowers are served in some good restaurants to grow them precise calculation is required. Sensor network can help to monitor and automate the activities in greenhouse. The objective of this chapter is to discuss the development of sensor nodes to monitor the growth of flower plants through XBee and internet of things. The system comprises of three sections- sensor nodes, local server and main server. Sensor nodes communicate to local server with XBee and then local server communicates the same data to main server through IoT.Fig.11.1 shows the generalized block diagram, sensor node is to be implemented on each flower pot and communicating to local and main server.

Extension is an “Out – of – School” system of education for rural people.

The term “Extension” have originated in Latin. It means stretching out.

The term “University Extension” was first used in 1866.

The person considered as Father of extension and the concept of Extension Education Process was given by Paul Leagans

The person considered as father of extension in India is K.N.Singh

The term “Extension Education” was first coined in United Kingdom

Extension education is an applied behavioral science and brings about behavioral changes in human beings.

The philosophy of extension is not “What to Think?.” It is “How to think?”

1. INTRODUCTION

The Technology Protection System (TPS) or “Terminator Technology” as it has been called, allows plant breeders to genetically modify and protect their crop rights so they produce seed for one generation only. TPS was co-developed by the US Department of Agriculture (USDA) and Delta and Pine Land Company in 1998. They received U.S. Patent 5723765 entitled “Control of Plant Gene Expression”. The patent was based on research conducted under a Cooperative Research and Development Agreement (CRADA) between Delta and Pine Land Co. and the ARS USDA. The CRADA was signed in 1993.

I. Classification of fruit crops

1. Based on botanical relationship