eChapters

Horticultural crops include fruits, vegetables, flowers, plantation crops, spices, aromatic plants and medicinal species. They contribute substantially to nutrition, farm income, employment, exports and livelihood security. However, their productivity and quality are highly sensitive to temperature, rainfall, humidity, drought, flooding, salinity and other climate-related stresses. Changing climatic conditions affect flowering, fruit setting, maturity, nutritional composition, pest incidence and postharvest quality. Annual and perennial crops respond differently depending on their location, growth stage and environmental requirements. This chapter examines the influence of major climatic factors on horticultural production and discusses adaptive practices required to maintain productivity, quality and economic sustainability under changing environmental conditions.

Climate refers to the long-term pattern of temperature, rainfall, humidity, wind and other weather parameters within a geographical region. Human activities such as industrialization, urbanization, deforestation, land-use change and intensive agriculture have accelerated climate change by increasing greenhouse-gas emissions. Rising temperatures, irregular monsoon rainfall, droughts, floods, cyclones and elevated atmospheric carbon dioxide now affect crop growth, development and productivity. Different crops and developmental stages vary in their tolerance to these stresses. Consequently, farmers are modifying cropping patterns, sowing periods and crop choices. This chapter examines the effects of changing climatic conditions on major agricultural crops and identifies suitable adaptation and mitigation measures.

Computational intelligence is central to the development of proactive, personalized and connected healthcare systems. This chapter examines artificial intelligence, machine learning, expert systems, medical-image analysis, IoT, big-data analytics, cloud computing and blockchain as key enabling technologies. It presents intelligent architectures for diagnosis, monitoring, treatment support and secure health-data management. Privacy, cybersecurity, explainability, bias, fairness, scalability and deployment challenges are discussed in relation to practical healthcare implementation. The chapter proposes a research roadmap involving trustworthy AI, advanced privacy-preserving mechanisms, edge-cloud intelligence, digital twins, multi-omics integration and personalized health models. It also emphasizes accessible computational-intelligence solutions for rural and resource-constrained healthcare environments

Intelligent healthcare is advancing through the integration of multimodal data, trustworthy AI, federated learning, digital twins, IoT devices and real-time decision-support systems. This chapter reviews the evolution of healthcare-data analysis and examines emerging methods for intelligent diagnosis and predictive care. It discusses explainability, privacy-preserving analytics, interoperability, data governance and ethical frameworks necessary for responsible implementation. Wearable technologies and connected sensors support continuous monitoring, while human–AI collaboration improves clinical decision-making. Case studies illustrate practical healthcare applications and implementation strategies. The chapter also considers global-health requirements, particularly in developing countries, and identifies future opportunities for scalable, equitable, secure and clinically effective intelligent healthcare systems.

Healthcare organizations require collaborative learning methods that protect sensitive patient information. This chapter introduces federated learning as a framework for training models across decentralized institutions without transferring raw clinical data. Horizontal, vertical and hybrid federated architectures are examined alongside communication protocols, threat models and security requirements. Privacy-enhancing methods—including differential privacy, secure aggregation, cryptographic techniques and trusted execution environments—are discussed. Applications in medical imaging, electronic health-record analysis, wearable devices and remote patient monitoring demonstrate the framework’s practical value. The chapter also evaluates accuracy, privacy, communication cost, scalability and robustness while addressing data heterogeneity, fairness, explainability, legal compliance and ethical challenges in collaborative healthcare analytics.

Data-centric artificial intelligence has transformed medical imaging, clinical prediction and electronic health-record analysis, but purely data-driven models face limitations involving generalization, bias, privacy and interpretability. This chapter examines the transition toward knowledge-aware and hybrid healthcare systems that combine machine learning with clinical knowledge, ontologies and knowledge graphs. It discusses explainable AI, clinical reasoning and the integration of structured knowledge into intelligent decision support. Applications include acute-care support, precision medicine, genomic oncology and population-health management. Ethical issues, regulatory compliance, fairness and privacy-preserving technologies are also considered. Future directions include quantum computing, large language models, multimodal integration and equity-focused healthcare-system development.

Predictive analytics estimates future health risks and outcomes, while prescriptive analytics recommends appropriate interventions and resource-allocation strategies. This chapter explains how statistical models, machine learning and healthcare data can support disease-risk assessment, prognosis and personalized treatment. Applications involving cardiovascular disease, diabetes, cancer, chronic-disease management and early-warning systems are examined. The integration of clinical, genomic, lifestyle and electronic health-record data is discussed alongside survival analysis, disease-progression modelling and treatment-response prediction. The chapter also addresses bias, fairness, transparency, privacy, regulation and interoperability. Future developments involving real-time analytics, IoT-enabled monitoring and precision medicine illustrate the transition toward proactive, preventive and data-driven healthcare.

Electronic health records contain extensive clinical, demographic, diagnostic and treatment information that can support medical research and decision-making. This chapter examines the characteristics of healthcare big data and the challenges associated with EHR storage, integration, quality and analysis. It presents an analytics pipeline covering data ingestion, secure storage, preprocessing, integration, pattern discovery, visualization and clinical decision support. Machine learning and deep learning methods are discussed in relation to clinical phenotyping, risk stratification, predictive epidemiology and adverse-outcome prediction. The chapter also addresses data privacy, governance, regulatory compliance, explainability, scalability and bias, highlighting the need for secure and interoperable EHR-mining systems that generate clinically useful knowledge.

Symbolic systems provide logical reasoning and explicit knowledge representation, whereas sub-symbolic models offer learning, adaptation and pattern-recognition capabilities. This chapter explains how combining these approaches can create more accurate, adaptive and interpretable intelligent systems. It discusses rule-based systems, logic programming, ontologies, neural networks, fuzzy systems, evolutionary computation and swarm intelligence. Neural-symbolic, neuro-fuzzy, rule-augmented and ontology-aware architectures are examined, along with loose, tight and deep integration strategies. Applications in healthcare, cybersecurity, manufacturing and knowledge-based information systems demonstrate their practical potential. Challenges involving integration complexity, scalability, knowledge engineering, transparency and continuous updating are considered, together with future directions in human-centred hybrid intelligence.

Advanced artificial-intelligence models can achieve high predictive performance, but their black-box nature limits clinical trust and accountability. This chapter examines interpretability and explainability as essential requirements for trustworthy healthcare analytics. It reviews intrinsically interpretable models, post-hoc explanation methods, example-based approaches and network-based explanations. A framework combining data preparation, model selection, ensemble learning, calibration, uncertainty estimation and explanation validation is presented. An explainable sepsis-risk prediction case study demonstrates logistic modelling, ensemble methods, Bayesian uncertainty, SHAP attribution and network analysis. The chapter also addresses causal reasoning, adversarial robustness, temporal and multimodal data, human-centred explainability, ethical responsibilities and regulatory requirements for dependable clinical AI.

Biomedical signals provide valuable information about physiological conditions and support continuous health monitoring. This chapter introduces ECG, EEG, EMG, PPG, respiratory and blood-pressure signals and examines the challenges associated with their acquisition and interpretation. It discusses noise removal, filtering, normalization, resampling and artifact correction before presenting time-domain, frequency-domain, time–frequency, wavelet and nonlinear feature-extraction methods. Feature selection and dimensionality reduction are considered in relation to model accuracy and clinical interpretability. The chapter also explores machine learning, deep learning and hybrid approaches through applications involving arrhythmia detection, seizure prediction and wearable cardiovascular monitoring, highlighting their importance in intelligent and personalized healthcare.

Clinical decision support systems assist healthcare professionals in diagnosis, treatment planning and patient management. This chapter introduces intelligent clinical decision support systems and explains how computational intelligence overcomes the limitations of conventional rule-based approaches. It examines artificial neural networks, fuzzy logic, evolutionary algorithms, swarm intelligence and deep-learning models. A computational architecture integrating clinical data, learning algorithms, fuzzy inference and optimization is presented. Applications in heart-disease diagnosis, diabetes-risk prediction and medical-image analysis illustrate the practical value of these systems. The chapter also addresses interpretability, interoperability, data quality, privacy, legal responsibilities, real-time processing and the challenges involved in deploying intelligent decision-support tools in clinical environments.

Healthcare artificial intelligence depends on the quality, fairness and reliability of the data used for model development. This chapter examines the characteristics of healthcare data and explains how incomplete, inconsistent or unrepresentative datasets can produce inaccurate and discriminatory clinical outcomes. It identifies sampling, demographic, measurement, historical, institutional and annotation biases and discusses strategies for mitigating them at the data, algorithm and evaluation stages. Model robustness across different populations and clinical environments is also considered. Particular attention is given to explainable AI, human oversight, continuous auditing and interdisciplinary collaboration as essential components of trustworthy, equitable and clinically dependable healthcare systems.

This chapter examines the principles, preparation and application of vaccines and biological products. It compares live attenuated, inactivated, toxoid, subunit, recombinant, vector, DNA and mRNA vaccines. Vaccine development phases, immunogenicity, safety, efficacy and post-marketing surveillance are introduced. The chapter discusses adjuvants, including alum, Freund’s adjuvants, liposomes, ISCOMs and delivery systems. Important veterinary vaccines for brucellosis, foot-and-mouth disease, anthrax, Newcastle disease, infectious bronchitis, goat pox, sheep pox and peste des petits ruminants are covered. Questions also address bacterins, toxoids, attenuation, booster requirements and reversion to virulence, providing practical knowledge of immunoprophylaxis in animal-health management.

This chapter deals with the principles and applications of serological tests used to detect antigens and antibodies. It distinguishes primary, secondary and tertiary binding tests and explains antibody titre, affinity, avidity, sensitivity and specificity. Important techniques include precipitation, agglutination, complement fixation, neutralization, immunofluorescence, ELISA, radioimmunoassay, Western blotting and the radioallergosorbent test. The chapter also addresses serum decomplementation and the interpretation of positive and negative reactions. These methods are central to the laboratory diagnosis, surveillance and control of infectious diseases. The objective questions enable readers to compare diagnostic techniques and select appropriate tests according to their principles, applications and analytical performance.

This chapter introduces hybridoma technology and its application in producing monoclonal antibodies. It explains the fusion of antibody-producing B lymphocytes with immortal myeloma cells, selection in HAT medium and the roles of HGPRT and polyethylene glycol. The survival and cloning of hybrid cells and the advantages of monoclonal antibodies are considered. The chapter also discusses tissue and organ transplantation, including autografts, isografts, allografts and xenografts. The immunological mechanisms of acute graft rejection, donor histocompatibility antigens and the involvement of T lymphocytes are addressed. These questions connect laboratory antibody production with transplantation immunology and its diagnostic, therapeutic and research applications.

This chapter examines immune-system failure arising from reactions against self-antigens or inadequate immune responses. It introduces immunological tolerance, central and peripheral tolerance, clonal deletion and clonal anergy. Important autoimmune diseases—including myasthenia gravis, Graves’ disease, systemic lupus erythematosus, multiple sclerosis, rheumatoid arthritis and Sjögren’s syndrome—are considered. The chapter also discusses molecular mimicry and the production of autoantibodies. Primary, secondary and severe combined immunodeficiency disorders are differentiated, with examples such as Chédiak–Higashi syndrome. Immune-privileged sites and immunological paralysis are also covered. These topics explain the mechanisms that normally prevent self-reactivity and the consequences that arise when immune regulation becomes defective.

This chapter explores the four types of hypersensitivity reactions described under the Gell and Coombs classification. Type I immediate hypersensitivity, Type II cytotoxic reactions, Type III immune-complex disease and Type IV delayed hypersensitivity are examined in detail. The roles of IgE, mast cells, basophils, antibodies, complement and T lymphocytes are highlighted. Clinical examples include anaphylaxis, milk allergy, haemolytic disease, transfusion reactions, serum sickness, glomerulonephritis, farmer’s lung and the blue-eye condition associated with canine hepatitis. Diagnostic applications, including the tuberculin and Coombs tests, are also addressed. The chapter explains how exaggerated or inappropriate immune responses can damage tissues and produce disease.

This chapter examines cytokines as essential signalling molecules that regulate immune and inflammatory responses. It introduces interleukins, interferons, chemokines, tumour necrosis factors and colony-stimulating factors. Their sources, target cells and biological actions are considered in relation to immune-cell activation, differentiation, migration and communication. The chapter explains important properties such as pleiotropy, redundancy, synergy and antagonism. It also covers antiviral activity, chemotaxis, inflammation, fever and the regulation of humoral and cell-mediated immunity. Special attention is given to excessive cytokine production, cytokine storms and septic shock. These questions help readers understand how cytokines coordinate protective immunity and contribute to immune-mediated disease.

This chapter introduces the complement system as an important component of innate and adaptive immunity. It explains the classical, alternative and lectin pathways of complement activation and identifies the molecules involved in each pathway. The formation and functions of C3 convertase, C5 convertase and the membrane attack complex are discussed. Questions address complement-mediated cell lysis, inflammation, chemotaxis and opsonization. The roles of C3b, C3a, C4a, C5a, properdin, factor H and other regulatory proteins are also examined. By covering the activation and regulation of complement, the chapter explains how this system enhances antibody activity and helps eliminate invading microorganisms

This chapter explains how B-cell receptors, T-cell receptors and major histocompatibility complex molecules participate in antigen recognition. It differentiates MHC class I and class II pathways and describes the processing of endogenous and exogenous antigens. The roles of dendritic cells, macrophages and B lymphocytes as professional antigen-presenting cells are examined. Topics include MHC restriction, antigenic peptides, proteasomal degradation, ubiquitination and recognition by CD4-positive and CD8-positive T lymphocytes. The chapter also discusses superantigens, opsonization, phagocytosis, T-independent antigens and species-specific MHC systems such as BoLA and the avian B complex. These concepts explain the initiation of adaptive immune responses.

This chapter focuses on the structure, classes, properties and biological functions of immunoglobulins. It introduces the basic antibody molecule, including heavy and light chains, variable and constant regions, antigen-binding sites and Fc fragments. The characteristics of IgG, IgM, IgA, IgE and IgD are examined in relation to their distribution and immune functions. Questions cover primary and secondary immune responses, placental transfer, mucosal protection, allergic reactions, complement activation and agglutination. The chapter also addresses antibody affinity, avidity, isotypes, allotypes, idiotypes, class switching and Bence-Jones proteins. It provides essential knowledge of how antibodies recognize antigens and contribute to immune protection and diagnosis.

This chapter describes the cells, tissues and organs responsible for immune defence. It examines lymphocytes, macrophages, dendritic cells, neutrophils, mast cells, natural killer cells and plasma cells, emphasizing their respective functions. Primary and secondary lymphoid organs—including bone marrow, thymus, bursa of Fabricius, spleen, lymph nodes and mucosa-associated lymphoid tissue—are discussed. The chapter also covers lymphocyte maturation, antigen presentation, phagocytosis, immune-cell surface markers and the organization of lymph-node regions. Positive and negative selection of T lymphocytes and the formation of memory cells are included. Together, these topics explain how immune components develop, communicate and coordinate effective responses against infectious agents.

This chapter examines the major forms and mechanisms of immunity. It distinguishes innate immunity from adaptive immunity and explains specificity, diversity, immunological memory and self–non-self recognition. Natural and artificial forms of active and passive immunity are discussed through examples involving infection, vaccination, maternal antibodies and antiserum administration. The chapter introduces pattern-recognition receptors, pathogen-associated molecular patterns and Toll-like receptors involved in microbial recognition. It also covers inflammation, its cardinal signs, acute-phase proteins and the roles of neutrophils and other innate defence components. These objective questions provide a clear foundation for understanding how animals resist infections and develop long-lasting protective immune responses.

This chapter introduces the historical development and fundamental concepts of immunology. It highlights the contributions of Edward Jenner, Louis Pasteur, Elie Metchnikoff, Paul Ehrlich, Emil von Behring and other pioneering scientists. Important discoveries related to vaccination, phagocytosis, antibody formation, cellular immunity, ELISA, radioimmunoassay and hybridoma technology are addressed. The chapter also explains antigens, immunogens, epitopes, haptens, adjuvants and the desirable characteristics of an effective immunogen. Questions concerning smallpox and rinderpest eradication, vaccine development and primary and secondary immune responses help readers understand the scientific milestones that established immunology as an essential discipline within veterinary and biomedical sciences.

Mental and emotional health encompasses psychological, emotional, and social well-being. It influences how people think, feel, behave, make decisions, cope with difficulties, and interact with others. Mental health is not merely the absence of mental illness; it is an essential component of overall health and quality of life. Regular self-care can help individuals maintain emotional balance and support treatment and recovery when mental-health problems occur. Psychologists and mental-health professionals have an important responsibility to assist emotionally distressed individuals in overcoming adjustment and personality-related problems and leading normal, productive lives. Mental and emotional difficulties may be triggered by stressful circumstances, including bereavement, family conflict, relationship changes, physical illness, or incomplete recovery caused by stopping treatment prematurely. Recognising such triggers and early warning signs can help prevent symptoms from worsening. Therefore, proper care, healthy habits, professional support, and preventive strategies are necessary to promote lasting mental and emotional well-being throughout every stage of human life.

Suicide among young people is a very serious problem in our society. Suicide is the second leading cause of death among children, adolescents, and young adults aged 15 to 29. Most children and adolescents who attempt suicide have a significant mental health disorder, usually depression.

Suicide is a problem throughout the lifespan. Suicidal behavior refers to talking about or taking actions related to ending one’s own life. Suicidal thoughts and behaviors should be considered a psychiatric problem. It is like injuring oneself and harming oneself. It is ending the life of the self.

Suicide is a psycho-social problem. It is related to the emotional life of a man. It has social ramifications, as it is a criminal offence, which is a kind of crime. Suicide is an act of intentionally causing one’s own death. It is considered self-murder. It is not concerned with inter-personal relations, but it deals with intra-personal relations. Because it is a self-injurious behavior with the desire to end one’s own life, it is a kind of mental disorder

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.

All human beings are prone to a state of anger, which affects their performance during their day-to-day life. Anger and aggression are the same, although they are often experienced at the same time. Anger is an emotion, whereas aggression is a behavior or form of intervention. Whereas anger is internal, aggression is external. But both are typically associated with physiological arousal.

A person who perceives that wrong has occurred, which should be corrected, usually feels anger. Anger is a reaction against somebody, a person, an event, or an object. It is resentment to some injustice which has been perceived to have been meted out. The emotion of anger leads to aggressive behavior, especially among adolescents and teenagers. Aggression further causes pain to individuals.

Let us try to understand what we mean by anger, aggression, and pain, and how to manage them.

The most important aspect of Bandura’s theory that has received most attention in recent research is his concept of self-efficacy. This theory emphasizes that an individual’s belief that he or she can perform some behavior or task successfully. If a person can expect to do well in some tasks, his self-efficacy is high, but if he has some doubts about his performance, then his self-efficacy is lower. Self-efficacy has been found to play a role in success in many tasks and personal happiness, and life satisfaction.

The concept of self-efficacy lies at the center of psychologist Albert Bandura’s social cognitive theory. Bandura’s theory emphasizes the role of observational learning, social experience, and reciprocal determinism in the development of personality. According to Bandura, a person’s attitudes, abilities, and cognitive skills comprise what is known as the self-system. This system plays a major role in how we perceive situations and how we behave in response to different situations. Self-efficacy plays an essential part in this self-system.

The concept of social health is not much known as compared to that of physical or mental health, but it forms one of the four pillars of most definitions of health, i.e., physical, mental, emotional, and social. Social health is a state of well-being and a positive dimension of health, which is included in the definition of health given by WHO. An individual can handle, and act based on different social conditions.

Social health is the aspect of overall psychological well-being that stems from connection with the community. It’s about having close bonds with family and friends, enjoying a sense of belongingness to groups, and feeling supported, valued, and loved. To say that our relationships determine both how well we live and how long we live; connection is as vital to survival as food and water.

For instance, research has shown that a positive, satisfying relationship is one of the best predictors of health across the lifespan, whereas loneliness is not. That’s why it is helpful to distinguish social health as a distinct aspect that is an interconnected pillar of overall well-being.

Positivism emerged out of the modernist era, which experienced its fullest expression during the Enlightenment of the 18th century, but which had been stimulated through the earlier writings of philosophers such as August Comte, John Stuart Mill, and David Hume. Modernists believed that through the systematic application of logical mental process, ignorance and superstition could be replaced by progress, justice, and beauty. The tremendous optimism of the modernistic era was accompanied by an unrelenting faith in both the epistemology and methodology of positivism.

The foundation of positivism was grounded in a mechanistic worldview based on the assumption of predictable cause-and-effect patterns of relationships. Furthermore, positivism was grounded in the belief that there exist some laws in the natural and social worlds that are unaffected by one’s perspective and that can best be understood through reliance on objective scientific. Positivism led to positive thinking, positive attitude, and positive actions. Positive thinking leads to good mental and emotional health. So, there is a strong relationship between mental health and the role of positive thinking.

For the maintenance of mental health, positive behavior or positivity in life is a very essential trait. Positive behavior helps develop love, mental peace, harmony, cordiality, happiness, and better inter-personal relationships; whereas negative behavior is responsible for creating animosity, hatred, fear and anger among us, which adversely affects our mental health. It will make us unhappy, miserable, and sad.

Positive behavior leads to positive thinking, positive feelings, and positive actions. On the other hand, negative behavior develops negative thoughts, negative attitudes, as well as nefarious activities. Psychologists are working in this area to make the life of a man happy, effective, and successful. This area is called Positive Psychology, which is a recent branch of psychology that is the youngest area in the behavioral sciences.

Positive psychologists seek “to find and nurture genius and talent and to make normal life more fulfilling” (Crompton, 2005) and not simply to treat mental illnesses. They are trying to make the world a happier place.

Emotional well-being is one of the most important dimensions of psychological well-being and mental health. Here an effort is being made to study the concept of emotional wellbeing. The concept of emotional well-being has acquired more importance in the field of health and positive psychology these days. It is much more concerned with mental and emotional health.

Emotional well-being, which is considered as the quality and subjective satisfaction of life is a measure of an individual’s perceived level of happiness. It is also related to self-concept. However, there is the relationship between self-concept with emotional well-being. But emotional health is related to emotional well-being, which is a part of mental health. Usually emotionally intelligent people represent better ability for problem-solving and for managing stress, more impulse control and a positive attitude towards oneself and others implying greater enjoyment of life, resulting in emotional well-being.

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.

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.

Human wellness is the psychological well-being of human beings. The behavioral skills of human beings are concerned with human wellness. The main purpose is to make life more comfortable and to help people be happier, healthier, and effective. So, the concept of human wellness has acquired significance in the field of positive psychology in this current era when people are suffering from strains and stress.

Ever since more attention has been paid to the quality of life, the concept of human wellness has become more popular. However, less importance has been given to the conceptual development of the theory behind it, thus creating confusion between terms like psychological well-being, subjective wellness, quality of life, satisfaction, happiness, and mental health.

Quality of life and life satisfaction are measures of an individual’s perceived level of human wellness and happiness. It is sometimes used as a synonym for subjective or general well-being. Human wellness is related to the psychological well-being of an individual. The latter is concerned with the mental and emotional health of a man. Psychological well-being may be stated as the general feelings of enjoyment, happiness, contentment, job satisfaction, and one’s role in the workplace, a sense of achievement, belongingness, as well as the is no distress, dissatisfaction, or worry, etc.

The strains and stresses of our modern living, i.e., insecurity, worry, unhappiness, have helped to make mental illness our number one health problem. The twentieth century was often referred to as the “Age of Anxiety”, but the twenty-first century is considered the period of ‘strains and stresses’ as well as ‘hustle and bustle’. These days, psychological burnout and the problem of depression are increasing day by day.

Despite the proximity and enormity of the problem of mental illness and the familiarity and understanding with which we should approach it, attitudes towards it exist in our culture that are very old now, as many people still regard mental illness as they once regarded cancer, polio, and other diseases—as incurable, something mysterious and fearful. Some people still consider that somebody has done magic on these people, or some bad element has entered their bodies.

Virtually, all of us will encounter mental illness at sometimes or another in our lives, either in our own family or in our circle of friends. We consider it a stigma, and we don’t want to reveal this bad omen to others. All these things are related to our mental health. Good mental health leads to mental hygiene. So, it is important to know what mental hygiene is and how to inculcate the different aspects of mental hygiene.

Mental health is the condition of the mind and mental processes, which function well within the societal laws and prevailing circumstances of a person. Just like physical health means being away from any physical ailments, similarly, mental health is the absence of any mental illnesses or mental disorders. Mental health is a life adjustment. If a person is well-adjusted in his personal, social, and professional life, it means that he has good mental health. Mental health refers to cognitive, behavioral, and emotional well-being. It is all about how people think, feel, and behave.

Mental health is an integral and essential component of health. The WHO constitution states: “Health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.” Mental health is a state of wellness in which an individual realizes his or her abilities, can cope with the normal stresses of life, can work productively, and can contribute to his or her community. Mental health is fundamental to our collective and individual ability as humans to think, emote, interact with each other, earn a living, and enjoy life. On this basis, the promotion and maintenance of mental health can be regarded as a vital concern of individuals, communities, and societies throughout the world.

Here in this chapter, we will discuss the concept and importance of mental health in our ordinary lives.

Psychological well-being includes general well-being, quality of life, satisfaction in life, happiness, and mental health. Quality of life and subjective life satisfaction are measures of an individual’s perceived level of psychological well-being and happiness. It is sometimes used as a synonym for subjective happiness and general well-being. Psychological well-being is also related to another variable, such as ‘self-concept’. Self-concept may be stated as the quality of perceptions that each person has of himself, and this self-identity or self-image plays an important role in the psychological functioning of human well-being.

Many attempts have been made in the past to measure positive mental and emotional health, only one of which is the measure of a subjective, general sense of psychological well-being. Attempts over the years have been made to find out more about its correlates.

These days, the concept of psychological well-being has gained more impetus in the field of health and positive psychology. Ever since research has paid more attention to ‘quality of life,’ psychological well-being has become popular. However, less importance has been given to the conceptual development of its construct, thus creating confusion between terms which at first appear similar: psychological well-being, subjective well-being, quality of life, satisfaction in life, happiness, and mental health.

The concept of psychological well-being is related to mental, emotional, and social health. Ever since research has started in this area, psychologists have started paying more attention to ‘quality of life,’ and hence psychological well-being has acquired more importance. But less importance has been paid to the conceptual development of its construct. As mental health is related to psychological well-being, it is essential to study psychological well-being.

The phases of green revolution and post green revolution of Indian agriculture have assured us of security. We are now producing 354 million tons of food grains and our target is to produce 550 million tons before 2050. This is really an incredible progress for any country dominating with rural and agrarian economy. As on date, the contribution of Indian agriculture to national GDP is 14.7 % but it has to support around 60% of population. While food security has been ensured for 1480 million of population, the issues of malnutrition are standing paramount. It sounds melancholic that India is also sustaining world’s highest count of hungry population close to 51% newborn babies are underweight, 60% of rural women are anaemic, millions are deprived of dedicated safe drinking water. According to FAO, between 702 and 828 million people in the world faced hunger in 2021. Health, hygiene and nutrition are organically linked to each other, in terms of calorie intake of rural women. We are still far below of international standard. Alongside, the hemoglobin level runs below the expected level to indicate that women are runningin a moderate to acute anaemic condition. Around 840 million people are malnourished from insufficient calories. According to Black et al., (2008) nutrition related factors were found to be jointly responsible for around 35% of the child fatalities and 11% of the overall global illness burden in an analysis that took into account co-exposure. Due to poor quality of drinking water, whatever available, the propagation of water born diseases has been endemic and robust. The geo-spatial distribution of hunger and malnutrition indicates that there is location to location variation, gender discrimination, and seasonal variability across the terrain of social-cultural distribution. To make India stronger and swashbuckling we need to refocus on women health, child care and removal of economic discrimination. With acute hunger, mapping, problem of chronic hunger as well, chronic hunger hasbeen reflected through seasonal sickness, broken health and psycho-somatic downfall. Sometimes, poverty has not been the only factor for malnutrition. The other factors for malnutrition can be our wrong belief system, superstition, wrong food habit, and unscientific cooking process. With this background the objectives of the studyhave been spelt out.