eChapters

Revolutionizing skin cancer detection
The diagnostic process for skin cancer is evolving. Physicians have in the past relied upon physical exams to be followed by scanning and biopsies taking anywhere between 15 days to return results. Although most abnormalities turn out to be non-cancerous, this is distressing to patients and contributes to healthcare costs. Additionally, certain growths that turn out to be cancerous remain undiagnosed since they have not been visible.
Breakthrough startup Damae Medical is set to reverse this process. The startup has developed an advanced probe that is able to take 3D images of the skin to unveil the full extent of abnormalities in real time. This enables doctors to diagnose in an instant, enabling improved personalized treatment. When an operation is required only diseased tissue is removed to prevent unnecessary treatments and improved outcomes in patients.
The Origins in the Institut d’Optique
The beginnings of Damae Medical can be traced to Palaiseau-based Institut d’Optique where in 2013 two photonics students envisaged potential in an emerging imaging tech. Together with the inventor himself in 2014, they cofounded Damae Medical by taking an exclusive license to the core family of patents held by three partner institutions. While this contract was beneficial in launching the company to an early growth spurt, in the long run created difficulty in exercising control. This was resolved by taking an equity-forcontrol purchase in 2019 by Damae to acquire the foundational patent

AI-enabled livestock technologies can improve productivity, health monitoring, animal welfare and environmental performance, but they also raise significant ethical and governance concerns. This chapter examines data ownership, privacy, algorithmic bias, transparency, accountability, cybersecurity, socioeconomic inequality and animal well-being. Precision livestock systems continuously monitor animals through sensors, computer vision, machine learning and IoT networks, enabling preventive decisions and automated interventions. However, excessive dependence on algorithms may reduce human oversight and treat animals merely as data-producing units. The chapter advocates an interdisciplinary framework for responsible AI that aligns innovation with animal-welfare standards, farmer interests, social values, equitable access, regulatory requirements and long-term environmental sustainability.

The Context

A series of interventions initiated in mid-1960s that led to the green revolution in cereal production transformed the country from a situation of food def iciency to self sufficiency. The green revolution was however, restricted to productivity improvements in cereals especially wheat and rice in the initial decades, primarily grown in irrigated regions. In subsequent decades, productivity increased in other crops, namely oilseeds, sugarcane, cotton, fruits and vegetables. The Green Revolution generally by passed India’s vast rain fed tracts, especially arid zones, hill and mountain ecosystems and coastal regions, thus exacerbating agro-ecological and economic disparities. Although self sufficiency was attained in food grain production, potential of different crop varieties are yet to be attained. The main features of the green revolution were:

• exclusive focus on food grains

• intensive use of water, fertilizer and pesticides to maximize yields from High Yielding Varieties (HYVs)

• practically no focus on sustainability issues

• benefited the resource-rich and large farmers and

• dependent on few technological options focusing on hybrids, changes in plant architecture.

SYNOPSIS

Nature produces plants with healing properties. Hundreds of phytochemicals and antioxidants have been identified in various food plants. Many plants or plant parts are eaten as food. There are several plant species which are cultivated for food, and many have several distinct cultivars. Seeds of plants are a good source of food for animals, including humans, because they contain the nutrients necessary for the plant’s initial growth, including many healthful fats, such as Omega fats. In fact, the majority of foods consumed by human beings are seed-based foods.

SYNOPSIS

Many plants or plant parts are eaten as food. In addition to essential vitamins, minerals, and fibers, plant foods contain phytochemicals and antioxidants, which actively provide protection against diseases. Several studies carried out all over the world have demonstrated the protective values of fruits. Fruits are the ripened ovaries of plants, including the seeds within. Many plants have evolved fruits that are attractive as a food source to animals, so that animals will eat the fruits and excrete the seeds some distance away.

Raster transformations involve mathematical manipulation of raster layers to generate new raster images. These transformed raster images either contain the information of interest or highlight the features which are not discernible in the original image. Transformations are also performed to preserve the essential information in reduced number of dimensions or layers. In this chapter, we are going to discuss few most commonly used transformation tools listed below:

Concept and Meaning of Empowerment Meaning and definition

Women empowerment has been widely recognized as an important goal in global development process. The term “empowerment” was coined in the second half of the seventeenth century (Oxford English Dictionary). It gained momentum in USA in 1960s when the activists of Black Panat Movement used the term ‘empowerment’ in the context of political mobilization. In 1980s the term was adopted by NGOs worldwide to signify an alternative development agenda for poverty alleviation based on principles of participation and self help. During this period, the participation and self help came to forefront. There after it has entered many fields of theory and practice. Since 1980s, the world has witnessed the concept, used to describe this phenomenon (empowerment).

The voiceless and powerless are the common elements that need the concept of empowerment in terms of socio-economic, technological, cultural and political development. In the context of power, empowerment depends on two things. These are: power can change and power can extend. The concept came to exist that power can change and power can extend giving the term ‘empowerment’ as the power is created in relationship, power and power relationship can certainly change. Therefore, empowerment simply is a process of change.

This chapter reports the analysis of the data collected from Phase One and Phase Two of the research .The chapter is organized in three sections. The first section presents the analysis of the data collected in the first phase through the administration of the survey questionnaire (Appendix-I). It deals with a study of the potential of Internet as a communication tool through an account of the Internet usage habits of the two cities followed by a presentation of their perception, attitudes and internet adoption among the people.

5.1 Basics of Writing

Writing news stories involves a specific set of guidelines and practices to ensure accuracy, clarity, and effective communication.

• Writing News Stories

A methodical approach is necessary when writing news articles in order to provide accurate, educational, and captivating information.

This chapter deals with the findings of the study along with the discussion based on the analysis. This study tried to represent its findings as per the objectives of the study. At the end of this chapter, interrelation has been made, explanation has been tried to put out down and attempt has been done to reveal the cause behind it. The results and their pertaining discussion are presented according to the specific objectives of the study.

This table 6.1 presents the distribution of 15 independent variables (x1-x15 ) in terms of their Minimum, Maximum, Mean, Variance, Standard deviation, and Coefficient of variation.

INTRODUCTION

Bangladesh is a very small country of 1,47,570 square kilometer area having a population of 150 millions. The country has only 8.29 million hectare (Bangladesh Krishi Diary, 2003) cultivable land against the huge population. The land area is gradually decreasing because of population growth, industrialization and other infrastructure development. This results in a declining trend of per capita land availability from 0.13 hectare to 0.06 hectare during the last few decades (1960 to 2000) (Food and Agriculture Organisation, Bangladesh Country Profile).

In order to ensure food security of this vast population and with the emergence of “Green Revolution” in 1960s, priority was given to produce more food in terms of grain through intensification of land usage. New crop variety (HYV), chemical fertilizers, pesticides and irrigation were introduced. As a result, immediate objective of more grain (rice) production had increased and Bangladesh had temporarily achieved self sufficiency in food (rice). Bangladesh made steady progress in crop agriculture in the post-independent period. Cropping intensity increased from 148 to 179 per cent and food grain production almost doubled during the period from 1969/70 to 1992/93 (Hoque, 2007).

However, a lot of HYVs, hybrids, which were introduced, required increased amount of chemicals, and over time they took a toll on the fertility of soil, gradually decreasing acreage production despite usage of high doses of chemical fertilizer and pesticides. Moreover, the natural disasters such as floods, droughts, etc., continued to result in fluctuation in production. Wide fluctuations in production led to large instability in food grain prices having serious implications for household food security and the welfare of the people. The attainment of food security and rural economic development, therefore, could no longer rely on the production of rice alone.

1. INTRODUCTION

1.1. The Agriculture Sector of Zimbabwe

Zimbabwe has a total area of 390 580 square kilometers of which one per cent is made up of rivers and lakes, 38 per cent is arable land and the rest is suited for livestock and wildlife production. The country is bordered by South Africa, Botswana, Namibia, Zambia and Mozambique. It is located between latitudes 15,30 and 22,30 degrees south of the Equator and between longitudes 25 and 33,10 degrees east of the Greenwich Meridian (CSO, 2006).

The Agriculture sector forms the backbone of Zimbabwe’s economy and accounts for about 17 per cent of the GDP. Zimbabwe‘s agricultural sector comprises mostly smallholder farmers who include communal, resettlement and small-scale farmers. However, this sector is besieged by a plethora of issues, namely high stocking rates, sub-optimal climate, and deforestation and land degradation. The Land Reform and Resettlement Programme which commenced in 1980 resulted in hundreds of thousands of Zimbabweans being resettled on former white commercial farms, in either Model A1(communally owned) or A2 schemes (large scale commercial farms). Thus the challenge to policy makers was now to ensure that future agricultural production is not compromised by current practices. The new farming sector largely comprises resource poor farmers, academics, corporate leaders, high-level policy makers and traditional farmers. Most of the new farmers lack requisite Agricultural skills and knowledge needed in modern Agricultural practice. Land reform measures led to the exodus of some white farmers in the beginning of the 21st century which crippled the economy depriving it of technological know-how and causing shortages of basic commodities.

The modernization of agriculture therefore, among other intervention strategies, through the use of ICTs can contribute directly to food security at national and household levels, beneficiation of agricultural produce, effective land management and an increase of national wealth.

Abstract

The field of bioinformatics emerged as a tool to facilitate biological discoveries more than 10 years ago. Structure prediction is fundamentally different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Structure prediction is fundamentally different from the inverse problem of protein design. While the genome of many organism have been sequenced over the last few year, transforming such raw sequence data into knowledge remains a hard task. A great number of prediction program for genes have been developed hat try to address this problem, which consists of locating the genes along a genome.

Abstract

Agriculture, which was once a livelihood for millions, is now turning into a not -so-profitable occupation. The interest has reduced especially among the youth because of its input intensive nature. Among all other  things, the most important input in profitable and sustainable agriculture is timely information. However, with the increasing value of the ratio of farmers to extension personnel, getting timely information is a challenge. Then again, rationally used, we are surrounded by communication devices and the most essential and affordable of all are mobile phones. They have made communication easier, faster, affordable and profitable. The boom in mobile based agro-advisory services in the developing countries around the world has found its own subscriber base among the bottom of the pyramid farmers in rural areas and has been developing their economic conditions. Their services range from crop information, market price alerts to holistic agricultural information which are available free of cost and under subscription.

Introduction

Today we are part of a highly complex and dynamic society. The complexity and dynamism are primarily due to the chain of changes induced by the scientific and industrial developments. The impetus provided by the information explosion coupled with scientific and technological developments to human life has triggered several unimaginable developments in the number, structure and functions of formal organizations. Realization of the supremacy of human mind over the tangible and exhaustible organizational resources like money, material and machine has led to the concept of ‘human capital’, which is now being considered as the most critical organizational resource to ensure organizational effectiveness and efficiency. Analogously huge investments are going in towards servicing and developing this critical resource of human capital in organizations. In this context, the concepts of human resource development (HRD) and training assume greater significance. In fact, training has been considered as a potential tool for HRD since ages. However, as a distinct profession, and also as a critical management tool, training is still in its early years. At the same time, there have been significant changes in the way training is conceived, understood and practiced.

Agricultural colleges and universities were first formed in the belief that farm production could be increased as a result of the systematic application of current technology and agricultural research findings. The mission of these early educational institutions was to scientifically study agriculture with the participation of the farming community; to carry the results to a broad range of farmers who could use them; and to train farmers, extension workers, agricultural teachers and researchers so that agricultural production could continue to be increased on a sustained basis. In many of the developing countries, agricultural education and training have failed to adapt and respond to the realities of rural societies. In response to the urgent need to review and adjust teaching and training in agriculture at all levels. The training is an important tool to overcome the problem faced by the rural people all over the world. The availability of the resource is the crucial determining factors to strengthen the training Programme for the needy people.

Maps make it easier to interpret and communicate the results of any GIS analysis. R has a large number of packages for making thematic maps. Static mapping is straightforward with plot()methods provided by core spatial packages sf and raster. The use of plot() function have been discussed in the previous chapters. Another package for mapping isspwithspplot() having enough options for producing good quality thematic maps.It is also possible to create advanced maps using ggplot2. This chapter discusses, separately, preparing thematic maps from vectors and rasters with the above mentioned packages. A dedicated map-making package tmaphas been given special focus in this chapter.

This chapter focuses on presenting empirical findings from data analysis to provide sufficient interpretation so to draw reliable conclusions. To enhance and complement the textual contents of the study, tables and models are frequently utilized. Additionally, the discussion serves to contextualize the study’s findings and establish connections with the research work.

The pattern of distribution of the variable, Education (x2 ) depicts that the maximum education of the respondents is 5 and the minimum is 2. The mean value of education of the respondents is 4.09 with standard deviation of 0.82. The Coefficient of Variation is 19.96 per cent which indicates the distribution of variable is highly consistent.

the maximum functional education of the respondents is 15 and the minimum is 2. The mean value of functional education of the respondents is 8.27 with standard deviation of 3.39. The distribution of the variable is fairly consistent with a CV value of 41.06 per cent.

The pattern of distribution of the variable, Size of family (x4 ) depicts that the maximum size of family of the respondents is 9 and the minimum is 3. The mean value of size of family of the respondents is 5.62 with standard deviation of 1.48. The Coefficient of Variation is 26.34 per cent which indicates the distribution of variable is fairly consistent.

The pattern of distribution of the variable, Cultivated Land Holding per capita (x5 ) depicts that the maximum cultivated land holding of the respondents is 1.92 and the minimum is 0.25. The mean value of cultivated land holding of the respondents is 0.77 with standard deviation of 0.30. The distribution of the variable is fairly consistent with a CV value of 38.83 per cent.

the maximum no. of land fragment of the respondents is 2 and the minimum is 1. The mean value of no. of land fragment of the respondents is 1.24 with standard deviation of 0.43. The Coefficient of Variation is 34.73 per cent which indicates the distribution of variable is fairly consistent.

The pattern of distribution of the variable, Avg. size of land fragment (x7 ) depicts that the maximum avg. size of land fragment of the respondents is 1.25 and the minimum is 0.25. The mean value of avg. size of land fragment of the respondents is 0.64 with standard deviation of 0.19. The distribution of the variable is fairly consistent with a CV value of 30.18 per cent.

Results and Discussion:

Concept Result is the outcome, consequences or conclusion of a problem, probe or experiment organized after a period of time. This conclusion can be one result, multiple results or no result as such. The length of time taken to find a result can vary from less than a second to many years. In this chapter the result of the Research has been elaborated and also discussed later.

The purpose of the discussion/revelation is to interpret and describe the significance of our findings in light of what was already known about the research problem being investigated, and to explain any new understanding or insights about the problem, after we have taken the findings into consideration. The discussion will always connect to the introduction by way of the research questions or hypothesis we posed and the literature we reviewed, but it does not simply repeat or rearrange the introduction and the discussion always explain how our study has moved towards the research problem.

This table presents the distribution of 19 independent variables(x1-x19) and 6 dependent variables (y1-y6) in terms of their Minimum, Maximum, Mean, Variance, Standard deviation, and Coefficient of variation.

Here, it is depicted that the average age (x1) of the respondents is 50.307. The C.V. value for the variable is 18.521. So, it indicates that the distribution of the variable is highly consistent.

From the table it is depicted that the average education (x2) of the respondents is 7.600. So, almost on an average the individual education is 8 for every respondent. The C.V. value for the variable is 41.553. So, it indicates that the distribution of the variable is fairly consistent.

7.1 Introduction
The preceding chapters have detailed the myriad ways in which meteorological data is collected, from direct in situ observations to various ground-based and space-borne remote sensing platforms. We have also explored the crucial aspects of data formatting, storage, and retrieval, recognizing the immense volume and diversity of atmospheric information. However, the journey from raw measurement to actionable insight is not complete without a critical intermediate step: data quality control (QC) and preprocessing. No observational system, regardless of its sophistication, is entirely free from errors, biases, or inconsistencies. Sensors can drift, communication links can suffer interference, environmental factors can contaminate readings, and automated systems can malfunction. Consequently, raw meteorological data often contains spurious values, missing records, or systematic biases that, if left unaddressed, can severely compromise the accuracy of weather forecasts, the reliability of climate analyses, and the validity of scientific research.
This chapter will delve into the essential processes of quality control, which involves rigorously identifying, flagging, and, where appropriate, correcting or removing erroneous data points. We will explore various automated and manual techniques employed to ensure the integrity and reliability of meteorological observations. Furthermore, we will examine preprocessing steps, which prepare the quality-controlled data for its intended use, including tasks such as unit conversions, interpolation to common grids, and handling of missing values. By understanding the meticulous procedures involved in data
quality control and preprocessing, we gain a profound appreciation for how raw atmospheric signals are transformed into the trustworthy information that underpins all of modern meteorology.

Introduction
Having meticulously explored the foundations of crop-weather interactions, the development and validation of crop growth models, the wisdom embedded in Indigenous Technical Knowledge, and the systematic organization of Crop Weather Calendars, we now arrive at the culmination of this knowledge synthesis: the Agroadvisory Based on Weather Forecast. This chapter delves into the critical process of transforming raw meteorological data and scientific understanding into actionable, timely, and location-specific advice for the farming community. An agroadvisory, at its core, is a targeted recommendation provided to farmers, guiding them on various agricultural operations by integrating current weather conditions, short- to medium-range weather forecasts, and the specific needs of their crops at different growth stages. It represents the final, practical output of complex agro-meteorological research and forecasting efforts, designed to empower farmers to make adaptive decisions that can significantly impact their yield, resource efficiency, and resilience against climatic shocks. In the upcoming sections, we will comprehensively examine the multi-faceted nature of weather-based agroadvisories. Our exploration will detail:
• The Conceptual Framework: Understanding the underlying principles and objectives of these advisories, emphasizing their shift from reactive responses to proactive planning.
• Essential Components of an Agroadvisory: Breaking down the key pieces of information typically included, such as weather forecasts (temperature, rainfall, wind, humidity), crop-specific phenological stages, potential risks (pests, diseases, extreme weather), and precise recommendations for farm operations (sowing, irrigation, fertilization, pest control, harvesting).

• Definition of Bioinformatics
• History of Bioinformatics 
• Structural Bioinformatics
• New Branch of Bioinformatics 
• Bioinformatics - Application in Agriculture
• Analyzing Protein Sequence
• Pairwise Alignment
• Multiple Alignment
• Blast - A Sequence Alignment Tool
• EMBL
• SWISS–PROT
• Rice Genome Project
• Software for Bio-informatics
• Major Categories of Bioinformatics Software
• Internet Sites For Bioinformatics

1. INTRODUCTION

This chapter looks at ICTs in Sub-Saharan Africa (SSA), with a focus on several selected countries in the region. Exciting and positive developments are happening throughout SSA Africa in ICTs. For instance, in spite of extensive poverty, SSA has had the fastest growing mobile market in the world over the last five years. The mobile telephone in the region has morphed to serve uniquely African development needs, including those in rural areas. It is being used for market information, extension messages and as virtual currency. In Kenya and Uganda, mobile phone services provide cheap messages about crop price information via text messaging. In Tanzania, there are ‘market spies’, farmers who visit local markets and remain in contact with the village using mobile phones to negotiate for better prices.

In spite of the growing use of mobile telephony and other ICTs, Africa has lagged behind in harnessing ICT potential for extension and other rural development issues in comparison to countries such as China, India, and Chile. Sub-Saharan Africa has the lowest teledensity in the world (Bertolini, 2006a). Many challenges exist to ICT use in SSA, and there are concerns that many rural African communities are being further left behind through the ‘digital divide’.

8.1. INTRODUCTION

The existence of Science could be in danger, if scientists did not record experiment performed, data collected and resuit obtained. Scientific writing doesn't mean to only keep records of progress and information, but to actually publish the results of studies in scientific journals. While keeping records is quite easy to do, publishing scientific papers can be really difficult, and especially for young researchers who are just starting to discover the world of scientific publications. A scientific writing is a method of communication, an attempt to tell others about some specific data that you have gathered and what you think those data mean in the context of your research. The rules of writing a scientific paper are rigid and are différent Uorr\ those that apply when we write an English theme. Scientific paper must be written clearly and concisely so that readers with backgrounds similar to yours can understand easily what you have done and how you have done it. The ultimate aim of most scientists is to publish their research findings in professional scientific reports. This includes peer-reviewed journal articles, which report original findings and contribute to the global pool of scientific knowledge. Scientists spend their time writing proposais, planning research, undertaking experiments, analysing data, tracing research, and reading related articles. Published reports and journal articles provide evidence of this dedication. Therefore, a scientific report is not simply some extra work that is done at the end of a project; it is an important historical document that provides evidence of work to the wider scientific community.

Farm Innovation and Promotion Fund (FIPF)
Introduction
Many innovative initiatives are being attempted by various agencies in the Held of Agriculture and allied sectors. To support these innovations, NABARD has decided to set up a fund titled “Farm Innovation and Promotion Fund” (FIPF).

Initial Corpus of Fund
Rs. 5 crore (2004-05).

Objectives of the Fund
The objective of the Fund is to support the activities listed below : 
        To demonstrate bankability of new concepts in farm sector
        To develop prototypes for further commercial development
        To support activities connected with market survey for potential assessment/market acceptability for new agri/rural products

3.1. Introduction

This chapter intends to examine the economic importance of cotton, turmeric and castor seed in the agricultural economy of Odisha. Given the fact that Odisha is one of the major producing states of the country for these three crops, their physical markets have national level relevance in terms of determining prices. The chapter presents a brief profile of the agricultural economy of Odisha with a focus on these three crops and their supply conditions including cropping season, pattern, area under cultivation and productivity. Secondly, it tries to investigate the market structure, supply chain and marketing practices in cotton, turmeric and castor seed based on the data obtained from the secondary sources.

Indian economy is agro-based and agriculture is its mainstay as it constitutes the backbone of the rural livelihood security system. Agriculture has been and still continues to be the life line of the Indian economy since economic security is essentially predicted upon the agricultural and allied sectors. The agriculture sector encompasses crop production, animal husbandry, fisheries, agri-business, etc. Crop production depends upon crucial inputs such as good seeds, fertilizers, pesticides, irrigation, human labour, machinery and management.

As the largest private enterprise in India, agriculture supports more than 60% of the population, contributes nearly 19% to India’s Gross Domestic Product (GDP) and 11% to the total exports. Around 51% of the geographical area in India is already under cultivation as compared to 11% of the world average¹. Agriculture is also a social sector where non-trading concerns like food and nutritional security, employment and income generation, poverty alleviation, ecological and environmental concerns play a significant role.

1. Introduction

Sustainability embodies an ecological vision aimed at fostering enduring human coexistence on Earth. Over time, its definition has evolved in literature and context, generating ongoing debate. Generally, experts frame sustainability around three pillars: social, economic, and environmental. While environmental concerns often dominate discussions, sustainability encompasses broader challenges like pollution, land degradation, biodiversity loss, climate change, and ecosystem service decline. This concept influences decision-making globally, politically, and personally.

Sustainable development, often used interchangeably with sustainability, is distinguished by UNESCO as a long-term objective versus the diverse processes and pathways to achieve it. Within the economic dimension, the tension between welfare and environmental preservation is explored through concepts like “weak and strong sustainability,” acknowledging the necessity of trade-offs. Ideal policies would aim to decouple environmental degradation from economic growth.

Environmental sustainability is pursued through various means such as ecosystem preservation, collaborative resource management, reducing food waste, advocating plant-based diets, managing fertility rates to curb population growth, and transitioning away from fossil fuels towards clean energy and innovative green technologies.

1. Introduction

The agricultural sector plays a pivotal role in driving economic development in India, a nation with a population of 1.39 billion, making it the world’s second most populous country according to the United Nations’ World Population Prospects 2019. With 54.6 percent of the workforce engaged in agriculture as per the 2011 Census, and contributing 18.6 percent to the Gross Value Added (GVA) in 2021-22, its significance cannot be overstated. Notably, women play a substantial role in this sector, with rural females exhibiting a higher workforce participation rate of 41.8 percent compared to 35.31 percent for urban women (MoSPI, 2017). In rural communities, agriculture and allied sector is the primary source of livelihood that includes 80 percent of all economically active women, out of which 33 percent constitute agricultural labour force and 48 percent are self-employed farmers. Rural women are engaged at all levels of the agricultural value chain; i.e., production- pre-harvest, post-harvest, processing, packaging, marketing to increase productivity in agriculture (Nilam Patel etal, 2022). As per Pingali et al. (2019), the ratio of women to men working in the agricultural sector has increased over the time and made a greater amount of contribution to GDP per capita. They are the momentous demographic group for a sustainable food system (FAO, 2011). Empowering women in agriculture through reforms aimed at ensuring equal access to resources, skill development, and opportunities is projected to increase agricultural output in developing countries by 2.5 to 4 percent (FAO, 2011).

Reduced price volatility and stability for the market are generally a result of increased yield of crop(x12) when supply is more balanced. By providing higher yields, an increase in product delivery can be had, thereby delivering a more sustainable and predictable source that helps to keep supply and demand balanced. This lowers market volatility, creates a more stable pricing environment and reduces risk for both producers (and end buyers). Elevated or variable farming expenses or cost of cultivation(x13) may contribute to market uncertainty by impacting farmers’ earnings and shaping their choices on yield. Unpredictable expenses make it challenging to project financial results, which causes pricing volatility and inconsistent supply levels. This pricing and production volatility adds to the general unpredictability of the market.
A rise in on-farm income(x14) gives farmers greater financial stability and resources, which enables them to better manage risks and schedule production for the future. An agricultural product supply that is more predictable is facilitated by this consistency. As a result, lesser income volatility corresponds to lower overall market uncertainty and steadier prices.

Climate Smart Agriculture (CSA) is an integrated approach to managing landscapes—cropland, livestock, forests, and fisheries—to address the interlinked challenges of food security, climate change adaptation, and mitigation [FAO, 2023]. In the context of the Centre on Integrated Rural Development for Asia and the Pacific (CIRDAP) Member Countries, which span diverse agro- ecological and socio-economic landscapes across South Asia, Southeast Asia, and the Pacific, CSA emerges as a pivotal strategy for fostering climate- resilient rural development [CIRDAP, 2023]. These countries, including Bangladesh, India, Indonesia, Pakistan, Vietnam, and others, face significant climate vulnerabilities such as rising temperatures, erratic rainfall, extreme weather events, and sea-level rise [IPCC, 2022]. CSA offers a framework to enhance agricultural productivity, strengthen resilience, and reduce greenhouse gas emissions, aligning with the region's Sustainable Development Goals (SDGs) and rural livelihoods improvement [UN, 2023]. The contribution of agricultural GHG emissions

4H: An agricultural club for children that features hands-on learning

Abiota: The nonliving component of an ecosystem, including the soil, water,

and air.

Aborigines: The original or native inhabitants of a country or region.

Absorption Losses: Loss of water from a canal or a reservoir by capillary

action and percolation and in case of canal during the process of delivery.

Absorptive capacity: The maximum amount of waste that can be absorbed

by the environment.

Acclimation: Adaptation to changing or new conditions.

Acid precipitation: Rain, snow, fog, or dew containing sulfuric and nitric acids

produced by fossil fuel combustion.

Acid soil: A soil which is deficient in available bases, particularly Ca and which

give an acid reaction when tested by a standard method.

Acre foot water: The amount of water that would cover an area of land to a

depth of one foot assuming no seepage evaporation and run off.

Acre inch day: Term used principally in irrigated section of united state for

measuring quantity of flow of water. It is equal to a flow which will cover

one acre to a depth of one inch in a 24 hours period or 0.042 cubic feet per

second.

Acre inch: It is a measure of quantity of flow of water and is equal to the flow

which will cover one acre to a depth of one inch.

Acre: (43560 sq. ft) an area of land about 220 feet long and 198 feet wide.

Active solar heating: The use of solar panels to collect and concentrate the

sun’s energy for heating.

Adaptation: Biological modification that allows species to better exist in a

specific environment.

Additives: Chemicals added to food, often con- sidered to represent a threat

to human health.

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

In the context of a thesis, theoretical orientation refers to the conceptual or theoretical framework or perspective that informs and shapes the overall approach and analysis of the research (Natalie, 2022). It involves selecting and adopting a specific set of theories, concepts, or models that provide a foundation for understanding and interpreting the research topic. The theoretical orientation helps to guide the methodology, and provide a coherent framework for organizing and analysing the data.

Theoretical orientation in a thesis serves several purposes. It helps to establish a theoretical basis for the study, providing a context for the research and connecting it to existing knowledge and theories in the field. It also helps to guide the selection of appropriate research methods and data analysis techniques. The theoretical orientation shapes the overall structure and content of the thesis, ensuring that the study is grounded in relevant theories and concepts and contributes to the existing body of knowledge. By adopting a specific theoretical orientation, the researcher can provide a clear and systematic framework for understanding and interpreting the findings of the study. This orientation also helps to establish credibility and validity for the research, as it demonstrates the researcher’s awareness of and engagement with the existing theoretical perspectives in the field.

This chapter addresses crucial terminology and concepts essential for effectively communicating the ideas of the current study. It lays the groundwork for empirical investigation and aids in the selection of predictor variables. Additionally, this section involves a scholarly and theoretical exercise that influences the operational definition and content of the research. It combines conceptual inputs, axiomatic inputs, logical discussions, and the pursuit of knowledge to construct a theory that aligns with the research objectives and designs.

Policy influence requires credible evidence, a clear understanding of decision-making processes and communication tailored to relevant audiences. This chapter explains how extension research, programme experience and stakeholder knowledge can be converted into evidence for policy change. It discusses identifying policy problems, assessing alternatives, setting advocacy objectives, recognizing policy champions, building coalitions and selecting appropriate routes of influence. Policy briefs, research reports, dialogue platforms, advisory committees, social media and ICT-based communication are examined as practical tools. The chapter also reviews global extension-policy experiences, helping readers understand how institutional, political and socioeconomic contexts shape policy decisions and how evidence-based engagement can support effective agricultural reforms.

Abstract

The chapter examines the relationship between the agricultural value chain and mobile apps. Using email survey data from mobile app developers, supplemented with basic desk research, the chapter reviews and analyzes 55 mobile apps based on their location within the value chain, the format of content delivery, the types of device used, the stage of deployment as of  2012, the type of business model used, and the geographic focus of the app. The analysis generally reveals an even distribution of apps within the three main components of the agricultural value chain but when it comes to the sub-categories within the agricultural value chain, skewed distribution was observed. Feature phones remain the dominant device for delivering agricultural information to users, however, increasing number of smartphone-specific applications gaining market. Most of the devices use text format for content delivery with voice, image and video as supplements.

1.1 Background

The whole world is characterized by diverse cultures, different approaches to life, divergent outlooks and world views and dissimilar living conditions and environments. The people in it live with cultural, social, economic and educational dissimilarities, differences, inequalities, and goals. Despite the disparities in everything, the whole world is unified by Information, Communication and Technology through the global media culture, technocapitalism, and information revolution. Gone are the days when people confined themselves to their hearths, farms, educational institutions and places of work, managing their lives with basic minimum requirements and needs! 

The provided table displays the distribution characteristics of seven dependent variables (y1-y6 ) and 18 independent variables (x1-x18 ). It includes their minimum, maximum, mean, variance, standard deviation, and coefficient of variation.

In terms of the respondents' average age (x1 ), the graph indicates a value of 48.17, which suggests a highly consistent distribution with a coefficient of variation (C.V.) of 19.24.

Similarly, the table reveals that the respondents' average level of education (x2 ) is 7.02, indicating an average education duration of around seven years per respondent. The variable demonstrates a fairly consistent distribution with a C.V. of 41.72.

Examining the respondents' average years of business experience (x3 ), the table indicates a mean value of 21.05. This implies a similar level of business experience across most respondents, with a fairly consistent distribution and a C.V. of 47.54.

Regarding the typical family size (x4 ), the table shows an average value of 3.92, indicating an approximate average family size of four. The distribution of this variable is also fairly consistent, with a C.V. of 37.21. The mean family education (x5 ) of the respondents is reported as 2.58, which corresponds to an average education level of 3 for the families. The variable exhibits a fairly consistent distribution, with a C.V. of 38.14.

Soil is a loose surface material that provides water, nutrients, and structural support to agricultural plants. It is made up of 45% minerals, 5% organic components, 25% air, and 25% water. Our soils are said to be the source of 95% of the food we eat, either directly or indirectly.

The basis of the food chain is healthy soil. Our soils are the foundation of agriculture and the growing media for almost all plants that provide food. Good crops come from good soils, and healthy crops feed people and other animals. Food quantity and quality are, in fact, closely related to soil quality.

A healthy soil is a dynamic, living ecosystem. It is packed with both microscopic and larger organisms that carry out a multitude of essential tasks, such as nutrient cycling—the process of turning dead and decaying matter and minerals into plant nutrients controlling plant diseases and insect and weed pests, enhancing soil structure, which has a positive impact on the soil's ability to hold water and nutrients, and ultimately increasing crop productivity. Because healthy soil retains or increases its carbon content, it also helps to mitigate climate change.

9.1 Introduction
Building upon our foundational understanding of statistical methods in meteorology, Chapter 9, “Advanced Analytic Techniques,” propels us into the forefront of data science applications within the atmospheric sciences. The imperative for these advanced methodologies stems directly from the evolving nature of meteorological data itself. Modern observations, numerical weather prediction (NWP) model outputs, and climate simulations generate an unprecedented volume of information, often arriving with incredible velocity and exhibiting immense variety in format and structure. Traditional statistical approaches, while robust for many tasks, often struggle to efficiently process such vast, high-dimensional datasets, or to fully capture the intricate, often non-linear, relationships inherent in atmospheric processes.
This chapter is dedicated to exploring why and how these sophisticated techniques are not merely supplementary, but increasingly essential. We will delve into how machine learning and deep learning algorithms excel at identifying subtle, complex patterns within massive datasets, enabling breakthroughs in areas like severe weather detection, nowcasting, and the bias correction of model outputs. We will also examine advanced spatial statistics, which provide powerful frameworks for explicitly modeling the intricate geographical dependencies of meteorological variables, crucial for accurate interpolation, downscaling, and understanding regional climate impacts. Furthermore, the chapter will introduce functional data analysis, a method particularly adept at treating continuous meteorological fields (like temperature profiles or pressure maps) as functions, allowing for a more holistic analysis of their evolution and variability. By embracing these advanced analytical techniques, meteorologists and climate scientists can unlock deeper insights, enhance predictive skill, more rigorously quantify uncertainties, and ultimately contribute to a more resilient society in the face of a changing climate. Prepare to expand your analytical toolkit and discover new frontiers in meteorological understanding.

The transition from an agrarian society to a more advanced and diversified economy represents a profound shift in how societies function and evolve. Initially, agrarian societies are primarily centered around agriculture, with the majority of the population engaged in farming and related activities. As agricultural productivity improves through technological innovations, such as advanced machinery and crop varieties, these societies begin to experience economic growth. This growth often spurs industrialization, leading to the establishment of manufacturing sectors that create new job opportunities and drive urbanization. Cities expand as people migrate from rural areas in search of better employment prospects, leading to significant social changes. Education and skill development become crucial, as improved literacy rates and vocational training prepare individuals for diverse professions beyond agriculture. The transition from an agrarian society to a more advanced and diversified economy marks a profound shift in societal functioning and evolution, encompassing multiple dimensions that can be examined through various disciplinary lenses. Economically, this transformation begins with improvements in agricultural productivity, driven by technological innovations such as advanced machinery and high-yield crop varieties. These enhancements not only increase agricultural output but also reduce the labour required for farming, thereby freeing up labour for other sectors. This shift often triggers economic growth, which spurs industrialization. As manufacturing sectors develop, they create new job opportunities, driving urbanization as individuals migrate from rural areas to cities in search of better employment prospects. This economic expansion is central to understanding the broader changes that occur as societies evolve from agrarian to industrial and post-industrial economies.
From a sociological perspective, the transition to a diversified economy leads to significant social changes. Urbanization alters family structures, social networks, and community dynamics. As people move to urban areas, traditional agrarian values give way to new social norms and practices associated with city life. Education and skill development become critical, as improved literacy rates and vocational training prepare individuals for diverse

The functioning of the Women Dairy Cooperative Societies depends upon the variations in managerial capacity leading to profit and loss of different WDCS. To make an in-depth analysis, the study was undertaken in undivided Cuttack and Dhenkanal district of Odisha covering 22 randomized WDCS with a sample of 110 women respondents.

The analysis of the findings after statistical treatment have been presented objective-wise as follows;

Socio-economic profile of the members of WDCS involved in dairy production activities.

Gap between procedures prescribed and followed in formation and functioning of WDCS.

Identification and analysis of key performance areas in the WDCS.

Determination of management practices and milk production profiles of WDCS members.

Extent of participation of women members in dairy activities.

Entrepreneurial characteristics of members of Women Dairy Cooperative Society.

Impact of WDCS on socio-economic status of the members.

Correlating variables and their interrelationship in predicting smooth functioning of WDCS.

Constraints faced by the WDCS members.

Suggestions of members for improvement in functioning of WDCS

The chapter deals with the Results and discussion of the study, whose purpose is to provide sufficient information so as to arrive at a valid conclusion. Tables and Figures are commonly used in this chapter to support and supplement textual materials. Discussion helps to interpret the Results of the study from a proper perspective and to relate them with other relevant studies.

Table 6.1. Descriptive Statistics of Variable with respect to Minimum, Maximum, Mean, Standard Deviation of Values, Variance, and Coefficient of Variance:

Supervised classification is the technique to classify raster image in which prior information about the classes in the form of training sites is provided by the user. Training site represents a homogeneous area in a particular class. The spectral response pattern of training sites is used to classify the raster image.The pixels of raster imagewhich have spectral response pattern similar to that of training sites of a particular class are grouped in that class. As there is some variability in the spectral response pattern of a particular class, therefore, multiple training sites per class are taken for supervised classification. Supervised classification of raster images can be performed by various methods. Conventional methods include maximum likelihood classifier, minimum distance to mean classifier, and parallelepiped classifier. Now a days, machine learning algorithms are also gaining importance in this context. These classifying algorithms are first trained or calibrated using the data of training sites.This trained model is then validated on the independent datasets for accuracy assessment. If the accuracy of the developed model is of acceptable level, then that model is used for the classification of raster data.

In this chapter, we are going to discuss the execution of maximum likelihood classifier and few machine learning techniques for supervised classification of raster image in R software. The training sites used in this exercise are in the form of points shapefile. The raster image is classified into six classesi.e. built- up, fallow soil, riverine sand, salt-affected soil, vegetation, and water. For performing this exercise, first of all,set the working directory and import the required packages.

With increasing food production, availability and accessibility the global agro-industrial food system has improved.However, malnutrition, biodiversity loss and climate change are newer challenges. The best solution to this is the utilization of indigenous and traditional crops which will bring a transformative change in the food system. There is a need to look into the development of smallholder producers. The agro-industrial food system has improved the food supply and has made way for significant trade-offs with agro-biodiversity, dietary diversity, environmental sustainability and socio-economic stability mainly amongst the rural poor. Now is the time to mainstream the underutilized indigenous and traditional crops into the food system. This will provide opportunities to develop a sustainable and healthy food system.It will also help towards the societal goals which include employment creation, wellbeing and environmental sustainability.

5.1 Introduction

This chapter presents analysis of data collected through the questionnaire survey from agriculture libraries in Maharashtra (Constituent including University Libraries i.e. Government and Affiliated i.e. Private colleges). The purpose of the survey was to explore the status of CRS (Cyber Reference Service), various aspects pertaining to the CRS, and the ICT infrastructure used for the CRS in the agriculture universities and college libraries. It also aimed to obtain agriculture library heads’ perceptions about the CRS, and explore issues and problems affecting implementation and management of the CRS in the agriculture libraries in the Maharashtra state.

Introduction

Challenges in agriculture and natural resource management in the past have prompted changes in agricultural education, research, and extension globally. The sustainable development of agriculture in a country largely depends on the effectiveness of its agricultural extension strategies, encompassing approaches, service delivery, methodology, and processes. The desired outcome of agricultural development is farmers’ outcomes, achievable through engagement, learning, and participation in research and extension processes. Agricultural extension played a significant role in the green revolution by providing farming communities with appropriate technologies and optimal cropping practices. This helped countries transition from being food deficit to food exporting (Ratnakar, 2016). Additionally, extension services play a crucial role in expanding knowledge, skills, and attitudes about the management of socio-economic-agricultural practices by understanding the existing techno political ecosystem and exploring a basket of technology alternatives for making informed decisions.

SYNOPSIS

Food is any substance consumed to provide nutritional support for the body. It is usually of plant or animal or fish origin. Plant foods are the most abundant sources of nutrition on earth. Only plants contain powerful substances called phytochemicals, which protect us from cancer, heart disease, and an array of other serious illnesses.

1. INTRODUCTION

1.1. National Agriculture Scenario

Agriculture is the most important sector of Indian Economy, contributes 23 per cent of national GDP, accounts for 11 per cent of exports, and 50 per cent of billion depends on it. Interestingly India feeds 16 per cent of population with 2.4 per cent of global land.

In the last five decades, there has been a steady and spectacular transformation of Indian agriculture from the food deficit to food sufficient status. Diffusion and adoption of modern technologies, high yielding varieties, dedicated efforts of farmers, extension personnel and scientists and also programmatic support of central and state governments have all contributed significantly from 50 million tonnes in 1950-51 to land mark achievement of 230.67 million tonnes of food production in 2008-09.