eChapters

Abstract

Water has become a scarce resource all over the World. Water resources of Earth can be classified as surface water and groundwater in which groundwater is the main source for the drinking, domestic and agriculture. The Pudukkottai district is one of the chronic drought prone areas in Tamil Nadu. But, at the same time, the district is pitted with over 5,400 tanks/water bodies widely distributed throughout in general and clustered more in Vellar delta in particular, as the interlobel depressions have provided basic depressions for the surface water to accumulate. However, these surface water bodies are heavily silted. In Pudukkottai district, there are three divergent aquifer systems, hard rock aquifer system in the western, sedimentary aquifer system constituted by the Tertiary Sandstone (Cuddalore Sandstone) in the central and Quaternary aquifer system constituted by fluvial, fluvio-marine and marine systems in the eastern parts of the district.

Abstract

The major objective of this chapter is to examine how knowledge management initiative can bring competitive edge and help organizations to compete in a knowledge era. People now viewed as being the most valuable asset and ‘people management’ being a pertinent issue in knowledge management, the pivotal role of HR is being increasingly recognized by the organizations in a knowledge economy. The chapter starts with a discussion on the nature of knowledge management, theory, and process and then explores the role of human resource practices in facilitating the KM process in organizations. The author examines how different HRM practices like talent management, performance management, training and development, fostering trust, reward systems, institutionalizing learning systems and leadership can be linked with the knowledge management process to achieve competitive advantage.

Abstract

Scarcity of resources, economic deprivation, gender bias in wages, prevention from decision making and using income generated by farm activities has made life miserable and unjustifiably hard for rural women. The plight of rural women can be improved by dissemination of latest technologies in agriculture, creating small entrepreneurial outlets for agri-based products, networking of support services for women, development of new and adoption of drudgery reducing technologies, improvement in rural infrastructure to improve the life style and to promote entrepreneurial opportunities, better access to resources, organizing women’s co-operative movement, larger role in decision making, mandatory involvement of women in all agencies and organizations involved in rural development, feedback and follow up of women’s programmes and recognizing the success of rural women by government and its highlighting by media.

In rural development, the sole aim is to transfer the technology for better living of people. The process by which the technology is transferred to users is called Transfer of Technology. Transfer of technology falls in the domain of adoption and diffusion. Therefore, it is necessary to understand adoption and its related issues. Adoption of sustainable agricultural practices is relatively difficult as people do not find newness in it. The transfer of technology is explained in terms of technology movement from place of generation to the hands of the users.

OBJECTIVE OF EXTENSION EDUCATION

Objective

Objectives are expression of the ends towards which our efforts are directed.

The objective of extension is to develop the rural people economically, socially and culturaly by means of education. Overall, these objectives are divided into 4 types they are :

a)   Material objective

b)   Educational objective

c)   Social and cultural objective

d)   Developing leadership objective

a) Material objective

According to National Commission on Agriculture (1976). Agriculture extension aims at improving the efficiency of human capital, an effort to rapidly increase the rate of agricultural production. It also seeks to import necessary skill to farmer to understand the improved agricultural operation and improve the their own income, own resource and also the money value.

b) Educational objective

Extension education also aims at development of individual to change in behaviour by identifying their knowledge, skill, attitude and action. It aims at increasing the knowledge of people to analyse their past, present and expected future situation, to become aware of problem identification, solution and also realising their felt and unfelt need.

• Agriculture Database Concepts and Importance
• The Orientation of Topic Selection for the Construction of the Agricultural Database
• The Principle of Specialization in the Construction of the Agricultural Database
• Top Quality Principle of Building Databases
• Agriculture Database Types
• Agriculture Libraries
• Agriculture Journals
• Technical Reports
• Conference Papers
• E-Books in Agriculture

Abstract

Watershed development and management programme appeared to an effective and integrated approach to manage all natural resources like land, water, vegetation, animal and human for sustainable benefit and maintaining balanced eco-system. The main principle of the programme is based on starting from its planning, making design outlay, formulation of technical works, execution and development of land along with creation of water resources developing a hydrological unit at downstream making a common drainage points for the purpose of sustainable development of agriculture. The present case study dealt with the integrated water resources management with specific guidelines to the farmers for clear understanding of installing small-scale irrigation system based on their own resources in accordance with actual land situations as well as judicious use of irrigation with adoption of water-saving technology for sustainable crop production through watershed approach. The work was carried out under National Watershed Development Project for Rainfed Area (NWDPRA), one out of 21 watersheds was identified for development of rainfed agriculture with mobilization of all natural resources like soil-plant-water-animal-human to uplift socio-economic status of the farmers. 

Abstract

Agricultural development in India provides support to a large section of farmers who operate on small holdings and have very limited risk bearing capacity. Farmers are often exposed to natural vagaries, which adversely affect their agricultural production and farm income. Moreover, there is huge financial exclusion in rural sector of the nation. If there is a crop failure, farmers are crushed under the burden of debt. Farmers seek to avoid risk in terms of various managerial and institutional mechanisms. But it is widely believed that ‘Crop Insurance’ is the only institutional mechanism available against production risk in farming. Unfortunately, penetration of crop insurance schemes in India has been low in terms of the area of land insured and the number of farmers covered. There are the problems of low risk awareness and lack of insurance culture among the farmers. In this backdrop, the paper documents the findings of a survey of 140 farmers, which was taken up in some selected villages of North 24 Parganas district of West Bengal. The study shows that likelihood of this awareness increases with increase in landholding size, education level, borrowing history and social participation of the farmers, whereas it decreases with the non-farm income and livestock of the farmers. The author proposes measures to promote and spread awareness of crop insurance among the farmers as a risk mitigation tool in farming, which will increase farm production and stabilize the fluctuation in farm income. The study provides valuable policy measures to the government in better designing of their crop insurance products and will also help the private agro-insurance business, which is recently taking off in the country.

Introduction

India is the largest consumer and second largest producer of sugar in the world next to Brazil. Among the sugar yielding crops like sugarcane, sugar beet, palms and sorghum, sugarcane is the second most important agro-industrial crop of the country. It is the only raw material for nearly 538 sugar mills (2014-15), producing about 28 million mt of sugar annually from a sugarcane production of 366 million tons in an area of 5.307 mh. Apart from this, it is the predominant source of potable alcohol, industrial alcohol and fuel-ethanol. In India, 35 million farmers are engaged in sugarcane cultivation and another 50 million depend on employment generated by these 538 sugar factories and other related industries using sugar. Sugarcane occupies a very prominent position in the agricultural crops of India covering large areas in UP, Punjab, Haryana and Bihar (sub tropical) and Maharashtra, Karnataka, Gujarat and Tamil Nadu (tropical). On an average, white sugar production accounts for 74% of total cane produced, 14-15% is utilized for jaggery and khandsari production and the rest is utilized for other purposes including seed.

Jaggery and khandsari, the traditional Indian sweeteners are the natural mixture of sugar and molasses. If pure clarified sugarcane juice is boiled, what is left as solid is jaggery, which contains 65-85% sucrose. Khandsari sugar is a finely granulated and crystallized which contains 94 to 98% sucrose. In the early 1930’s, nearly 2/3rd of sugarcane production was utilized to manufacture these two alternate sweeteners. With the introduction of sugar mills and their multiple growth and better standard of living and higher per capita income, the demand for sweetener has shifted to white sugar which contains purely sucrose (99.7%).

Introduction

Fish is a source of valuable animal protein and is considered a health food. This has resulted in increased consumer demand. Fish is now more expensive than meat and other animal foods. Being a highly perishable commodity, fish require immediate processing and various options are available for the value addition of fish. Fish processing, particularly seafood processing and marketing have become highly complex and competitive and exporters are trying to process more value added products to increase their profitability. Value can be added to fish and fishery products according to the requirements of different markets. These products range from live fish and shellfish to ready to serve convenience products. In general, value added food products are raw or pre-processed commodities whose value has been increased through the addition of ingredients or processes that make them more attractive to the buyer and/or more readily usable by the consumer.

Introduction

Pulse production in India has fluctuated widely with no long-term trend, leading to a steady decline in per capita availability per day, i.e. from 60.7 grams to 33.40 grams during 1951 to 2001, while its average requirement is about 65 gram per day per head. The pulses used to serve a low cost food to meet the protein requirement of a large sector of people in India. But, the pulses are becoming out of reach for the common people of country because of its continuing shoring prices. A Technology Mission on Pulse production was launched by Government of India in 1986-87 as a special drive to increase the pulse production in the country. The vision of Technology Mission of Pulse is attaining self reliance in pulses for household nutritional security and sustainability of the production system. The mission statement was to increase Pulse production from existing (IX plan) 131.4 lakh tonnes to 162 lakh tonnes; Productivity from 594 kg/ha to 702 kg/ha and per capita availability of pulses from 35 g to 40 g per day at affordable price. Unfortunately, the country has not been able to achieve self-sufficiency in the pulse production. During the last 40 years, the acreage under pulse crops and its production remained almost between 21-24 million hectares and 10-15 million tonnes, respectively. Consequently, the country has had to depend on import of pulses every year to meet the part of its shortage. The National Commission of Agriculture had estimated that the country should plan to produce about 25 million tonnes of pulses by the end of 2000, but we could achieve only about 14 million tonnes. Presently, the area and the production of pulse crops account for about 18.50 and 7.20 per cent (2003-04) of total area under foodgrains and total food grains production in the country, respectively.

Introduction

Research and development (R&D) is one of the main components to tackle the problems persisting or likely to take place in future. Priority areas of research are depending upon the overall situation and requirements of the problem under consideration. Under these broad areas, topic of interest for research may be varying at different geographical level from household to nation or global. If it is addressing vast geographical area like states, nations, regions and/or global, there may be many individuals/groups/institutions are working over similar type of problems. With the growing communication facilities and rising fund requirements, collaborative research programmes emerged to provide effective and economic solution to the problem with respect to time, money and manpower etc. Earlier, it was limited to high priority areas like defense and long run planning of the nations or kingdom at nation or state level. Declining environmental conditions and biological diversity became global concern in seventh decade of twentieth century. To tackle this problem, The United Nations Conference on the Human Environment (Stockholm) resolved to establish the United Nations Environment Programme (UNEP) in 1972. Further, to speed up the progress, global community through world leaders had identified two burning priority areas during conference United Nations (U N) Environmental Programme Rio de Janeiro, Brazil in 1992, well known as Earth Summit. One of those two priority areas was Biological Diversity. To address the issues at global levels, The Convention on Biological Diversity was signed by party nations, which was later ratified by the 187 countries. India is also one of the signatory nations and need to fulfill some time bound commitments. Moreover, later, importance of biodiversity and germplasm has been underlined by different forum at regional and global level for its present and future values in the life of human kind. Countries and various geographical regions are now becoming more and more aware about its judicious exploitation, conservation and sustained higher output over period of time.

Key words : NRSA, Natural Resource and Disaster Management, Agricultural Drought, Ecosystems, Biodiversity Information System, Water Resources, Sea Surface Temperature.

Introduction

A few decades ago, paper maps were the principal means to synthesize and represent geographic information. Manipulating this information was limited to a manual, non-interactive process. Since then the rapid development of new technologies to collect and digitize geographic data, together with an increasing demand for both interactive manipulation and analysis of this data, has generated a need for dedicated software’s namely geographic information systems (GISs).

A GIS is more than a cartographic tool to produce maps. It stores geographic data, retrieves and combines this data to create new representations of geographic space, provides tools for spatial analysis, and performs simulations to help expert users to organize their work in many areas like public administration, transportation networks, military applications and environmental information systems. These above mentioned are few among many others where we are concerned with geographical locations, their present status, its potential for developmental activities, patterns of change over the years and the processes on the surface of the earth.

Geographic information technology is used to manipulate objects in geographic space, and to acquire knowledge from spatial facts. Spatial information theory provides a basis for GIS by bringing together fields that deal with spatial reasoning, the representation of space, and human understanding of space.

Abstract

Satellite photographs depict exciting evidence on the migratory melodrama of river systems. A study has been conduced in parts of Tamil Nadu using IRS-IA Satellite pictures, archaeology and Tamil literature, which reveals that from Pleistocene to 2700 years B.P.(Before Present) the river Cauvery flowed in a northeasterly direction from the Stanley reservoir via Chinnar, Palakkodu, Mattur, Tiruppathur (Tiruppattur), Gudiyatham (Gudiyattam), Vellore and Walajapet to meet the sea at Madras. From 2700 to 2300 years B.P., it flowed via Uttangarai and Tirukkovilur to meet the bay of Bengal near Pondicherry, over which the present-day Ponnaiyar is a misfit stream . From 2300 to 1300 year B.P. it has flowed via Erode, Tirukkampuliyur, Alagarai , Tiruchy, Kiranur and Pudukkottai meeting the sea in the region where the present-day Agniar and Ambuliar meet the sea. Subsequently, between 1600 and 1300 years B.P., the Cauvery flowed along the present-day tracts of the Vennar and Vettar, after which it seems to have flowed as the Kodamurutti, Arasalar and PalanCauvery from 1300 to 1000 years B.P. From about 900 years B.P. it flowed via Tirupurampayam (Tirupurambiyam), Achalpuram till around 750 years B.P. and then it is stabilised as the Colleroon (Kollidam). Such periods and phases of river migration as well as their implications in the search for archaeological remains are discussed in this paper.

Models Definitions

In social science research a model is a tentative description of what a social process, say the communication process or a system might be like. It is a tool of explanation and analyses, very often in a diagrammatic form, to show how the various elements of a situation being studied relate to each other.

The term model can also refer to a particular process or object, which is used as a point of reference, when an attempt to explain the unknown is being made. It basically comprises involving an analogy to throw up the similarities between the phenomena to be explained and one, which is well known, i.e., the model.

The simplest definition of a model is that it is an analogue. A model is a relatively well-developed analogy. Given two objects or processes which are dissimilar in many respects, one is an analogue of the other to the extent that the physical or logical structure of one re-presents the physical or logical structure of the other.

The advantage of models in communication research is that it allows the researcher to account for different variables in different communication situations. Models only represent systems or processes. Since they are not real, they are just symbolic ways of looking at systems to help us to think about them more lucidly. Again since models do now show every part of a system, they are usually incomplete in that sense. Even those that are shown are represented only in enough detail to help us look at the processes or features in which we are interested. Models give us an idea of complicated objects or events in a general way. They enable us to see how a particular communication event fits into the general pattern. They provide a classification for an old problems, and familiar events. They help us by providing a structure of references for purposes of study. Theories are not models and the most fundamental difference between a theory and a model is that the former is an explanation whereas the latter is a representation.

1.1. Prologue

In present era, agriculture is a cause of global concern in the context of price volatility with a rising trend growing concerns for food security and resultant trade restrictions, global economic conditions in the recent past, the forecasted rate of reduction of growth of agricultural land over the next two decades, increasing mismatches between supply of agricultural products in relation to growing demand and the climatic changes which are wielding pressures on agricultural production. Thus, enhancing agriculture production and productivity have emerged as a global challenge. India, with 2.4 per cent of the world’s geographical area, is the largest producer of pulses, tea, and milk and second largest producer of fruits, vegetables, wheat, rice, groundnut and sugarcane in the world but supports about 16.2 per cent of the world’s population. Coupled with small scale land holdings and deep rooted poverty in rural areas, the magnitude and dimensions of challenges for agriculture policy-makers have increased manifold. So far as the agriculture sector in Odisha is concerned, it contributes only 15.6 percent in 2013-14 towards State Gross Domestic Product (SGDP), but provides employment and sustenance to more than 60 percent of the total workforce of the State. In this sense, the agriculture sector is still the mainstay of the economy of Odisha. According to the Economic Survey 2013-14 of Odisha, despite wide annual variations in its growth, the agriculture sector had grown at a rate of 12.72 per cent in 2012-13. However, a negative growth of 3.53 percent is anticipated during 2013-14 due to cyclonic storm Phailin and flash floods in the State in October 2013. The real per capita income of Odisha was Rs. 25,891 in 2013-14 which was around 65 per cent of All-India real per capita income of Rs.39, 961. According to the 68th round of National Sample Survey Organization (NSSO), the monthly per capita consumer expenditure (MPCE) for rural and urban Odisha is below the respective national averages. In the food and non-food consumption behaviour, an average Indian spends more than an average person in Odisha. In short, the above parameters pinpoint that the State of Odisha has been lagging behind the national economy & highlights the necessity of achieving higher growth on a sustainable manner across the sectors particularly the agriculture sector in order to uplift the society from underdevelopment & poverty. Though the contribution of agriculture to Net State Domestic Product (NSDP) has declined, the percentage of workforce engaged in agriculture has remained somewhat unchanged. This implies that there has been an overcrowding in agriculture without any noticeable increase in production.

11.1 Introduction

Pandas is an open-source Python Library providing high-performance data manipulation and analysis tool using its powerful data structures. The name Pandas is derived from the word Panel Data - an Econometrics from Multidimensional data.

In 2008, developer Wes McKinney started developing pandas when in need of high performance, flexible tool for analysis of data.

Prior to Pandas, Python was majorly used for data munging and preparation. It had very little contribution towards data analysis. Pandas solved this problem. Using Pandas, we can accomplish five typical steps in the processing and analysis of data, regardless of the origin of data - load, prepare, manipulate, model, and analyze.

Python with Pandas is used in a wide range of fields including academic and commercial domains including finance, economics, Statistics, analytics, etc.

Climate and Agriculture

Soil, climate and water are three basic requirements of a crop to be grown in a particular region. Climate affects the temperature trends, seasons, length of the growing season, amount of sunlight and the seasonality of sunlight etc. A change in climate may cause recurrent droughts, floods and weather extremities that would affect the agricultural production, human livelihoods, health and biodiversity. The relationship between agriculture and climate is complex as it is dependent on climate and also plays a contributing role in emission of greenhouse gas (GHG). Greenhouse gases include carbon dioxide, nitrous oxide, methane, chlorofluorocarbons (CFCs), hydro-chlorofluorocarbons (HCFCs), hydro-fluorocarbons (HFCs), per fluorocarbons (PFCs) etc. , which play a significant role in climate change.

This chapter has focused on providing readers with a comprehensive understanding of business communication strategies and techniques in the Indian agricultural context. The chapter has highlighted the importance of communication in business, the challenges faced by the agricultural sector in India, and the need for effective communication strategies to overcome these challenges. The chapter has also provided an overview of relevant communication theories and techniques and their application in the Indian agricultural context. Understanding business communication is critical to developing effective marketing, supply chain, and other business-related strategies in the Indian agricultural context, and this chapter has laid a strong foundation for the same.

The COVID-19 pandemic has significantly impacted agribusiness communications, creating unprecedented challenges and opportunities for the sector. With restrictions on transportation, shortage of labor, and changes in consumer behavior, agribusinesses have had to adapt their communication strategies to remain operational and retain consumer trust. The objective of this chapter is to analyze the impact of the COVID-19 pandemic on agribusiness communication and suggest effective communication strategies to overcome the challenges posed by this and similar crisis which might arise in the future.

Negotiation is a communication and problem-solving process built on a broad foundation of skills and knowledge. It is also one of the most popular and effective means of resolving conflicts and misunderstandings. Negotiation is back and forth communication designed to reach agreement while leaving the other side intact and positive.

Basic principle, without which negotiation is impossible

Successful negotiation requires compromise from both sides. Both parties must gain something, and both parties must lose something. You must be prepared to give something up to which you believe you are entitled. You cannot expect to defeat your opponent or “win” a negotiation by either the power of your negotiating skills or the compelling force of your logic. This is not to say that good negotiating ability is irrelevant. In most cases, a range of possible outcomes exists. A skilled negotiator often can achieve a settlement near the top of the range.

Introduction

Entrepreneurial and start-up firms share traits but also differ. It takes courage to start a new business, but not always with the latest technology. Founders of new companies, almost always based on new technology, take risks. Both types of firms must overcome limited resources and talent. Both entrepreneurs and start-ups seek to segment and expand markets. Starting a business involves risks, but start-ups face additional risks of innovation. (Rao, 2018).

The project is the very foundation of any business. As a result, the success or failure of a company is primarily determined by the project. In layman’s terms, a project is an idea or plan meant to be carried out. According to the dictionary, a project is a scheme, design, or proposal for something intended or devised to be accomplished. (MANAGE, 2013)

Beginners often wonder where to begin. Some options are obtaining power-water connections, pollution control clearance, approvals of weights and measures/drug control, and registration with sales and income tax departments. But, first, an entrepreneur must set priorities. (IGNOU, 2017).

14.1 Introduction

The theory of simple correlation (r_xy), regression coefficients (b_yx & b_xy) and their test of significance have been discucsed in chapter 13. The test of significance of observed partial correlation coefficient p₁₂₃(k+2) and multiple correlation coefficient R₁₂₃, have also been discussed in sections 13.4 and 13.5 respectively. Now in this chapter mainly the process of how to calculate spearman’s rank correlation coefficient, partial correlation and regression coefficients and multiple correlation coefficient using their fundamental definitions as well as appropriate statistical formule in terms of pairwise simple correlation coefficient r_ij (i = j = 1, 2, 3) in trivariate populations have been provided to make the students and its users to be familiar with basic and crystal clear concepts of the subject matter with the help of an empirical studies based on some original data on (X₁, X₂, X₃). Here X₁ has been considered as study variate and (X₂, X₃) as covariates.

Network in Project Management

A project network is a graph that shows the activities, duration, and inter dependencies of tasks within our project.

Networking is a crucial aspect of project management that can provide various benefits, including access to new job opportunities, industry insights, and professional development opportunities.

What is network with diagram?

A Brief History of Project Management.

12.1 Introduction

Technological advancements have completely changed human existence, bringing about profound societal shifts and stimulating the economy. Empowering women will have a good impact on women's daily lives and is essential to the growth of any society. Women now have many possibilities to showcase their creativity, ideas, and technological prowess both in India and around the world thanks to the advancements and inventions in the field of information technology. This review's main goal is to investigate how women use digital technology in urban and rural areas. India is rapidly digitizing, embracing all facets of technological advancement, and as a result, offering plenty of job prospects for women.To reduce the disparity between genders in technology fields in Indian society, women's involvement in these fields, both in rural and urban areas, must be the main focus.

2.1 Gender Analysis

Inequalities between men and women are becoming more visible and glaring particularly in developing countries of the world triggering serious concern over developed experts. UNESCO statistics reveals that women perform 75 per cent of work, earn 10 per cent of the income and own 1 per cent of property. The 3rd UN Millennium Development Goal (MDG) has called for gender equality and the components of women to battle poverty, hunger and disease and to restorative development that is precisely sustainable.

The Beijing Platform for Action (1995) very well support this fact in form of twelve objectives and action points viz., women and poverty, education and training for women, women and health, violence against women and armed conflicts, women and the economy, women in power and decision making, institutional mechanism for the development of women, human rights of women, women and media, women and environment, and the girl child. Prior to the above declaration there were First, Second and Third World Conference on Women at Mexico (1975), Copenhagen (1980) and Nairobi (1985), respectively.

The research setting provides specific details about the location where a study is conducted. This study area typically encompasses a particular geographical region, such as a state, district, block, or gram panchayat, chosen according to the research requirements. The researcher must have a thorough understanding of the locality, including its communication methods, in order to effectively access all parts of the region for data collection.

In social science research, a clear comprehension of the characteristics, attitudes, and behaviours of the individuals within the study area is essential. Without this understanding, accurately conceptualizing, perceiving, and interpreting data becomes challenging. To obtain a comprehensive understanding of the implications and behavioural intricacies of the local people representing a broader community in the referenced study area, researchers must have a solid grasp of these factors. Therefore, this chapter critically analyses the socio-demographic background of the residents in a rural setting.

The term “research setting” denotes the context in which research inputs and elements are absorbed, interacted with, and mutually contribute to the system’s overall performance.

The research setting is crucial because it shapes and influences the interactions of various factors and components. Therefore, conducting a study on how farmers perceive persuasive issues and other topics requires a local context that takes into account the unique natural environment, demographics, crop ecology, institutional framework, and socio-cultural factors. For example, when writing a paper about the social behaviour of chimpanzees, it is important to include details about the research setting. This may include information such as where the chimpanzees were studied (in the wild or in captivity), the number of chimpanzees that were observed, whether they were part of the same social group, the geographic location, the time of the study, the season/weather conditions, the availability of resources such as food, water, and shelter, and any environmental factors that were present. There are two types of research settings: macro and micro. The macro research setting encompasses the entire state, while the micro research setting focuses on specific districts, blocks, or village peripheries. The aim of this approach is to understand the study environment from broader perspectives using the state as a reference frame and the district and block profiles as units of in-depth analysis.

1. Introduction

Information and Communication Technologies (ICT) has transformed the functioning of modern libraries in the 21st century. The applications of ICT to data, information and knowledge resources have given rise to data centers, digital libraries, and knowledge repositories. New software’s that are based on international standards have emerged to undertake a wide range of jobs that suit the requirements of individual libraries. Rapid advances in the application of ICT have given rise to ‘Open Standards and Open Source Software’s. Libraries can benefit a great deal now by using these standards and software, as during the last twenty five years only rich libraries could afford to use commercial software. As a result the transformation of libraries was not universal in India. Now with the advent of open source software, we are expecting many libraries are going to be modernized. This transformation is not going to be limited to libraries only but to users as well who belong to different disciplines and walks of life due to social networking which is emerging as a major activity of libraries around the world. Libraries

Statistics is a branch of science which deals with the collection, classification, description and interpretation of data obtained by conducting surveys and experiments. The essential purpose of it is to describe and draw valid inferences about numerical properties of populations” (Ferguson 1966). The experience in statistics application indicates that a single statistical method can be used in different research areas for dealing with different types of problems. Various possibilities which application of a statistical method provides in certain research areas should be considered as an adequate way of dealing with a problem of the research. However, it should be noted that statistics is not a method by which it is possible to solve all the problems in a research. Nachmias and Nachmias (2009) stated that there are basically two types of statistics which include descriptive and inferential statistics. Descriptive statistics enable the researcher to summarize and organize data in an effective and meaningful way. It involves the use of tables, charts, graphs, mean, modes, median, standard scores and correlation to treat collected data. Inferential statistics is concerned with making inferences from a unit of a population. Inferential statistics is concerned with making inferences from a unit of a population. Inferential statistics allow the researcher to make decisions or inferences by interpreting data patterns. Researchers use inferential statistics to determine whether an expected pattern designated by the theory and hypotheses is actually found in the observations. To decide whether this hypothesis is true, researchers might survey the respondents and then use descriptive statistics to make comparison between these groups and would employ inferential statistics to determine whether the differences between the groups are significant or not.

Multivariate analysis is essentially the statistical process of simultaneously analyzing multiple independent variables with multiple dependent (outcome or criterion) variables using matrix algebra. During the last two or three decades, multivariate statistical analysis has become increasingly popular. The theory has made great progress, and with the rapid advances in computer technology, routine applications of multivariate statistical methods are implemented in several statistical software packages. The traditional approach to the teaching of multivariate statistical analysis, as exemplified by Anderson (1958), relies heavily on advanced matrix mathematics. On the other hand, Hury and Riedwyl (1988) suggest that it is possible to understand most of the basic ideas underlying multivariate statistical analysis without a mastery of such mathematics, provided that these are conveyed with the help of real data sets. In this chapter we propose a non-mathematical data-driven approach for teaching multivariate statistical methods to students. Despite this, we are mindful of the need for students to know some basic linear algebra and univariate statistical concepts. Such basic knowledge provides students with the foundation necessary for the application of the appropriate multivariate statistical procedures and for the interpretation of results.

8.1 Medicinal use of Bamboo in Cattle: The important parts of bans (Bambusa arundinacea) used are the leaf and stem, which contain choline, betain, nuclease, urease, cyanogenetic and glucoside. The leaf acts as an emmenagogue, stimulant, astringent, febrifuge, echbolic, and diuretic. It also acts against leprosy, tympany/bloat, diarrhea, retained placenta, threadworm, cough, and cold in horses. Flowering occurs once in ten to twelve years. The plant dries after flowering. (Parabia et al., 2000).

8.2 Medicinal uses of Dendrocalamus Strictus: The leaf and other parts of kaban (Dendrocalamus strictus), which contain siliceous matter, are used as astringent and ecbolics in animals. (Parabia et al., 2000).

8.3 Medicinal uses of Datura metel, D. alba, D. fastuosa: The leaf, root, fruit, and ripe seed of sadah datura (Datura metel) contain alkaloids such as hyoscyamine, hyoscine, atropine, scopalamine, allantoin, and vitamin C. They are used for treating insanity, fever with catarrh and cerebral complications, and the fruit is used to induce heat in animals and treat prolapse of uterus/ vagina. (Parabia et al., 2000).

8.4 Medicinal uses of Dalbergia Sissoo: The stem bark, root, leaf, and mucilage of sisam (Dalbergia sissoo) contain tannin, dalberginone, dalbergin, allylphenol of latitontype, 5,7,4-trihydroxy-s-methoxyisoflorone, and are used for leprosy, boils, eruptions, to allay vomiting, and the oil is used for cutaneous afflictions. Mucilage of leaves mixed with sweet oil is applied in excoriations. (Parabia et al., 2000).

8.5 Medicinal uses of Cyperus Rotundus: The tubers of motha mutha (Cyperus rotundus) have essential oils, myristic and stearic acid, unstable alkaloid, b-seilinne, cyperenone, and are used as diuretic, emmenagogue, anthelmintic, stimulant, tranquilizer, and antipyretic. (Parabia et al., 2000).

5.1 Introduction
The Earth’s atmosphere is a vast, dynamic, and interconnected system, constantly in motion and influencing every aspect of our lives. Accurately observing and understanding this complex system is fundamental to predicting weather, monitoring climate change, and responding to environmental challenges. While ground-based platforms provide invaluable high-resolutiondata at specific locations, theitr  spatial coverage is inherently limited. This is where satellite remote sensing emerges as a revolutionary tool in meteorology. By observing the Earth and its atmosphere from space, satellites offer an unparalleled vantage point, providing global and continuous coverage that is impossible to achieve with ground-based instruments alone. They can capture data from remote oceans, deserts, and polar regions, offering a truly holistic view of atmospheric processes.
Satellite remote sensing enables meteorologists to measure a wide array of atmospheric parameters, including temperature and humidity profiles, cloud properties (type, height, movement), wind fields, precipitation rates, and the distribution of atmospheric gases and aerosols. This wealth of data is crucial for initializing and validating numerical weather prediction models, tracking severe storms, monitoring long-term climate trends, and conducting fundamental atmospheric research. This chapter will delve into the fascinating world of satellite remote sensing in meteorology, exploring the principles behind how these orbiting observatories collect data, the various types of meteorological satellites and their specialized instruments, and the diverse applications of the information they provide for understanding and forecasting
our planet’s weather and climate.

Imagine the air around us. Even though we can’t see it, air has weight. Atmospheric pressure is essentially the force exerted by the weight of the air molecules above a particular point on the Earth’s surface.
Think of it like this: Imagine you’re at the bottom of a swimming pool. The water above presses you down, and you feel that pressure. Similarly, the atmosphere, a giant ocean of air, has layers of air molecules, and their weight presses down on everything below, including us.
• Atmospheric pressure is defined as the force per unit area exerted by the weight of the air column extending from the surface of the earth ,to the top of the atmosphere above that area
• It can be explain in simple terms like:
• Air has weight: Just like water or a pile of books, the air surrounding the Earth has mass, and thus, weight due to gravity.
• Weight creates pressure: This weight of the air presses down on the surface. The more air there is above a certain point, the greater the pressure.
• Like a stack: Imagine a stack of blankets. The blanket at the bottom has to support the weight of all the blankets above it, so it experiences more pressure. Similarly, the air at lower altitudes has the weight of all the air above pressing down on it.

Introduction
Social sustainability has gained significant attention in the contemporary development, especially in information technology (IT). Social sustainability refers to the ability of a society to maintain and improve social well-being, equity, and quality of life for its present and future generations. It involves fostering an environment where all individuals, irrespective of their socioeconomic backgrounds, have equal access to resources, opportunities, and services. Information technology (IT) has emerged as a transformative tool in achieving social sustainability by addressing various social challenges such as inequality, lack of access to education, healthcare, and basic services. It also fosters community engagement, empowerment, and participation in governance.

Introduction
Information Technology (IT) has emerged as a cornerstone of modern economic, social, and environmental systems, pivotal in driving innovation and sustainabilit across various sectors. As the world grapples with the urgency of achieving sustainable development, IT offers powerful tools to monitor, analyze, and optimize resource use, reduce environmental footprints, and promote social and economic equity. However, measuring the impact of IT on sustainability requires a nuanced understanding of its diverse contributions, challenges, and longterm consequences. It is essential to assess how IT can simultaneously support environmental conservation, economic growth, and social well-being, often called the three pillars of sustainability.

Agriculture is the backbone of human civilization, providing food, fiber, and livelihoods for billions of people around the world. Crop yields, which are a critical component of agricultural productivity, are influenced by a complex array of factors, including genetics, soil quality, water availability, and management practices. However, among these factors, weather and climate stand out as two of the most significant drivers of crop yields.
Weather and climate are intimately linked, with weather referring to short-term atmospheric conditions, such as temperature, precipitation, and wind, and climate describing the long-term average atmospheric conditions in a particular region. Together, they form a dynamic duo that shapes the fate of crops, influencing their growth, development, and productivity.
The impact of weather and climate on crop yields is multifaceted. Weather events, such as droughts, floods, and heat waves, can have devastating effects on crops, leading to reduced yields, lower quality produce, and even complete crop failures. Climate, on the other hand, influences the overall growing conditions, determining the suitability of a region for specific crops and the timing of planting, growth, and harvest.
Understanding the complex interplay between weather, climate, and crop yields is crucial for ensuring food security, improving agricultural productivity, and promoting sustainable farming practices. This chapter aims to explore the intricate relationships between weather, climate, and crop yields, examining the ways in which these factors interact and influence each other. By delving into the latest research and findings, this chapter will provide insights into the following key topics:
The impact of weather events, such as extreme temperatures, precipitation, and wind, on crop yields
• The influence of climate on crop growth, development, and productivity
• The role of climate change in altering weather patterns and crop yields
• Strategies for mitigating the negative impacts of weather and climate on crop yields, such as climate-smart agriculture and weather-based crop insurance

Introduction 
India’s urban transition is among the most significant in the world, both in scale and complexity. With over 34% of the population residing in urban areas as of 2018 and projections indicating that nearly half the nation will be urban by 2047, the quality of urban governance will decisively shape India’s developmental trajectory (United Nations, 2018). Urban areas are expected to contribute over 70% of the GDP by 2030. However, cities face multifaceted governance challenges ranging from infrastructure deficits and environmental stress to inadequate service delivery and institutional fragmentation (NITI Aayog, 2021). In response, digital urban governance has emerged as a transformative paradigm, leveraging information and communication technologies (ICTs) to enable responsive, efficient, and inclusive urban administration. Digital technologies are increasingly embedded into urban governance structures and processes, from e-governance portals and grievance redressal apps to real-time traffic monitoring systems and digital financial tools. This shift is reflected in flagship national programmes such as Digital India, Smart Cities Mission, and the National Urban Digital Mission (NUDM), which aim to digitise public service delivery, enhance citizen engagement, and enable data-driven decision-making at scale (Ministry of Housing and Urban Affairs [MoHUA], 2021; MeitY, 2015). At the heart of this transformation is the creation of robust digital infrastructure such as Integrated Command and Control Centres (ICCCs), city data platforms, and open APIs combined with evolving institutional frameworks that promote interoperability, decentralisation, and cooperative federalism (Kapur & Joshi, 2021; NIUA, 2023). The chapter explores the evolution and current landscape of digital urban governance in India by first outlining the conceptual underpinnings of urban governance and then transitioning into the digital domain. It analyses the role of urban digital infrastructure and the institutional architecture that supports it, highlighting the coordinated efforts under NUDM to build an open, interoperable, and citizen-centric digital ecosystem across India’s 4,400+ towns and cities (MoHUA & MeitY, 2021). Complementing this are the

The concept of climate-resilient agriculture encompasses a range of approaches, including climate-smart agriculture, conservation agriculture, and agroforestry. These approaches recognize that agricultural development and growth are inextricably linked to climate change, and that farmers, policymakers, and other stakeholders must work together to promote climate-resilient agriculture practices. The dynamics of development and growth engineering in the context of climate-resilient agriculture are complex and multifaceted. They involve understanding the interactions between climate change, agricultural productivity, and rural livelihoods, as well as the role of institutions, policies, and technologies in promoting climate-resilient agriculture practices. Several driving factors are influencing the dynamic development of climate-resilient agriculture (Fig. 7.1). These include:
Increased awareness of climate change impacts on agriculture, leading to growing demand for climate-resilient agriculture practices.
• Advances in climate information and early warning systems, enabling farmers and policymakers to make more informed decisions.
• Growing recognition of the importance of soil health, biodiversity, and ecosystem services in promoting climate-resilient agriculture.
• Increased investment in climate-resilient agriculture research and development, leading to the development of new technologies and practices.
• Effective governance for growth is critical for promoting climate-resilient agriculture. This requires:
• Strong institutions and policies that support climate-resilient agriculture, including laws, regulations, and incentives.
• Inclusive coordination and collaboration among stakeholders, including farmers, researchers, policymakers, and private sector actors.
• Investment in climate information and early warning systems, as well as climate-resilient agriculture research and development.
• Support for capacity building and extension services, enabling farmers to access and adopt climate-resilient agriculture practices.
• Agricultural insurance and risk management mechanisms, enabling farmers to manage climate-related risks and uncertainties. By understanding the driving factors and governance requirements for climate-resilient agriculture, policymakers, researchers, and practitioners can work together to promote dynamic development and growth in the agricultural sector, enhancing food security, sustainability, and climate resilience.

Introduction 
Having explored the fundamental principles and various types of elementary crop growth models in the previous chapter, we now arrive at a pivotal juncture in their journey from theoretical constructs to practical, dependable tools. It‘s one thing to conceptualize and build a mathematical representation of crop growth; it‘s quite another to ensure that this model accurately reflects realworld plant behavior and can be reliably used for predicting outcomes and informing critical agricultural decisions. This chapter, Calibration, Validation, Verification, and Sensitivity of Elementary Crop Models,” will guide you through the indispensable processes that establish a model‘s credibility and utility. We will delve into the systematic steps involved in calibration, where we meticulously fine-tune a model‘s parameters to accurately reflect a specific crop‘s response within a particular environment, effectively adapting the general model to local conditions. Following this, we will explore validation, a rigorous process of independently testing the model‘s predictive power against datasets not used during calibration, ensuring its robustness and generalizability. Beyond accuracy, we will also cover verification, which confirms the model‘s logical consistency and computational correctness, ensuring that its internal workings are sound. Finally, we will examine sensitivity analysis, a crucial technique for understanding how changes in various input factors—especially weather parameters—or internal model coefficients influence the model‘s outputs, thereby revealing the model‘s critical drivers and potential vulnerabilities. These four processes are far more than mere technical formalities; they form the bedrock upon which the utility, accuracy, and trustworthiness of any crop model, no matter how elementary, are firmly built. By engaging with these essential steps, we can transform theoretical frameworks into powerful instruments capable of supporting sustainable agricultural planning, risk management, and adaptive strategies in a dynamic climate.

Introduction
Following our comprehensive exploration of scientific crop modeling and the rigorous processes of model assessment, we now pivot to an equally vital, yet distinct, realm of understanding weather in agriculture: Indigenous Technical Knowledge (ITK). This chapter, Indigenous Technical Knowledge for Weather Forecasts and Its Validity,” delves into the profound and often overlooked wisdom embedded within local communities worldwide, knowledge systems accumulated over generations that offer unique insights into anticipating future weather patterns.
In the upcoming sections, we will embark on an in-depth examination of the diverse forms that ITK related to weather forecasting takes. This includes detailed discussions on:
• Observational Indicators: How traditional communities keenly observe subtle changes in the natural world, such as specific patterns in animal behavior (e.g., bird migration patterns, insect activity, animal calls), plant phenology (e.g., early or late flowering, unusual fruiting patterns of wild plants), and the behavior of flora and fauna as harbingers of upcoming weather shifts.
• Atmospheric and Astronomical Signs: The interpretation of sky conditions (e.g., cloud formations, specific colors of sunrise/sunset, halos around the sun or moon), wind patterns, atmospheric pressure changes (often perceived through bodily sensations or changes in local sound travel), and celestial phenomena (e.g., star brightness, moon phases) as indicators for short-term or seasonal forecasts.
• Traditional Ecological Calendars and Proverbs: The role of traditional calendars that map out expected seasonal weather based on historical observations, and folk proverbs or sayings that encapsulate generations of empirical weather wisdom in concise, memorable forms, guiding agricultural practices.

Introduction 
Building upon our foundational understanding of how weather intrinsically shapes crop development, from the micro-scale physiological responses to the broader patterns revealed by Indigenous Technical Knowledge, we now transition to a chapter dedicated to a highly practical and actionable synthesis of this critical interrelationship: Crop Weather Calendars. These calendars are far more than mere chronological charts; they represent systematically organized and dynamic compilations of meteorological information meticulously integrated with precise crop-specific data, designed to serve as an indispensable guide for optimizing agricultural practices. In this chapter, we will embark on a comprehensive exploration of Crop Weather Calendars, moving beyond the often informal or culturally embedded ecological calendars previously discussed. We will delve into how these powerful tools systematically integrate historical weather patterns, which involves analyzing longterm meteorological data to establish reliable averages and identify probabilities of specific weather events, such as the typical onset of monsoons, average frost dates, or periods of peak solar radiation. They also incorporate real-time meteorological data, bringing in current weather observations to track actual conditions against historical norms and initial forecasts. Furthermore, Crop Weather Calendars utilize future weather forecasts, drawing on short-, medium-, and long-range meteorological predictions to anticipate upcoming conditions (Fig.12.1). This integrated weather information is then critically aligned with the precise phenological stages of a given crop cultivar, recognizing that a crop’s sensitivity and requirements vary significantly throughout its life cycle. Our exploration will detail the essential components that constitute a robust crop weather calendar, including the identification of crucial growth periods, pinpointing the most sensitive and influential developmental stages of the crop like germination, tillering, flowering, and grain filling, where weather impacts are most pronounced. It also involves the establishment of weather thresholds, which means defining the optimal, critical, and damaging ranges of key weather

The establishment of a technology transfer office is an important and complex process for an organization. It needs careful planning to ensure its long-term sustainability. Before establishing a TTO, it is essential to evaluate whether institution’s core mission includes research commercialization, and if the volume and quality of its research output justify the need for an inhouse TTO. For institutions that may not meet all criteria, those institutions can collaborate or outsource for TTO services. It is also important to decide about its operational scope, funding, management, and for what kind of issues the office should develop a policy. There is no “right” way to set up a TTO, but successful TTO does require considering some key issues. This chapter outlines key steps and considerations for establishing a TTO. It also explains what physical infrastructures are needed, manpower, outlines the responsibilities and powers of TTOs.
2.1 Evaluating the need for a TTO
Establishing a TTO is an important step for any research focused organization. But before initiating a planning process for a new TTO, the organization must review its relevance by considering a few fundamental points:
Key considerations for institutions
1. Is institution’s mission focused on “research commercialization” If an institute’s primary mission is education, or it does not support research it might not be justified to create a TTO. For such institutions, it usually makes better sense to seek alternative solutions to the occasional technology transfer without the expense of a formal office. But institutions with strong research commercialization focus, a TTO has the ability to contribute meaningfully to the mission. The Association of University Technology Managers (AUTM), USA has identified following key motivations for initiating academic technology transfer:

The effectiveness of community mobilization efforts depends significantly on the quality of analysis and understanding that guides strategic planning and decision-making processes, requiring sophisticated tools and frameworks that can capture the complexity of community circumstances while providing actionable insights for collective action. The integration of systematic analysis tools with deep understanding of value systems creates powerful foundations for community mobilization that can navigate both technical challenges and cultural dynamics that influence success and sustainability of development initiatives. Analysis tools provide structured approaches to understanding community conditions, opportunities, and constraints while helping communities develop strategic perspectives that can inform effective action planning and resource allocation decisions. These tools transform complex information into accessible formats that can facilitate community dialogue and consensus-building while building local capacity

Farmer Producer Organizations represent a transformative institutional innovation in agricultural development that addresses the fundamental challenges of small-scale farming through collective action and cooperative enterprise development. These organizations emerge from the recognition that individual small farmers face insurmountable obstacles in accessing markets, obtaining fair prices, securing quality inputs, and achieving economies of scale necessary for sustainable agricultural livelihoods in increasingly competitive and globalized food systems. The concept of FPOs builds on the rich tradition of agricultural cooperation while adapting to contemporary market realities and policy frameworks that require formal institutional structures for accessing services, credit, and government support programs. FPOs represent a hybrid institutional form that combines the democratic governance and member ownership characteristics of traditional cooperatives with the business orientation and professional management capabilities of modern enterprises, creating organizations that can operate effectively in comp

Conflict represents an inevitable and potentially constructive dimension of community mobilization that emerges when individuals and groups with different interests, values, perspectives, or needs interact in pursuit of shared or competing goals. Rather than viewing conflict as purely destructive or problematic, effective community mobilization requires sophisticated understanding of conflict dynamics and skilled application of management strategies that can transform disagreements into opportunities for learning, innovation, and strengthened relationships that enhance collective capacity and democratic participation. The complexity of contemporary community challenges requires bringing together diverse stakeholders with varying backgrounds, experiences, priorities, and approaches to problem-solving, creating natural conditions for disagreement and tension that must be navigated skillfully to maintain group cohesion while harnessing the creative potential that emerges from diverse perspectives and approaches. Understa

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.

Pre-training and fine-tuning constitute two fundamental stages in the development of modern Large Language Models. This chapter provides a comprehensive examination of how LLMs acquire general language capabilities through large-scale pre-training and subsequently adapt those capabilities to specific tasks through fine-tuning. Pre-training uses extensive unlabeled datasets and self-supervised learning objectives to develop representations of language, context and knowledge. The chapter discusses Transformer-based architectures, data preparation, cleaning, tokenization and the importance of high-quality training corpora. It then examines fine-tuning approaches including Supervised Fine-Tuning, Reinforcement Learning from Human Feedback, Parameter-Efficient Fine-Tuning, LoRA, QLoRA, adapter tuning and soft prompting. Major challenges such as data quality, privacy, computational cost, catastrophic forgetting, overfitting, hallucination, bias and security vulnerabilities are addressed. The chapter also considers emerging approaches that allow models to adapt during inference and improve reasoning efficiency. Overall, it highlights the continuing need for training strategies that balance accuracy, adaptability, efficiency, safety

Programme evaluation requires a systematic sequence of activities through which programme objectives, implementation processes, outcomes and impacts can be examined using credible evidence. This chapter presents the practical process of conducting an evaluation from programme identification through the use of evaluation findings. It explains how evaluators identify the programme and its objectives, determine the appropriate stage and type of evaluation, and assess the technical, financial, operational and time feasibility of the evaluation. Particular attention is given to identifying and consulting key stakeholders because their perspectives, expectations and information are important for a relevant and participatory evaluation process. The chapter further addresses approaches to data collection, sampling, quantitative and qualitative analysis, interpretation and communication of findings. It emphasizes that evaluation findings should not merely be reported but should contribute to programme improvement, decision-making and learning. The chapter also considers the evaluation of evaluation itself, or meta-evaluation, as an important mechanism for assessing the quality, credibility and usefulness of evaluation processes and reports