eChapters

Modern agriculture requires certain precise information on pattern of rainfall, temperature, occurrence of drought and flood etc. for formulating required strategy for crop production. It also requires knowledge about agro-climatic conditions of the region for deciding a planned cropping pattern. Therefore climatic classification and delineation of agro-climatic zones would be imperative for a country or state.

Climatic factors like increase in temperature, carbon dioxide (CO₂) concentration, moisture, and other factors directly or indirectly affect agriculture, which have been elaborately dealt in previous chapters. Climate change causes weather variability that may result in low production, hike in price of agricultural commodities including food grains, vegetables, fruits, meat, egg and milk. It is now realised that climate resilient agriculture (CRA) will be imperative to reduce the vulnerability of agriculture to the climate change.

Climate-smart Agriculture Practices and Indicators

Considering the three pillars of climate-smart agriculture such as productivity, adaptation and mitigation, different technologies and practices have been evolved.

The CSA practices are grouped under soil and land management, water management, crop management, livestock management, forestry, fishery & aquaculture and energy management. The World Bank Group (2016) has suggested broad indicators of CSA practices (Table 7.1; Chapter 7)

Definitions of Energy

Energy is a key topic in science and technology, as well as in society in general. In terms of energy, a typical definition found in popular literature as well as textbooks is “energy is the ability to do work” or, much more precisely, “energy is the capacity of a system to do work” [Atkins 1990].

Energy is described as the ability to generate change or carry out work, and that work can be separated into numerous easily identifiable tasks: Energy produces light, heat, motion, sound, growth, power and technology etc.

Energy in Agricultural Context (FAO)

Agriculture’s fundamental and foremost function is to produce food and other primary products, so contributing to food and nutritional security. Sustainable Agriculture and Rural Development (SARD) attempts to promote ecologically non-degrading, technically suitable, commercially successful, and socially acceptable development in the agriculture, fishery and forestry sectors. Achieving food security necessitates policies that promote social, cultural, political, and economic stability. Integrating agriculture’s economic, social, and environmental roles can help to attain these objectives.

Agriculture may provide a variety of non-food commodities and services. This can include its application as a viable, long-term source of energy. According to the FAO, agricultural activities and related land use directly contribute to non-agricultural functions such as social, environmental, economic and cultural products and services. They can have major advantages or disadvantages. Research reveals that, in addition to food security, agriculture contributes significantly to attaining sustainability at the local, national and global levels in rural development, energy and the environment. The efficient operation of the market encourages the identification and strengthening of these many functions, as well as the development of new techniques and technologies. Plant and crop-based resources are utilised as raw materials in a wide range of industrial goods, including wood for paper and board production, starches for adhesives, and vegetable oils for paints and resins.

Services for CSA

Under the CSA projects and programmes, the services like supply of inputs and technology transfer through extension services are provided to the farmers. The inputs like seeds of crops are provided by the input dealers at the subsidized rate and seedlings of fruits and vegetables are provided by both private and government agencies to grow under general cultivation and poly-house cultivation technology. Similarly other services like soil testing facilities, issue of soil health cards, construction of micro-irrigation projects and rain harvesting structures are made available to farmers. Under insurance scheme, loanee farmers are supported to pay premium dues for availing crop insurance facilities. Other services like trainings at various levels, demonstrations, exposure visits, exhibitions, kisan melas, field days, monitoring and evaluation of all these activities under these programmes are provided to the farmers with collaboration of extension officers.

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.

Weather and climate have profound influence on agriculture of a region. There are some differences between these two terms. Weather describes the state of the lower atmosphere of a place with respect to temperature, precipitation, wind direction, wind speed, humidity, cloudiness and pressure etc. over a short period of time. The short term variations over minutes to days are indicated as weather of a location. It says whether the atmosphere is hot or cold, rainy or dry, sunny or cloudy, still or cyclonic and so on usually for period of 24 hours. The weather may vary from place to place and from time to time due to difference in temperature, cloudiness, humidity, rain and other events of atmosphere. It may be sunny at one locality, but rainy at another locality.

Principle

β-Glucosidase (BG) plays a major role in the degradation of soil organic matter and plant residues. It catalyzes the hydrolysis of β-d-glucopyranosides, the final, rate-limiting step in the degradation of cellulose, the most abundant polysaccharide providing simple sugars for the soil microbial population. BG has been shown to be sensitive to changes in soil and residue management as well as an early indicator of changes in SOC before these changes are reflected in total or organic C analyses. The method is based on colorimetric determination of the p-nirtrophenol released by β-glucosidase when soil is incubated with buffered PNG solution and toluene.

Introduction 
Artificial intelligence (AI) has undoubtedly had an important influence in the restructuring of higher education by altering traditional teaching techniques and opening the way for long-term growth and innovation. This paradigm shift is distinguished by the usage of sophisticated software algorithms, data mining models, and data analytics into pedagogical and administrative practices. AI technologies have the potential to transform higher education by improving individualized learning experiences, streamlining institutional procedures, and enabling novel research approaches. Universities and colleges that embrace AI technology can not only better prepare students for the problems of tomorrow’s labor market, but also make important contributions to accomplishing sustainable development goals (Lomine, 2024). The inclusion of AI into higher learning is about more than just keeping up with technical breakthroughs; it is about completely altering the educational landscape to satisfy the demands of a digitally native population. Furthermore, the use of AI in this domain not only promises to improve educational outcomes, but it also poses important concerns regarding equity, ethics, and educators’ future role. Artificial intelligence (AI) has undeniably transformed the structure of higher learning, providing a blueprint for long-term progress and innovation in academia. The prospect of AI to revolutionize traditional education techniques and drive long-term growth for future leaders is unsurpassed. Aggarwal, Sharma, & Saxena (2023) proposed that incorporating AI into higher education is critical for educating graduates for the dynamic needs of tomorrow’s labor market as well as also building a more inclusive and forward-thinking academic environment. This paradigm shift toward integrating AI in academia has the capacity to generate a lively and efficient learning ecosystem which suits the different demands of students while also giving real-time feedback to improve academic achievement and retention rates. Furthermore, the application of AI in academic settings can transform research processes by enabling data-driven insights, boosting interdisciplinary partnerships, and hastening the pace of innovation in a variety of disciplines of study.

Introduction

Thar Desert is unique both from floristic and climatic parameters. Biodiversity in this region survives on a very/ fragile ecosysytem under a highly hostile environment. Major area consists of dry undulating mass of loose sand, thus, leading to shifting sand dunes. The sandy plain is full of sand-hills with serve as low depressions where salt and soda are deposited after drying. The whole area is inhospitable and sterile. Trees are rather a few and far between (Bhandari, 2005).

The Thar Desert of western India is known for its rich and ancient culture system and traditions. The communities have long been part of the Thar Desert ecosystem and have evolved specific strategies to live in harmony with its hostile environment. Orans have remained mainstay in balancing this arid ecosystem. Man of this region has never been greedy as he is today. Orans were repositories of ancient system of gene pool conservation. But, there are unregulated encroachment on the marginal lands and over-exploitation of groundwater resources. Orans has been part and parcel of the lifestyle of the Thar Desert inhabitants. Orans are used to provide vital grazing land for livestock, water, minor forest produce, medicinal plants and green cover for the villages. They were worshipped as devbhumi. Orans preserve the endemic, endangered or threatened species, medicinal plants and wild variety of cultivars found.

8.1 The purpose of erosion research

The need for research

A soil conservation programme needs to be based on factual information about rates and quantities of erosion. For example some land obviously needs to be protected by mechanical works such as channel terraces, some land equally obviously does not need any protection, and a great deal of land lies somewhere between the two extremes. At some point the terraces become unnecessary or uneconomic, but a logical decision on where to draw the line can only be made if data are available on how much soil erosion is occurring and how much it would be reduced by terraces. Similarly, the effect of channel terraces should be compared with the effect of alternative measures, and the effect should also be measured on the different soils and crops which are likely to be encountered.

Nowadays there are excellent opportunities for research workers to exchange the results of their work. The national and iniernational journals are packed with accounts and results of research reports in their proceedings (as listed in Further reading). Some of the reported research results can be usefully applied in countries other than where the research was done, but care is required in any transfer of technology. If the local conditions of soil, climate, or land use, are different, the results may not apply. However, research in other situations can often serve as a pilot trial to show which factors should be studied locally. Even when local conditions are so different that the results do not apply at all, the techniques and apparatus developed by other workers can still be helpful.

7.1 The purpose and type of models

Sometimes the simplest way to estimate the effect of a physical process is to use an established equation, or formula, or charts and diagrams based on existing knowledge. The current fashion is to call such aids and solutions models, and they tend to become increasingly complicated and consequently dependent on computers to handle the mathematical processes.

It is important to identify the exact objective and purpose of models which are designed to estimate soil erosion. Two main divisions are models for prediction and models to assist with explanation. If the purpose is to predict amounts of erosion under alternative management practices then empirical models such as the USLE are efficient and effective. For an understanding of the processes of erosion it is necessary to turn to physically-based or deterministic models. The two objectives should not be cross-threaded onto the wrong kind of model, i.e. the USLE should not be seen as a vehicle for research studies on the mechanics of erosion. Neither should sophisticated simulation models be used as the basis for evaluating conservation practices which are better designed on the basis of experience, and evaluated by direct testing in the field.

The different kinds of models need a short explanation:

An empirical solution or model is one based on observation or experiment, and not derived from theory. It fits observed facts, and allows us to predict what will happen in certain circumstances, because we know what has happened before in those circumstances. The reliability of such methods depends on the database of experience: we might say This will certainly happen’ (because it always does), or “Will probably happen’ (because it usually does), or ‘it may happen’ (because it sometimes does). An empirical solution may be a simple approximate relationship or a complex multiple regression equation.

12.1 The nature of gully erosion

Gully erosion is spectacular and widespread, and so it is often used by conservationists as a characteristic symptom of erosion. As a result there is a danger of its importance being over-emphasized. Certainly it is most important as a source of sediment in streams, but in terms of damage to agricultural land or reduction of agricultural production, it is usually not very important for the simple reason that most land subject to severe gully erosion is of little agricultural significance. The really spectacular erosion so popular in non-technical reports shows large areas cut up by deep interconnecting gullies, but this situation is usually found in semi-arid climates unsuitable for any serious agriculture, or on soils which have such adverse chemical or physical properties that their potential production is very low. Added to this is the fact that gully control is always difficult and expensive, so the cost of reclamation usually exceeds the value of the land. Certainly in the sense of reducing the amount of eroded soil choking the dams and rivers it may be highly desirable to do something about gully erosion, but it is very much a case of prevention being better than cure. Limited resources in manpower, money and materials can usually be better employed in preventing future gullies than in curing existing ones.

The worldwide occurrence and recognition is well demonstrated in the variety of names: in English and American - gully, in Egypt - wadi, in South Africa - donga, in French-speaking lands - ravine, in India - nulla, in South America - carcava, or arroyo, and many others. The definition is the same in any case, a steep-sided eroding watercourse which is subject to intermittent flash floods. They are more common in semi-arid climates with infertile soils and sparse vegetation, but some spectacular examples are found in tropical forests in deep soils with dense vegetation.

5.1 Definitions

The erodibility of soil is its vulnerability or susceptibility to erosion, that is the reciprocal of its resistance to erosion. A soil with a high erodibility will suffer more erosion than a soil with low erodibility if both are exposed to the same rainfall. Whereas the erosivity of rainfall was shown in chapter 4 to be a fairly straightforward measure of the rain’s physical properties, the assessment of erodibility is more complicated because it depends upon many variables. There are alternative uses of the term erodibility. In the widest sense it can be used to include all the variables which effect erosion except the erosivity of rain, as in the first line of figure 2.2. It is also used in the narrower sense as a measure only of the effect of physical characteristics of the soil, as in the erodibility index K of the Universal Soil Loss Equation, where the effects of land management and crop management are assessed separately, as shown in the last line of figure 2.2.

5.2 Factors influencing erodibility

In this chapter we will look at the three broad groups of factors which affect erodibility. First, there are the physical features of the soil, including the chemical and physical composition. Second, there are the topographic features, such as the slope of the land. Third, there is the management of the land, i.e. how it is used.

6.1 Quantities and rates of runoff

Before a start can be made on the design of the channels and ditches and other works which can deal with surface runoff we need to know the probable quantity of water. If the object is to impound or store the runoff then it may be sufficient to know the total volume of water to be expected, but the usual conservation problem is conveying water from one place to another, and in that case the rate of runoff is more important, and particularly the maximum rate at which runoff is likely to occur. That is the flow which a channel must be designed to accommodate.

In a hypothetical catchment area* with an impervious surface and no losses the maximum rate of runoff would be directly proportional to the rate of rainfall. In natural catchments there are other factors: some of the rain is intercepted by vegetation, some infiltrates into the soil, some starts moving over the surface but is trapped in depressions, and some is lost by evaporation. Estimates of rates of surface runoff therefore depend on two processes: estimating the rate of rainfall, and estimating how much of the rainfall becomes runoff.

There are several empirical methods for doing both and for combining the two factors, but because they are empirical two points must be stressed. Firstly, as with all empirical solutions, data, tables, and formulae developed in one situation should not be applied in different conditions without careful checks on whether the method is valid in the new situation. Secondly, each of the three main methods which will be

Introduction

Much of the world’s agricultural biodiversity is found in environments marginal for agricultural production. It is in such environments where management of high levels of diversity can become a central part of the livelihood management strategies of farmers and the survival of their communities. Abiotic stress can be termed as the negative impact of environmental factors on the organisms in a specific situation. It is a natural phenomenon that occurs in multiples and interdependent, and its impact varies across the sectors of agriculture. Abiotic stress is the primary cause of crop loss worldwide, reducing average yields for most major crop plants by more than 50%. Drought and salinity are becoming particularly widespread in many regions, and may cause serious salinization of more than 50% of all arable lands by the year 2050 (Wang  2003). Environmental stresses such as erratic and insufficient rainfall, extreme temperatures, salinity, alkalinity, aluminium toxicity, acidity, stoniness and others limit yield and productivity of many cultivated crop plants. Not only are such problems serious today, it seems they are inevitably worsening.

Mammals are homeothermic, meaning that they have the ability to control their body temperature within a narrow range in an environment whose temperature may change over a wide range.

India is experiencing a phenomenal spurt in the growth of livestock and poultry sectors through various timely and quality measures scientifically over a few decades. Milk production rose by a large leap from about 17.0 million tones in 1950 to about nearly 100 million tones in 2005 standing first in the world for maximum quantum of milk production. From about a ‘naught’ during 1950, the commercial layers have increased to 220 millions in 2005 producing 4500 crores of eggs every yearranking 5th in the world. The meat production is absolutely fascinating with 20 million birds in 1960 to about 2100 million in 2005 (Table 10.1).

Increase in ambient temperature, drought, rainfall, desert, feed and fodder scarcity, water scarcity and other climatic stresses are very common to tropical climatic conditions. The animals living in tropical climate have to undergo some modification for their survival under such extreme conditions. Interestingly, higher percentage of livestock is found in tropical and sub-tropical regions of the world. These areas are rich in animal resources. There are several descriptive and non-descriptive breeds of bovine distributed in different agro-climatic conditions of India. They possess several traits which make them adaptive to such climatic conditions. Identifying those traits and propagation of such traits is beneficial in near future in respect of climate change scenario. Climate change is the major concern for the improvement and sustainability of livestock under tropical climatic conditions. The rising of temperature and humidity is one of the major threats to animal’s productive performance that leads to great economic losses. Upadhyay et al. (2009) estimated 2% loss of milk production due to thermal stress in India. It has also been expected that 3.2 million tons reduction by 2020 and more than 15 million tons by 2050. The decline in milk production reported to be higher in crossbreds (0.63%) followed by buffaloes (0.5%) and indigenous cattle (0.4%) (Upadhyay et al., 2009).