eChapters

The movement of water from soil to the crop canopy and leaves to provide water for transpiration and the effect of weather factors on transpiration is most important area of study. When the crop is just sown, there will be an only evaporation of water from the soil. After germination of seeds there will be emergence of seedlings. After the emergence of seedlings there will be formation of leaves. The small leaves start intercepting the incoming solar radiation and absorb some portion of solar energy, get heated and there will be evaporation turn off water from the stomata of the leaf. When water vapour escapes into the atmosphere through the stomata of leaf, the plant absorbs carbon dioxide which results in photosynthetic activity. During night time, there will not be any photosynthesis due to absence of sunlight. The plants use parts of the photosynthetic accumulate for its metabolic activity and the process is called maintenance respiration. The balance of the photosynthetic accumulate contributes to the expansion of leaves and increased dry matter accumulation in crop plans. The process of dry matter accumulation in plants is called crop growth. When the seedlings start growing, there will be formation of tillers or branches. When the leaves grow it reaches a stage when the crop will be completely shading the ground and the soil evaporation will be minimum and maximum amount of water is lost only through evapotranspiration (Fig.6.1).

19.1 Introduction

The combination of two separate processes whereby water is lost on the one hand from the soil surface by evaporation and on the other hand from the tree by transpiration is referred to as evapotranspiration (ET).

19.2 Evaporation

Evaporation is the process whereby liquid water is converted into water vapour (vaporization) and removed from the evaporating surface (vapour removal). Water evaporates from a variety of surfaces, such as lakes, rivers, pavements, soils and wet vegetation. (Penman, 1963).

Energy is required to change the state of the molecules of water from liquid to vapour. Direct solar radiation and, to a lesser extent, the ambient temperature of the air provide this energy. The driving force to remove water vapour from the evaporating surface is the difference between the water vapour pressure at the evaporating surface and that of the surrounding atmosphere. As evaporation proceeds, the surrounding air becomes gradually saturated and the process will slow down and might stop if the wet air is not transferred to the atmosphere. The replacement of the saturated air with drier air depends greatly on wind speed. Hence, solar radiation, air temperature, air humidity and wind speed are climatological parameters to consider when assessing the evaporation process.

Where the evaporating surface is the soil surface, the degree of shading of the tree canopy and the amount of water available at the evaporating surface are other factors that affect the evaporation process. Frequent rains, irrigation and water transported upwards in a soil from a shallow water table wet the soil surface. Where the soil is able to supply water fast enough to satisfy the evaporation demand, the evaporation from the soil is determined only by the meteorological conditions. However, where the interval between rains and irrigation becomes large and the ability of the soil to conduct moisture to pear the surface is small, the water content in the topsoil drops and the soil surface dries out. Under these circumstances the limited availability of water exerts a controlling influence on soil evaporation. In the absence of any supply of water to the soil surface, evaporation decreases rapidly and may cease almost completely within a few days.

The geologists of the Indian subcontinent have all along been of the opinion, that, the southern part of the Indian Peninsula is a stable shield area. But, the recently acquired IRS-1A image of June, 1988 vividly displays spectacular geomorphic anomalies suggesting that this part of the Indian subcontinent is prone to earth movements. In order to unearth more evidences on such earth movements / neotectonism in Tamil Nadu, the IRS-1A image of Coromandel coast of Tamil Nadu was analysed ( Fig. 1).

OBSERVATIONS

• The IRS-1A image conspicuously displays three contrasting morphotectonic domains in the study area marked by the western undissected Tertiary upland (Vallam upland), central highly dissected Tertiary upland (Pattukottai -Mannargudi upland) and the eastern Cauvery delta (Fig 1 and 2). These three domains are separated by two conspicuous N-S trending lineaments (E and F, Fig.1 and 2) namely the Tanjavur - Avadaiyarkovil lineament in the west and Kumbakonam -Muttupet lineament in the east.
• In addition, two more E-W trending lineaments (G and H, Fig.1 and 2) are also observed trifurcating the undissected Vallam upland into three blocks.
• Along these lineaments, especially the Tanjavur -Avadaiyarkovil and Kumbakonam -Muttupet lineaments, the rivers show conspicuous drainage anomalies in the form of drainage deflection, drainage compression etc., wherever they transect the lineaments.

Agriculture has progressed from labour-intensive traditional practices through mechanization and the Green Revolution to precision agriculture and Agriculture 5.0. This chapter traces that historical development and identifies limitations associated with conventional farming, including inefficient resource use, environmental degradation and weak adaptability. It explains how GPS-guided machinery, sensors and precision technologies prepared the foundation for intelligent systems. Artificial neural networks, deep learning and fuzzy logic now process data from IoT devices, UAVs and satellites to support automated irrigation, crop monitoring and soil analysis. The chapter emphasizes that integrating human knowledge with computational power is increasingly essential for global food security, sustainability and climate resilience.

Modern farm planning involves nonlinear, discontinuous and multi-objective problems that conventional optimization methods may not solve effectively. This chapter examines Genetic Algorithms, Particle Swarm Optimization and Differential Evolution for improving agricultural resource allocation. These nature-inspired techniques can simultaneously address crop yield, water use, fertilizer application, environmental effects and financial viability. Their integration with deep-learning forecasts and crop-simulation systems enables more realistic optimization. Multi-objective evolutionary algorithms identify Pareto-optimal alternatives, allowing decision-makers to balance productivity and ecological sustainability. The chapter also emphasizes explainable artificial intelligence, economical implementation and farmer usability as necessary conditions for transferring evolutionary optimization methods from experimental research to practical farm management.

6.0 General

No lessons can be drawn without the experiences of the past. In fact, much of engineering, rather all sciences have developed in bits and pieces from the experiences of the past. The engineers by and large have never become wiser in one day. They have become wiser slowly and slowly with their own experiences and from the experiences of past engineering works. Wisdom lies to gain wisdom from experiences/draw lessons from the marvellous engineering works constructed so far. It helps us in a direction for further development of technological skills.

Here an effort is made to draw lessons from experiences of the canals constructed in the past.

 There are several aspects of such experiences. A few important aspects of studies are:

 (i) Internal hydraulic sections of the canal with respect to discharge, topography, stability of side slopes, type of lining, operation and maintenance problems and their solutions etc.

 (ii) Design of canals banks (embankment) with respect to discharge, depth of flow, depth of cutting /filling, below/above natural ground level, type of soil, topography, operation and maintenance, drainage of banks etc.

 (iii) Canals aesthetics and arboriculture

 (iv) Other utility/service of canal such as multi-objectives of hydropower, irrigation, drinking/industrial water supply, social needs of recreation, forests etc.

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

ABSTRACT

Remote sensing, especially high resolution satellite data has a major role to play in locating (localizing) mineral targets. The present study is carried out on exploration and discrimination of magnetite ore deposits of Tirthamalai region of part of Dharmapuri district, Tamil Nadu, India, using IRS P6 LISS IV high resolution satellite data. The applicable image processing techniques and associated put forth of field knowledge is used in the present study. The image processing classifications namely band rationing, principal component analysis and contrast enhancement are carried out in visualizing images using ERDAS Imagine 8.7 software. The visual interpretation of FCC of digital data shows that the raw pixel values of iron ore bands in the blue ranges 95 to 120, green ranges 85 to 125 and red ranges 55 to 75 and provided better delineation for iron formations.

The interpretation of satellite data shows that the iron ore band exhibits in dark color, linear shape, fine texture and sharp contact with associated rock types. To rectify and reduce misinterpretation all above image processing techniques are undertaken along with the detailed filed-check in the selected test sites using GPS 178 and delineated the in situ iron formations. The interpretations show that the occurrence of few more iron bands and weathered formations along with massive formations in the region traced on the imagery since the absorptions themselves are different. The availability spectral absorption of iron formation is inferred highly in visible and near infrared region (0.9-1 Ìm). Remote sensing high resolution satellite data proved that the satellite parameters are important criteria and play a vital role in mapping of low-grade iron ore deposits of the Tirthamalai region of Dharmapuri district of Tamil Nadu state.

1. Background
The growing global population, industrialization, and urbanization have driven rising energy demand, with primary energy use increasing by 5.8% in 2024 (BP Statistical Review of World Energy 2024). The need for secure, affordable, and low-carbon energy is critical due to fossil fuel depletion, global warming, and geopolitical tensions. Clean energy sources like solar, wind, and biofuels are being explored, with biodiesel standing out as the only biofuel capable of fully replacing fossil fuels (Aizouq et al., 2020). Many countries, including India and China, are advancing biofuel production, with the latter viewing it as a key to energy security. Biofuels, derived from various sources like algae, crops, and waste, include biodiesel, bioethanol, and biogas. They are categorized into four generations based on feedstock. First-generation biofuels, made from edible materials, face food vs. fuel competition. Second-generation biofuels from non-edible sources are more sustainable but still face resource limitations (Lv et al., 2019). Thirdand fourth-generation biofuels from microalgae offer higher yields and better land use, with species like Chlorella vulgaris and Nannochloropsis oceanica showing promise for biodiesel production. Microalgae’s fast growth and efficiency have led to advances in biodiesel production, although challenges remain, such as species selection and production scale-up (Arora et al., 2021). But there is a constraint for commercial availability of these biofuel which are the economic and environmental obstacles that are creating problematic condition for approval and use of genetically engineered microalgae for their potential to enhance lipid yields. This chapter delves into the current opportunities and challenges in microalgae biofuel production, focusing the need for regular research and innovation (Maliha and Abu-Hijleh 2022).
2. Choosing the Different Classes Of Microalgal Strains
The achievement of huge-scale microalgal culture relies on picking appropriate species. The production of various lipids greatly affects the selection of strains and biofuel properties. For the biodiesel, Triacylglycerol (TAG) is the preferred lipid but compared to green algae its content is typically low in cyanobacteria. with the average lipid content of 25.5%, green algae (Chlorophyceae) stand as the largest class of oleaginous microalgae, which can rise under nutrient stress (Saini et al., 2021). Also, the biomass productivity is equally important for high lipid productivity as high lipid content is beneficial. For biodiesel production, strain selection should focus on both lipid content and biomass. Chromochloris zofingiensis shows the highest lipid productivity among all classes of green algae. The saturated (SFA) and monounsaturated fatty acids (MUFA) fatty acid (FA) being dominant, their composition also plays a vital role in biodiesel quality. It has seen those high levels of C16:0 and C18:1 in microalgae is ideal for biodiesel production (Bharti et al., 2021). Therefore, for improved biodiesel performance, strain selection should consider both lipid productivity and FA composition (Bagchi and Mallick, 2016).

1.1. Extension

Educational process for bringing about maximum number of desirable changes among the people

In India’s National Extension Programme, professional workers constitute the link between the people and the institute created to advance economic and social change upon the character philosophy, technical knowledge and compliance of these workers largely rests for the success of the programme. Hence the quality of these workers and their training is the important element to be dealt with properly and guided wisely.

In early fifties, the Gramsevak / Village Level Workers (VLW’s) served as a key-man in Community Development Programme and therefore, the Government of India aimed at imparting him by better training and supervisory assistance. As a step in this direction, Gramsevak Training Centers were started to impart training to GramSevaks / VLW’s and Extension Officers were appointed in block for better supervisory assistance.

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.

In previous section we discussed about the ability of the research design to precisely detect the relationship between cause and effect under controlled conditions. But in social research it becomes difficult to conduct the research under highly controlled conditions and moreover many of the researches in social science aim at prediction rather than understanding.

As we discussed earlier, aim of science is development theory, understanding, prediction and explanation of natural phenomenon. In many of the cases we are more interested in predicting the occurrence of social phenomenon rather than explaining it or understanding its relationship with other phenomenon. Under such conditions internal validity is of less use because a relationship that is established in artificially controlled conditions (with high internal validity) may fail to express itself in natural setup due to effect of extraneous variables. When the relationship between cause and effect is weak enough to be expressed in natural setup then it is of less use in predicting the phenomenon. Under such conditions we require experiments that are conducted in nearly natural setup, so that we can generalize the findings of the research to the wider domain.

Introduction 
The increasing prices of fast-depleting fossil fuels and their environmental impact have driven the quest for alternative fuels for diesel engines. Because of their higher biomass yield, faster growth rates, and superior photosynthetic efficiency when compared to other energy crops like soybean and rapeseed, microalgae are considered as promising candidates for biofuel production (Mubarak et al., 2015). Numerous species of microalgae have been found to have high lipid contents, making them attractive cell platforms for the synthesis of lipids. Their significance as a backup source of bioenergy in the future is indicated by the ease with which their lipids can be transformed into biodiesel (Ren et al., 2021). Tiny photosynthetic organisms known as microalgae are the ancestors of eukaryotic plants on Earth. These organisms range in size from one to hundred microns and are either unicellular or multicellular (Udayan et al., 2022). Due to the genetic and biochemical diversity of their lineages, algae are able to synthesize a wide range of metabolites, including lipids (Manning, 2022). Glycerolipids are the most prevalent and well-known lipid class in microalgae. Glycerolipids are categorized into two classes based on their functions: storage lipids and structural lipids. Membrane lipids, a type of structural lipid, play a crucial role in forming cell and organelle membranes. They typically consist of two fatty acid groups attached to a glycerol backbone, along with a polar group bound to the glycerol structure (Morales et al., 2021). In contrast, polar lipids have a higher oxygen content and possess charged side groups, enabling them to moderately interact with water. Examples include phospholipids and glycolipids (Manning, 2022). Microalgal lipid metabolism predominantly relies on the de novo fatty acid biosynthesis pathway and the triacylglycerol (TAG) synthesis route (Zhu et al., 2022). Therefore, accurately estimating the composition of the lipid fraction is crucial for determining its potential applications, whether as a raw material for biofuel production or for nutraceutical and/or food purposes (Viegas et al., 2020). The production of biodiesel from microalgae presents a novel approach to generating renewable and sustainable energy. Additionally, different techniques, including lipid extraction and transesterification, are utilized to transform lipid-rich microalgae biomass into biodiesel (Gaurav et al., 2024). Microalgae possess thick-walled cell structures, which restrict the release of their bioactive compounds due to the rigidity of the microalgal matrix. Consequently, selecting suitable pre-treatment and extraction methods is essential for effectively obtaining lipids from microalgae while preserving their bioactivity. Traditional methods for lipid extraction, such as Soxhlet extraction, Folch extraction, and Bligh-Dyer extraction, have been used for a considerable time. While these techniques are generally easy to use and cost-effective, which encourages their adoption, they also have drawbacks, including high consumption of organic solvents, environmental pollution, and extended extraction times that can last several hours. Thus, it is essential to investigate suitable techniques that enhance the extraction rate and lower costs while ensuring the bioactive properties of lipids, enabling better industrial applications of microalgae (Zhou et al., 2022). In recent years, the use of nanotechnology and nanoparticles has emerged as a novel approach for extracting valuable metabolites or bioproducts from microalgae. Nanoparticles (NPs) are materials engineered with at least one dimension measuring less than 100 nanometers (nm). Due to their small size and large surface

Abstract

It has been established beyond doubt that the drainage architecture and the fluvial histories of river systems give excellent indications not only on the surficial lithology but also on the ongoing morphotectonic processes of the planet earth. Among the various drainage patterns, the ‘eyed drainage’ pattern is considered to be one of the most significant anomalies and such ‘mega eyed’ drainages interpreted from IRS-IA imagery in some of the major river systems in Tamil Nadu, Indian Peninsula, are found to signify ongoing tectonic movements in an otherwise seismically inert shield area.

3.1. Non-Climatic Factors

Apart from climate several other non-climatic factors has to be considered before selection of proper greenhouse technology, which are listed in the following text.

1. Location and selection of site: The ideal location for greenhouse cultivation is an area having moderate climate with high sunlight, low humidity and good natural drainage. It is better to avoid storm prone areas or it is a must to take necessary protection, like wind-break and shelter belt, in such areas. However, selection of site, where the greenhouse will be constructed, is the first consideration to select the proper greenhouse technology. The proper selection of site will also depend upon various non-technical factors, which are listed below.

    1.    Wohler (1828) synthesized the first organic compound, urea from inorganic components.

    2.    Emil Fischer (1894) demonstrated the specificity of enzymes and the lock and key relationship between enzyme and substrate.

    3.    Michaelis and Menten (1913) developed kinetic theory of enzyme action

    4.    Watson and Crick (1953) Proposed the double-helical model for DNA structure

    5.    Ingo potrykus (1999) Golden rice- rich in b-carotene.

    6.    Glyoxysomes : Glyoxysomes are temporary in that they occur during transient periods in the life cycle of a plant such as in certain beans and nuts which store fats in their seeds as energy reserves. Glyoxysomes appear in the first few days after seed germination in endosperm cells and associate closely with lipid bodies. They disappear after the storage fats are broken down and converted into carbohydrate.

1.1. Farm business management

Concerned with resource allocation.

Useful to impart knowledge and skill for optimizing the resource use and maximizing profit.