eChapters

Introduction

The egg production in India is 75 billion and the broiler production is 4.2 million tonnes per annum. The growth rate of layer market is 6-7 percent per annum and broiler market is 8-10 percent per annum. The Indian poultry sector is valued at INR 1 lakh cr or USD 15.38 bn. Approx. 80 percent of egg production is contributed by commercial poultry farms, remaining comes from household/ backyard poultry. Backyard poultry plays a key role in supplementary income generation and family nutrition to the poorest of the poor. It is estimated that there are around 30 million farmers engaged in backyard poultry as per 19^th Livestock Census. Backyard poultry are being practiced for its inherent strengths. Free range birds reared by the farmers have the advantage of small body size, coloured plumage, broodiness to hatch chicks, adaptation to harsh climatic condition, lower diseases and production with least investment. The birds are scavenging in the backyard, supplemented by kitchen waste and are kept in low height houses for shelter using locally available materials. It helps to improve the nutritional status of rural poor and also improve the subsidiary income of the poor people. Such stocks make minimal use of land, labour and capital and integrate well into the backyard. Backyard poultry production system is self-sustaining because of minimal needs and can be afforded by poor people of the rural areas. The high yielding white feathered chicken varieties being reared in the intensive poultry farming are not suitable for backyard / free range backyard poultry farming due to the adverse climatic and high pathogen load prevailing in such rearing practices. Backyard poultry farming is an in-separable part of the poor tribal people and it will continue to be due to its advantages. Although backyard poultry production is not an occupation per se, it often supplements household income, primarily for poor families. Strengthening backyard poultry production may help overcome poverty and malnutrition in impoverished communities. However, the effect of climate change on these birds needs to be studied for its sustenance.

9.1 Introduction

Background increase in anthropogenic emissions of Greenhouse gases, associated climate change and its global consequences are issues of concern. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (FAR) reveals that warming of the climate system is evident from the increase in global average air and ocean temperatures, widespread melting of ice and the rising global average sea level. The report states that the global mean temperature may increase between 1.4 and 5.8^oC by 2100, which will have severe impact on the global hydrological system, other ecosystems, the sea level, and agriculture. The impact could be particularly severe in tropical countries including India. Thus climate change is unavoidable and associated weather extremes such as high temperature and heat waves; increase frequency of droughts and high intensity rainfall causing flood are the issues of concern for Indian Agriculture.

Additive manufacturing is increasingly important for developing resource-efficient and customized products while reducing material waste associated with conventional manufacturing. This chapter examines the role of additive manufacturing in supporting green and sustainable production systems. It covers environmental benefits, economic and operational advantages, additive manufacturing technologies, sustainable applications, life-cycle assessment, environmental impact analysis, challenges, and design strategies. Industry trends, case studies, sustainability standards, and future research directions are also considered. In the context of green composites, additive manufacturing can support flexible fabrication and potentially improve material utilization and product customization. The chapter emphasizes the need to evaluate manufacturing technologies across their complete environmental and economic life cycle.

ABSTRACT

The use of Geographic information system to locate groundwater possible zone in Valapadi taluk of Salem was carried out using remote sensing and geophysical studies. The remote sensing methods involved in the visual interpretation of the satellite images for hydrogeomorphological and hydro structures favourable for groundwater. The geophysical method involved vertical electrical soundings to predict the sub-surface variation and to locate the water domain. Three geoelectric layers were delineated from the interpretation of vertical electrical sounding data and the map of the above results predict the depth extent of groundwater zone. The spatial distribution of the above results was identified through GIS.

Introduction

The hot arid regions of India are spread over 32 million ha (0.32 million Sq.Km.) in the state of Rajasthan (61%), Gujarat (20%), Andhra Pradesh (7%), Punjab (5%), Haryana (4%), Karanataka (3%), and Maharashtra(0.4%) which are characterized by hostile agro-climatic conditions and fragile eco-system. Out of total hot arid area of the country (India), more than 60% area falls under the state of Rajasthan which covers 12 districts viz., Jaisalmer, Barmer, Bikaner, Churu, Sikar, Jhunhjunu, Naguar, Jodhpur, Pali, Jalor, Sriganganagar, and Hanumangarh of the state. In general, the hot arid region of Rajasthan receives very low rainfall, varies from 100 mm annun^-1in north-western district of Jaisalmer to 450 mm per annum in the eastern boundaries of arid district of Rajasthan. The potential evapo-transpiration varies from 2063 mm in Jaisalmer to 1503 mm in Sikar districts of Rajasthan. The rainfall is very erratic and often experienced prolong drought. The ground water table is very deep and often brackish in nature. The extremes of temperature having severe winter during December-January with temperature as low as -4 °C and very hot summer during May-June with temperature as high as 48-50 °C is another important characteristic of the hot arid regions. The solar radiation is very high. Atmospheric vapour pressure deficit reaches as high as 30 mb during summer (May-June). The wind velocity in June is very high which leads to heavy wind erosion and formation of sand dunes. Some time strong sand storms of very high speed (60-0 km h^-1) with huge amount of sand particles also occurs. The soils are coarse textured with low silt, clay and humus content and water holding capacity is very low and infiltration rate is very high. The soil fertility is very poor having low organic carbon (0.02-0.06%).

Understanding the mechanisms controlling the adsorption of organic molecules on clay minerals is of significance in many branches of science and industry. The interaction between clay minerals and organic compounds elicits interest that emanates from the prospect that the adsorption of the organic matter fraction in the soil on the mineral particles would render physical stability to soil aggregates.

Organic compounds tend to interact with clay minerals by:

• adsorption process at the external surfaces
• adsorption process at the external and internal surfaces

Introduction

Agriculture contributes a vital part within the financial stability of smallest emerging nations such as Pakistan as well. The economic system of Pakistan is fundamentally based upon agriculture (Govt. of Pakistan, 2004-2005). The total surface of Pakistan approximately 796,095 km2, of which 8.3 million km2 are uncultivated and 22 million km2 are farmed (Govt. of Pakistan 2015 2016). Despite an average yearly increase of 2.7%, agriculture contributes 21% of Pakistan’s GDP (Govt of Pakistan, 2004–2005). Farming is a sector whose fundamental and commercial models combine. Agriculture’s importance to the economy may be examined through three distinct perspectives: 1) as a source of nutritious food for the country and raw materials for internal industry; 2) as a way to generate currency from abroad and 3) as a source of products and services for local industries and the global market (Govt. of Pakistan, 2015-16).

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

6.1 INTRODUCTION

Besides simple analysis, GIS is useful to do advanced analysis like network analysis, spatial analysis, 3D analysis and modeling. Different softwares are available to perform such analysis and the above mentioned analysis is done in separate modules of the softwares.

6.2 NETWORK ANALYSIS

Network consists of well connected linear features. Roads, railway line, water distribution system, sewer line, streams are some of the examples of networks. These networks consists of nodes and arcs with designated directions and connection with other linear features. Networks are topology based with attributes for the flow of objects like traffic. Road network will be considered for explaining network analysis.

Road map is digitised with nodes and arcs. Signals, accidents are represented as points. Road is represented as line and two or more roads intersect at nodes. Attributes are added to the nodes and lines. Dynamic segmentation model is used for network analysis. It is built on lines of network. In road network analysis, attributes for travel time, one way street, two way street, right turn, impedance are added to the nodes and arcs. A link is the line running between two nodes. Link impedance is the cost of passing through the link. Travel time is different in links in cities due to varying traffic at different locations. Time taken to pass through a known length of link may give the cost but the travel time in a link is not uniform because of varying speed designated in the link as 20 km per hour and 30 km per hour. Hence it is important to consider the length of link and also the travel time. If the speed limit is 20 miles per hour for a length of 2 miles, then the travel time is 6 minutes (2/20x60 minutes). Also tuning in the network is considered. A road may have a maximum of 12 possible turns excluding U turns. There are right turn, left turn, straight way for each road. Also U turn is possible. This turning takes different time depending on the signal. Straight way takes less time but left and right turn may require some more time. If signals is available then signal time should also be taken into account. Fig 6.1 show the possible turns in a road.

The advent of advanced technologies and methodologies has revolutionized the field of crop disease forecasting, enabling researchers and practitioners to develop more accurate, reliable, and efficient forecasting systems. Conventional methods of disease forecasting, such as weather-based forecasting and statistical modeling, have been widely used for predicting crop disease outbreaks. However, these methods have several limitations, including reliance on historical weather data, limited spatial and temporal resolution, and lack of mechanistic understanding of disease development. In recent years, advanced methods of crop disease forecasting have emerged, leveraging cutting-edge technologies and methodologies to improve the accuracy, reliability, and efficiency of disease forecasting systems. These advanced methods include machine learning algorithms, artificial neural networks, geographic information systems (GIS), remote sensing technologies, and precision agriculture techniques. These methods have been shown to be highly effective in predicting crop disease outbreaks, and have the potential to revolutionize the field of crop disease management. Machine learning algorithms, for example, can be trained on large datasets of weather, crop, and disease data to identify complex patterns and relationships that may not be apparent through conventional statistical analysis. Artificial neural networks can be used to develop predictive models that can learn from experience and adapt to changing conditions. GIS and remote sensing technologies can be used to analyze and integrate spatial data on weather, crop, and disease patterns, enabling researchers and practitioners to identify areas of high disease risk and target interventions more effectively. Precision agriculture techniques, such as precision irrigation and fertilization, can be used to optimize crop growth and reduce disease susceptibility. These advanced methods of crop disease forecasting have the potential to transform the field of crop disease management, enabling researchers and practitioners to develop more effective and efficient disease management strategies. This chapter will provide an overview of these advanced methods, highlighting their potential applications and benefits in crop disease forecasting.
11.1 Remote Sensing Technology
Crop disease forecasting using remote sensing involves the use of satellite or aerial imagery to detect and predict crop disease outbreaks. The principles

Biofuel crops play a crucial role in the global transition towards renewable energy. With increasing concerns about climate change and energy security, biofuels have emerged as a viable alternative to fossil fuels. However, their economic viability is influenced by various factors, including production costs, market demand, government policies, and environmental implications. The United States has been the most prominent fuel ethanol producer since 2007, followed by Brazil. Together the United States and Brazil account for 84% of the global ethanol production. European Union, China and Canada are the other leading fuel ethanol producers. Fuel ethanol production and consumption continue to rise, regardless of variations in crude oil prices. The United States is the largest producer, generating 60 billion liters primarily from corn, while Brazil follows with 33 billion liters, mainly derived from sugarcane (https://www.statista.com.) Ethanol production in India started in 1938 with recommendations to convert molasses into alcohol, eventually resulting in the enactment of the Power Alcohol Act in 1948. The Ethanol Blending Programme (EBP), introduced in 2003, mandated a 5% ethanol blend (E5). However, due to supply shortages in 2004-2005, the blending requirement was made optional. In the 2013-14 period, a total of 38 crore liters of ethanol was procured for blending with petrol. This amount significantly increased to 567 crore liters in the Ethanol Supply Year (ESY) 2022-23, achieving an ethanol blend level of E11.7. Acknowledging the substantial progress in the ethanol fuel blending initiative for a greener transition and Atmanirbhar Bharat, the government revised the target to E20 by 2025–26 and set an E30 goal for 2030 (NAAS, 2024). The proposed share of E20 is from sugarcane-based ethanol 10%, maize 7% and other damaged food grains 3.0%. The recently reported data during Jan 2025 showed the achievement of 19.6% blending in petrol (PIB, GOI, 2025)

Introduction 
Fossils fuel resources are crucial for producing and distributing other goods, making them one of the most important global commodities. Fossil fuels account for more than 75% of total energy consumption in society. It is critical to recognize that the fossil energy problem and anthropogenic climate change problem are inextricably linked and must be addressed as two intertwined challenges requiring a comprehensive solution. The features of coal, oil and gas which are employed as fossil fuels for power generation, have different classification of characteristics (Shindell & Smith, 2019). Fossil fuels are natural fuels and derived from the decompositions, heating and pressurization, of buries phytoplankton (plants) and zooplankton (animals). Over time, these waste materials get decomposed to produce carbon rich deposits that are now used to create energy products (Holechek et al., 2022). They are essential for the synthesis of steel and polymers in addition to energy. Fossil fuels fall into three main categories: coal, oil, and natural gas (Singh et al., 2023). Biofuels are produced from plants and animals waste materials and considered as a renewable source of energy. The sources are key components to overcome the issues related to greenhouse gas emission. Due to rapid change in climatic conditions, demand of renewable energy sources has increased. There are some drawbacks for fossil fuels due to presence of high carbon footprints and environmental impacts. On the other way, biofuels offer two major benefits first they reduce carbon emissions and modify waste management method, the other paving the way for a sustainable future. The carbon neutrality of biofuels is among their most alluring features. Biofuels only release the carbon dioxide that plants consume during growth, as opposed to fossil fuels that release old, stored carbon into the atmosphere. They are an eco-friendly choice because of this balance(Jeswani et al., 2020). Bioethanol, biodiesel, and biogas are among the several types of biofuels(Esmaeili & Tamjidi, 2021). Bioethanol is used in transportation and produced by using crops like corn and sugarcane. Waste management and sustainable energy production are further enhanced by biogas after producing with the help of anaerobic digestion of organic waste and is a great source of energy for heating and power generation. We can take a comprehensive approach to sustainability, improving energy efficiency and lessening our environmental impact, by combining the production of biofuel with waste management and the use of organic fertilizers. Significance environmental benefits of biofuels include lower GHG emission, reduced dependency on the fossil fuels and better air quality. By diversifying energy sources and possibly stabilizing prices, they also lessen exposure to changes in the world's oil markets, which promotes energy security. Nonetheless, it is essential to evaluate the wider ramifications of biofuel production and make sure that its advantages exceed any potential disadvantages in order to completely match with sustainability goals(Jeswani et al., 2020).

Introduction

Solar energy could be converted to electricity both through thermal route and photovoltaic cells but the latter is more advantageous as it has no moving part, it doesn’t require water, a rare commodity specifically in arid regions. Moreover, the maintenance of PV systems is easy, it can be installed right at the place of utility, the system is modular and these are reliable having life more than twenty years and of course eco-friendly.

In photovoltaic cells, generally known as solar cells, charge carriers are generated by the incoming irradiance (energy greater than band gap) and these are separated and swept away by an internal electric field, which is created by either making metal semiconductors contact (Schottky barrier) or p-n junction or MIS (Metal Insulator Semiconductor) or SIS (Semiconductor Insulator Semiconductor) devices. The height of potential barrier at the junction determines the voltage and the flowing charge carriers contribute to the current when connected externally. The choice of material depends on its band gap, absorption coefficient, diffusion length, mobility of charge carriers, ease in contact formation, type of junction with thermal and electronic compatibility, availability of material, toxicity and several other fabricational opto-electronic and practical aspects. PV cells based on single crystal and polycrystalline silicon, amorphous silicon, CdS, CdTe, CuInGaSe, InP, GaAs etc. have been much studied. PV modules of efficiency above 16% on silicon and 10% on CdTe, CuInGaSe and 8-9 % on amorphous silicon are commercially available. Dye sensitized TiO₂ devices have also been receiving more attention with coloured panels for windows. Organic semiconductors are explored and more recently perovskite solar cell has been studied. Flexible solar cell panels based on thin film devices are in use. The applications have gone from solar lighting to operation of pumps, small and medium size equipment, stand alone and grid connected solar power plants, roof top and building integrated PV and now even energizing cars and aero planes. With technological advancement and enhanced production (233 GW in 2015) the cost of commercially available PV modules, which used to be high at one time has been brought down from 30 $/Wp in seventies to about $0.5/Wp at present.

The age-old struggle between crops and diseases has been a perpetual challenge for farmers and agricultural stakeholders worldwide. Weather patterns play a pivotal role in the development and spread of crop diseases, making it essential to integrate weather wisdom into crop disease management strategies. By analyzing historical and real-time weather data, farmers and agricultural experts can anticipate, prepare for, and respond to disease outbreaks more effectively, minimizing crop losses and ensuring food security. Effective crop disease management based on weather wisdom involves a three-pronged approach. It begins with caution, where historical climate data and disease surveillance reports are analyzed to identify potential correlations between weather patterns and disease outbreaks. This information helps farmers and agricultural experts to recognize early warning signs of disease susceptibility, such as temperature fluctuations, precipitation patterns, and humidity levels. For instance, excessive rainfall can lead to an increased risk of fungal diseases, while drought conditions can exacerbate bacterial diseases (Fig. 13.1). The confirmation phase involves closely monitoring real-time weather forecasts and disease surveillance data to detect early warning signs of an impending disease outbreak. Advanced technologies, such as satellite imaging and sensor-based monitoring systems, provide valuable insights into crop health and disease development. By combining these data streams, farmers and agricultural experts can confirm the presence of disease-causing pathogens and take targeted action to prevent their spread. Finally, a call to action is triggered, prompting farmers and agricultural stakeholders to implement integrated disease management strategies. These may include cultural practices, such as crop rotation and sanitation, biological controls, such as introducing beneficial microorganisms, and chemical controls, such as targeted fungicide applications. By leveraging weather wisdom, farmers can optimize their disease management strategies, reducing the reliance on chemical pesticides and minimizing environmental impact. By embracing weather wisdom, crop disease management can be transformed from a reactive to a proactive approach. Farmers and agricultural stakeholders can stay one step ahead of disease-causing pathogens, protecting their crops and ensuring a stable food supply. As we explore the intersection of weather wisdom and crop disease management, it becomes clear that this integrated approach holds tremendous potential for revolutionizing the way we predict, prevent, and respond to crop diseases.
13.1 Caution
Approaches to Caution Farmers on Crop Diseases, Information Generation, and Communication using Mobile Technology To caution farmers on crop diseases, it is essential to adopt a multi-faceted approach that leverages mobile technology to generate and disseminate critical information. This approach should focus on empowering farmers with timely and accurate information, enabling them to take proactive measures to prevent and manage crop diseases. Firstly, a robust disease surveillance system should be established to monitor and track crop disease outbreaks in real-time. This can be achieved through a network of field scouts, extension agents, and research institutions that report disease incidence and severity to a central database. Mobile-based applications can be used to facilitate data collection, transmission, and analysis, ensuring that critical information is captured and disseminated promptly. Once disease outbreaks are detected, mobile technology can be harnessed to generate and disseminate alerts to farmers. This can be achieved through Short Message Service (SMS) or voice messages, which can be sent to farmers’ mobile phones, warning them of potential disease risks and providing advice on management strategies. Mobile-based applications can also be used to push disease alerts, advisories, and management recommendations to farmers, ensuring that they receive critical information in a timely and accessible manner. To enhance the effectiveness of these alerts, it is essential to ensure that they are tailored to the specific needs and contexts of farmers. This can be achieved

Introduction

Although both maps and aerial photos present a “bird’s-eye” view of the earth, aerial photographs are NOT maps. Maps are orthogonal representations of the earth’s surface, meaning that they are directionally and geometrically accurate (at least within the limitations imposed by projecting a 3-dimensional object onto 2 dimensions). Aerial photos, on the other hand, display a high degree of radial distortion. That is, the topography is distorted, and until corrections are made for the distortion, measurements made from a photograph are not accurate. Nevertheless, aerial photographs are a powerful tool for studying the earth’s environment. 

Because most GISs can correct for radial distortion, aerial photographs are an excellent data source for many types of projects, especially those that require spatial data from the same location at periodic intervals over a length of time. Typical applications include land use surveys and habitat analysis. 

This unit discusses benefits of aerial photography, applications, the different types of photography, and the integration of aerial photographs into GISs.

ABSTRACT

Airborne geophysical methods are presently used all over the world to support mineral exploration by providing basic geological information to supplement existing geological maps. The popularity of airborne geophysics is due to its lower cost for unit of area surveyed, as compared to all other methods of exploration. South India has been extensively covered by high altitude regional aeromagnetic surveys jointly by GSI and NRSA, low altitude multi-sensor surveys by foreign agencies, viz. M/s. Parsons, U.S.A. (Operation Hard rock Project) and BRGM/CGG, France, on contractual basis for GSI and by GSI (Twin Otter surveys) in selected belts and low altitude aeromagnetic surveys by NGRI in the SW part of the Cuddapah basin and the adjoining crystallines. Integrated studies of geophysical (airborne and ground), geological and remote sensing data have greatly helped not only in augmenting the geological knowledge of the region, but also in identifying several metallic prospects/ deposits. The present paper illustrates several case studies in demonstrating the utility of aerogeophysical data in geological mapping (identifying lithologies, structures and basement characteristics) and locating metallic prospects/ deposits.

Agricultural drought management is a critical aspect of ensuring food security and sustainable agricultural practices, particularly in regions prone to water scarcity. Droughts, characterized by prolonged periods of abnormally low rainfall, can have devastating effects on crop yields, livestock productivity, and the livelihoods of farmers. Effective drought management strategies are essential for mitigating these impacts and enhancing the resilience of agricultural systems. Agricultural drought occurs when the soil moisture is insufficient to meet the needs of crops, leading to reduced growth, lower yields, and increased plant stress. This type of drought can be particularly challenging because it directly affects food production and the agricultural economy. Unlike meteorological droughts, which are defined by the degree of dryness compared to normal conditions over a specific period, agricultural droughts focus on the impact of drought on crops and agricultural productivity.