eChapters

Rainfed agriculture constitutes 80% of global agriculture and plays a critical role in achieving global food security. However, growing world population, water scarcity, and climate change threaten rainfed farming through increased vulnerability to 1 droughts and other extreme weather events. Out of the total population of 7.3 billion, about 1 billion are food insecure and 60% of these live in South Asia and Sub Saharan Africa.

Rapeseed
Rapeseed (Brassica napus L.), a member of the Brassicaceae family, is one of the primary oilseed crops cultivated for biodiesel production, particularly in Europe and Canada (Hoekman et al., 2012; Demirbas, 2009). Its seeds contain 40-45% oil, making it one of the most efficient oil crops for biofuel production (Ramos et al., 2009). The extracted oil is known as canola oil, which is preferred for both food and fuel applications due to its low erucic acid and glucosinolate content (Atabani et al., 2012). Rapeseed (Brassica napus L.), is one of the biofuel species that has achieved global attention, primarily due to its high yield, climatic versatility as well as its low environmental impact than fossil fuels (Singh et al., 2010). The crop is being grown all over the temperate region because its ability to resist cold temperatures and pests is a major advantage for the practice of sustainable agriculture. Moreover, the rapeseed has been positively affected by the development of biotechnology and the utilization of hybrid breeding that has been significantly increasing the oil yield and disease resistance of rapeseed, thus, facilitating the biodiesel production from this plant (Zanetti et al., 2013). Biodiesel from rapeseed has ecological advantages, significantly reducing greenhouse gas emissions by up to 50% compared to regular diesel (Hill et al., 2006). It also supports rural economic development through the diversification of farmer income and diminishing reliance on imported petroleum (FAO, 2021). The increasing price of the biofuel, chiefly supported by sustainable energy policies and reducing carbon footprint policies, is one of the driving factors for increasing demand of rapeseed as global demand for renewable energy sources rises (Euopean Commission 2021).
Sunflower
Sunflower (Helianthus annuus L.) is an important oilseed crop used for biodiesel production, especially in temperate regions like Europe and North America (Demirbas, 2009). The oil content of sunflower seeds ranges from 25-50%, making it a suitable feedstock for biofuel (Atabani et al., 2012). The characteristics of sunflower oil, such as the high content of unsaturated fatty acids, lead to better cold flow properties of its biodiesel (Ramos et al., 2009). In addition, the creation of high-oleic sunflower varieties allowed considerable improvement in oxidative stability and led to the fact that sunflower biodiesel is more suitable for storage and combustion (Dimitrijevic et al., 2017). A second

The great Indian epic ‘Ramayana’ says that ‘Lord Rama’ has tried to cross over the Bay of Bengal so as to reach Sri Lanka from India from three points along the southeastern fringe of the Indian coast. Firstly, he is said to have tried to cross from Vedaranniyam which is mythologically called as ‘Kodiyakkarai’ Secondly from Manamelkudi and finally crossed over to Sri Lanka from Rameswaram Island (Fig.1), as the former two coastal locations were widely separated from Sri Lanka by Bay of Bengal and the Rameswaram Island was nearer to Sri Lanka during that period. But, the recently acquired satellite data shows the huge accretion of sediments and rapid land building activity off Vedaranniyam coast (Fig. 2 and 3). The geomorphic interpretations carried out using IRS 1A imagery and 14^C archaeological dating of such geomorphic features have shown that such ongoing sediment accretion phenomena off vedaranniyam nose might in future connect the Vedaranniyam part of Indian Peninsula with Jaffna Peninsula of Sri Lanka if the sediment accumulation continues unabated. The sediment accretion in this area, therefore, requires detailed studies particularly in the context of the coastal ecosystem (Fig. 1).

The satellite data is available in raster format. Raster data consists of two – dimensional array of pixels or grids which stores the values representing features. All the pixels are of same size and shape with their particular coordinate location. A raster data format is shown below.

The calculation of raster data statistics is very essential before performing some geoprocessing operations. Raster data statistics involve knowing the distribution of pixel values in a band, comparing the pixel values of two bands, extracting values of all bands for a particular geographical location or point, and computing statistics like mean, median, standard deviation, etc. at pixel level across all bands of raster dataset.

In R, codes to perform raster data statistics are present in raster package. The visualisation of raster data statistics can be done by rasterVis package. So, we need to import these packages in R in order to perform this exercise.

3.1. Reserve Bank of India

Established in April 1, 1935 as per RBI Act, 1934.

Agricultural Credit Department (ACD) organized in 1935 coordinated Bank’s operations with State Co-operative Banks and other banks and organization dealing with agricultural credit

Financing agriculture by commercial banks is looked after by Department of Banking Operations and Development (DBOD)

While, ACD continued to take care of co-operative credit

The growing adoption of Generative AI in academic institutions has moved the technology from experimental applications toward practical implementation across teaching, learning, research, student support, and university operations. This chapter examines real-world applications and institutional case studies that demonstrate how GenAI can be incorporated into higher education and other academic environments. Key applications include AI tutoring and learning support, curriculum and course development, assessment and feedback, research assistance, student-success services, and institutional operations. AI writing coaches can provide individualized guidance, while dialogic mathematics and coding assistants can support problem-solving without simply providing answers. Educators can use GenAI to develop learning objectives, case studies, examples, question banks, rubrics, multimedia scripts, synthetic datasets, and practice environments. The chapter also considers institutional experiences with AI policies, academic integrity, accessibility, privacy, and professional development. Successful implementations generally combine technological capabilities with human review, clear institutional guidelines, and AI literacy. Case studies demonstrate both the potential and limitations of GenAI, emphasizing that effective adoption requires contextual evaluation rather than technology-driven implementation alone. The chapter provides practical insights for institutions seeking evidence-based and responsible approaches to educational transformation through generative AI.

5.3.1. Main components

Shear tube: It absorbs heavy shocks and protects the components of rear transmission and main transmission from breaking.

Crown wheel and pinion: It transmits the drive from the main shaft to the rear axle shaft and inverts the direction of rotation to 90° from the main shaft. It reduces the speed and multiplies the torque.

Rear axle: It is a semi floating type. It transfers the drive from the sun gear to the rear wheel.

5.3.2. How does it work?

The drive from the main shaft of the gear box is taken to the rear drive shaft through the coupler planetary. Depending on the position of the high–low gear and lever which moves the coupler, power is transmitted directly or through epicyclic gear train. The drive from the rear drive shaft is transferred to a safety coupling also known as shear tube. The coupling is a safety device. In case the rear wheels encounter any shock loading, the coupling breaks and disconnects the gear box from the rear transmission. This prevents damage to costly parts in the transmission, clutch and engine. Power is transmitted from safety coupling to a pinion which has a spiral bevel gear at one end. The bevel pinion is supported on two tapered roller bearings carried in a housing which is mounted in the centre housing.

Abstract

Food lost during the production chain is referred to as postharvest loss. Reducing postharvest loss can effectively feed starving mouths while conserving resources and decreasing the pressure to produce more. There are five main areas where postharvest loss can be reduced – harvest, storage, transportation, processing, and retail. New approaches and technologies in each of these areas will increase the amount of food available for human consumption. The total loss due to poor post- harvest processing of agricultural products in India when valued in terms of monetary reflects a tremendous loss in the economy. Annual value of harvest and post-harvest losses of major agricultural produces at national level to be of the order of Rs. 92,651 Crore calculated using production data of 2012-13 at 2014 wholesale prices. Deficits in food items or financial loss should not have occurred if postharvest losses were reduced through proper processing and preservation from harvest to consumption. Both the government and private sector need to invest in research so as to improve and modernize post-harvest facilities for attaining more efficient market infrastructure and distribution channels. Research and extension activities have to be closely coordinated particularly in the public sector for the benefit of farmers, traders and consumers.

Introduction

For human beings, the three most important necessities for their survival are food, clothing and shelter. among all of these food is the top most priority. Food safety and Standards defines food into 8 categories (Nutraceutical, Heath Supplements/Dietary Supplements, Food for special medical Purpose, food for Special Dietary Use, Novel Food, and Functional food) in regulation, 2016. A growing trend of health products, concept of food as medicine, associated public interest and consumers demand leads to a progressive research interest in functional foods and nutraceuticals development. Abnormal lifestyle, food habits (consumption of junk food) and low physical activity creates an exponential growth in a number of chronic diseases; obesity, cardio-vascular syndromes, osteoporosis, arthritis and cancer (Das et al., 2012) among the developing and developed countries. While nutraceuticals and functional foods are becoming an alternative affordable system to reduce the risk of disease through prevention in spite of high tech therapies and costly medicines.

The current survey showed that worldwide revenue of functional foods is projected to increase from about 300 billion U.S. dollars in 2017 to over 440 billion dollars in 2022. Also according to the International Food Information Council (IFIC), health benefits achieved from functional food components may provide benefits far beyond than basic nutrition. Products like dietary supplements containing vitamins, functional foods such as sports drinks or products fortified with probiotic play a major role in the market rise (www.statista.com).Indian and Chinese traditional foods, recipes, spices and diversified ingredient market is well known around the world from centuries. Hence, a double-digit growth rate is also experienced in Asian nutraceutical and functional food market. Another reason for the growing trend in consuming functional foods is education and proper health awareness. Furthermore, people are more concern about the optimization of health-promoting capabilities in their diet using dietary supplement and fortified foods. While, food product based industries are marketing health supplements using scientific facts and the relationship between diet and health. Government, non-government organizations (NGOs) and web-based online information also play a key role in promoting and trending food based health products.

INTRODUCTION
Efficient management of record-keeping, inventory, finance, and human resources is crucial to the success of any agro-processing business. Proper recordkeeping ensures accurate documentation of transactions, operations, and adherence to legal and regulatory standards, promoting transparency and accountability. Effective inventory management is vital for maintaining appropriate stock levels of raw materials, work-in-progress, and finished products, which directly affect production efficiency, cost management, and product availability. In financial management, sound practices allow businesses to monitor cash flow, manage costs, evaluate profitability, and secure necessary capital for growth and day-to-day operations.
Moreover, human resource management plays a significant role in building a skilled, motivated workforce by ensuring proper staffing, providing employee training, and adhering to labor regulations. Collectively, these components are essential for the smooth functioning of an agro-processing business, contributing to enhanced operational efficiency, financial health, and sustained growth.
RECORD KEEPING FOR AGRO-PROCESSING
Record-keeping in agro-processing is a fundamental aspect of the food production and manufacturing sector. It ensures traceability, adherence to food safety regulations, operational efficiency, and transparency in converting raw materials into finished goods. Well-maintained records are crucial for managing quality control, inventory, and ensuring compliance with health and safety standards.
Key Areas and Types of Records Kept in Agro-Processing
Below are the key areas and types of records that should be kept in agroprocessing:

1.1. FYM compost

Decomposed mixture of dung and urine of farm animals along with litter and left over materials from roughages or fodder fed to the cattle.

Farmyard manure contains 0.5% N, 0.2% P₂O₅ and 0.5% K₂O.

Urine contains one per cent nitrogen and 1.35% potassium.

10 to 20 t/ha is applied, but more than 20 t/ha is applied to fodder grasses and vegetables like potato, tomato, sweet potato, carrot, radish, onion etc., respond well to the farmyard manure.

Crops like sugarcane, rice, oranges, banana, mango and coconut respond good to FYM.

16.1 Conservative Technology

Recycling technology being practiced by ancient times by the people who used for municipal industrial effluent. In India the people in rural area, they collected cow dung in a pit. They applied a layer of soil on the cow dung to composting. After three to four months period, they used as manure for the agricultural fields. In a household waste, they collected as organic waste from a kitchen, store a pit allow it for decompose for conversion of compost. People who are residing in house constructed in a plot, they used to generate industrial effluent in a pit and cultivate a kitchen garden like vegetable crops and banana trees etc. in ancient times, the amount organic waste is limited and self purification is taken in small amount of organic waste therefore no organic pollution occurs in rural India.

Educational content development traditionally requires substantial time and effort from teachers, instructional designers, and academic institutions. Generative AI is changing this process by enabling the rapid creation, adaptation, personalization, and transformation of learning materials. This chapter examines how GenAI can redesign educational content generation across different subjects, educational levels, and learner requirements. It explores automated lesson-plan generation, question-bank development, personalized learning materials, visual and interactive resources, simulations, and multimodal educational content. AI systems can generate explanations at different levels of complexity, create assessments aligned with learning outcomes, and adapt instructional materials to student performance. Such capabilities can support differentiated instruction, self-paced learning, and improved learner engagement while reducing repetitive preparation work for educators. The chapter also examines important challenges, including content accuracy, algorithmic bias, copyright, data privacy, academic integrity, and teacher readiness. Future possibilities include adaptive tutors, multimodal content generation, AI-supported curriculum design, and intelligent learning resources. Overall, the chapter emphasizes that GenAI should augment professional educational judgment rather than replace it.

ABSTRACT

Pests and diseases cause serious economic losses in yield and quality of many cultivated crops. Detection and assessment of their damage symptoms is very crucial to initiate timely control interventions. The conventional scouting technique adopted for assessment of pest and disease in field crops is very laborious and time consuming. Remote sensing may provide a better means to objectively quantify disease stress than visual methods and it can be used to repeatedly collect sample measurements non-destructively and non-invasively. In this paper we report the changes in the reflectance spectra due to pest and disease incidence in three crops viz., groundnut, castor and rice. Canopy reflectance measurements were made with a hand held multispectral radiometer (MSR 16-R, CropScan Inc) which records incoming radiation and light reflectance with up looking and down looking sensors, respectively in 16 pass bands. Data of percent reflectance at each pass band were processed subsequently using the calibration and correlation constants through a mini computer connected to the sensor. A total of 10 samples were selected for each level of pest/disease. At each sampling, six measurements were recorded and the resulting data were averaged. The reflectance spectra varied for different biotic stresses in the three test crops. Higher absorption in the NIR region between 760-1240 nm was observed for healthy plants compared to the diseased plants in all the three crops tested. The spectral signatures from severely defoliated (by semilooper pest) castor crop showed that the percent reflectance in the visible region between 560-710 nm was higher in the defoliated crop compared to healthy and reverse is true in the NIR region between 810-1100 nm. In case of rice, spectral reflectance in the region between 760-1100 nm could differentiate the healthy and brown plant hopper affected plants. Decrease in reflectance in this region was proportion to the number of hoppers per plant. This could be due to collapse of leaf tissues by hopper damage. The higher reflectance in the visible region (560-710 nm) was observed only when the damage is very severe (hopper burn). Different spectral indices viz., SR (simple ratio), NDVI (normalized difference vegetation index), NPCI (normalized total pigment to chlorophyll index), DWSI (disease water stress index) and WBI (water band index) were compared to distinguish healthy and diseased plants. NDVI was found useful in distinguishing semilooper damaged (defoliated) castor crop from healthy castor. All the indices tested were useful to differentiate the rice plants damaged by sap-sucking pest, BPH at different levels of infestation. Incase of groundnut, the differences in the spectral indices between different disease incidence levels were not significant. Results of the present study demonstrated that by comparing the reflectance spectra generated using ground based high-resolution radiometer, it is possible to distinguish healthy and pest/disease affected crops.

A refrigerant is heat transfer medium through which phase change occurs from liquid to vapour i.e. evaporation at low temperature and pressure in the evaporator and then the phase change occurs from gas to liquid i.e. condensation at high pressure and high temperature in the condenser. The cycle of phase change of refrigerant, continues in the refrigeration system.

Refrigeration mean cooling i.e. lower the temperature by artificial means. It is a process of attaining lower temperature of the space or product below the surrounding temperature. It further involves maintaining the lower temperature achieved.

Q. 1 Unit of refrigeration is:-
(A) Quintal    (B) Gram
(C) kg            (D) Ton

Global Packaging Regulations: FDA, EU, FSSAI, and Others FDA (U.S. Food and Drug Administration): The FDA ensures that food packaging materials are safe for contact with food in the United States. Under the Food, Drug, and Cosmetic Act (FDCA), the FDA provides guidelines through the Code of Federal Regulations (CFR), Title 21. Key points include: • Food Contact Substances (FCS): Materials in contact with food must be either pre-approved or recognized as safe (GRAS). Packaging materials, including plastics, paper, and adhesives, must undergo tests to ensure they do not release harmful substances into food. • Migration Limits: The FDA sets allowable limits on the migration of substances from packaging into food, including chemicals from inks, coatings, and polymers. • Food Packaging Certification: Packaging manufacturers must confirm that their materials meet FDA standards for safety in food contact

Introduction 
Crop-weather models are sophisticated constructs, meticulously designed to replicate the dynamic and intricate interplay among atmospheric conditions, complex soil processes, nuanced plant physiology, and the decisive influence of human management interventions. The agricultural system is a prime example of a highly interconnected and non-linear system, where changes in one component can ripple through and affect many others, often with time lags and feedback loops. To truly comprehend, effectively design, rigorously develop, and clearly communicate the inner workings of such multifaceted simulations, relying solely on dense textual descriptions or abstract mathematical equations can prove daunting and often insufficient. This is precisely where relationship diagrams emerge as indispensable tools. At their core, relationship diagrams are powerful visual representations that translate the abstract scientific concepts and mathematical formulations embedded within crop-weather models into intuitive graphical formats. They are essentially the architectural blueprints and flowcharts of these complex systems, allowing us to see, rather than just read, how various components of the agricultural ecosystem interact. Imagine trying to understand the intricate wiring of a skyscraper or the precise movements of a symphony orchestra purely from a written description; diagrams provide the essential visual mapping that brings clarity and coherence to complexity. These diagrams are not mere aesthetic additions; they are fundamentally required because of the inherent complexity and interdisciplinary nature of crop modeling. They bridge critical gaps: Bridging Disciplinary Gaps: Agricultural system modeling brings together experts from diverse fields – agronomists who understand plant responses, meteorologists who provide weather insights, soil scientists who grasp soil physics and chemistry, and computer scientists who implement the models.