eChapters

Abstract
Grain legumes face significant biotic stresses fromvarious pests and pathogens, leading to substantial yield losses worldwide. This chapter synthesizes recent advances in molecular approaches and biotechnological tools for developing resistant varieties and managing diseases in legumebased cropping systems. Novel genomic technologies, including CRISPRCas9 gene editing, marker-assisted selection (MAS), and next-generation sequencing (NGS), have revolutionized our understanding of host-pathogen interactions and accelerated the development of resistant cultivars. RNA interference (RNAi) technology has emerged as a promising tool for targeted pest control, while transcriptomics and proteomics approaches have helped identify key resistance genes and defense-related proteins. Integration of these molecular tools with traditional breeding programs has resulted in improved varieties with enhanced resistance to major pests like pod borers and diseases such as fusarium wilt and ascochyta blight. Additionally, biotechnological applications including biopesticides and disease-forecasting systems have strengthened integrated pest management strategies. This review highlights the potential of combining multiple molecular approaches for sustainable pest and disease management in legume cultivation while identifying future research directions and challenges in their widespread adoption.
Keywords: Biopesticides, Biotechnological tools, Marker-assisted selection, Legume

Introduction

Sugarcane is a vital commercial crop of our country that occupies around 5.11 million ha of land with an annual cane production of around 400.16 million tonnes and yield of 78.25 t/ha. Sugarcane occupies 2.67% of the cultivated land area and about 7.5% to the agricultural production in the country (DAC, 2020). This crop is a source of earning and livelihood for about 35 million farmers and approximately equal number of labourers. After textile industry, the sugar industry holds its place for the largest agro-based industry in country. Around 40-50% of the cane is utilised in 435 sugar industries present in India for the manufacture of about 15 million tonnes of sugar.

This crop is also a source of raw material for two important small scale industries, i.e., gur and khandsari. These industries utilises about 50-55% of the sugarcane produced for production of about 10 million tonnes of these products altogether. Besides, sugarcane crop is also the producer of molasses, chief by product, which is the main source for production of alcohol. In the year 2018-19, about 13.79 million tonnes of molasses is produced by our country. Apart from this, the left over fibrous material of sugarcane termed as sugarcane bagasse is also a source of production of electricity in the sugar mills. The left over extra bagasse is now-a-days utilised for even production of paper in paper industries. Also, co-generation of power by this product of sugarcane as fuel is considered to be best practical thing in most of the sugar mills. Using this as a raw material, about 3500 MW power may be generated each year without the use of any extra fuel and money being less than normally utilised in case of fuel production from thermal powers. Press mud is also one of the by-products obtained from sugarcane which is considered to be rich source of organic matter and micro and macro nutrients. Even the green tops of sugarcane are being used as cattle fodder. Besides, the cool sugarcane juice full of energy is in great demands in urban area to quench the thirst of people, especially in hot summer seasons (Anonymous, 2008). The trend of sugarcane production over the years is given

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.

Advances in technology are revolutionizing the detection of metabolic diseases in animals, making diagnostics more precise, rapid, and non-invasive. From wearable sensors and metabolomics to AI and nanotechnology, these tools are enhancing animal health and productivity. As these technologies become more accessible, they promise to transform veterinary medicine and animal husbandry, ensuring early detection, effective management, and improved outcomes for animals.
Sensor-based technologies have emerged as a game-changer in the detection and management of metabolic diseases in dairy animals. These tools provide continuous monitoring, early detection, and real-time insights, enabling better health management and increased productivity. This chapter explores the most promising sensor-based technologies used for diagnosing metabolic diseases in dairy animals, their applications, and the future of sensor-driven animal health management.
Metabolic diseases like ketosis, milk fever (hypocalcemia), acidosis, and displaced abomasum significantly impact dairy productivity and animal welfare. Early detection is critical for reducing treatment costs, improvingrecovery rates, and minimizing production losses. Traditional diagnostic methods are accurate and often invasive, time-consuming, and not feasible for large-scale monitoring. Therefore, sensor-based technologies offer a solution by enabling continuous and non-invasive monitoring of physiological and biochemical parameters.

Biomedical signals provide valuable information about physiological conditions and support continuous health monitoring. This chapter introduces ECG, EEG, EMG, PPG, respiratory and blood-pressure signals and examines the challenges associated with their acquisition and interpretation. It discusses noise removal, filtering, normalization, resampling and artifact correction before presenting time-domain, frequency-domain, time–frequency, wavelet and nonlinear feature-extraction methods. Feature selection and dimensionality reduction are considered in relation to model accuracy and clinical interpretability. The chapter also explores machine learning, deep learning and hybrid approaches through applications involving arrhythmia detection, seizure prediction and wearable cardiovascular monitoring, highlighting their importance in intelligent and personalized healthcare.

9.1 Magnetic seed separator

These machines use a magnetic force to separate damaged seeds or other particles from the good seeds. This is used to solve special problems in seed lots that can not be taken out with our other basic seed cleaning equipment. Most of the time it is used for vegetable and field seeds that have problems in seed damage (fish mouth in cucumber or melon seeds / cracked radish or cabbage seeds), insect damage (beetle holes in cotton seeds) or contamination with soil or plant parts (white plant parts in onion seed) etc.

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.

Renal failure is one of the most commonly presented conditions in veterinary clinics world over. Although the potential for recovery is favorable, most animals die due to multisystemic effects induced by azotemia. Hence, extracorporeal removal of endogenous and exogenous toxins is very essential for expanding the window of recovery. Hemodialysis has been used in treatment of veterinary patients for the last 50 years and is still one of the most expensive and technically demanding treatment modalities in veterinary medicine. It is an advanced extracorporeal renal replacement therapy which has recently transitioned from a clinical curiosity to a more advanced standard for management of acute kidney injury (AKI) and chronic kidney disease (CKD) in companion animals particularly dogs and cats.

In addition to eliminating selective toxins that cause AKI, regardless of renal function, hemodialysis is also effective in the removal of pharmacokinetically active soluble uremic substances in CKD to enhance life expectancy and quality of life (Singh, 2021). Other common indications of hemodialysis in veterinary medicine include fluid overload, dysregulated body fluid composition, drug overdose or intoxications (Foster, 2020; Singh et al?, 2024). Medical management alone is often insufficient to control the clinical signs and metabolic abnormalities associated with uremia when AKI is severe or when there is involvement of acute on chronic kidney disease. Consequently, animals are at risk of death within a short therapeutic window, despite the potential reversibility of AKI and the improvement of life expectancy in CKD.

Aquaculture or farming and husbandry of aquatic organisms and plants is the future for increasing aquatic food production. It is the fastest growing food production sector with an annual average growth of >6% in the last two decades. It increased from <1 million tonne in 1950 to 70.2 million tonnes in 2013. An update of aquaculture production (FAO) revealed that the total world aquaculture production continued to grow in 2013, reaching 97.2 million tonnes (live weight) with an estimated value of US$157 billion. A total of 575 aquatic species and species groups are grown in freshwater, seawater and brackish water have been registered in the FAO Global Aquaculture Production Statistics Database. The production of farmed food fish (finfish, crustaceans, molluscs and other aquatic animals) was 70.2 million tonnes in 2013, up by 5.6 % from 66.5 million tonnes in 2012. The production of 27 million tonnes of farmed aquatic plants was a 13.4% jump on the 23.8 million tonnes of 2012. The contribution of aquaculture to the world total fish production reached 43.1%, up from 42.1% in 2012. It was only 30.6% a decade ago in 2003. Meanwhile, world production of aquatic plants, mostly seaweeds, is still overwhelmingly dominated by aquaculture (95.5% in 2013). On a global scale, the production of major non-fed species contributed 30.7% to world food fish aquaculture production in 2013, including 13.9 million tonnes of bivalves and 7.7 million tonnes of filter-feeding carps.

Mariculture involves the cultivation of marine organisms for food and other products in an enclosed section of the sea (cages/pens), or in tanks, recirculating systems, ponds or raceways in seawater..It is a promising sector by which the additional marine fish requirement can be met in the future years. It is also the fastest growing sub-sector of aquaculture. At global level, mariculture produces many high valued finfishes, crustaceans and molluscs viz. oysters, mussels, clams, cockles and scallops. In 2013 mariculture has contributed around 25.5 million tonnes of foodfish globally which formed about 36.3 %of the foodfish aquaculture production(World food fish aquaculture production was 70.2 million tonnes in 2013). Molluscs dominated the global mariculture production (59.7%) followed by finfish (22.7%), crustaceans (16.2%) and others (1.4%). In addition about 26.9 million tonnes of macro algae were also produced by mariculture. The total mariculture production including seaweeds was 52.4 million tonnes in 2013 which constituted 53.9% of the total aquaculture production (The total global aquaculture production including the aquatic plants was 97.2 million tonnes in 2013).

Advanced marketing of agricultural produce encompasses innovative strategies and technologies aimed at enhancing the efficiency, reach, and profitability of agricultural markets. This approach integrates modern tools such as digital platforms, precision marketing, and data analytics to better connect farmers with consumers and markets. It also emphasizes the importance of value addition, branding, and sustainable practices to meet evolving consumer preferences and market demands. By leveraging these advanced marketing techniques, agricultural producers can optimize their supply chains, reduce post-harvest losses, and achieve higher economic returns, ultimately contributing to a more resilient and sustainable agricultural sector.

In the Indian aquaculture sector, the rising frequency of disease outbreaks caused by bacterial, viral, fungal, and parasitic pathogens has necessitated the adoption of advanced molecular diagnostic techniques. Traditional methods, though useful, often lack the sensitivity required for detecting low pathogen loads or distinguishing between closely related strains. To address these limitations, molecular diagnostics have become integral to enhancing fish health management across diverse aquaculture environments—freshwater, brackishwater, and marine systems.
Among these tools, Polymerase Chain Reaction (PCR) is one of the most widely adopted techniques. PCR is both highly sensitive and specific, capable of detecting trace amounts of pathogen DNA or RNA from biological samples such as tissues, mucus, blood, and even environmental matrices like water and sediment. Organizations like ICAR-CIBA, ICAR-CIFA, and various state fisheries universities routinely employ PCR and quantitative real-time PCR (qPCR) to detect viral infections including White Spot Syndrome Virus (WSSV) in shrimp, Koi Herpesvirus (KHV) in ornamental fish, and Nodavirus in marine finfish like groupers and sea bass.

Abstract
Fish, a vital source of nutrition globally, faces challenges in maintaining microbiological safety and sensory quality due to its perishable nature. While effective in microbial reduction, traditional thermal processing methods often compromise fish’s nutritional and sensory attributes. In response, non-thermal technologies such as High Pressure Processing (HPP), Ultrasound (US), Ozone, and Pulsed Light (PL) have emerged as promising alternatives. These technologies offer effective microbial control while preserving the sensory and nutritional integrity of fish products. Ultrasound processing, has shown efficacy in microbial inactivation and quality enhancement without significant thermal impact. Studies on oily and white fish varieties demonstrate its capability to reduce microbial load while enhancing specific sensory attributes. In the same way, Ozone, which is known for its durable oxidative qualities, is useful in eliminating a wide range of bacteria on fish surfaces, although it must be taken into account when considering penetration depth and any sensory effects. Pulsed Light (PL) has shown quick microbial inactivation on fish surfaces and packaging materials by using high-intensity, short-duration pulses over a wide spectrum. High Pressure Processing (HPP) has become a reliable technique for increasing shelf life and guaranteeing microbiological safety in a variety of fish species. It works at moderate temperatures and high pressures. This chapter reviews the principles, applications, strengths, and limitations of these advanced non-thermal techniques in fish processing. It highlights their
potential to revolutionize the industry by meeting consumer demands for safe, high-quality fish products while overcoming the drawbacks associated with conventional thermal methods.
Keywords: Fish processing, Non-thermal techniques, Ultrasound, Ozone, Pulsed light, High pressure processing

Food packaging protects products from physical, chemical, biological and environmental influences while helping to maintain safety, freshness and quality. Advanced packaging systems perform functions beyond simple containment by regulating gases, moisture, temperature and microbial activity. The chapter examines modified-atmosphere, controlled-atmosphere and vacuum packaging, together with active and intelligent systems. Time-temperature indicators, freshness indicators and biosensors enable real-time monitoring of product condition. Edible and biodegradable materials provide more sustainable alternatives to conventional packaging, while nanotechnology can improve mechanical, barrier and antimicrobial performance. Shelf-life modelling and hurdle technology are also considered as tools for designing integrated packaging systems suited to specific foods and storage conditions.

ABSTRACT

Coastal resources represents highly productive ecosystems and are under pressure on account of increased anthropogenic activity on the coast. There is an urgent need to protect coastal resources aiming at sustainable development. Management of coastal resources requires spatial information on land and water resources, processes, water quality in a repetitive basis. Availability of high resolution and very high resolution data made the spatial tools indispensable in planning and management of resources such as mangroves and coral reefs. Monitoring mangrove degradation and aquaculture development, land use pattern, site selection for developmental activities adhering to coastal regulation zone notification requires highly accurate spatial information that can be extracted from IRS, IKONOS data. Extensive applications of remote sensing were hindered by cost, lack of familiarity and expertise in the developing countries. A national frame work must be established involving all available spatial datasets to build up the technical capabilities and ensure sustained support.

Advanced storage methods of agricultural crops play a pivotal role in mitigating post-harvest losses, ensuring food security, and enhancing the economic viability of farming. These methods encompass a range of innovative techniques and technologies designed to prolong the shelf life of crops, maintain quality, and reduce spoilage. From controlled atmosphere storage and modified atmosphere packaging to cold storage facilities and hermetic storage bags, advanced storage methods offer diverse solutions tailored to different crops and environments. This chapter explores the key principles and benefits of advanced storage methods, highlights notable technologies and approaches, and underscores their significance in addressing the challenges of post-harvest management in agriculture.

Introduction Plant disease detection is a crucial aspect of modern agriculture, as it allows early identification and management of diseases, minimizing crop losses and maximizing yields. In recent years, advancements in technology have led to the development of more sophisticated techniques for plant disease detection. Point-of-care (POC) diagnostic assay for plant disease detection is a rapid, advanced, and on-site testing method designed to identify the presence of pathogens or diseases in plants. This type of diagnostic tool is particularly valuable for farmers, agronomists, and researchers who need immediate results to make timely decisions about disease management and crop protection strategies.

As video editing continues to evolve, so do the techniques and software that enable editors to create polished, captivating visuals. Advanced editing techniques like precision cutting, mixing, and using sophisticated software tools allow editors to enhance storytelling, manipulate pace, and shape the emotional experience of their audience. This chapter dives into these advanced techniques, exploring how each tool and method contributes to a compelling final product.
1. The Art of Cutting: Techniques for Seamless Storytelling
Cutting is a fundamental editing skill that determines the pacing, continuity, and flow of a video. Advanced cutting techniques, such as L-cuts, J-cuts, and match cuts, serve as the foundation for creating dynamic narratives.
• Types of Cuts
• L-Cut and J-Cut: L-cuts and J-cuts are used to transition between audio and video in ways that flow more naturally and create smoother  continuity between scenes. These are essential techniques for dialogue-driven scenes or scenes that require seamless transitions between different locations or times.

Electrophoresis

The mobility of ions in an electric field is the basis for the separation method known as electrophoresis. Ions that are negatively charged move toward a positive electrode, while those that are positively charged move toward a negative electrode. Usually, one electrode is biased either positively or negatively, and the other is at the ground for safety reasons. Ions can be distinguished from one another based on their size, shape, and overall charge, which determine their migration rates.

Poly Acrylamide Gel Electrophoresis (PAGE)

Introduction

Electrophoresis is an electrochemical process in which substances with a net electric charge migrate under the influence of an electric current. This migration occurs in an agar gel or a liquid- filled buffered matrix such as cellulose acetate. Positively charged substances travel toward the cathode (negative electrode), while negatively charged substances go toward the anode (positive electrode). Different substances move at different rates depending on their charge. This movement is called electrophoretic mobility.

Proteins are charged molecules. They have a positive as well as a negative charge. Among proteins, particularly caseins, they have different contents. The charge density also varies depending on the molecular weight. Proteins have a net negative charge at a pH above 4.6, and hence they move towards the anode (positive electrode) when subjected to an electric field under alkaline conditions. Due to differences in the charge of individual protein fractions, their migration rates also differ and are hence separated into distinct bands. These bands are stained with the dye amido- black, destained with 7% acetic acid, and observed for the electrophoretic pattern.