eChapters

Abstract

Tremendous hike inworld population has increased thrust on the limited resources which has considerably affected the viability of the food. The emerging challenge for policy makers and food scientists is to put forward viable solutions. Utilization of underutilized crops/plants that act as good sources of starch could be explored in a better way for the sustenance of the limited sources like food crops/plants. The demand for starch and the foods containing starch has been increasing continually. Since, the starch in its native form has certain limitations in its functional properties to be used for different applications. Therefore, it becomes important to explore certain technologies which could be used for modification of starch. Among different technologies gamma irradiation ensures food safety while inducing physicochemical changes of the components. Although, the chemical modifications have been used widely so far but the concerns related to the chemical residues left are diminishing their demand. Hence, the physical processes particularly the gamma irradiation process has emerged as an efficient alternative with some benefits over other process like eco-friendly, economical, reliable and safe for altering the physico-chemical and biological characteristics of the product. Gamma Irradiation of starch has been successfully employed for the achievement of some desired physico-chemical, biological and functional properties of the foods and other related items. In this chapter, valuable impact of gamma irradiation on the physico-chemical, biological and functional properties of starch has been summarized.

13.1 Biopolymer-Based Coatings with Antimicrobial Properties 13.1.1 Understanding Biopolymer-Based Coatings Biopolymer-based coatings are a game-changer in food packaging, offering natural, sustainable solutions for food safety. These coatings, derived from renewable sources, like polysaccharides (e.g., chitosan, starch, cellulose), proteins (casein, gelatin), and lipids (wax, shellac), have proven to be biodegradable and consumer-friendly alternatives to synthetic polymers. 13.1.2 Antimicrobial Properties and How They Work • Antimicrobial coatings are crucial in slowing down spoilage and extending the shelf life of perishable foods. They work by disrupting cell membranes, inhibiting cell processes, and creating oxidative stress in microbes. This is achieved through natural antimicrobials like essential oils (e.g., oregano, thyme, clove), plant extracts, and organic acids; inorganic agents like silver nanoparticles, zinc oxide, and titanium dioxide; and microbial-derived substances like nisin, lysozyme, and bacteriocins (Yu, Z et al ., 2022)

17.1 Modules

• A module is a file containing python definitions and statements.

• A python module is (.py file) containing variables, class definitions, statement and function related to a particular task. The major feature of having module is that its content can be reused in other programs, without having to rewrite or recreate them.

• They are executed only the first time the module name is encounter in an import statement.

Type of modules:

• User defined modules

• Built-in modules

Ex.-array, math, numpy, sys, etc.

India is an agricultural country. The geographical area of India is about 328 mha out of which 147 mha of land under cultivation and 84-mha land is under irrigation. The population is increasing at an alarming rate that requires producing more food for the growing population. This problem can be solved either by increasing the land under irrigation or using different soil water conservation techniques. It is well known fact that during rainfall a considerable amount of water goes to sea due to high rate of runoff. It is highly needed to trap as much as water falling in the form of rainfall and recharge the groundwater so that it is made available for irrigation purposes.

Term moisture stress is generally applied to the stomata opening and transpiration increases with time until they close due to high temperature.

5.1. Causes of moisture stress in plants

Main reason is extent of transpiration which is affected by leaf size and composition, size and distribution of stomata on leaf, atmospheric humidity, temperature, wind velocity and day length.

High atmospheric temperature due to intense sun and increased transpiration causes closure of stomata and wilting of leaves even, if soil moisture content is not limiting.

This deficit is made up during night due to decreased transpiration.

In plants, moisture content decreases either due to increased transpiration or reduction in absorption or both.

Abstract

Anantapur is the driest district of Andhra Pradesh and hence, agriculture conditions are very often precarious. Groundnut grows where other crops fail and thus it is the predominant crop of Anantapur district. Groundnut is grown in about 7.5 lakh ha in Anantapur district; however the average yields are low at 500 kg ha^-1. Among various available vegetation indices, normalised difference vegetation index (NDVI) is widely used for all reasons, which is a single numerical indicator of presence and condition of green vegetation. NDVI mapping at a regional scale helps to assess the spatial changes in the vigour of green vegetation and thus occurrence of any moisture stress. Climate tools have a great role in understanding the crop performance and estimating the yields. This study was taken up by using freely available MODIS data to understand NDVI in terms of abiotic stresses over Anantapur district and linking with the actual rainfall conditions, groundnut crop acreage and production. Results indicate that low groundnut yields in general could be related to NDVI-based stress measurements and rainfall quantum and distribution in the area however, with a few exceptions. It is hoped that by combining improved practices through IWM with climate-adapted crop varieties, rainfed farmers of Anantapur district can sustain their crop production under present climate variability and become resilient to future climate change.

Keywords: Climate, MODIS, NDVI, Anantapur, Groundnut, Integrated Watershed Management

Introduction

Improvement of wheat grain quality depends on the knowledge of quality requirements of different end-use products and the genetic components controlling different quality traits. In previous chapters we have dealt in-depth with quality requirements of different end-use products and their genetic components. Depending upon the goal of quality improvement, different strategies are adopted to improve wheat quality. It depends upon the number of genes controlling the traits as well as the availability of the simple methods for phenotyping the traits especially during early segregating generations. In addition stability analysis of the traits across the environments is essential before we go for breeding. Constraints in time, cost, and sample availability usually necessitate the use of predictive tests during early generations, followed by milling and baking tests on advanced lines that have met a number of agronomic, disease and predictive quality criteria. Knowledge of germplasm lines having specific quality traits is needed to initiate breeding for the improvement of wheat grain quality for different end-use products. The quality requirements of different major end-use products are provided in the following table (Table 1).

Key words : GPS, GIS, DSS, SDSS, RS, Digital Elevation Model (DEM), Ground Water Exploration, Conjunctive Use of Surface and Ground Water, Digital Terrain Modeling (DTM).

Introduction

Water is one of the most precious gifts of nature to living beings and particularly to the mankind. On account of erratic distribution of rainfall both in time and space, the country is subjected to cycles of floods and droughts. With the increase in demand for water for various purposes and to mitigate the twin problems of floods and droughts faced by the country, a coordinated approach for optimum utilization and proper management of this precious resource is of prime importance. In addition, proper development and management of both irrigation and drainage systems are essential. This would require integrated management of surface water as well as gorund water. All the water related problems whether mitigating droughts or floods or better irrigation management practices, dictate for adoption of state of the art water management practices. Water management deals with the control, distribution and allocation of water flows and the treatment of rivers and catchments, consequently, solutions to many of the problems in water management require the knowledge and expertise from diverse sources.

Monitoring the microclimate inside protected cultivation systems—such as greenhouses, polyhouses, net houses, and other semi-controlled environments— plays a crucial role in modern agricultural practices that aim to enhance crop productivity, quality, and resource efficiency. As global demand for high-quality and high-yield crops continues to rise, protected agriculture has become a key solution for mitigating the effects of climate variability, pest infestations, and limited available land. However, the effectiveness of these systems largely depends on the ability to continuously monitor and regulate the essential microclimatic factors that directly influence plant health, disease resistance, and overall productivity. Microclimate refers to the localized climate conditions within a specific area— in this case, within the protected structure—that can differ significantly from external environmental conditions. Key parameters typically monitored include temperature, relative humidity, solar radiation or light intensity, carbon dioxide (CO?) concentration, vapor pressure deficit (VPD), and air movement or circulation. These factors are interrelated, and even minor fluctuations can greatly impact plant health, photosynthesis, transpiration, and reproduction. Thus, accurate and continuous monitoring of these variables is essential for effective climate control and optimal crop growth.
Temperature is arguably the most critical variable, as it controls metabolic processes, enzyme function, flowering time, and fruit development. A deviation from the ideal temperature range can either accelerate or stunt plant growth, leading to reduced yields or even crop failure. In tropical or semi-arid climates, temperature spikes inside protected structures can result in heat stress, while in temperate or mountainous regions, low temperatures can hinder growth. To mitigate this, temperature sensors—such as thermistors, RTDs, or thermocouples— are placed at different heights and zones within the structure to ensure uniform monitoring. These sensors typically transmit real-time data to centralized systems that control heating, cooling, and ventilation systems. Along with temperature,

The word ‘monsoon’ is derived from the Arabic word mawsim meaning season. The Arabs during their travel towards India recognised that by June strong southwesterly winds commence over the Arabian Sea and bring a lot of rains to the subcontinent. The term was first used in English in British India and neighbouring countries to refer to the big seasonal winds blowing from the Bay of Bengal and Arabian Sea in the southwest bringing heavy rainfall to the area. In the Indian subcontinent, monsoon is one of the oldest weather observations, an economically important weather pattern over June through September every year, and the most anticipated weather event and unique weather phenomenon. Due to its effects on agriculture, flora and fauna, and other economic, social, and environmental effects, a monsoon is one of the most anticipated, followed and studied weather phenomena of the Indian subcontinent. It has significant impact on the overall well-being of subcontinent residents.

The term ‘monsoon’ is customarily used in India to refer to the rainy season during the northern hemisphere summer from June to September and is traditionally defined as a seasonal reversing wind accompanied by corresponding changes in precipitation, but is now used to describe seasonal changes in atmospheric circulation and precipitation associated with the asymmetric heating of land and sea. Now the term monsoon has been broadened to include almost all of the phenomena associated with the annual weather cycle within the tropical and subtropical land regions of the earth.

ABSTRACT

As we all know that emergence of internet has completely changed the way of transferring knowledge. Online videos and lectures have been adopted by the online educational community to meddle into the MOOCs massively to disperse the knowledge. No field has remained untouched from MOOCs. This is basically a study on the available MOOCs in India in Library and Information science.

Keywords: MOOCs, Massive Open Online Course, SWAYAM, Library and Information Science.

1. Introduction

Dave Cormier devised the term Massive Open Online Course (MOOC) in 2008 to describe an open online course “Connectivism and Connective Knowledge” designed by Siemens and Downes. University of Manitoba offered MOOC for the first time in 2008 formally as a credit course to regular students and informally with enrolment open to anybody in the world free of cost. Since then, there is proliferation of MOOCs worldwide.

It is estimated that the country needs about 245mt of food grains, 30mt of sugar and jaggery, 7 lakh of tea, 1.7 lakh t of coffee, 10mt of vegetable oil and 17m bales of cotton. For realizing this, irrigated agriculture has to play an important role. To achieve this water use efficiency (WUE) in the irrigation sector has to be improved considerably as bulk of the available water is used in agriculture. But, with the ever-increasing population and industrialization problems, the demand for water by these sectors is bound to increase manyfolds in future. The requirement of water by different sectors during 2025 is estimated to be 105 m ham, which is 30 m ha m more than the present one. The share of water utilization for agriculture is expected to get reduced from the present percentage of 8~ to a value of 73 by 2025. Further, the demand for water for agricultural purposes is estimated to increase from 470 krrr’ to 740 krrr’ in a period of four decades (Table 1). During the same period there will be four­fold increase in the water demand for non-agriculture purposes.

Abstract

There is a consensus amongst the geoscientists that overall there has been progradation along the east and west coasts of peninsular India. However, the present day configuration of the coasts and some of the geomorphologic features such as absence of spit and delta along west coast and absence of major estuaries and petroliferous structures along east coast still remain controversial. The present study, based on the appreciation of certain geomorphological and tectonic features on Landsat imagery and aerial photographs of southern part of Indian Peninsula, suggests that the evolution of the coastline has been mainly controlled by tectonism.

The tapering nature of the coastline is attributed to the Precambrian orographic axis. The serrated nature of the post Precambrian coast line is due to the Precambrian transverse faults, whereas the serrated margin of the post Gondwana, Post cretaceous and post Tertiary coast lines are attributed once again to the Precambrian faults reactivated time and again. During the Quaternary period the coast line has undergone many modifications. The coast line attained sinuosity due to Pleistocene folding which is well manifested by river migration. The coast line was subsequently faulted and shifted with en echelon pattern due to N-S regional compression which is referable to the collision of Indian Plate with Tibetan plate.

Mosaic is the combination of two or more raster images into single image. Sometimes, single image captured by remote sensing satellite doesn’t completely covers the desired study area mostly. Therefore, users resort for mosaicking two or more images captured by satellite sensors from different paths so that the whole study area is merged into a single raster image to facilitate the image processing and analysis. The pixel size of the raster images should be same for mosaicking.

In most of the cases, there is spatial overlapping among the raster images from which we want to create mosaic. These overlapping areas are handled in multiple ways which is being discussed further using R – code example. For mosaicking raster images in R, mosaic function of the raster package is used.

MS-ACCESS is a very powerful RDBMS (Data Base Management System) which manages data in term of special table called relation. Using MS-ACCESS you can manage all your information from a single database file. Database files are stored with extension. MDB.

ACCESS stores information in the form of tables and you build your database on its basis. Each row in a table holds all information’s & for a particular person it is called a record. And each column contains different pieces of information regarding that person, like Roll No, Name, Class, Address etc. Same as MSACCESS involves.

In ACCESS, you have few things known as Forms, Reports and Queries. They allow you to check and get desired information as and when required.

15.1. Minimum Support Price (MSP)

MSP are announced by GOI at beginning of sowing season for certain crops on basis of recommendations of CACP.

MSP is price fixed by GOI to protect producer - farmers against excessive fall in price during bumper production years.

Guarantee price for their produce from the Government.

Objectives are to support farmers from distress sales and to procure food grains for PDS.

The word mulch was coined by Wagganor in 1960. It is derived from the German word ‘molsch’ means “easy to decay,” and mulches have widely been used for vegetable production since ancient times (Lightfoot 1994). Therefore the term mulching refers to the practice of covering the soil surface with different organic and inorganic materials, known as mulch materials to reduce moisture loss, balance wide variations in diurnal soil temperatures especially in the root zone, control weeds, insect-pests and diseases and finally enhance crop yield (Nalayini 2007; Kader et al. 2019).

ABSTRACT

Mangrove wetlands are well known as the dominant feature of the intertidal areas of the tropical and subtropical regions. Ecologically mangrove forests are important for their inherent biological productivity in the habitat and also by exporting organic matter produced into coastal waters. Apart from that mangroves act as bioshield against natural coastal hazards like cyclones, storms and tsunamis. Remote sensing coupled with GIS is an important tool in monitoring the coastal areas such as mangroves, where the physical survey is difficult and time consuming. Remote sensing has a wide range of products with higher spatial, spectral and temporal resolutions, the combination of which can be applied in different themes based on the requirement. The present study used multispectral, multi-temporal and high-resolution remote sensing data to map and monitor the distribution of mangrove forest of Pichavaram, south India over a period of 30 years. The study shows that the mangrove area had decreased from 628 ha to 411 ha from 1977 to 1994 and increased to 858 ha in 2006. The high resolution remote sensing data with 4 m spatial resolution was used to prepare the mangrove wetland map in 1:5000 scale.

Keywords : Mangroves, remote sensing, visual interpretation, IRS, IKONOS

Introduction

Time series data is data that has been collected in a specific pattern with time stamps. (Nayak and Ghosh, 2013). This type of time-oriented data is collected at regular intervals, such as hourly, daily, monthly, or weekly. Time series data can be used to make accurate predictions in a variety of fields and domains, such as foreign currency rates, stock market trends, energy consumption estimates, and climate change. Machine learning and data mining techniques can be used to uncover hidden patterns in historical data and forecast future trends (Aftab et al. 2018a, 2018b, Mishra et al. 2017).

Weather forecasting based on historical data is a complex but very beneficial task that comes with several issues that must be resolved to achieve optimal results (Wu and Chau, 2013). Weather data includes attributes or features such as temperature, pressure, humidity, and wind speed. Machine learning techniques are used to forecast future weather conditions by identifying hidden patterns and relationships in historical weather data (Aftab et al. 2018b). Prediction of precipitation is an important part of the weather forecasting process. The use of machine learning and artificial intelligence techniques is regarded as a critical component in farmer services and policy formulation. Farmers require weather forecasting to plan their activities following the predicted weather. Accurate and timely rainfall prediction in farming, in particular, can be extremely beneficial in planning and security measures for operations, agricultural tasks, water reservoir systems, and construction and transportation activities (Chau and Wu, 2010). Forecasting rainfall will become increasingly important in the future.