eChapters

Accurate crop-yield forecasting supports food-security planning, resource allocation and farm decision-making. Yield is influenced by interacting factors such as weather, soil, irrigation, fertilizer and pesticide use, making reliable prediction challenging. This chapter presents an algorithmic framework using historical agricultural and environmental data. It covers cleaning, missing-value treatment, categorical encoding, normalization and feature extraction. Decision Tree, Gradient Boosting, AdaBoost and XGBoost regression models are evaluated individually and combined through soft voting. Performance is measured using standard prediction-error metrics. The case study demonstrates that ensemble modelling can improve accuracy and robustness, helping farmers and planners optimize inputs, anticipate production and strengthen agricultural productivity.

Abstract

The objective of the study is to build a framework of Geo-spatial Information System for effective decision making by empowering all the stake holders with spatial and non-spatial data. The Interface of this information system is developed as a deployable windows application using Map Objects in Visual Basic programming language with MS Access database. The practical utility of the proposed information system was explained with a case study in Aquaculture. This geo-spatial information system provides required information through maps based on spatial and attribute quarries. These dynamic maps help in taking effective decisions.

1.0 Introduction

Computer based information systems proved to be very efficient and effective tools for managing data and information to aid in decision making . FAO (2000) proposed agricultural knowledge and information system for rural development (AKIS/RD) to link rural people and institutions to promote mutual learning and generate , share and utilize agricultural technology , knowledge and information. This serves as vehicle for sharing ideas and principles with various stake holders addressing the problems and seeking solutions to rural development. Although the rural development planning is top-down prescriptive approach , in reality the decisions are made by the stake holders based on their perspectives, knowledge and priorities. Problems particularly related to environmental impacts are location specific and contextual. Geo-spatial technologies may serve as better vehicle to store and share all kinds of location specific data and information. The state of mapping and management of geospatial data changed during the recent years with the diffusion of modern geospatial information technologies such as GIS(Geographic information system), GPS(Global positioning system) and image analytical system for remote sensing(RS) data. Adinarayana et al., (2008) proposed a geographical information and communication technology (Geo-ICT) based information system called Grama Vikas( rural development) to assist the user in analyzing the rural information for rural development, planning . During the recent years there is a paradigm shift in GIS applications for rural development particularly in developing countries, by way of integrating top-down approach with bottom-up approach by the stake holders who stand to be affected by the decisions based on these technologies. Emerging concepts include “ community - integrated GIS”, “GIS in participatory research” and ‘participatory GIS”. (Abbot et al., 1998)

Abstract

The East Coast of Tamil Nadu exhibits a spectacular network of deltas formed by the easterly flowing river systems. The study of raw and digitally enhanced Landsat TM and IRS data shows, that these deltas were formed due to multivariate dynamic processes of fluvial, marine and aeolian actions. The wide fan shaped delta observed northwest and north of Madras city spanning out over an area of 700 sq.km is a feature, standing testimony to the PaleoCauvery river systems.

The regional slope and the overall arcuate arrangement of the crescent shaped lakes in the area and the tentacles of paleochannels show, that it is overall a fan shaped delta and its successive growth towards the sea might have been due to the constant progradation of lobes by continuous reworking of preceding lobes. The depressions in between successive concentric lobes have become the lakes. The absence of any beach ridges in such palaeo deltaic regime suggests that, it would be a sub aerial delta only. The overall arcuate shape of the shoreline in between Madras city in the south and Pulicat lake in the north is due to this fan delta. This feature once again symbolises the active river dominated delta. The Palar delta is a ‘cuspate’ one. The Ponnaiyar river has developed a linear delta, along a narrow depression found in between Tertiary uplands. While the avulsion phenomenon indicates the ancient shoreline near Villupuram, the east-west trending micro sandy uplands within the delta suggest, that it is a tide dominated delta.

8.1 Introduction

The objective of this chapter is to develop a smart control for site-specific management of fixed irrigation system with Blynk app. Mobile app is designed to control the water management in field. The complete system comprises of two sections field device and mobile app. Field device comprises of Arduino, Node MCU, Power supply, LCD, Relay board, soil moisture sensor, temperature & humidity sensor, water level sensor, motor1, motor2. The system is designed to establish control and communication with specific agricultural field to take sensory data from the sensors and control the PUMP IN motor and PUMP OUT motor with the help of mobile app. Fig.8.1 shows a block diagram for a system.

Abstract

Amongst all types of major land-use change, extending irrigated agriculture using a surface-water source has the greatest influence on groundwater – both significantly increasing recharge and changing water quality as excess irrigation water infiltrates into shallow aquifers. Hence, in order to understand the impact of the landuse on the groundwater system the study has been aimed to understand the process by adopting geophysical, geochemical and microbial analysis of groundwater samples. The study has been conducted in Chidambaram taluk, with a total area of 92.51Sq.km. A total of 39 groundwater samples were collected for the analysis of major cation and anion along with the microbial analysis, like Total Coliform, Total Viable Counts, Fecal coliforms, Vibrio cholera and Total Streptococci. The geochemical studies reveal that there is no correlation between these parameters and the microbial population. The migration of the water from the elevated regions (urban region) is witnessed and the concentration of the microbial population is higher in these regions except in the southern region which has impermeable clay and this arrest the movement of water.

Abstract

Radon being the radioactive daughter product of Uranium; the interrelationship between U and Rn has been established in the present study. It is found that Radon coexist with Uranium in the region. A total of 61 samples were collected spatially from hand pumps and bore wells of the study area. Major ions such as Ca²⁺, Mg²⁺, Na⁺, K⁺, F^-, Cl^-, HCO^3-, NO^3-, H₄SiO₄,PO₄- and SO₄^2- and U, Rn were analysed. The lithological influence of U and Radon occurrence is also highlighted. Hard rocks especially Granites are the source for both U and Rn in the study area whereas the lack of correlation exist between U and Rn in sedimentary terrain can be attributed to difference in flow conditions and chemical properties of these elements. 

Key words: Radon, Uranium, Granite, Ground water, Source.
 

Abstract

Groundwater is most favored as a source of drinking water in all over world. It is often thought to be cleaner and easier to treat when compared with surface water and as a result, many wells have been sunk. Uranium and other radionuclides in water can lead to health problems if present in higher concentrations. In order to study the behavior and to understand the influence of lithology in groundwater of Madurai district, a study was conducted by collecting a total of 216 samples of different seasons (Premonsoon, South west monsoon, Northeast monsoon and Post monsoon) with respect to lithology and the number of samples was depending upon their spatial coverage in the study area. The groundwater samples were analysed for U, Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃^-, Cl^-, SO₄^2-, PO₄^3-, NO₃^-, F^-, H₄SiO₄, pH, EC, TDS. It was identified that the higher concentration of Uranium (156 ppb) were noted in the northern part of the study area. They are chiefly restricted to the Granitic terrain and nearby Charnockitic regions. The weathering process induces the release of higher U ions from the granitic terrain and the evaporated recharge water from the tank /reservoir  also induces the release of U ions from the rock matrix, it may also be due to fertilizer enriched agricultural return flows. The key source for all these processes and hydrogeochemical processes is identified to be lithology which inturn controls all the other processes in the study area.

Abstract

Deduction of overindulgence fluoride (F)  from the water has been endeavor by numerous investigators by using different materials both natural and artificial. The objective of this paper was to attempt the fluoride removal by using the locally available natural materials such as red soil, untreated charcoal, local powdered brick, fly-ash from Neyveli (thermal power plant) and mineral serpentine were used, adopting column method. Maximum defluoridation occurs immediately after the experiment has started. The morality of fluoride removed per gram is more in red soil when compared to the other materials. Variation of fluoride removal with time was studied after the erection of the column /unit, the defluoridation setup was then connected to the public water supply from the overhead tank of 50,000L capacity. Higher F removal was noted when flow rate was lesser. An attempt on the regeneration of the fluoride adsorbed soil was also made.

Abstract

A survey of various wheat milling units (atta chakki) available around Indian Agricultural Research Institute, New Delhi was conducted to study the performance of these. The mills of various sizes (12", 16", 18", 20", 24" and 30" stone disc diameter) with horsepower ranging between 2 to 20 are in operation. Both horizontal and vertical disc types of mills are in use. The capacity of these units ranges between 10 kg/h to 200 kg/h. The stationary sieve, hand sieve, pedestal/exhaust fan are used for cleaning. The average wheat cleaning cost is Rs. 200 per ton. A small room of 8' x 10', 10' x 10' and 10' x 12' size is used for running the mills and storage of wheat grains. The grinding charges (Rs./q) of wheat, coarse grains (maize, sorghum, millet etc) and spices are 100, 200 and 1000, respectively. Sample of 500 g of wheat and flour were collected from each chakki and were analysed for wheat grain and flour quality. Infested, damaged grains were observed to be in 2-10% range. Sieve analysis of the flour was done and the average particle size, fineness modulus and uniformity index of the flour were calculated. Average particle size, fineness modulus and uniformity index were found in the range 0.1875 to 0.2023 mm, 1.052 to 1.297 and 0:1:9, respectively. Average particle size of the flour obtained from horizontal mills was found to be higher than vertical mills. Temperature of the flour at the outlet was observed in between 45 and 50°C at room temperature of 18.5°C.

Introduction

Time series analysis is a powerful tool for detecting and describing sequential processes, and it has become increasingly important in water resource management, especially in the context of global warming and climate change. Statistical methods have been widely used for analyzing climatological time series, such as precipitation, air temperature, and evapotranspiration, and hydrological time series, such as streamflow and surface water quality. However, most of the linear time series models depend on strict assumptions, such as homogeneity, trend-freeness, stationarity, non-periodicity, and lack of persistence, which are often violated in real-world datasets. Therefore, there is a need to develop new models that are more flexible and can accommodate different types of data (Machiwal & Jha, 2006).

One of the most popular and widely used classical time series models is the Autoregressive Integrated Moving Average (ARIMA) model, which has linear statistical properties and can be built using the Box-Jenkins methodology (Box and Jenkins, 1970). This model adoption is important for hydrological analysis because it can help in accurately characterizing and predicting the behavior of hydrological time series data. ARIMA models can capture complex patterns and trends in the data and can be used to forecast future values of the time series. This can help in better understanding the underlying processes that drive hydrological variability, such as changes in precipitation patterns or land use. Furthermore, hydrological data often exhibit seasonality and long-term trends, which can be accounted for in ARIMA modeling. ARIMA models can also be used for anomaly detection, identifying unusual events that may have significant impacts on water resources. Overall, ARIMA modeling provides a f lexible and powerful framework for analyzing and forecasting hydrological time series, which is essential for effective water resource management in the face of changing environmental conditions.

Introduction

The study of spatiotemporal time series forecasting has gained significant attention in recent years, as it involves analyzing records of events that occur over both space and time. Spatiotemporal models group time- and location-specific discrete variables and are used in various sectors, including agriculture, transportation, meteorology, economics, disease mapping, sociology, environmental sciences, and ecology. However, the popular Autoregressive Integrated Moving Average (ARIMA) (Box and Jenkins, 1970) model has two major flaws: it assumes linearity, which is not always the case in time series data that may exhibit nonlinear interactions, and it is a univariate model that cannot capture spatial linkages. Hence, when investigating time series data that are not perfectly linear and involve spatial correlation, the ARIMA model should not be used. Other multivariate time series models like VARMA have also been used to represent spatiotemporal data. However, VARMA models require more parameters, and the STARMA model introduced by Cliff and Ord has fewer parameters (Cliff and Ord, 1975). In previous literatures, the STARMA model was commonly used for modeling different spatiotemporal time series data (Kamarianakis, 2003). The STARMA model was previously employed to forecast the spatiotemporal data in different fields such as economics, disease mapping, climate modeling, agriculture, etc. (Pfeifer and Bodily, 1990; Lee, 2005; Rathod et al., 2018; Saha et al., 2020 and Rathod et al., 2021).

Abstract

Soil quality assessment has been recognized as an important step towards understanding the long term effects of land management practices within agricultural watersheds. Potential soil quality issues include continued high rates of erosion, losses of organic matter, reductions in soil fertility and productivity, as well as chemical and heavy metal contamination. This case study addressed the spatial variability of soil properties and its quality at the watershed level using geostatistical methods. Soil samples from the 0- to 20-cm depth were collected on a 100- by 100-m grid across an 88-ha watershed at Sakaliseripalli village in the Nalgonda District in Andhra Pradesh State, India. Geostatistical analysis showed that most of the soil parameters were moderately spatially dependent. An assessment framework, that included a minimum data set, linear scoring technique, and additive indices, was used to evaluate the soil quality index (SQI). Through principal component analysis, cation exchange capacity, exchangeable Na percentage, DTPA-extractable Zn, available P, available water, and dehydrogenase activity have been emerged as the most important indicators for evaluating soil quality. A kriged map of SQI was prepared for the watershed. The SQI was found to be higher in irrigated systems than under rainfed conditions. In the study, potential soil loss calculated using the Universal Soil Loss Equation and crop yield were identified as the quantifiable management goals; the results indicated that soils having higher soil quality indices were more productive and less erosion prone.

Keyword : Principal Component analysis, SQI, Watershed, Geostatistics, Potential soil loss

Bread, cloth and house (Roti, Kapra and Makan) are the basic need of human life and linked directly with agriculture because agriculture provides livelihood for nearly two-thirds of the population in India and it currently accounts for 14.2% of the GDP and also employs 55% of country’s total workforce. The sharp fluctuations in agricultural growth are mainly attributed to the vagaries of monsoon. Rainfed agriculture is spread over 55% of net cultivated area, contributing over 40% to the national agricultural production.

4.1 Introduction

Precipitation is a major component of hydrological cycle. It occurs because of condensation of water vapour molecules in the atmosphere. When the precipitation falls on the grounds, it undergoes several phases before it appears as runoff in the streams. Certain amount of precipitations is intercepted by the foliage of plants and roofs and other parts of the building and other hydraulic structures. This intercepted water is called as interception loss which is evaporated to the atmosphere. Sometimes the dried surface of the buildings and other structures soak certain amount of precipitation while falling on them which also adds to interception loss. After striking the land masses, certain amount of the precipitated water gets infiltrated into the soil surface which then moves both in lateral as well as in vertical direction. This loss is called as infiltration loss. For the study of groundwater, infiltration loss is not a loss but rather it is a gain in terms of groundwater recharge. However for a surface water hydrologist, it is a loss since it decreases the amount of runoff contributing to the stream or any other water bodies.

The increasing capabilities of Large Language Models have created strong demand for real-time AI services, but their computational complexity makes low-latency deployment difficult on conventional systems. Transformer models require substantial memory, high computational throughput and efficient data movement, creating challenges for mobile devices, embedded systems, edge platforms and latency-sensitive applications. This chapter introduces hardware–software co-design as an integrated strategy for addressing these challenges. Rather than optimizing hardware and software independently, co-design aligns model algorithms with the characteristics of processors, memory hierarchies, accelerators and communication systems. The chapter examines hardware platforms including GPUs, TPUs, FPGAs and ASICs, together with software techniques such as quantization, pruning, knowledge distillation, operator fusion and memory scheduling. Hybrid architectures are discussed for reducing latency, improving throughput, lowering energy consumption and increasing scalability. Applications in healthcare, finance, autonomous driving, robotics, industrial IoT and real-time translation illustrate the importance of efficient inference. The chapter demonstrates that coordinated optimization across the full computing stack can bridge the gap between LLM capability and practical real-time deployment while maintaining acceptable accuracy and reliability.

environmental conditions tailored to the specific needs of the crop. Key factors managed include water availability, light intensity, humidity levels, temperature, and soil moisture. While this technique is extensively adopted in developed nations, its use in India remains relatively limited.
In recent years, the climate of India has experienced several disasters such as droughts, floods, and pest attacks.
India’s agricultural landscape has faced numerous challenges in recent times due to frequent natural calamities like droughts, floods, and pest infestations. These conditions have led to substantial crop losses and have pushed many farmers into financial distress. To combat this, the adoption of protected cultivation techniques has become increasingly essential, offering a path to higher productivity and profitability.
Every year, India’s Northeastern state and Coastal regions face extreme crop damage due to high rainfall.
Heavy rainfall causes severe crop destruction annually in the Northeastern and Coastal areas of India. Fortunately, greenhouses now offer a viable solution by acting as protective shelters from rain, enabling farmers in these regions to safeguard their crops effectively.
TYPES OF PROTECTED CULTIVATION TECHNIQUES
Though there are several protected cultivation techniques, the most commonly used are:
• Greenhouses
• Shade net houses
• Insect-proof net houses

Agro processing involves a diverse range of unit operations aimed at converting raw agricultural products into value-added goods. These processes serve to enhance the shelf life, quality, and overall appeal of agricultural commodities while also boosting their nutritional content and market value. The unit operations employed in Agro processing are determined by the specific characteristics of the product and the desired outcome. Common steps include cleaning, sorting, peeling, grinding, and milling. Preservation methods such as blanching, fermentation, drying, and freezing play a crucial role in preparing products for consumption or further manufacturing. Furthermore, operations like extrusion, canning, juicing, and packaging are essential for producing a variety of processed food items, while proper storage and warehousing ensure the long-term availability and sustainability of these goods. Each unit operation is designed to contribute toward creating high-quality, market-ready products, minimizing waste, and ensuring optimal utilization of raw materials. By combining these processes effectively, Agro processing maximizes the potential of agricultural resources and strengthens the overall food industry.
OVERVIEW OF MATERIAL HANDLING
Materials handling encompasses a broad spectrum of activities, including mechanical harvesting on farms, transportation of live animals, refrigerated transport of perishable goods, and pneumatic conveying of flour from rail cargo to bakery storage facilities. It is important to minimize product losses during these operations while maintaining the quality of raw materials, such as preserving vitamin content and physical appearance, ensuring sanitary conditions, reducing bacterial growth, and optimizing the timing of transfers to avoid delays that could compromise both the economy and product quality. The journey of agricultural produce from farms to processing areas often results in significant transformations. For instance, grapes are transported via tractors, trucks, or trailers to juice plants or wineries, where they are graded, washed, and processed further. However, there are limitations on the size of transport vehicles and the duration fruits and vegetables can be held. Since these are living, respiring products, prolonged storage can increase batch temperatures to levels that encourage spoilage.

INTRODUCTION
In order to guarantee that the food products produced are safe for consumption, free of contaminants, and prepared in a clean and controlled environment, food safety and hygiene are essential steps in the food production process. Maintaining consumer confidence and preventing foodborne illnesses require following food safety procedures and earning the appropriate certifications.
FOOD SAFETY SYSTEMS AND STANDARDS
HACCP (Hazard Analysis and Critical Control Points)
The HACCP method is a methodical approach to food safety that finds, assesses, and manages risks that are important to food safety. This covers biological, chemical, and physical risks.
Principles of HACCP
• Perform an analysis of the hazards.
• Determine the production process’s critical control points (CCPs).
• Determine critical limits, such as food temperature limits.
• Keep a regular eye on CCPs.
• When boundaries are crossed, set up corrective measures.
• Maintain documentation of observations and actions.
• Regularly review and revise the HACCP plan.
Good Manufacturing Practices (GMP) GMP includes all of the procedures and standards that guarantee food products are produced in a controlled and hygienic setting. GMP emphasizes

ABSTRACT

It is very important for every library to have all the resources/materials necessary to fulfil its target. The working of a library can be classified into two forms: dealing with the users and behind the scene. There are numerous different sections in a library divided on the basis of their functions. Most important of these is the Acquisition section. A library’s success lies in a well organized acquisition section. Main aim of the library is the contentment of the users. However, collection development is the primary task of the acquisition section which further contributes to user satisfaction itself. It performs the process of selection, procurement and accessioning of reading materials as well as maintains records. It organizes the monetary as well as human resources in such a manner that collection is facilitated more and that too in an economic and less time consuming way. All this is the responsibility of the librarian. Before acquiring the reading materials, the librarian is supposed to decide that which items are actually required in the library and which are to be rejected. A librarian must study the requirements of the library and acquire materials as per the priorities of the institution to achieve its goal.

Every practical problem need not have a documented solution. Most of the times to solve a practical problem, we need to apply our experience, creativity and experiment with the novel solutions in order to address the problem which have no readymade solution. Under such circumstance, we will apply our knowledge and experience in selecting, planning, experimenting and evaluation of the possible solutions. This type of problem solving approach involves action research.  Action research is a type of social research that aims at gaining an insight into the problem by learning from experiences gained in an effort to solve the problem. Here, action itself is a source of knowledge.