eChapters

1. ………… is the father of plant pathology.

   a) T J Burril

   c) Anton De Barry

   b) Needham

   d) E J Butler

2. ……… first time reported that plant diseases are caused by bacterium.

   a) Robert Koch

   c) Kuhn

   b) E F Smith

   d) T J Burril

Q1. The exit of drug from C.S.F. irrespective of its entry is by

1. Passive diffusion
2. Filtration
3. Facilitated diffusion
4. All of the above

Q2. The number of half-lives required to reach 99% of steady state concentration is

1. 3.3
2. 4.4
3. 5.5
4. 6.6

Q3. The receptor concept was first introduced by

1. J.N. Langley in 1878
2. Simonis in 1964
3. Paul Ehrlich in 1926
4. Walksman in 1826

This chapter introduces the integration of Geographic Information Systems (GIS), remote sensing, and artificial intelligence (AI) for modern forest monitoring and management. It explains how remote sensing provides spatially continuous information, GIS functions as a spatial database and decision-support environment, and AI and machine learning enable prediction and pattern recognition. Applications include forest inventory, carbon estimation, biodiversity assessment, forest-fire detection, insect monitoring, and disturbance mapping. The chapter also examines GeoAI, smart forestry, emerging technologies, data challenges, and future opportunities such as cloud-based geospatial platforms and explainable AI.

Since the dawn of the Industrial Revolution, mankind has been introducing numerous hazardous compounds into the environment at an exponential rate.  Environmental pollutants have become a major global concern. The modern growth of industrialization, urbanization, modern agricultural development, energy generation, have resulted in indiscriminate exploitation of natural resources for fulfilling the human desires and need, which have contributed in disturbing the ecological balance on which the quality of our environment depends.
 
Technological revolution has brought new changes in products and processes in industry. The waste generated from the development of products and processes are of concern to the environmental list. A variety of pollutants such as heavy metals, xenobiotics, polycyclic aromatic hydrocarbons (PAHs), chlorinated and nitro-aromatic compounds are found to be highly toxic, mutagenic and carcinogenic for living organisms (Zhang and Bennett. 2005; Samanta et al., 2002).

There are various weather hazards that affect agricultural productions. These hazards affect crops and agricultural productivity negatively if they are not checked. Weather hazards include cyclones, droughts, floods, hailstorms, heatwaves and cold-waves. The hazard is distinguished from an extreme event and a disaster. An extreme event is simply an unusual event; it does not necessarily cause harm. A disaster is an event that does cause harm in significant amounts. Weather hazards are often called as natural hazards. The natural hazards become natural disasters when people’s lives and livelihoods are destroyed. Hydrologic hazards are the result of either excess or a severe lack of water, i.e., flood or drought. By issuing accurate forecasts and warnings in a form that is readily understood and by educating people about how to prepare against such hazards, before they become disasters, lives and property can be protected.

DROUGHT

Drought is a relative term used with reference to deficiency of rainfall when compared to normal rainfall of a given location. However, drought cannot be defined in terms of amount of rainfall or number of days without rain. Since ancient times droughts have had far-reaching effects on humankind by causing the failure of crops, decreasing natural vegetation, and depleting water supplies. Drought is different from other hazards; in that it develops slowly. It is a hazard that requires many months to emerge and that may persist for many months or years thereafter. This type of hazard is known as a ‘creeping’ hazard. Generally, this occurs when a region receives consistently below average precipitation.

12.1 Introduction

There is no other pair of words except the pair “Multi-Collinearity” which is more misused both in “Econometric Texts” and in “Applied Literature”. In many practical problems, many of our explanatory variables are found to be highly correlated among themselves.

One of the assumptions of the “classical linear regression model (CLRM) is that there is no “Multicolinearity” among the regressor variables included in the regression model.

Sustainability refers to productive performance of a system over time. It implies use of natural resources to meet the present needs without jeopardizing the future potential. The Technical Advisory Committee of the Consultative Group of International Agricultural Research has defined sustainability as “Successful management of resources for agriculture to satisfy changing human needs while maintaining or enhancing the quality of the environment and conserving natural resources” (TAC, 1989). A sustainable system must be sustainable both ecologically and economically.

During the past several decades, production of horticultural crops has undergone a tremendous change in both developed and developing countries due to the development and use of fertilizers, pesticides, mechanization, soil fumigation, container production in soil-less media, breeding, micropropagation, pathogen elimination and a number of other innovations for attaining its future stability and sustainability. Recently, in modern horticulture, enhanced productivity depends heavily on inputs of fertilizers and pesticides to maintain an economic level of productivity. On the other hand, social and economic pressures are demanding that agricultural/horticultural practices, that have a damaging impact on the environment and pose risk to health of mankind, be curtailed. Thus throughout the world, agriculture including horticulture is at crossroads in terms of its future stability and sustainability. The solution for the above lies in developing new technology with reduced use of fertilizer and pesticides besides maintaining a sustainable level of productivity. The increased concern about the sustainability and undesirable side-effects of chemistry-based agriculture is prompting many researchers to more seriously evaluate alternative approaches. One such effort was put forth in the management of microbes that live in the rhizosphere soil around the roots of nearly all terrestrial plants. It has been believed that the main orchestrators of microbial activity in the rhizosphere are mycorrhizal fungi.

Female Genital System

Developmental Anomalies

Agenesis

Absence of ovary, uterus, oviduct and cervix in females. It may be unilateral or bilateral.

Hypoplasia

Complete or partial lack of germ cells in ovaries. Hypoplasia of uterus is related with agenesis of gonads. Ovaries of freemartin are also hypoplastic. Hermaphrodite animal has ovary and testicular tissue both in the gonads.

Hermaphroditism

In hermaphrodites, there is presence of organs of both sexes in same individual animal. Both ovarian and testicular tissue occur in one animal leads to sterility in animal (true hermaphrodite) while in pseudohermaphrodite the gonadal tissue of only one sex is present but there is some degree of development of opposite sex organs.

What is Nanotechnology? Answers differ depending on who you ask, and their background. Broadly speaking however, nanotechnology is the act of purposefully manipulating matter at the atomic scale, otherwise known as the “nanoscale.” Coined as “nano-technology” in a 1974 paper by Norio Taniguchi at the University of Tokyo, and encompassing a multitude of rapidly emerging technologies, based upon the scaling down of existing technologies to the next level of precision and miniaturization. Taniguchi approached nanotechnology from the ‘top-down’ standpoint, from the viewpoint of a precision engineer.

Foresight Nanotech Institute Founder K. Eric Drexler introduced the term “nanotechnology” to the world in 1986, using it to describe a ‘bottom-up’ approach. Drexler approaches nanotechnology from the point-of-view of a physicist, and defines the term as “large-scale mechano synthesis based on positional control of chemically reactive molecules.” In the future,“ nanotechnology” will likely include building machines and mechanisms with nanoscale dimensions, referred to these days as Molecular Nanotechnology (MNT).

The word meat comes from the old english word mete, which referred to food in general. Most often this means the skeletal muscle and associated fat but it may also describe other edible tissues such as organs, livers, skin, brains, bone marrow, kidneys and lungs etc. In other words we can say meat is those animal tissues which are suitable for use as food by the man. It is composed of numerous types of tissues like muscle tissues, epithelial tissues and nervous tissues but the major component of meat is muscle. Particularly skeletal muscle is the principal source of muscle tissue in meat while smooth muscle contributes little to meat. The muscle and connective tissues are the major compositional components and contributes towards qualitative and quantitative characteristics of meat. Broadly muscle can be classified into striated and smooth muscles. Striated muscles have transverse band pattern as seen in skeletal and cardiac muscle. However, smooth muscles do not show such pattern and mainly found as a component of blood vessels.

Abstract

Plant Bioinformatics is a new and rapidly evolving field driven by the advances in ‘Omics’ technologies. This chapter is intended to help both beginners and experienced researchers to develop and apply bioinformatics tools to specific areas of plant genomics research. This chapter will also help plant biologists to access and implement comparative genomics studies of the plant genes of interest. Also discussed are the databases which house the data on plant genes and genomes. The chapter ends with a review of basic Perl Programming for sequence motif analysis beneficial for plant biologists.

Introduction

Ever since the discovery of DNA structure, the field of plant genomics has experienced a dramatic change in the ways scientific problems are approached. With the recent advances in High Throughput analysis clubbed with methods like Physical mapping of genes, RFLP, RAPD, large scale EST sequencing and mRNA protein profiling, there is an enormous amount of biological data available for various analysis. As the amount of data grows tremendously, there is a demand for developing tools and methods to effectively access these assembled data for analysis, modeling, visualization and prediction. In this chapter, we emphasize on some of the key concepts in bioinformatics, tools and databases relevant to plant genomics.

The climate system is the highly complex system consisting of five major components; the atmosphere, the hydrosphere, the cryosphere, the land surface and the biosphere, and the interactions among them. The climate system evolves in time under the influence of its own internal dynamics and because of external forcings such as volcanic eruptions, solar variations and human-induced forcings such as the changing composition of the atmosphere and land-use.

The term ‘climate variability’ is often used to denote deviations of climatic statistics over a given period of time (e.g., a month, season or year) from the long-term statistics relating to the corresponding calendar period. In this sense, climate variability is measured by those deviations, which are usually termed anomalies.

‘Climate change’ refers to a statistically significant variation in either the mean state of the climate or in its variability, persisting for an extended period (typically decades or longer). Climate change may be due to natural internal processes or external forcings, or due to persistent anthropogenic changes in the composition of the atmosphere or in land use. The United Nation’s Framework Convention on Climate Change (UNFCCC) defines ‘climate change’ as ‘a change of climate behaviour which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods’. The UNFCCC thus makes a distinction between ‘climate change’ attributable to human activities altering the atmospheric composition, and ‘climate variability’ attributable to natural causes. Climate change is a long-term shift in weather conditions measured by changes in temperature, precipitation, wind, snow cover, and other indicators.

A key difference between climate variability and change is in persistence of ‘anomalous’ conditions. In other words, events that are used to be rare occur more frequently, or vice versa. Occasionally, an event or sequence of events occurs that has never been recorded before, such as the exceptional tsunami in the Indian Ocean in 2004 or hurricane season in the Atlantic in 2005. Yet even that could be a part of natural climate variability. If such a season does not recur within the next 30 years, by looking back it could be called as an exceptional year, but not a ‘climate change’. Only a persistent series of unusual events taken in the context of regional climate parameters can suggest that a potential change in climate has occurred.

15.1 Agricultural Economics and Definition

As a separate subject, agricultural economics emerged in the beginning of 20th century when the economic issues related to agriculture aroused interest at various educational centres. The depression of 1890s which wrecked have in agriculture at many places and it forced organised farmers groups to take keen interest in farm management problems. The study and teaching of agricultural economics was started at Harvard University (U.S.A.) in 1903 by Professor Thomas Nixon Carver. Agricultural economics may be defined as the “Application of Principles & Methods of economics to study the problems of agriculture to get maximum output and profits from the use of minimum in but for the wellness of society in general as well as the farming industry in Particular.

1. Introduction

Foods available in nature and, in some cases, the products made from it thereof contain quite an amount of water. This water not only adds volume to the food products but also provides a sight for attack by the micro organisms. Also, removal of water becomes essential if this water interferes with the end product chracteristics. There are several processes in food industries which are designed to get rid of this excess water, such processes are called concentration processes. The processes which can remove water from food substances are,- evaporation, freeze concentration and membrane based processes. All these process have their limitations in rendering solid content to the final product (Fig. 1). Perhaps, these limitations can be overcome by combinig the processes.

The objectives that are fulfilled by the concentration processes can be enumerated as follows:

Introduction
The integration of bioinformatics into plant breeding has been shaped by several key milestones over the past few decades. Concepts like Breeding 4.0 (Wallace et al.,2018) and, 5G Breeding (Varshney et al., 2020) have gained global prominence, strengthened by the availability of extensive omics data. The advent of DNA sequencing technologies marked a key milestone in this field, catalyzing numerous genome sequencing projects worldwide such as Arabidopsis, rice, tomato, maize, wheat, etc. Next-generation sequencing (NGS) platforms, such as Illumina, PacBio, and Oxford Nanopore, have enabled rapid sequencing of entire plant genomes, facilitating the identification of genetic variations, including single nucleotide polymorphisms (SNPs), insertions, deletions, and structural variants (Deschamps & Campbell, 2010; Fuentes-Pardo et al.,2017). These advancements have significantly improved comparative genomics, enabling researchers to compare the genetic makeup of different plant species or varieties and identify genes associated with agronomic traits, such as yield, disease resistance, and environmental stress tolerance (Khan et al., 2024). As a result, these developments have revolutionized plant genetic research and crop improvement strategies, providing unprecedented opportunities to enhance agricultural productivity (Bellare et al., 2018; Shendure and Ji, 2008).
Bioinformatics has revolutionized plant biology by combining computational and statistical tools to analyze genomes, transcriptomes, proteomes, and metabolomes facilitating insights into genome structure, function, and evolution (Yadav et al., 2015; Saha et al., 2023; Roychowdhury et al., 2023). Genomics, emerged in the 1980s primarily focussing on mapping and sequencing genomes and there after laid the groundwork for functional genomics, which systematically explored gene functions (Hieter and Boguski, 1997; (Jackson et al., 2011). Further, advances in sequencing technologies, such as long-read platforms, have enabled detailed analyses of structural variants in crop genomes, crucial for identifying agronomic traits.
The large volumes of genomic sequence data have allowed researchers to identify genetic markers for crop improvement and candidate genes for trait development. However, the full potential of these genomic sequencing efforts depends on assigning functions to the thousands of genes with unknown roles. Model organisms such as humans, mice, Arabidopsis, rice, tomato, Medicago, and wheat have been instrumental in advancing genomic investigations (Bult, 2006). A notable example is the model organism Arabidopsis thaliana, which has provided a foundation for exploring fundamental biological phenomena using resources such as the TAIR database (Lamesch et al., 2012). Leveraging advanced bioinformatics techniques, researchers have enhanced crop productivity, mitigated diseases, and optimized resource management in agriculture. Advanced approaches like genome-wide association studies (GWAS) and transcriptome analysis continue to refine the understanding of genetic underpinnings, revolutionizing modern agricultural strategies (Mai et al., 2023).

1. Introduction:- Understanding Good Laboratory Practices (GLP)
1.1 Definition and Core Principles of GLP
The Organisation for Economic Co-operation and Development (OECD) defines Good Laboratory Practice as “a managerial quality control system that governs the organizational process and the conditions under which non-clinical health and thus, environmental safety studies are well planned, executed/ performed, vigilantly monitored, properly recorded, reported, and finally archived”. This definition highlights that Good Laboratory Practices (GLP) is a comprehensive framework focused on ensuring the quality and integrity of the entire study lifecycle, rather than dictating the scientific validity of the research itself. The primary goal of GLP is to ensure process integrity and data traceability, which are essential for the regulatory acceptance of safety data for a variety of products. These products include pharmaceuticals, pesticides, cosmetics, veterinary drugs, food additives, feed additives, and industrial chemicals, all of which undergo non-clinical testing to assess their potential health and environmental risks. It is important to note that GLP principles specifically apply to these non-clinical studies and exclude research involving human subjects. The OECD Principles of GLP are internationally recognized and serve as the basis for GLP regulations in numerous countries worldwide. These principles outline the responsibilities of key personnel involved in non-clinical studies, including test facility management, the study director, study personnel, and quality assurance personnel. Furthermore, they establish minimum standards concerning the suitability of facilities and equipment to perform studies, as well as the necessity for comprehensive Standard Operating Procedures (SOPs) to guide all aspects of laboratory operations. The core principles of GLP encompass a wide range of elements critical to ensuring the quality and integrity of laboratory studies. These OECD principles of Good Laboratory Practices (GLP) include: the proper organization team and personnel staff members within the testing facility, the well establishment of a robust quality assurance programme, the better suitability and proper maintenance of various necessary facilities, the efficient management of apparatus, materials, and reagents, the characterization and control of test systems, the handling of test and reference items, the development and adherence to Standard Operating

Seepage is the movement of water through the soil body and foundation of a hydraulic structure. In an earthen dam, uncontrolled seepage may produce excessive water loss, high pore-water pressure, slope instability, internal erosion, piping, or complete structural failure. Seepage analysis therefore determines the quantity and path of water movement and helps engineers design filters, drains, impervious cores, cut-offs, and other protective components. This chapter explains the objectives and importance of seepage analysis, Darcy’s law, permeability, seepage velocity, phreatic lines, flow nets, equipotential lines, and flow channels. It also examines seepage forces, piping conditions, exit gradients, and methods for improving dam safety.

1.1 Water and its Importance

Water has played a crucial role in sustainace of lives of all living beings including animals, plants and human beings in this earth since time immemorial. It is there since the creation of the nature and will probably remain till the destruction of the nature. It is used in multifarious uses including domestic, industrial, agricultural, recreational and many other uses. It occurs in the nature in practically three forms i.e. solid, liquid and gaseous forms. All the three forms are important to living beings; but the liquid form of water is more beneficial. The weight of the water helps in running hydroelectric turbines, the density of water helps in floating the ships, the steam energy produced by heating the water helps to run the locomotives and thus is beneficial in many ways. It is considered as the most important resource of the society. It has become part and partial in our life so that we cannot live without water. That is why water is called as life.

Abstract

Ongoing rise in human population and affluence, and socioeconomic imperatives continue to demand more efficient and productive use of global finite resources. This is particularly true with water which society has to share between its domestic, industrial, agricultural, environmental and recreational purposes. With greater concern for nature and environment, and the socioeconomic development more water must be allocated to non-agricultural uses. Increasing crop water productivity (WP) is a key response option conserves water, energy and soil while satisfying society’s increasing demand for crops for agricultural products. Improvements to crop WP help to meet rising demands for food from a growing, wealthier, and increasingly urbanized population, when at the same time there are pressures to reallocate water from agriculture to cities and to make more water available for environmental uses contribute to the urgency for achieving gains in agricultural water management. The papers in addition to the rationale and basic concept of crop WP, explore the techniques for crop WP increases.

Botanical Name: Elaeis guineensis Jacq.

Family: Arecaceae / Palmae

Chromosome No: 32

Place of Origin: Guinea Coast of West Africa

Common Name: Oil Palm

4.1 Introduction

The cultivated oil palm Elaeis guineensis Jacq. is a native of West Africa and exists in wild, semi- wild and cultivated forms. It was introduced as an ornamental crop in 1860 and planted at National Botanical Garden, Kolkata. Research on oil palm in India started during 1960 with the establishment of a research station at Thodupuzha by the Department of Agriculture, Kerala with Dura and Tenera germplasm imported from Malaysia and Nigeria. National Research Centre (NRC) for oil palm is situated at Elur, Andhra Pradesh. Oil palm crop is one of the highest oil yielding crops among all perennial crops. It gives 4 to 6 tonnes of edible oil/ha from 3 to 25 years of its life span compared to less than one tonne of oil per ha from other cultivated oil yielding crops. This oil palm is considered as golden palm due to its high yielding capacity. Among the 10 major oilseeds, oil palm is accounted for 5.5% of global land use for cultivation, but produced 32.0% of global oils and fats output.