eChapters

1. Guidelines on Analytical Terminology

    1.    Accuracy : The closeness of agreement between a test result or measurement result and a reference value.

    2.    Analyte : The chemical substance sought or determined in a sample. This definition does not apply to molecular biological analytical methods.

    3.    Applicability : The analytes, matrices, and concentrations for which a method of analysis may be used satisfactorily.

    4.    Bias : The difference between the expectation of the test result or measurement result and the true value. In practice conventional quantity value can be substituted for true value.

    5.    The bias of a measuring instrument is normally estimated by averaging the error of indication over the appropriate number of repeated measurements. The error of indication is the: “indication of a measuring instrument minus a true value of the corresponding input quantity”.

    6.    Calibration : Operation that, under specified conditions, in a first step, establishes a relation between the values with measurement uncertainties provided by measurement standards and corresponding indications with associated measurement uncertainties and in a second step uses this information to establish a relation for obtaining a measurement result from an indication.

    7.    Certified reference material (CRM) : Reference material accompanied by documentation issued by an authoritative body and providing one or more specified property values with associated uncertainties and traceability, using valid procedures.

The family Solanaceae consists of 85 genera, which include both tuberiferous and non-tuberiferous ones. Brinjal (Solanum sp.), chilli (Capsicum sp.) and tomato (Lycopersicon sp.) are the major fruit vegetables under the family. In all genera, fruit is an indehiscent berry.

A key for the identification of the above three genera are furnished below:

A. Anthers connivant in a cone, longer than filaments

B. Anthers dehisce by apical pores or short slits, leaves entire, lobed or pinnatifid - Solanum

BB. Anthers dehisce introsely by longitudinal slits, the tips empty, leaves pinnatiset - Lycopersicon

AA. Anthers not connivant in a cone, not larger than the filaments, dehisce by lateral slits - Capsicum

Introduction

Castor plant (Ricinus communis L) is an age old crop of India which has been in use in Ayurvedic medicine since 2000 BC, when the oil was used in lamps and also in local medicine particularly as a laxative and also to cure arthritis. The seeds of the crop yield non-edible viscous oil which has a number of applications in industry apart from its medicinal properties, which are well documented in Ayurvedic, Siddha and Unani medicine. The word Ricinus in the scientific name of the castor plant has cropped due to the appearance of its seed resembling dog’s tick!

Castor is cultivated on commercial scale in an area of 1,296,855 ha in 30 countries with global castor seed production at 1,396,104 MT (FAO STAT, 2019). India is the world’s single largest producer of castor seed accounting for more than 85% followed by China with about 7% and Brazil with about 5% of world castor seed output. There has been a consistent increase in output primarily on account of rise in yield levels in India. In recent years, however, Brazil and China have experienced stagnation in castor crop. Castor is widely grown in Ethiopia too. Among oilseed crops of India, castor crop has registered positive and high growth rate along with soybean (Mohapatra 2017).

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.

The transition from an agrarian society to a more advanced and diversified economy represents a profound shift in how societies function and evolve. Initially, agrarian societies are primarily centered around agriculture, with the majority of the population engaged in farming and related activities. As agricultural productivity improves through technological innovations, such as advanced machinery and crop varieties, these societies begin to experience economic growth. This growth often spurs industrialization, leading to the establishment of manufacturing sectors that create new job opportunities and drive urbanization. Cities expand as people migrate from rural areas in search of better employment prospects, leading to significant social changes. Education and skill development become crucial, as improved literacy rates and vocational training prepare individuals for diverse professions beyond agriculture. The transition from an agrarian society to a more advanced and diversified economy marks a profound shift in societal functioning and evolution, encompassing multiple dimensions that can be examined through various disciplinary lenses. Economically, this transformation begins with improvements in agricultural productivity, driven by technological innovations such as advanced machinery and high-yield crop varieties. These enhancements not only increase agricultural output but also reduce the labour required for farming, thereby freeing up labour for other sectors. This shift often triggers economic growth, which spurs industrialization. As manufacturing sectors develop, they create new job opportunities, driving urbanization as individuals migrate from rural areas to cities in search of better employment prospects. This economic expansion is central to understanding the broader changes that occur as societies evolve from agrarian to industrial and post-industrial economies.
From a sociological perspective, the transition to a diversified economy leads to significant social changes. Urbanization alters family structures, social networks, and community dynamics. As people move to urban areas, traditional agrarian values give way to new social norms and practices associated with city life. Education and skill development become critical, as improved literacy rates and vocational training prepare individuals for diverse

In this chapter, a comprehensive list of all plants and trees mentioned in epic Ramayana has been furnished with salient details in order to establish their botanical identity and references of Sholka where it had been mentioned. Some of the plants and trees had been mentioned in multiple sholokas but the plant has been taken into account as a single reference to avoid repetition and to get correct count of the trees and plants in whole of the Epic (Amirthalingam, 2013, Arun Kumar, 2019; Balapure et al., 1987; Bast, 2022; Ghimire et.al, 2021; Mao and Dash, 2010; Prasad and Mishra, 1976).

The plant species mentioned in Ramayana were of different types having various usages. Considering their morphological characteristics, usages and other importance, they have been categorized broadly into the following heads.

1. Economically important plants (Timber value, product yielding etc. having commercial importance).

2. Edible (major and minor fruits etc.).

3. Culturally important plants (Plants used for plantation for shade, greening etc.).

4. Non-Edible Plants (Ornamental importance and other usages)

5. Medicinal Plants (having therapeutic uses).

6. Sacred Plants (having religious importance).

7. Others (having multipurpose uses).

1. DISEASES OF MANGO

Mango is considered to be the king of fruit. India is the largest producer and exporter of mango in the world. Mango possess unique nutritional and medicinal qualities apart from being a rich source of vitamins A & C, besides its attractive form and appearance, delicious taste and appetizing flavor, the ripe mango fruit according to nutritional experts is also highly invigorating, fattening, laxative and diuretic. Every part of mango from root to tip is used in a variety of ways. This crop is affected by many fungal, bacterial and other non parasitic diseases.

1. Mango Malformation Disease (MMD)

Mango Malformation Disease is a fungal disease of mango caused by several species of Fusarium, some yet to be described. Mango is the only known host of the disease. The disease spreads on a tree very slowly, but if left unchecked, can severely reduce yields. The main method of spreading MMD to new areas is through infected vegetative planting material. There is no evidence that the disease can spread on fruit or the seeds, or that it affects human health. It usually associated with the bud mite, Aceria mangiferae but the mites have been shown to spread the disease within a tree and not between the trees. Mango malformation, also known as bunchy top, is a very serious threat to the mango industry, particularly in northern India. The Etiology of the disease still remains obscure and diverse claims have been made about its causes, e.g., physiological, viral, fungal, acarological and nutritional.

5.1 INTRODUCTION: THE PHYSICAL CHEMISTRY OF COLLOIDAL SUSPENSIONS

This chapter is concerned with understanding the factors which influence the partition of ions between solid surfaces and aqueous solutions. There are many aspects of soil science such as some of those concerned with soil formation, transfer of nutrient ions from soil particles to plant roots, soil pollutant interaction and soil management which are critically dependent on what happens in the space of the order of 1 nm wide between solid and equilibrium solution. A broad survey of the development of ideas on soil-electrolyte interaction shows that there have been two main avenues of approach. One views the soil as an electrically charged surface with its adsorbed hydrated ions as one phase in equilibrium with solution, which is seen as the second phase. The other approach focuses on the electrical double layer extending from the charged solid surface out into the solution. In the latter approach the solid surface, the outer equilibrium solution and the make up of the transition zone between these two phases must all be involved in any detailed consideration of the micro structure of the system. For a full and proper understanding of soil-electrolyte interaction anything less than a detailed analysis of the micro-structure is likely to be inadequate and in this it must be remembered that the interaction between electrical double layers which overlap with one another is likely to be important.

4.1. Data Set Generation for Modelling
We have generated 54 transfomed spectra by applying different combination of parameter. Now this spectrum is to be tagged with respective soil sample and desired soil properties for which spectral modeling has to be done. Here we are generaring data tagged with CaCO3.
For that we have to use cbind() fuction. Here we are keeping soil properties in first column and spectra after that column. We are storing data in R memeory and naming data in such way that we can identify properties and transfoemed spectra attached with that data. After generating data for modeling, data is divided into calibration and validation data set by using random sampling method or Kedard-
Stone method
# Data set for CaCO3 with raw spectra ####
Data.CaCO3.pc.113=cbind(data10nm_$CaCO3_equivalent_per, First_ derivative10nm113) #case 1st
Here in case 1st, CaCO3 indicating properties and 113 indcating without smoothed 1st derivative, 1st order polynomial 3rd point spectra is tagged with these soil samples. Same was followed with other cases also

Abstract

Design, operation and optimization of dryers demands the calculation of energy consumption, in most cases in the form of thermal energy, equipment sizing, temperature and moisture distribution of solids as well as temperature and humidity distribution of drying air. Energy calculations are very important as drying is a widespread process in a variety of industries and is highly energy demanding. In the energy analysis of the process the first step is the estimation of the minimum energy requirement followed by the estimation of energy rejection through solids stream and especially through drying air. Increase of thermal efficiency is always willing and the two most common ways for its achievement is the application of heat exchange between cold feeding air and relatively hot rejecting drying air and hot air recirculation. The later is also employed for the adjustment of air temperature and humidity gradient through the dryer. The combination of a heat pump with the dryer decreases considerably the thermal energy consumption but demands electricity and the method can be beneficial in cases of excess electricity production in the process plant, e.g. by cogeneration. Utilization of exhaust hot air from the main drying unit for the predrying of wet solids can also decrease the total energy requirement. The application of humidity adsorption from the feed air increases its drying potential, but regeneration of adsorbent is required. Grand composite curve of the process plant can reveal potential heat sources from different unit operations.

9.1 Introduction

Water is a precious commodity. Necessity of conservation of water supply is increasingly felt all over the world as the demand of it continues to increase when the sources of supply are increasingly scarce. The conveyance and proportional distribution of water is one of the most important part of any irrigation project. Water available in the stream, reservoirs or wells is carried to the field of use through canals. The economy of any irrigation project largely depends on how efficiently the water is being transported and distributed in respect to water losses and cost.

Water losses in irrigation channels are mainly due to evaporation from the water surface and seepage from the bed and side of the channels. Seepage losses some time become the single important factor which causes unavailability of water particularly in downstream of the channel in canal irrigation system and excess pumping of water in tube wells and river lift irrigation system.

INTRODUCTION

Mango (Mangifera indica L.) belonging to Family Anacardiaceae is the most important commercially grown evergreen tree of tropical and subtropical regions of the world. Due to its wide range of adaptability, high nutritive value, colorful fruits, richness in variety, delicious juicy taste and excellent flavor, it possesses high commercial value. It is sometimes also called ‘apple of the tropics’. It is believed that cultivation of mango originally started in South East Asia where it is being cultivated for last four to six thousand years. Now, it is cultivated in 112 countries of the world. India has the richest collection of mango cultivars.

1. The protein is derived from Greek word “Proteins” which means
   1. Principal
   2. Prime
   3. Holding the first place
   4. All of the above
2. The name protein to the group of organic compounds that are utmost important to life is suggested by
   1. Mulder
   2. Berzelius
   3. Kulim
   4. Sanger

TRUE ANESTRUS IN A HEIFER OR POST PARTUM COW / BUFFALO

The animal has both ovaries small and inactive

No palpable structures in the ovaries

Animal does not exhibiting estrus signs

Comparison of different cropping systems with reference to land use and yield advantages is possible through various efficiency indices. The various cropping and farming systems practiced in an area have to be properly evaluated to decide their suitability and relative advantages. The comparisons can be made with reference to many factors viz., yield, monetary, water use efficiency, nutrient use efficiency, total dry matter production, intensity of land use etc., The cropping as well as farming systems research are being perused at national level with major focus for identification of location specific efficient systems since 1990. However, on perusal of research publications we find that the data of cropping systems are interpreted in different ways with major focus only on production and net return on hectare basis. In fact, these two aspects are not the indicator of the efficiency of a particular system. Many advances have been made in recent years to identify the efficient system for a particular location. Some of the methodologies, which are of concern to crop scientists in general and agronomists in particular, are highlighted here for ready reference to the researchers, agronomists and crop planners. Different indicators of system efficiency are as follows (Gangwar et al., 2003).

In India, goats are known as “poor man's cow” because they are an important source of income for poor and landless people. They can be reared on cheaper resources easily than other livestock.

Goats come under the genus Capra have evolved from five wild species, including Capra hircus (which includes Bezoar), Capra ibex, Capra caucasica, Capra pyrenaica, and Capra falconeri. This evolutionary pattern contributes to their phenotypic diversity and adaptability to various environments. The chromosome profile of goats (specifically the Capra hircus species) reveals some interesting features which are as follows:

Chromosome Number
The modal chromosome number for goats is 60.
These chromosomes can be categorized into different types based on their centromere position:
Autosomes: These are either acrocentric or telocentric.
X Chromosome: It is acrocentric.
Y Chromosome: It is submetacentric.

Identification

Quinacrine-mustard staining and fluorescence microscopy allow us to identify 28 out of 30 chromosome pairs in goats.

Soil Chemistry is the study of chemical composition of soil in relation to crop needs. It deals with the chemical constitution of the soil, the chemical properties and the chemical reactions in soils. Traditional soil chemistry focuses on chemical and biochemical reactions in soils that influence nutrient availability for plant growth, and potential environmental consequences associated with inorganic and organic fertilization. Soil chemistry has increasingly focused on soil genesis and the environment over the past few decades.

1.1 Weather Parameters

The atmosphere is a gaseous component surrounding the earth as an integral part and its interaction with ocean (water bodies), other planets of the solar system and land (Earth) generates one physical product namely weather elements (temperature, pressure, wind, humidity, precipitation, etc.,) and these form the weather and climate of the Earth. The process of generation of weather and climate of the region is purely natural and cannot be modified by the human being. But they can do adaptation to the existing climate and weather for their sustainable life. The weather can be defined as day to day change in the atmosphere in terms of heat and moisture exchange, while the climate is average of long period weather covering larger area or a region.

The particular climate of a region dictates/permits the genesis of a particular bio-organism in that domain and this selected organism’s growth and multiplication are triggered by the prevailing weather of that particular climate. Hence weather parameters of the atmosphere are very important to human being and other organisms of the Earth. The details on weather elements are given in question and answer section of this book (Annexure-I)