eChapters

Jasmonic acid: Jasmonic acid is derived from the fatty acid, linolenic acid. It is a member of the jasmonate class of plant hormones. It is biosynthesized from linolenic acid by the octadecanoid pathway. The major function of JA and its various metabolites is regulating plant responses to abiotic and biotic stresses as a well as plant growth and development processes.

Jasmine is one of India’s most important fragrant loose flower crops, valued for garlands, Veni, Gajra, religious ceremonies, festivals and perfume production. Flowers and buds are also important raw materials for jasmine oil, cosmetics, soaps and other fragrance products. The chapter describes jasmine’s origin, distribution, genetics and commercially cultivated species, particularly Jasminum sambac, J. auriculatum and J. grandiflorum. It discusses climate and soil requirements, propagation, planting, nutrient management, irrigation, pruning and other cultural practices. Major pests and diseases and their management are included. The chapter also explains harvesting, postharvest handling, marketing and the value-addition potential of jasmine flowers and essential oil.

Ketose: A simple sugar in which carbonyl group is a ketone.

Kinases: Enzymes that catalyse phosphorylation of an acceptor molecule such as protein molecule by ATP.

Nitrogen, a key component of organic materials like proteins, is analyzed using the Kjeldahl method, which is the global standard for determining protein content in various substances, including human and animal foods, fertilizers, wastewater, and fossil fuels. The Kjeldahl method involves three main steps:

A. Digestion

B. Distillation

C. Titration

Nitrogen, making up 1-4% of a plant’s dry weight, is vital for synthesizing chlorophyll, proteins, and other key compounds. Plants with high nitrogen levels turn dark green due to increased chlorophyll. Understanding nitrogen content in plant tissues is crucial for diagnosing deficiencies or toxicity and for effective nutrient management to improve crop production.

Determining the nitrogen content in plants is crucial for understanding plant nutrition, assessing the efficiency of fertilizer use, and making informed decisions in agricultural practices. Various methods can be used to determine nitrogen in plant tissues, with the most common ones being the Kjeldahl method, the Dumas method, and near-infrared reflectance spectroscopy (NIRS).

In this chapter we will look at the Expert system which can guide and assist an individual once it is provided with the enough Knowledge to do so. Here we will discuss about expert system and its architecture with proper steps of making an expert system in any field by several tools which are available to do so. For expert systems the most important is Knowledge Engineering which is the collection of Knowledge from an expert and Engineering it in such a form that a machine could understand it.

Introduction

One of the pioneering fields of AI study is Expert Systems (ES). It is proposed by researchers in the computer science department of Stanford University. An expert system is a computer system which emulates a human expert’s decision-making skills. Expert systems are developed by reasoning through information structures, representing laws, rather than through traditional procedural code, in order to overcome complex problems.

Expert Programs use professional expertise systematically to address human expert problems. An expert is an individual with experience in a specific field. The expert has expertise or special credentials which most people do not learn or care about. An expert can solve or solve problems more effectively than people can solve. Expert System actually emulates all these qualities of expert and solve the problem in a better way and fast.

Today, Expert System (ES) is used in the fields of finance, research, engineering, technology, medicine and many others where there is a well-defined problem area. The fundamental principle is that an expert method should also define the steps to illustrate why a problem can be solved. Unless an individual can justify his reasoning for Expert System.

Lactate dehydrogenase: An enzyme that reversibly catalyses conversion of pyruvate to lactate by utilizing NAD as coenzyme. This operates under anaerobic respiratory condition.

Lactate fermentation: Lactic acid fermentation is a biological process by which glucose and six carbon sugars (also, disaccharides of six carbon sugars, e.g. sucrose or lactose) are converted into cellular energy and the metabolite lactate. It is an anaerobic fermentation reaction.

Latent heat: The heat required to convert a solid into a liquid or vapour, or a liquid into a vapour, without change of temperature. It is also called as hidden heat.

Leaching requirement: (LR) The amount of water in excess of the plant requirement that is needed to remove salt from the root zone in order to prevent soil salinity from exceeding a specified value.

Leaf Area Duration (LAD): It is the functional leaf area or estimated photosynthetic area which contributed for the total biomasss. To correlate dry matter yield with Leaf area, Power et al., (1967) integrated the Leaf area with time and called as Leaf Area Duration. LAD taken into account, both the duration and extent of photosynthetic tissue of the crop canopy. The LAD is expressed in m². days.

For efficient nutrient use, most important factors are the timely supply/recycling of adequate amount of nutrients to the production system and its retention and release by soil for timely and ready availability in the root zone for its mobility to the plant in the presence of optimum moisture content in the soil. For keeping the applied nutrients retained in the root zone one has to reduce the soil erosion and leaching losses through technologies available in hand which include direct measures of soil and water conservation and maintain the soil aggregation and porosity through suitable tillage and organic residue recycling. For movement of nutrients into plant system we need to ensure optimum soil moisture content through water management.

A cereal is any grass cultivated for the edible components of its grain (botanically, a type of fruit called a caryopsis), composed of the endosperm, germ, and bran. The term may also refer to the resulting grain itself (specifically “cereal grain”). Cereal grain crops are grown in greater quantities and provide more food energy worldwide than any other type of crop and are therefore staple crops. Edible grains from other plant families, such as buckwheat, quinoa and chia, are referred to as pseudo cereals. In their natural, unprocessed, whole grain form, cereals are a rich source of vitamins, minerals, carbohydrates, fats, oils, and protein. When processed by the removal of the bran and germ the remaining endosperm is mostly carbohydrate. In some developing countries, grain in the form of rice, wheat, millet, maize etc. constitutes a majority of daily sustenance. 

Sugarcane, (Saccharum officinarum), perennial grass crop of the family Poaceae, primarily cultivated for its juice from which sugar is processed. Most of the world’s sugarcane is grown in subtropical and tropical areas. The plant is also grown for biofuel production, especially in Brazil, as the canes can be used directly to produce ethyl alcohol (ethanol). The by-products from cane sugar processing, namely the straw and bagasse (cane fibres), can be used to produce cellulosic ethanol, a second-generation biofuel. Other sugarcane products include molasses, rum, and cachaça (a Brazilian alcohol), and the plant itself can be used as thatch and as livestock fodder.

Oilseed crops have been grown all over the world and are considered important crops due to their economic value. Oilseed crops are primarily grown for edible oil. Recently, oilseeds attracted more attention due to an increasing demand for their healthy vegetable oils, livestock feeds, pharmaceuticals, biofuels, and other oleochemical industrial uses. The increased interest resulted in an 82% expansion of oilseed crop cultivation areas and about a 240% increase in total world production over the last 30 years.

Pulses are high in protein, fibre, and various vitamins, provide amino acids, and are hearty crops. They are most popular in developing countries, but are increasingly becoming recognized as an excellent part of a healthy diet throughout the world. Pulse crops are one of the most sustainable crops a farmer can grow. It takes just 163 litres of water to produce 0.45 kg (1 pound) of pulses, compared with 818 litres for soybeans. They also contribute to soil fertility by fixing nitrogen in the soil.

In this chapter, we explore Latin square design (LSD), a specialized form of experimental design renowned for its efficiency in controlling variation. This chapter thoroughly discovers the foundational principles, structure, and application of LSD in experimental research. It details mathematical models for LSD and guides readers through the interpretation of ANOVA tables. Furthermore, the chapter provides a systematic approach to conducting LSD analysis using R software.

Latin Square Design

The LSD is a statistical design used extensively in experiments, especially when specific conditions are met:

• Controlled variation in two directions: LSD is particularly suited for experiments where variation can be controlled along two different factors. This design structures the experimental units into a square matrix, allowing two sources of variability to be accounted for.

• Adherence to experimental design principles: Like other designs, LSD follows the key principles of randomization, replication, and local control. Randomization in LSD is applied within the rows and columns of the square matrix, ensuring unbiased treatment comparisons.

• Efficient use of resources: LSD allows for an effective utilization of resources by controlling two variables simultaneously. This makes it a more efficient design compared to RBD or CRD when there are two sources of nuisance variables.

As we have seen how artificial Intelligence can be useful in agriculture but the nest question always come in mind is that from where and how we can start to learn and what are the model of learning an artificial Intelligence. As Artificial Intelligence is a huge part of Computer Science which means we need an language as medium to perform it and we always prefer Python for that which is very dynamic and easy to learn. In this chapter we will learn about python basics so that in further implementation of artificial Intelligence it will be helpful to us.

I. Introduction

Python is a remarkable language that can claim to be easy and strong. You will be amazed to see how simple it is not to focus on the language you are programming, but on solving the problem. Guido van Rossum was the creator of the Python language which is named after the BBC show “Monty Python’s flying Circus”.

Python is formally introduced as:

“Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.”

Soil-rejuvenation power of legumes in crop rotations has been known in several parts of the world since ages. It is mentioned in the Indian agriculture of the Chalcolithic period (ca 1000 BC) (Raychaudhuri and Mira, 1993), in Chinese agriculture in the Han dynasty (ca 2nd century) (Hsu, 1980) and in Roman agriculture (White, 1970). Legumes can be ?tted in cropping systems in India in a number of ways, such as, a crop in a cropping system, a catch crop in an intensive cropping system, an intercrop and as a green manure. A brief discussion on these follows.

Fatty acid esters of glycerol are known as fats or lipids. A fat, in its liquid state, is called ‘oil’. Oilseed plants such as castor, groundnut, sunflower, safflower, linseed etc. contain oil as reserve food in their seeds.

It must be noted that a small quantity of free fatty acid is usually present in oils along with the triglycerides. It increases during storage. The free fatty acid content of an oil is called as ‘acid number’ or ‘acid value’. The keeping quality of oil relies upon the free fatty acid content.

During germination of oilseeds, lipases play an important role in hydrolyzing the stored oils to fatty acid and glycerol. Fatty acid is metabolized to acetyl-COA, which may take part in glyoxylate cycle forming sugars from fatty acid involving the enzymes- Isocitritase and Malate Synthetase.

The importance of lipids have already been elaborated. They play a major role as source of energy and as components of membranes which have implications in plant growth regulation. The complete metabolism of fat leads to oxidation, the final products being CO₂ and water. The burning of one mole of palmitic acid gives 2340 kcal.  The molecular weight of palmitic acid is 256. This works out to approximately 9 kcal/g of palmitic acid. This energy is twice that derived from either sugars or proteins. Fats and oils are thus better and more efficient forms of storage of energy in living beings.

Lipids are non polar substances of biological origin that are sparingly soluble in water, but soluble in organic solvents like chloroform, hexane, benzene etc. The word lipid comes from the Greek word lipos meaning lard or fat. The lipids present in biological systems are either hydrophobic (non polar) or amphipathic (both polar and non polar). Lipids like fats, oils or glycerophospholipids can be hydrolyzed to get fatty acids and other products. Hydrophobic nature is useful in making lipids as membranes which act as effective barriers to more polar molecules. Steroids are also considered lipids, but cannot be hydrolysed and are components of non-saponifiables in fats. Waxes, which are esters of fatty acids with long chain alcohols are also considered as lipids.

Lipids are a group of naturally occurring molecules that include fats, waxes, sterols, fat-soluble vitamins (such as vitamins A, D, E, and K), monoglycerides, diglycerides, triglycerides, phospholipids, and others. The main biological functions of lipids include storing energy, signalling, and acting as structural components of cell membrane. Lipids have applications in the cosmetic and food industries as well as in nanotechnology.

Lipids may be broadly defined as hydrophobic or amphiphilic small molecules; the amphiphilic nature of some lipids allows them to form structures such as vesicles, liposomes, or membranes in an aqueous environment. Biological lipids originate entirely or in part from two distinct types of biochemical subunits or “building-blocks”: ketoacyl and isoperen groups. Using this approach, lipids may be divided into eight categories:fatty acids, glycerolipids, glycerophospholipids, sphingolipids, saccharolipids and polyketides (derived from condensation of ketoacyl subunits); and sterol lipids and prenol lipids (derived from condensation of isoprene subunits).

Although the term lipid is sometimes used as a synonym for fats, fats are a subgroup of lipids called triglycerides. Lipids also encompass molecules such as fatty acids and their derivatives (including tri-, di-, monoglycerides and phospholipids), as well as other sterol containing metabolites such as chloestrol. Although humans and other mammals use various biosynthetic pathways to both break down and synthesize lipids, some essential lipids cannot be made this way and must be obtained from the diet.

Lotus is an important aquatic flowering plant with exceptional cultural, religious, ornamental and commercial significance in India. Its flowers are extensively used in worship, religious ceremonies, decoration and traditional floral practices. The chapter introduces lotus and discusses its botanical characteristics, origin, distribution, genetics and important varieties. It explains the environmental conditions required for successful cultivation, including suitable water, soil and climatic conditions. Propagation, pond or field preparation, planting, nutrient management, irrigation and routine cultural practices are described for commercial production. The chapter also covers pest and disease management, harvesting of flowers, postharvest handling, yield and potential uses, providing practical information for growers and students of floriculture.

Macromolecule: A molecule having molecular weight ranging from few thousand to millions.

Macronutrients: The essential elements which are required by plants in comparatively large amounts are called as major elements or macro nutrients. Examples: C, H, O, N, P, K, Ca, S, Mg. In this C, H, O, N, P, K are called primary elements and Ca, S, Mg are called as secondary elements.

Malate shuttle: A mechanism of transferring reducing equivalent of cytosolic NADH in the form of malate across the inner mitochondrial membrane by a specific ketoglutarate malate transporter for oxidation through electron transport chain in little animal tissue like heart muscle.

Malic enzyme: An enzyme that catalyzes the oxidation of malate to pyruvate and carbondioxide.

Machine learning provides powerful approaches for extracting useful information from complex plant, environmental and agricultural datasets. This chapter examines the principles and applications of machine learning in plant data analysis. It introduces different types of plant data, including phenotypic, genotypic, environmental and image-based information, followed by preprocessing, normalization, feature extraction and feature selection. Supervised learning techniques such as regression, decision trees, random forests and support vector machines are discussed for applications including crop yield prediction and disease detection. Unsupervised learning, clustering, principal component analysis and advanced ensemble and deep learning approaches are also considered, along with model evaluation, data limitations and future developments.

In this chapter of machine learning algorithms we will cover the basic algorithms of machine learning with their implementation using dataset and discuss their pro’s and cons of algorithms for better understanding and how to use them in any project or with any dataset to get an correct result which can useful for research or study.

Key Component

We defined a data set composed of audio, images and binary labels that provided an understanding of how we could train a model from snippets to classifications. This sort of problem is one of many kinds of machine learning problems when we try and predict a specified unknown label given known inputs, provided that a dataset of examples for which labels are known is called supervised learning. Let’s discus what are the major key components we have to get there

As we know there are different branches of artificial Intelligence and machine Learning of one of them which has become a most advance and widely used branch of artificial Intelligence in every field of this generation whether it may be either electronics, civil, mechanics, Bioengineering, medical or agriculture etc., In this chapter we will study about machine learning and its types with the most common algorithms of machine learning which are being mostly used in different scenarios and their implementation using python language has been discussed in the implementation part of this book. Here we will also see where machine learning can be used.

i. Introduction

Machine learning is a subset of Artificial Intelligence and one of the most important part of artificial Intelligence. It is a field of Computer science which is totally differs from traditional computational approaches. In traditional approaches, a set of instruction is explicitly provided to the algorithm to solve any problem. Whereas in Machine Learning is a domain of an AI which uses a statistical analysis and can enables a system to always learn from its data without any external inputs in order to give an essential output. Due to this machine learning makes computers in advance to make model which provide decision based on input data.

Machine Learning involves a lot of algorithms which usually based on their requirements and functionalities to use where and when. To make a machine learning model we always require the data on which model can be made. Machine learning uses the algorithm which continuously learns from the data available as training data. A machine learning model is generated after the training of algorithm from the data. After the training completes, when trained model is provided with other real-life data then you can get an essential outcome. For example, in figure 3.1 Machine learning Model we use a predictive algorithm and make a model by providing it with some data, and later on we can receive prediction’s based on real data as input.

A Flame Photometer has long been in use for analysis of elements; however, it is now being gradually replaced by Atomic Absorption Spectrophotometer. The reason being, that the former can analyze only a few elements such as sodium (Na), potassium (K), calcium (Ca), barium (Ba) and lithium (Li), whereas the later can be used to analyze almost all the elements known, provided a specific Hollow Cathode Lamp (HC), for a specific element, is available. In addition, Atomic Absorption Spectrophotometer is more precise and accurate in measurement as compared to Flame Photometer.

In this chapter, we shall deal with the operation techniques, working principles and a brief description of each and every component/constituent unit of a Flame Photometer as well as an Atomic Absorption Spectrophotometer.

Cells Contain 4 Major Types of Giant Molecules (Macromolecules, Polymers)

Carbohydrates

Lipids

Proteins

Nucleic Acids

BIOLOGICAL POLYMERS ARE MADE FROM ABOUT 60 SMALL BUILDING BLOCKS

Cells contain thousands of types of giant molecules (macromolecules, polymers)

Polymers are macromolecules made from a single building block molecule Most of the macromolecules are made from about 60 types of small building block molecules

Most macromolecules are linear: building blocks linked head to tail- a few have branches (some polysaccharides)

This is what you would get if you heated cells in hydrochloric acid overnight at 110 degrees C:

Madar, represented mainly by Calotropis gigantea and related species, is a hardy flowering plant adapted to a wide range of environmental conditions, including marginal and dry lands. Its flowers are valued for religious purposes and loose flower use, while different plant parts have traditional medicinal significance. The chapter discusses the origin, distribution, genetics, botanical characteristics and important species of Madar. It emphasizes the crop’s drought tolerance and adaptability to arid and semi-arid conditions. Production practices include seed propagation, land preparation, planting, nutrient management, irrigation and cultural operations. The chapter also addresses pests and diseases, harvesting, special postharvest handling because of latex, yield and commercial opportunities.

Magnolia champaca, formerly known as Michelia champaca, is a highly fragrant flowering tree valued for loose flowers, religious offerings, garlands, landscaping and perfumery. Its strongly scented cream to yellow-orange flowers are an important source of fragrance and essential oil. This chapter discusses the origin, distribution, genetics and botanical characteristics of the crop, including important varieties. It explains climatic and soil requirements, propagation, land preparation, planting, nutrient management and irrigation. Cultural practices for maintaining growth and flowering are also described. The chapter further covers major insect pests and diseases, harvesting, postharvest handling and yield, highlighting the importance of Champak as both a traditional flower crop and a valuable raw material for perfumery.

AIR POLLUTION FROM AUTO EXHAUST

Motor vehicles are the major source of a number of pollutants, in particular carbon monoxide (CO),nitrogen oxides (NOx), unburnt hydrocarbons (HC),ozone (O3) and other photo chemical oxidants and lead (Pb) and, in smaller proportions Total Suspended Particulate Matter (TSPM), sulphur dioxide (SO2) and volatile organic compounds.

Fertilizer recommendations are generally made on the basis of soil test. Recommendations of fertilizer for top-dressing are best made on tissue testing.

SOIL TEST

A number of approaches have been adopted to increase the precision of soil-test values in making fertilizer recommendations. Four most important ones are discussed.

Low-Medium-High Approach

Making fertilizer recommendations based on soil test for a nutrient involves conducting a large number of ?eld experiments on soils similar to those which are intended for making recommendations. For an individual nutrient (say P for example) experiments are conducted with graded doses of P on a crop for which the fertilizer recommendations are to be made. Thus, agronomic experiments are to be conducted for each crop on each kind of soil. The response curve can then be divided into three sections: a, low soil-test value and high response to fertilizer zone; b, medium soil-test value and medium response to fertilizer zone; and c, high soil-test values and no response to fertilizer zone. In India, this was done

Marigold is one of the dominant loose flower crops in India, particularly important for religious ceremonies, festivals, weddings, garlands and decoration. The principal cultivated types include African marigold (Tagetes erecta) and French marigold (Tagetes patula). The chapter discusses the origin, distribution, genetics, botanical characteristics and important varieties of marigold. It also highlights emerging applications such as lutein extraction, natural colourants, culinary uses and companion planting. Detailed production practices cover climate, soil, propagation, nursery management, land preparation, nutrient management, planting, irrigation, pinching and flower harvesting. Important pests and diseases, postharvest handling and yield are also discussed for efficient commercial production.

Marketing is a critical component of loose flower production because flowers are highly perishable and subject to substantial seasonal price fluctuations. This chapter examines important local and national markets, export opportunities, transportation systems and marketing channels. It explains direct marketing, commission-agent systems, wholesaler-retailer networks and emerging contract arrangements. The role of APMC markets in price discovery, grading, auctioning and market access is discussed along with online trading, e-commerce and digital payment systems. The chapter also considers institutional support, export promotion, value addition and crop insurance. Improved packaging, cold-chain infrastructure, processing and market information systems are highlighted as important strategies for reducing losses and improving farmer profitability.

Mass spectrometry (MS) is a powerful and versatile analytical technique through which mass of an atom, or a molecule is assessed. It helps for identification and structure elucidation of various complex compounds. The instrument used is known as Mass Spectrometer. It serves the purpose of qualitative identification, confirmation as well as the quantification of an atom or a molecule. MS identification is conclusive because the mass spectrum of each substance is unique. In general, MS instruments are composed of a sample inlet, an ionization source, a molecule accelerator, a detector, an amplifier, and a recorder (Figure 7.1)

Object: Measurement of absorption spectrum of chloroplastic pigments.

Material required: Spectrophotometer, plant leaves, ethanol, electric balance, beaker, test tubes and water.

Object: Measurement of leaf area by graph paper method.

Material required: leaves, graph paper and pencil or pen.

Introduction

Measurement of pH of a solution and preparation of different types/strength of buffers are common practices in a laboratory, particularly in the Biochemistry and Molecular Biology laboratories. Therefore, in this chapter you will be acquainted with the procedures of measuring pH of a solution as well as preparation of some of the commonly used buffers in a laboratory.

Potential or Power of Hydrogen Ion (pH)

Measurement of pH of a solution is measuring the molar concentration of hydrogen ion [H+] in the solution, which is an indication of the acidity or basicity of the solution. The symbol pH stands for “power of hydrogen” and numerical value for pH is just the negative logarithm of the molar concentration of hydrogen ions [H+]. The ionic product of water (Kw ) is the basis for the pH scale. The total hydrogen ion concentration from all the sources and it can be experimentally measured.

The pH scale designates the concentration of H+ (and thus of OH−) in an aqueous solution, which ranges between 1.0 M H+ and 1.0 M OH−. The term pH is defined by the expression

Thus, the ionic product of water makes it possible to calculate the concentration of H+, with given concentration of OH−, and vice versa. The value of 7 for pH of a neutral solution is not an arbitrarily chosen figure; it is derived from the absolute value of the ionic product of water. A solution having pH greater than 7 is basic, and the concentration of OH− is greater than that of H+. A solution having a pH less than 7 is acidic.

Photosynthesis is an important physiological process associated with plant growth and productivity. During the process of photosynthesis, the solar energy is trapped and converted into chemical potential which is later used for the reduction of CO₂ into carbohydrates. The powerful reductant, NADPH that is needed for carbon reduction is generated by the light driven reactions of the chloroplast lamellar system. Photosynthesis can be summarized as follows.

SEX IS VERY COSTLY

Large amounts of energy required to find a mate and do the mating: specialized structures and behavior required

Intimate contact provides route for infection by parasites (AIDS, syphillis, etc.)

Genetic costs: in sex you pass on only half your genes to your children

Males are an expensive luxury- in most species they contribute little to rearing offspring

But There are Some Advantages

More genetic diversity: more potential for survival of species when environmental conditions change

Shuffling of genes in meiosis (random separation of homologous chromosomes)

Crossing-over in meiosis (see below)

Fertilization (genes from 2 individuals brought together)

ALL MOLECULES MOVE CONTINUOUSLY BY SIMPLE DIFFUSION

Heat energy causes molecules to move randomly (sometimes called Brownian motion)

If the concentration of molecules is different in 2 regions (this produces a concentration gradient), diffusion will cause molecules to move from a region of high concentration to one of low concentration

The higher the concentration gradient the more rapid the net diffusion

Diffusion evens out the concentrations so they are equal everywhere (maximum entropy)

If 2 different substances have the same concentration gradient, usually one will move faster than the other

Differences in speed between molecules with the same concentration gradient are given in terms of diffusion constants

A substance with a high diffusion constant moves faster than one with a low diffusion constant

In general, large molecules move slower than small molecules

Diffusion across a membrane is called permeability, and membrane diffusion constants are called permeability constants

A fair number of practical breeding experiments were done in ancient times

People knew there was a connection between sex and reproduction

The idea had developed that “like begets like”

By selecting certain plants and animals and breeding them many domestic varieties of plants and animals had been developed

Example: corn was developed from a wild grass in Mexico and Central America, probably about 5000 years ago

149 of the top 150 plant crops were domesticated by primitive man

Metabolism - sum total of all chemical reactions in living cells

Catabolic reactions - degrade macromolecules and other molecules to release energy

Anabolic reactions - used to synthesize macromolecules for cell growth, repair, and reproduction

Can divide metabolism into 4 groups: carbohydrates, lipids, amino acids, nucleotides.

INTRODUCTION

The metabolism of carbohydrates is vital for plant growth and development, and to the yield of major plant products such as starch and sucrose. Starch, sucrose and fructose are the three important carbohydrates which are utilized in most of the higher plants. The majority of sucrose that is synthesized in higher plants during photosynthesis is exported to non-photosynthetic cells (ap Rees, 1992). Starch serves as an important storage for carbohydrate residues. The degradation (breakdown) of starch ensures retaining of important life processes in plants when there is carbon shortage, for instance, during night period in leaves or in resting organs such as potato tubers.

Introduction to Metabolism Metabolism is the sum of all biochemical reactions (physical and chemical processes) occurring within the body to sustain life. In total, it encompasses all the processes converting the energy from nutrients into usable forms, thereby facilitating the synthesis of biomolecules necessary for sustaining life. This process occurring in all living organisms ensures that a continuous supply of energy and precursors is maintained to perform cellular functions, such as growth, reproduction, maintenance and response to environmental stimuli. Therefore, studying the body’s metabolism provides insights into the physiology, mechanism of disease occurrence and potential therapeutic interventions. Specifically, metabolism is a highly regulated process involving a set of biochemical reactions that can be broadly grouped into: a) Catabolism involves the breakdown of complex molecules into simpler components, releasing energy in the form of adenosine triphosphate (ATP). Catabolic reactions assist in the extraction

Atmosphere serves as the medium through which pollutants are transported and dispersed. While being transported, the pollutants undergo chemical reactions, which may be lethal or scavenged by chemical or physical process/method. But it all exclusively depends upon the meteorological conditions (Lee et .al, 1994). Historic air pollution episodes reveal that atmospheric conditions influence the pollutant concentrations as well as their toxicity (Goldsmith & Friberg, 1976; Wichmann et.al, 1989 and Pope et.al, 1992). However, the location, duration of release, height as well as the pollutant concentrations are also important, which effect the secondary pollutant transformation under the influence of meteorological conditions, but the atmospheric behavior is independent of their sources (Holzworth, 1974).

1. Introduction

The study of systematics and genetic diversity between or within different species, populations, and individuals is a central task for many disciplines of biological sciences. Systematic studies can indicate which genomes in the plant kingdom to search, sample, and study for the answers to questions relating to the evolution of chemical and physical structures and their synthesis or ontogeny as well as questions about the kinship of the individuals. Such studies would help find new and useful genes and provide information about the phylogenetic relationships among crop species and their wild relatives. The application of molecular markers has been the most active area of research in both animal and plant systematics. The analysis of the genetic variability within and among populations of the species is crucial for understanding their future maintenance and developing improvement as well as conservation programs.

Classical phenotypic characters, such as morphological traits, are still extremely useful but they can sometimes be influenced by environmental conditions. Therefore, during the past decade, classical strategies of evaluating genetic variability such as comparative anatomy, morphology, embryology and physiology have been increasingly complemented by molecular techniques. These include the analysis of chemical constituents (e.g., plant secondary metabolites) and, most importantly, the characterization of macromolecules. The development of molecular markers, which are based on polymorphisms found in proteins or DNA, has greatly facilitated research in a variety of disciplines such as taxonomy, phylogeny, ecology, genetics, and plant breeding (Weising et al. 1995). The greater utility of molecular markers derives from following five inherent properties that distinguish them from morphological markers.

1. Introduction

The objective of algal taxonomic collections is to represent the natural population, flora and diversity in size and form. Therefore, it is important to collect the representative samples seasonally from various habitats. Collection of information about the habitats and other details are also very important. For algal sampling the first thing to consider is how to collect the specimens. The freshwater algae show an ability to tolerate a wide range of environmental condition. Under natural conditions, they usually grow in mixed communities which may include many species and genera. Field study provides information about the site, environment, season and size and shape of the living algal thallus in its natural surroundings. Many algae can be tentatively identified by their appearance, shape and colour of thallus in a particular habitat. Algal population can be sampled in a number of different ways, depending on the nature of the habitat and the location of the algae within the water body. The specimens must be prepared carefully so that important morphological characters are displayed as fully and completely for further researches.

1. Introduction

The word ‘lichen’ has a Greek origin, which was referred to the superficial growth of fungus like organism on the bark of olive trees. Theophrastus, the Father of Botany coined the term ‘lichen’ during 300 BC and introduced this group of plants to the scientific world.

Lichen is a combination of two organisms, an alga and a fungus, living together in symbiotic association. Sometimes instead of an alga a cyanobacterium (blue-green alga) may be present in the lichen thallus. The algal component in the lichen is generally called as ‘photobiont’ as it contains photosynthetic pigment. The fungal part is called as ‘mycobiont’ (myco = fungus). The photobiont and the mycobiont loose their original identity in symbiotic association and the resulting organism is the lichen which behaves as a single organism, both morphologically and physiologically. Hence, the lichen is called as a composite organism. The lichen thallus is made 90% of mycobiont which provides shape, structure and colour to the lichen. In a lichen thallus whatever visible from outside is fungal part, which holds algae inside its body (Fig. 1) and therefore, the lichens are placed within the Kingdom - Fungi. The fungi present in lichens are called as ‘lichenized fungi’. Among the 20,000 lichen species present in the world, 98.9% of them belongs to Ascomycetes group while Bacidiomycetes and Deuteriomycetes groups are represented by only 0.1% and 1%, respectively.

1. Introduction

Microbial diversity is becoming increasingly essential with the requirement to preserve the integrity, function and long-term sustainability of natural and managed ecosystems. However, our knowledge of the diversity of microbes remains obscure due to lack of appropriate approaches to evaluate the contribution of different components of the soil microbes to ecosystem. This lack of approaches together with the complex and heterogeneous matrix that soil microbes are embedded in, poses great challenges to understand the dynamics of microbial communities in soils (Nautiyal et al. 2010; Chauhan et al. 2013).

In classical terms, diversity is described as the total number of species present, i.e. species richness or species abundance, and the distribution of individuals among those species i.e. species evenness or species equitability. However, the incorporation of these two components into diversity indices has led to much controversy among ecologists (Atlas 1984). The Shannon-Weaver index (Shannon and Weaver 1949) is probably the most widely used index for measuring diversity of a microbial community. But this index, as many others that have been proposed, has its own limitations. A major difficulty is that both richness and evenness play a role in determining the value of the index. Therefore, any diversity index is a single value and thus cannot indicate the total make-up of a community. It is recommended that evenness, richness and diversity values should be calculated in order to obtain an objective assessment of community structure (Atlas 1984). From molecular point of view, diversity often refers to the number of different sequence type present in a habitat e.g. a soil (Ogram 2000). Measuring this type of diversity does not give information about the frequency of individual species, but it can give valuable information about changes in the community structure and species richness in response to changes in the physico-chemical properties of the soil and soil management practices (Nautiyal et al. 2010).

Introduction

The main objective in analysing fertilizers is to assess their quality. The analysis examines both their physical and chemical composition. The quality of fertilizers is stated by the manufacturers and, in most countries, it is statutorily notified. Hence, analysis is carried out to determine whether the stated quality meets the statutorily notified standards or not. Together with the statutory notified composition of the fertilizers, the testing methods are specified. In situations where the testing methods are not notified, the prevalent standard methods are followed. Generally, the term fertilizer refers to mineral fertilizers, which are manufactured chemical products of standard composition, while the term manures refers to organic manures, compost, agro-industrial wastes, etc. The compositions of organic fertilizers, unlike mineral fertilizers, are quite variable and, thus, difficult to regulate precisely.

Fertilizer quality is notified in terms of physical and chemical characteristics. The physical parameters include moisture content and particle size. The chemical parameters refer to the amount and form of nutrients, and to various impurities that may be toxic to plants above a critical limit, e.g. biuret in urea. The efficiency of a fertilizer depends on its form of nutrient content. A phosphatic fertilizer may have water-soluble, citrate-soluble, water-insoluble or citrate-insoluble forms of phosphate. A nitrogenous fertilizer may contain ammoniacal, nitrate and amide forms of N in various proportions.

Introduction and Scope

Plant and soil testing enable scientific assessment of the needs of the plant for nutrient elements and of the capacity of the soil to supply them. The nutrient elements enter the plant in ionic form from the soil solution. Ion transport to the root surface may take place through ion diffusion and bulk transport (mass flow). Mass flow is the sweeping along of ions as water moves to the root. It is particularly important for ions that are not absorbed on soil colloids such as nitrates and sulphates. Because of mass flow, a plant deficient in N can extract all the nitrates from the soil. Potassium, phosphate and the micronutrient cations are absorbed on soil colloids with various degrees of affinity and are greatly retarded in movement with the soil water. Diffusion (movement along a concentration gradient) is the main mode of transport from the solid phase to the root surface for these non-mobile ions. There is also a possibility that some of them are absorbed by a direct exchange of an ion, usually hydrogen, between the root surface and ions absorbed on soil colloids. Most ions are sorbed by the root against a concentration gradient and, thus, the process involves the use of metabolic energy. The fact that nutrient uptake is an active process explains some of its peculiarities. Plants not only accumulate nutrients against a concentration gradient, they are also able to select from the nutrients at the root surface according to their requirements (preferential uptake).