eChapters

Abstract

Systems biology is an interdisciplinary field that combines computer and mathematical analysis with biological research to understand the complex interactions within biological systems. This chapter explores the history and evolution of systems biology and its significant impact on modern biology. Systems biology uses a holistic approach to analyze biological systems at the molecular, cellular, and organismal levels, providing a better understanding of biological processes and the interactions between genes, proteins, and other molecules. Systems biology has immense potential in improving human health, agriculture, and the environment, and this chapter explores the ongoing efforts to translate systems biology research into practical applications.

Abstract

Drug design is a complex computational process that involves studying the structural and physicochemical properties of biological moieties in order to identify new chemical or biochemical substances that can be used as drugs with specific pharmacological properties. The drug discovery pipeline is a crucial aspect of drug design that requires a detailed understanding of the various phases involved. In this chapter, we discuss the fundamental principles and phases of drug design. Additionally, we delve into the concept of docking, a critical step in the drug discovery process that involves predicting the orientation and affinity of a ligand binding to a protein target. The use of computational tools and techniques in drug design has revolutionized the field and is essential for the development of safe and effective drugs.

Abstract

Molecular modeling is a computational technique used to simulate the three-dimensional interactions between atoms and molecules. It allows for the visualization, manipulation, and prediction of molecular structures and chemical reactions. In this chapter, we discuss the different types of molecular models used in computational chemistry, including ball-and-stick models, space-filling models, wireframe models, and ribbon models. Ball- and-stick models depict atoms as spheres and bonds as sticks. Molecular modeling has numerous applications in drug discovery, materials science, and other fields of research, making it a valuable tool for computational chemists and molecular biologists. Here, this chapter focuses on different types of molecular models.

Abstract

When only sequence data is available, homology modeling has become a useful tool for predicting protein structure. Protein structure is often more important than sequence data when evaluating protein function. Homology modeling, also known as comparative modeling, is based on the principle that two sequences that exhibit a high degree of identity or similarity will also share similar structures. This chapter explores the steps involved in homology modeling, including template selection, alignment, model building, refinement, and validation. The Ramachandran plot is a valuable tool for assessing the conformation and bond angles in a protein model, and we discuss its significance in the context of homology modeling. Ultimately, homology modeling is an effective method for predicting protein structure and has numerous applications in protein engineering, drug discovery, and other fields.

Abstract

Proteins are complex molecules composed of one or more polypeptide chains made up of amino acid residues. These molecules perform a variety of essential functions in living organisms, including DNA replication, molecule transport, catalyzing metabolic processes, and providing structural support to cells. In this chapter, we explore the four levels of protein structure: primary, secondary, tertiary, and quaternary. Primary structure refers to the specific sequence of amino acids in a polypeptide chain, while secondary structure describes the folding of the chain into alpha-helices, beta-sheets, or other patterns. Tertiary structure is the three-dimensional shape of a single polypeptide chain, and quaternary structure refers to the interactions between multiple polypeptide chains to form a larger protein complex. Additionally, this chapter covers various methods used to predict protein structure, including homology modeling, ab initio prediction, and threading algorithms.

Abstract

Omics arise from ome which means complete or totality. It refers to the collection of technologies used to investigate the roles, relationships, and actions of the various types of molecules that make up an organism’s cells. Omics technologies provide the tools required to investigate differences in DNA, RNA, proteins, and other cellular molecules between species and individuals within a species. These technologies comprise, genomics, transcriptomics, proteomics, metabolomics, ionomics, glycomics, lipomics, cultureomics, pharmacogenomics, metagenomics, foodomics, eigenomics, phenomics, etc. The inclusion of all omics domain is known as multiomics. In this chapter we describe from basic, type structure of omics to all the recent cutting edge technologies in multiomics.

Abstract

FASTA, which stands for “Fast All”, is a sequence alignment tool developed by William R. Pearson and David J. Lipman in 1985. It is commonly used to identify similarities between DNA and protein sequences. FASTA employs a “hashing” strategy to locate matches for short stretches of identical residues with a length of k, referred to as k-tuples or k-tups. This method enables FASTA to quickly search large databases for sequence similarities, making it a popular tool for identifying homologous sequences, predicting gene functions, and analyzing evolutionary relationships. This chapter elaborates some basics of FASTA.

Abstract

The Basic Local Alignment Search Tool, or BLAST, is an online tool provided by the National Center for Biotechnology Information (NCBI) that allows users to search for matches between their query sequences and the sequences stored in NCBI databases. BLAST can be used to search for nucleotide sequences against nucleotide sequences, protein sequences against protein sequences, and protein sequences against translated nucleotide sequences in the databases. BLAST is widely used to study sequence similarity, identify target sequences, analyze the functional aspects of molecular sequences, and investigate evolutionary relationships. This chapter details on the BLAST and its applications.

Abstract

Real-time PCR, also known as qPCR, is a highly sensitive technique used to determine the real-time amplification of a target DNA sequence. However, the presence of secondary structures or spurious amplicons can distort the results. When using SYBR Green chemistry, the features of qPCR primers differ from those of standard endpoint PCR primers. As a result, designing primers for SYBR Green qPCR requires extra caution and attention. This chapter outlines the essential features and conditions for designing qPCR primers, including primer length, melting temperature, GC content, specificity, and avoiding primer-dimer formation.

Abstract

PCR primer design is a crucial skill for molecular biologists, as it enables the study of gene expression, gene amplification, and molecular markers. Primer3 is an online tool widely used for designing optimal PCR primers, which are pairs of short oligonucleotides that initiate DNA synthesis in vitro using a thermocycler. This tool uses a range of parameters to generate high- quality primers, including target sequence length, melting temperature, GC content, specificity, and product size. Understanding and effectively utilizing these parameters is essential for achieving accurate and reliable PCR results. In this chapter, the practical aspect of primer designing using the online tool Primer3 has been discussed. The parameters and the purpose of their usage have been given in a tabulated manner.

Abstract

Molecular phylogeny is an important method for understanding the evolutionary relationships between different organisms. Molecular phylogeny is based on the idea that organisms that share a more recent common ancestor will have more similarities in their DNA or protein sequences. The chapter seems to cover the basic concepts and terminology used in molecular phylogeny, including the difference between rooted and unrooted trees, as well as various methods used for constructing phylogenetic trees. Further, chapter also covers some common tools and software used for analyzing molecular data and constructing phylogenetic trees. Overall, this chapter provides a useful introduction to molecular phylogeny and the methods used for understanding the evolutionary relationships between different organisms. Understanding these concepts is important for many areas of biological research, including evolutionary biology, ecology, and biotechnology.

Abstract

Sequence alignment is the positioning of DNA, RNA, or protein sequences with each other to identify the regions of identity, which may be the result of functional, structural, or evolutionary relationships between the sequences. Therefore, sequence alignment is the process of aligning two sequences to achieve the maximum levels of identity and conservation. This chapter deals with the basic concept of sequence alignment and the tools associated with multiple sequence alignment. Further, it describes various matrices used in sequence alignment.

Abstract

Biological databases that are composed of a large collection of digital nucleic acid sequences, protein sequences, or other polymer sequences stored on a computer, which is made available to the research community worldwide using web servers. The vast amount of information generated in molecular biology is analyzed, curated, tabulated, and arranged in databases. There are different types of biological databases, based on their contents. Besides, the database management system, a program to manage the databases, can be of two types: distributed DBMS and relational DBMS. This chapter briefly narrates the importance and purpose of biological databases.

Abstract

The knowledge of programming language(s) is necessary to solve biocomputational problems and also understand the data pattern. Computer programming is used to develop software to extract information from data which is very crucial while practicing bioinformatics. Programming language is a man-made, computer-understandable, artificial language, that is designed to instruct a machine, particularly a computer to get the desired output. This chapter briefly narrates the concept of algorithms, programming languages, and the historical perspective of the same.

Abstract

This chapter provides a brief overview of the key milestones in the development of bioinformatics that would help to understand the historical context and evolution of a subject. As an interdisciplinary field, bioinformatics has grown gradually from molecular biology, with the development of various algorithms, databases, and other important tools that have helped to advance computational biology. Some important events in the history of bioinformatics might include the development of the first algorithms for sequence alignment and comparison, the creation of early databases such as GenBank and Swiss- Prot, and the development of software tools for molecular modeling and drug design. Other key milestones might include the sequencing of the first genomes, the development of high-throughput sequencing technologies, and the emergence of new areas of research such as systems biology and synthetic biology. By understanding the historical context of bioinformatics, students and researchers can gain a deeper appreciation for the current state of the field and the ongoing efforts to advance our understanding of the molecular mechanisms that underlie life.

Abstract

Bioinformatics is an important interdisciplinary field that brings together several areas of science, including molecular biology, biostatistics, and computer science (vis-a-vis information technology). With the rapid increase in the sequencing of DNA/RNA/protein molecules, as well as the growing understanding of the interconnections between different areas of biological science, the importance of bioinformatics is only increasing. This chapter seems to provide a thorough introduction to the definition, concept, and importance of bioinformatics. It also appears to highlight the relevance and potential scope of the subject for students interested in pursuing a career in the field. As bioinformatics continues to evolve and expand, it is likely to become an increasingly important area of research and development in the life sciences.

Remotely gathered data are available from a range of sources and data collection techniques is often one type of tool that is not always found within the public domain easily. This is larger due to the fact that most of the data are acquired by equipment is expensive to build and maintain. However, there are many types of basic imagery, high-quality imageries are readily available widely at subsidized costs, particularly the purpose intented.

In beginning of aerial photography, the photos were taken to evaluate existing topography, plan observation and sampling incursion. After World War II, the assessments of aerial photographic data were much more difficult, and real geological data started to be extracted. The use of stereoscopic pairs enabled geologist to explain height structural features. But, the basic use of remote sensing data were collected was in explanation. These trends of comparative photography until development took place into the satellite age when satellite imagery began popular and commercially available. The availability of various imageries in several combinations opened a option to analyze regions in much more detail. Apart from this, the multiple flying allowed a prospect to be viewed in various light during differnt seasons. The development drastically decreased the cost of regional exploration by minimizing repeated trips to a place for reassessing. This permitted data to be gathered from the tropics and arid regions that was previously difficult task in wide regional field exploration. As computer age progressed being developed and enhanced the value of data that allows imagery as digitally highlighted specific features. Ground features like differential cropping, drainage patterns, and folds/faults may be identified.

The information of image is perfectly accepted by eyes when the image will be in convenient form. Always pictures accurately detail about information related to their position, sizes and inter-related with each other is objects. Actually images portray positional information which can be recognized as objects. Human eyes are exact example for differentiating that information from images to innate visual and mental ability.

Aerial photography is objective of getting panoramic view of earth surface to analyze the features of earth and their interrelation at particular time period which may be changed in further events. In this concerned, the observation may play a vital role in achieving the goals of photography. Undoubtedly it is widely used in social function and so on, but still awaited for scientific or research use. Drone can measure the geometry of ground surface at lower altitude with more accuracy in the form of visual feature in natural colour. flight height of drone mainly limits the large area coverage due to lower flying and drone can work perfectly at low altitude planning with good quality feature/photography.

Fundamentally toposheet represents a kind of map in which topographic features of particular area is given details on the map features in two dimensional land surfaces. It shows both horizontal and vertical portion of the terrain with a combination of contour lines, contours, symbols, labels and related representation together in one piece of paper. Toposheet portray the shapes, location of mountains, many natural and manmade features, and the toposheet combinedly uses for extracting accurate information about particular area containing land surface features.

Age old practice of photography was taken with still camera in parallel direction, not aerially scan or snapping which really present wider prospective of any object or places in rearranging or planning skilfully in two dimensional working. Earlier aeroplane played a important role in over head condition to capture snaps but again accuracy and angle of camera limited the works because these photographs were diagonally or trigonally not matched the reality of ground.

Preparation of base map being in mind, the forest, agriculture, water, road and boundary are almost same for all but theme may be different as per requirement. Base information is to survey and need terrain information, the preparation includes land forms by separation of water, kart area, coastal area. Meanwhile preparation of focus might be on DEM (Digital Elevation Model) and water movement helps in demarcation of boundaries on map.

GPS stands for Global Positioning System, basically Navstar GPS is a radio based space aviation system developed by United state government which was operated by United State Air Force. It provides geographic location and time related information to GPS receivers under global navigation satellite from anywhere of earth where unobstructed line of sight to 4 or more GPS satellite co-ordinate (Anonymous, 2018). Even GPS not required any user for transmitting data, with working independently on any telephonic or internet receivers; through these technologies we can enhance usefulness of the GPS location based information. The GPS serves as critical positioning capacity to various fields like army operation, civil aviation, and commercial scope to wider scope in around world.

In modem days, many informations receive through electronic media with instant connecting by satellite based information on social, economical, environmental etc. the informations are coded with feasible electronic encrypt and delivered to people. Similarly remote sensing, GIS (Geographical Information System) and GPS (Global Positioning System) also serve world for better understanding the ground reality along with reducing cost of operation, transforming data through electronic webs easily. In earlier phase, ground related information was not easily obtained because all kind of work had been done manually using analog maps of earth; even map draw was done by drafting from totposheet or hand maps, no interface of analog and digital world.

Cartography has much back history than what we seen in portable form by its name or definition. Many prehistoric painting of caves had their own time frame record of maps, artifacts and design have been preserved hoping that they are sufficient to the era of forgotten habit and culture, and treasure explicit ancient world. The ancient wall painting of seventh millenium BC, might have indication of oldest maps in the world and the painting is assumed to be the location of ancient city Antolia as Mellaart, depicted 1967. Onward 600 BC, the modern form of cartography started to develop map. The pioneer contribution in map designing and development, old Greek and Roman were main contributor in this direction. One Greek Philoshopher Ptolemmy, multi-talented genius are recalled in this context, who later credited with first documented map of world during production of Geographica, is a treatise on cartography, very soon one Arabian Scholar Muhammad Al-Idrisi prepared a medieval Atlas involving knowledge of world collected by Arabic merchants in 1154.

The large volume, type and nature of animal breeding data and the complex nature of analytical requirement warrants additional tools for handling, storage, retrieval and solving complex equations. Accuracy, speed, computational requirement, applicability, etc., has resulted in the development of numerous software exclusive for animal breeding data analysis. The database management system is already explained in the chapter on ‘Nature of animal breeding data and database management’. This chapter gives a note on the commonly used animal breeding software.

This chapter describes various multivariate techniques which are useful in animal breeding. The genetic correlation with multiple response variables is already explained in the chapters on Correlation and Genetic Parameters. The other techniques including MANOVA, Principal Component Analysis, Factor Analysis, Cluster Analysis and Discriminant Analysis are explained.

Multivariate analysis is referred to a set of data with multiple response variables in general and such data is encountered often in animal breeding analysis. The simplest form of multivariate analysis is the genetic correlation where two or more traits are analysed together as response variables with factors affecting them on the right-hand side (RHS) and details of these are already explained in earlier chapters.

Meta-analyses has been used extensively to combine the results of existing studies and obtain powerful estimates of a parameter. In animal breeding, attempts have been made to obtain meta-analysis estimates for genetic parameters. This tool is more pertinent to animal breeding on account of heterogeneity in terms of location, sample size and other factors in the estimation of genetic parameters. This chapter explains the background, methodology, precautions and implications of meta-analysis with respect to genetic parameters.

A meta-analysis is a powerful tool of statistics that could combine several estimates from different studies for a parameter and the resulting weighted estimate could be used as a representative value for the particular parameter. However, not all the studies are similar with respect to location, sample size, and methodology used and thus various precautions are to be taken right from the selection of studies to incorporating of between-study heterogeneity in the models. In animal breeding, met-analysis is very much useful for obtaining meaningful estimates of genetic parameters and this chapter explains the methodology of meta-analysis in animal breeding.

The aim of the breeder is to improve on various economic traits through selection. However, due to the lesser number of parents used, over a period of time, there creeps in the effect of inbreeding and loss of genetic variability which in turn causes depression and loss of fitness. This is more prominent in finite endangered populations and evaluation for genetic variability also forms an integral part of the animal breeding analysis.

Genetic variability is an integral part of domestic animal populations as fitness is directly related to the variability.

Milk yield is one of the most important economic traits and modelling the lactation curve is important with respect to the unique shape with ascending, persistent and descending phases. The non-linear relationship of daily milk yield with days in milk has led to extensive research in modelling the lactation curve. The nature of the lactation curve, different models, identifying the best model of fit, factors affecting the curve parameters and orthogonal polynomials to model the curve are discussed in this chapter.

Traits such as growth, lactation test day yield, semen evaluation are longitudinal traits measured repeatedly on the animal and random regression models (RRM) have been found to be suitable for modeling these traits, The methodology used, data requirement, assumptions, validity, software available and application of RRM are explained in this chapter.

Growth, test-day milk yield, and semen traits are examples of longitudinal traits measured repeatedly on the animal and random regression models (RRM) have been found suitable for modeling such traits. RRM is based on a covariance function which could be defined as “a continuous function to give the variance and covariance of traits measured at different points on a trajectory” (van der Werf, 2001). Kirkpatrick et al. (1990) showed that variance components for longitudinal data can be modelled through covariance functions. Random regression models (RRM) and the resulting covariance function have been recognized as ideally suited for the analysis of longitudinal data (Hill, 1998; Meyer, 1998).

Linear models have been extensively used in animal breeding. This chapter explains the basics of linear models including description; fixed, random and mixed models; model diagnostics and covariates. The concept of linear models in animal breeding is explained with representation and actual examples of use in different types of livestock.

Introduction to Linear Models

A model can be defined as a physical, mathematical or otherwise logical representation of a system, entity, phenomenon, or process. Linear models are a way of describing response variables in terms of a linear combination of the predictor variable. They provide a framework for a large set of models whose common goal is to explain or predict a quantitative dependent variable by a set of independent variables that can be categorical or quantitative.

Estimation of variance is primary for any breeding program as all the genetic parameters are dependent on these estimates. The properties of an estimate, their assumptions, type of data, availability of data, and computational requirement make it important to understand the method of estimation of variance components so as to make a wise choice that would suit the breeder’s requirement. This chapter explains the methods of estimation of variance with merits and demerits of each and the reader could use these as a guide to choose the right method of estimation.

The genetic parameters are the basis for any animal breeding program and the important parameters such as heritability, repeatability and genetic correlation are ratios of (co)variances and their reliability depends on the accurate estimation of variance components. Estimates of variance components are used extensively in animal breeding.

The key genetic parameters available with the animal breeder to attain improvement are heritability, repeatability and genetic correlation. This chapter will mainly deal with the theoretical considerations of these parameters.

The goal of an animal breeder is to bring about permanent improvement in different economic traits, either individually (univariate) or simultaneously in multiple traits (multitrait). The phenotypic value available from the animal is a combination of genotypic value and environmental deviation. By permanent improvement in a trait, we mean the improvement in genotypic value, which could be carried over to future generations. The environmental deviations are spatially and temporally specific, and thus will not be the same over generations. The genotypic value, itself is made up of additive effect, dominance deviation and interaction deviation. The additive effect is a value of genes (the sum of the average effect of genes) and hence is more important for the breeder as only the genes are passed on to the next generation.

It is known that the phenotype of an individual is a combination of genotype and environment. Animal breeding analysis is mainly done to partition the genetic part from the environmental part so as to assess the actual genetic worth of the animal. In this process correction for the known environmental part is integral to any animal breeding analysis. In this chapter, a list of common factors affecting important economic traits are described. The analytical part for these effects will be explained in later chapters.

Correction or standardization of data is very important in any animal breeding analysis. Unless the candidates under selection are placed on a common platform, various factors affecting the trait will lead to bias in assessing the performance of the individual with respect to a particular trait. For eg. a lamb born during a favorable season, a lactating cow in its third parity, first lactation yield of a cow with longer age at first calving.

Correlations and regression are important components of animal breeding analysis. The genetic correlation is an important genetic parameter that is useful in the planning of breeding programs involving multiple traits. In this chapter, the basic concepts of correlation and regression including method of estimation, assumptions and test of significance are presented. An example using SPSS software is also given at the end for better understanding.

Basic knowledge of statistics is important to understand animal breeding analysis. In this chapter, the hypothesis testing, principles of experimental design, types of data and probability distribution are described with examples using appropriate software.

Animal breeding data is unique in terms of volume, statistical analysis, type of information required etc. The large volume of data extended spatially and temporally warrants additional tools in the form of databases to handle data and enable accuracy, retrieval, efficient utilization and adaptability to software. This chapter explains the nature of animal breeding data and the importance of databases with examples and explanations.

Animals are raised for some utility including meat, milk, hide, wool etc., and efforts are on to continuously improve the quality and quantity of these products. Some of the important economic traits in this regard were already discussed in earlier chapters. Record maintenance is primary for decision-making with respect to the selection of animals. The details of record maintenance including the format of registers are already explained in chapter 2. Apart from the actual information required for economic traits, pedigree information forms an important part of animal breeding data.

Maintaining the required type of information in the form of records is primary for any type of animal breeding analysis and this chapter explains the importance of records and ways to maintain them in the form of registers or computer databases. The formats for different types of registers to be maintained are also given as a template in appendix. Any breeding plan is formulated to improve the economic traits depending on the utility of species reared and the chapter lists important economic traits of livestock and poultry with definitions and formulae, where ever required.

Basic record maintenance is a must for any animal breeding program. Every farm or breeding program is expected to maintain records in the form of registers or computerized databases. The goal of animal breeding is to select mates with the objective to improve economically important traits. In this chapter, the most common economic traits in different species of livestock are described. Even though the list is not exhaustive the basic economic traits that have been worked for improvement are explained. Breeders also explore new composite traits which are a combination of these base traits.

Domestic livestock plays a major role in meeting the food requirement of human beings. Especially with dwindling resources, improvement in production efficiency is primary to meet the ever-increasing demand for animal protein. The role of an animal breeder is to bring about a sustained improvement in the quality and quantity of such products. Over the years, there has been an enormous improvement in the production ability of livestock and statistical analysis has played a predominant role in the application of principles of animal breeding to improve the productivity of animals. The combination of genetics and statistics developed into a separate branch of science called biometry.

Cowpea is a quick growing leguminous forage crop. It is usually grown mixed with cereal fodders and grasses to improve the nutritive value of the herbage. It contains 20 – 24 % crude protein, 43 - 49 % neutral detergent fibre, 34 – 37 % acid detergent fibre, 23– 25 % cellulose and 5 – 6 % hemicelluloses on dry matter basis. The digestibility of cowpea fodder is above 70%. Cowpea can be grown under partial shaded conditions. It is an excellent cover crop, which suppresses weeds and enriches the soil. Cowpea requires warm climate with good atmospheric humidity. It can be grown in kharif as well as in zaid season.

Cumbu Napier hybrid grass is a cross between Cumbu (Pennisetum glaucum) and Napier grass (P. purpureum Schumach.), widely cultivated across India, Africa, Sri Lanka and South East Asian countries. As the hybrid is a triploid, it displays complete sterility and high vegetative growth. In Tamil Nadu, land area utilized for growing fodder is negligible, accounting only 1.6 per cent of the total cultivated area.

Forages: The term forages denote plants that are used for feeding the animals that are cultivated in the farm, or it may be a wild used for stock feeding grown for the vegetative purpose. The vegetative phase is encouraged and the reproductive phase is suppressed.

History of jute in India: In Mahabharata times the mention has been made regarding Jute garments as pattagam (patta produced) for jute fibre products and kitajam (insect produced) for silk products. In Ain-e-Akbari, there is mention of sack cloth made from jute, in Rangapur district.

Cotton is often called as “white gold”. True to its name cotton supports the largest agro based industries in India and cotton industry ranks first in the agro based industries and engages 4 to 5 million people in cotton growing. The industrial sector employs 1.0 million people. At present there are 3660 ginning and 1570 textile mills in India. India earns foreign exchange to a tune of Rs. 2500 million through exports of cotton textiles and products. Cotton is cultivated for ‘lint’ which is used for preparing threads, yarns and medical cotton mixed with synthetic fibre and for various other purposes.

The earlier view was that the cultivated sesame originated from Ethiopia. But Bedigian and Harlen (1984) established evidence to indicate that sesame is native of India. In vedic period, liberal mention about Til (Gingelly seed) and Taila (Gingelly oil) are mentioned. The Charred seeds of Gingelly were extracted from Harappa (2500-1500 B.C).

Oilseed crops are crops which are rich in fatty acid, cultivated for the production of vegetable oil. They are used either for edible or industrial or medicinal purposes. The important oilseeds are groundnut or peanut, sesame or gingelly, sunflower, rapeseed and mustard, soybean, castor, linseed or flax, niger and safflower.

Mungbean is one of the most important pulse crops. It is grown in almost all parts of the country. Mungbean is primarily a crop of rainy season; however, with the development of early maturing varieties, it has proved to be an ideal crop for spring and summer seasons. Middle of March to last week of June is the most suitable growing period where there is a plenty of life-giving sunshine. During this period high temperature and low humidity keep insects and disease infestations at their lowest. Summer season offers an excellent opportunity for raising short duration pulses.

Pulses are seeds of leguminous plants used as food. They produce dal rich in protein. The important pulse crops are greengram, blackgram, redgram, bengal gram, soybean, cowpea, peas, lentil and lathyrus. The total area under pulses in India is 29.81 m ha with a production of 25.42 m t and the productivity is 853 kg / ha. Pulses can grow both in rainfed and irrigated conditions.