eChapters

Classification involves grouping organisms into a series of hierarchical categories. Actual method of establishing a classification consists in defining groups or categories on a hierarchical scale. The animals can be classified in a taxonomic hierarchy consisting of a series of categories of ascending ranks from species to kingdom. Each of these categories includes one or more groups from the next lower level. Therefore, all animals can be classified in a taxonomic hierarchy consisting a series of categories in ascending order from species to kingdom such as species, genus, family, order, class, phylum and kingdom.

According to the history of biological classification, Aristotle, a Greek philosopher classified different animals based on the habitat, characteristics etc. Later Swedish botanist Carolus Linnaeus introduced taxonomic hierarchy categories during 18th century and this system is followed globally.

Taxonomic hierarchy refers to the sequence of categories in increasing or decreasing order. Kingdom is the highest rank and species is the lowest rank in hierarchy. Taxonomic hierarchy is the process of arranging various organisms into successive levels of biological classification. Each of the level of the hierarchy is called taxonomic category or rank.

Code of Ethics was observed by International Commission on Zoological Nomenclature for renaming of homonyms. The commission had issues declarations or opinions from time to time, which together constitute the start of a code of ethics in the field of nomenclature. The first Declaration of the international Commission was as follows:

• When it is noticed by any zoologist that the generic name or specific name published by any living author as new is in reality a homonym, and therefore unavailable under articles 34 and 36 of the Rules of Nomenclature, the action is for said person to notify the said author of the facts, and give said author an opportunity to propose a substitute name.

• When the author of a newly discovered generic or specific homonym is dead, the discoverer is free to rename the genus or species as he likes. It is common practice to rename the category after the author of the homonym. However, this practice was never universal and it is not a matter of ethics.

Taxonomic keys are devices that make identification of taxa easy and enjoyable. A key is presentation of appropriate diagnostic characters in a series of attractive choices to facilitate identification of a specimen.

Key characters are the characters that are easily perceived of very low variability, usually present in preserved material. They are useful as convenient labels for distinguishing taxa by the process of classification. Many taxonomic characters such as chemical, chromosomal, physiological and behavioural may have high value of identification because they are inaccessible in preserved material. Ideal key characters apply equally to all individuals of the population. They are absolute, relatively constant and external so that they can be observed directly without special equipment.

Identification of the insects is the integral part of systematics. It utilises all taxonomic procedures. The collections in the world are the accumulation of past taxonomists and are stored for the future identifications. Every species name is based on a published description or figure and usually on the type specimen. Identification is the association of other specimens with the appropriate description or with type specimen.

The steps in identification are as follows:

1. Preliminary key to orders and families

2. Key to genera and species if recent monographs or faunal works are available

3. Reference to the most recent catalogues

4. Reference to current bibliographies for literature published subsequent to the most recent catalogues

5. Reference to original descriptions

6. Comparison with the authentic described specimens or with types.

Super Species

According to Mayr (1931, 1942) Linsleg and Usinger (1953),“A super Species is a monophyletic group of very closely related and largely or entirely allopatric Species”.

Super species are, in other words, groups of populations that seem on other grounds (morphology, ecology etc.) to have passed beyond the point of potential interbreeding and to have acquired separate evolutionary roles. They are so by the more conclusive evidence of remaining separate when sympatric. It is to be assumed that they are still near the critical point of specification, near a definitive isolation. They are nascent species that will, if they survive, collectively form a subgenus or eventually a genus but have hardly get reached that degree of divergence.

They are not given special names; the Rules of Nomenclature make no provision for that usual designation and they are mostly known by the name of an included species and are in fact super species.

The Species Concept in Systematics

The modern biological or, more strictly, genetical concept of a species is a group of interbreeding organisms, genetically isolated from other such groups. The definition of the category species has long been one of the major problems of taxonomy. It is because of two reasons:

1. Because of the congruity of lingering typological concepts with the nature of evolving species.

2. Because evolutionary species may have changing characters and are only gradually differentiated in phylogeny.

For evolutionary study and descriptive purposes, many kinds of variation within species come in to consideration, but the only regular intra specific taxon is the subspecies. Subspecies are widely but not universally useful and their definitions yield to the same sort of criteria as for dividing other phylogentic continuance.

Man has tendency to classify everything in a hierarchical manner for example, ships may be classified on size, weight, what they carry or naval versus merchant or passenger. Any of these classification is as valid as any other.

But classification of biological species is unusual in that a predefined system exists i.e. the evolutionary relationships among organisms. But evolutionary relationships can only be estimated; and contrary to popular belief, even a good fossil record does not conclusively show the phylogeny or evolutionary tree of a group species.

Numerical taxonomy can be defined as “Numerical evaluation of the affinity or similarity between taxonomic units and ordering of these units into taxa on the basis of their affinities”. The term includes drawing of phylogenetic inferences from the data by statistical or other mathematical methods to the extent to which this should prove possible. The practice involves a number of fundamental assumptions and philosophical attitudes toward taxonomic work.

The science of taxonomy started with Linnaeus, who used two Latin names for an organism by a universally agreed name and identity, and further provided means for their realistic classification. These identifications and classifications got strengthened further with accumulated biological knowledge. In the recent times taxonomy has become more demanding subject for areas in entomology, which are dependent on access to accumulated experience and knowledge for their survival and development. By providing name and classifying an insect, taxonomy provides information on the nature of population, life cycle, habitat and behaviour and thereby developing hypotheses, concepts and theories, which are basic to biological control. In addition, it enables comparison and synthesis, all of which lead to refinement and fine tuning of the concepts and theories for identification.

Origin of systematics is as old as Vedas (1500 BC), Ramayana (1900 BC), Mahabharat (1400 BC) and Upanisad (350 BC) in which mention had been made about various animals.

History of Insect Classification

Linnaeus (1758-1766) in the 12th edition of Systema Naturae, divided insects into 9 orders

1. Coleoptera (earwigs – Dermeptera).

2. Orthoptera.

3. Hemiptera.

4. Lepidoptera.

5. Neuroptera (ant lion, Sialis, termites and dragon flies).

6. Hymenoptera

7. Diptera.

8. Thysanoptera.

9. Aptera (wingless insects, spiders, scorpions, terrestrial crustacians and Myriapods).

The foundation of modern insect classification was laid by Brauer in 1885. According to Brauer insects were classified as Subclass: Apterygogenea (pterous) and Pterygogenea (winged) based on:

• Presence or absence of wings.

• Mouthparts.

• Metamorphosis.

• Number of Malpighian tubules.

• The nature of wings.

• Thoracic segments etc.

The earliest classification of insects was based on habits and habitats and on certain gross anatomical features that define the general aspects of different kinds. In classifying insects, not only anatomical characters but also facts pertaining to physiology, biology, distribution, ecology and sometime cytology of the species is taken into consideration.

Classification

Classification is ordering of organisms into groups (or sets) on the basis of their relationships that are of associations by contiguity, similarity or both.

Classification of living things is an attempt to interpret nature. It attempts to bring together the kinds that are alike and closely related and to separate those that are unlike and unrelated.

Animals might be classified in various ways but the classification is based primarily on structural characters. Those animals with certain structures in common are classified into one group, and those with other structures into other group. Thus the animal kingdom is divided into a dozen or so major groups called phyla (singular, phylum); each phylum has a name, and its members have certain structural characters in common. The characters used to distinguish phyla include the number of cells, symmetry, body form and segmentation, the nature of the appendages, and the arrangement of the internal organs.

On the basis of degree of complexity, and probably evolutionary sequence, the animal phyla are usually arranged in a series from the lower phyla to the higher ones.

Nomenclature should not be confused with terminology which deals with terms, like antenna, abdomen, radius etc. Names of animal and plants may be either vernacular or scientific.

Vernacular names or local names of plants and animals are different from region to region, from language to language.

Scientific names or Latin or International names are used universally all over the world. Without them we would not be able to communicate and to use the knowledge accumulated about animals and plants in literature. These international names are under certain rules or nomenclature.

Nomenclature

No-men-cla-ture means a system of names. It is derived from Latin Nomen means name and calor means to call, which means to call by names. Nomenclature is the “language of Zoology” and the rules of nomenclature are its grammar. Since all zoologists work with animals and used their names, it is essential that the general principles of zoological nomenclature be familiar to all zoologists.

Origin of Insects

Insects are highly specialized group of invertebrates belonging to the largest animal Phyla, the ARTHROPODA, which also includes in it, the prawns, crabs, lobsters, centipedes, millipedes, scorpions, ticks, mites and spiders. Practically three fourth of the animal species come under this phylum.

The Arthropods evolved during Cambrian period from primitive annelidan ancestor. The main evolutionary stem of Arthropod is represented by the Crustacia- Insecta- Myriapoda.

The insects originated in the Devonian period of Palaeozoic era. Diplura and Thysanura are the most primitive wingless insects while mayflies, damselflies, dragonflies and stoneflies represent the primitive winged insects.

Evolution

Evolution is a process whereby population are altered over a period of time and may split into separate branches, hybridize together or terminate by extinction.

Arthropods occur up to the height of over 6,080 meters on land and up to the depth of about 59,728 meters in water. Different arthropod species are adapted for living in air, on land, in soil and in fresh, brackish or salt water.

Many insects are economically important for being pests of crops, stored grains, stored food, household goods and clothing etc. Some insects and arachnids are in one way or the other responsible for certain diseases of crops, domestic animals and human beings. Some arthropods, on the other hand, such as crabs, lobsters, prawns and shrimps form a part of human diet while, small sized crustaceans are staple food for fishes. Many parts of the world have witnessed some insects and spiders eaten by many land animals including man.

Insects share many characters with other arthropods, but the other arthropods have not been able to exploit these to the extent insects have evolved. The presence of functional wings is a very important character which insects do not share with other arthropods, that is why insects have distinct advantage over other arthropods in their struggle for existence and dominance. A comparative account of Insecta and other arthropod classes is given in Table 1.

Origin of Systematics

In Vedas (1500 BC), Ramayana (1900 BC), Mahabharata (1400 BC), and Upanishad (350 BC) mention had been made about various animals. The number of known species of animals is much greater than that of plants and has been estimated at about more than one million. When subspecies are included, the number may double to more than two million named forms of animals. The new animals are being described at the rate of about 10,000 per year. Metcalf (1940) estimated that one and a half million species names are already applied while Silvestre (1929) calculates an estimated 3 million probable species of insects.

Systematics

Systematics is a term coined by a Swedish naturalist Linnaeus (Systema Naturae 1735) which is a Latinized Greek word Systema, as applied to the systems of classification. According to Simpson, “Systematics is the scientific study of the kinds and diversity of organisms and any or all relationships among them.” It includes Taxonomy, identification, classification and nomenclature. Now-a-days, both terms are used inter-changeably in the fields of plant and animal classification.

Arthropod life began very early in Palaeozoic region, about 600 million years ago in the sea. The arthropod foundations were laid with the evolution of metamerism in segmented worms, and in the ancestral arthropods it resembled the now extinct Trilobites. They had harder cuticle forming the exoskeleton and a pair of jointed legs with each of its metameric segments.

The Trilobite stock soon diversified into:

a) Chelicerates.

b) Mandibulates.

a) Chelicerates: In Chelicerates, the anterior body segments fused to form the prosoma, bearing a pair of chelicerae, the feeding organs; a pair of pedipalps and four pairs of walking legs. The remaining segments formed the legless opisthosoma. This gave rise to Eurypterids (Extinct) Xiphosurians, Pycnogonids and the highly successful Arachnids, including the scorpions, spiders, ticks and mites.

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The craniofacial region presents a unique challenge for implantable biomaterials because the pull of the craniofacial muscles produces variable loading in different regions. In addition, craniofacial skin loses elasticity with the age and develops subcutaneous tissue sags.

Even though surgeons are familiar with the use autogenous bone grafts for craniofacial reconstruction, the usage of alloplastic bone substitutes has increased continuously, because autogenous bone is difficult to harvest, time consuming, causes significant donor morbidity, and bone resorption, but most important thing is that the biocompatibility of current alloplastic materials are improving.

Synthetic substitute creates a new avenue for clinicians to explore as adjunct in surgical procedures. These materials may not necessarily be used solely for reconstructive procedures, but when used in the right situation in combination with autologous, allograft or other synthetic, the result have the potential for more desirable results.

In the past, there was no targeted development of biomaterial based on scientific criteria. Instead devices consisting of material that had been designed, synthesized and fabricated for various industrial needs (the textile, aerospace, and defense industries) were tested in a trial and error fashion in the bodies of humans and animals. These unplanned and sporadic attempts had modest success. Most frequently, the results were unpredictable, mixed, and confounding both in success and in failure. In addition to traditional medical devices, diagnostic products, pharmaceutical preparations and healthcare disposables, now the list of biomaterial application includes smart delivery systems for drugs, tissue cultures, engineered tissues and hybrid organs. Undoubtedly biomaterial have had major impact on the practice of contemporary medicine and patient care in both saving and improving the quality of lives of the humans and animals4.

Biomimetics is defined as the study of the formation, structure, or function of biologically produced substances and materials and biological mechanisms and processes especially to synthesize similar products by artificial mechanisms which mimic natural ones.

Biomimetic materials and molecules have been applied in many of the potential research areas in medical and dental sciences and highlight their foundation from plants, animals, or microbes that can be used to treat human disease.

A bioactive/biomimetic material and biocompatible material is an artificial or natural material used to change part of the living system or to function in internal contact with living tissue. Bioactive materials can interact with living tissues or systems.

There are several types of biomimetic materials like

Osteogenic Materials

Osteoconductive Materials

The term “artificial intelligence” (AI) refers to a wide variety of theories and technologies that are used to the resolution of issues characterized by a high level of logical or algorithmic complexity. It cuts across a wide range of f ields, such as mechanical modeling, software engineering, data science, and statistics. Many artificial intelligence (AI) technologies, which first appeared in the 1950s, have lately been refined or extended thanks to advances in computer performance. Recent advancements have been made possible by the creation of interfaces between artificial intelligence and other fields of study, such as biomedicine, and by the collection of enormous amounts of data from a variety of fields, notably those related with the healthcare industry. First, Artificial intelligence helps with situational awareness, which is relevant in animal health and animal husbandry because it allows for the detection of patterns like repeated sequences of observations, forms like a protein, and signals like increased mortality especially in comparison to a baseline at various scales. A third option is computer-based decision making, or more practically, human decision support via knowledge - based systems, diagnostic support, and resource allocation, for instance.

Biostatistics is a branch of statistics that focuses on the analysis and interpretation of data from biological and health-related research studies. It involves the application of statistical methods to design, collect, analyze, and interpret data from studies involving living organisms like: animals, birds including human beings. Biostatistics plays a crucial role in public health, medicine, epidemiology, genetics, and other related fields.

With the increasing availability of data and advancements in biostatistics, breeders can expect further improvements in breeding practices that will results in better outcomes for both livestock farmers and the animals they breed. Animal breeding is a crucial aspect of agriculture and food production, as it helps to improve the quality and quantity of animal products as well ensuring food security to the masses.

Introduction

Estimated breeding values (EBVs), often estimated for sires, are used in traditional animal breeding (TAB) programmes to make selections based on an animal’s performance and that of its relatives. Using, typically, the best linear unbiased projections, EBVs are calculated using attributes measured in own performance, pedigree, sib, and/or progeny evaluation schemes in specialised testing stations and/or selected farm conditions (BLUP; Henderson, 1975). One of the main time-consuming challenges for phenotypic evaluation to enable a meaningful estimation of breeding values is generation intervals of 4 to 5 years in beef cattle, more than 5 years in dairy cattle, and 2 to 2.5 years in pig breeding schemes (Schefers and Weigel, 2012). Modern breeding techniques like marker-assisted selection (MAS) and, more recently, genomic selection (GS) are based on the use of genetic DNA markers to aid in selection and breeding (Williams, 2005). The fundamental reason why MAS, that only further uses a few markers as a selection tool, hasn’t made as much progress as was initially anticipated is that finding trustworthy markers is challenging, particularly when dealing with complex traits. Only relatively few consistent markers could be identified, despite successful identification of many quantitative trait loci (QTL; Hu and Reecy, 2007)

Livestock breeding for genetic improvement faces many challenges including feed conversion efficiency, fertility and adaptation to changing climate. These improvements have to be realized while maintaining or improving the nutritional properties of meat, milk and other animal products while giving emphasis to animal health and wellbeing also. Environmental stresses induced by climate change affect livestock productivity, reproductive efficiency and health, resulting in severe economic losses. Under the current climate change scenario, the viability of producing animals for human consumption is in jeopardy. In order to lessen the negative effects of heat stress in today’s world, it is urgently necessary to develop methods that are centered on breeding animals with increased thermal tolerance and climate resilience. The breeding of animals having genetic potential to sustain under changing environment conditions can be achieved through the various molecular genetics tools.

Livestock is one of the fastest growing agricultural subsectors in developing countries. In India has a vast diversity of animal genetic resources. Among them, sheep is an important ‘five star’ livestock species contributing significantly to rural economy through production of mutton, wool, manure, skin and milk etc. Sheep make a valuable contribution to the livelihood of the economically weaker sections of the society. The total Livestock population is 535.78 million and total sheep population is 74.26 million in in the country showing an increase of 4.6% and 14.1%, respectively over Livestock Census-2012. And it’s ranking 3rd in the world after China and Australia. Rajasthan is the fourth largest sheep rearing state in India with 7.9 million population (Livestock Census, 2019). Malpura sheep is one amongst the heaviest sheep breed of India, widely distributed in the semi-arid region of Rajasthan, mostly Tonk, Jaipur and Sawai Madhopur districts. Malpura sheep is reared and improved for mutton production since year 1975 at CSWRI, Avikanagar. The objective since then has been to improve the growth characteristics of this sheep breed for producing more carcass yield.The sheep is known for its adaptability to the harsh environment and potential for high meat production.Coat colour of Malpura sheep is white with coarse wool. The face is light brown with short, blunt ears. Animals have square compact body and long legs. Farmers also have liking for the long tail of animals for aesthetic purpose. The farmers like Malpura sheep for its properties like good mothering ability and produce sufficient milk to sustain and accelerate the growth of their neonates (Mishra et al., 2005), higher weight gain, number of lambs weaned, wool quality, walking capacity and the ease of management.

Introduction

Wool which obtained primarily from sheep is an essential textile fiber that is used across the world. Whether for clothing, canvas work, carpets, or even upholstery, wool is a vital resource supporting many industries and occupations. This natural fiber has many benefits, such as being biodegradable, easy to clean and even having a natural structure that traps air which is excellent for heat retention. The annual wool production is 2 million tones. China ranks first in terms of global wool production. With a production of more than 333,624 tonnes of wool in 2020, China accounts for approximately 19% of the global wool clip. Australia produces 16% of global wool and is by far the largest wool exporter in the world. There has been a constant increase in the demand of wool products worldwide. This has made scientists to try to improve livestock and livestock associated derivatives. The conventional system along with the recent biotechnological interventions will be helpful for enhancing wool quality and production.

The global human population is increasing exponentially with time, and it is expected to reach 9.6 billion by 2050 (UN 2013). With rapid population growth, food consumption is predicted to more than double in the next 40 years. Due to limited land resources for cultivation and a stabilising trend in agricultural productivity, the role of livestock sector is increasing significantly to meet the rising food demand. Meanwhile, global livestock production has increased significantly in both number and productivity. Unprecedented urbanisation has a significant impact on food consumption patterns in general, as well as demand for livestock products. Animal diseases are a significant factor in reducing livestock productivity, particularly in developed countries. The limitations of traditional animal breeding hinder further improvement of livestock productivity. The use of biotechnological tools has major applications in improving animal health and production, increasing disease resistance, using assisted reproductive techniques, improving rapid diagnostic techniques, and improving vaccines in livestock systems. These interventions cover advancements in feeding, nutrition, genetics, reproduction, animal health control, and overall improvement of animal husbandry. Since genomic tools and selection have been widely adopted in developed countries to improve both productivity and quality of animal products, the prospects for increasing productivity in developing countries using genomic tools and selection have not been adequately investigated.

Introduction

The key factor of sustainability in the animal sector depends upon genetic improvement in domestic livestock. There are many reproductive and molecular biotechnologies used for the genetic improvement of domestic livestock and they are synergistically coupled with the breeding program in distinct breeding targets. With the help of gene editing techniques (e.g. CRISPR etc.). To improve the specific traits of interest scientists can add, delete or replace the nucleotides (e.g. milk production, meat production, disease resistance, etc.) in less than one generation. Gene editing with the conventional breeding program in livestock is an important factor for genetic improvement for increasing the rate of genetic gain. In the present topic, here, we delved into the most important reproductive and molecular technologies used in livestock genetic improvement, as well as the most effective ways for incorporating gene editing into existing genetic improvement programmes and targeting specific traits for enhancement. The improvement in genetic level is a most powerful part of sustainable animal development because it is permanent and the effects are long-lasting and cumulative. Genetic advancements produced in one generation are passed on to the following, unlike dietary and animal health treatments, which are a continuous process. The many livestock operations that involve chemical and mechanical methods such as dehorning requires time, worker, money, animal safety, etc., but their genetic alternation of the concerned gene for the polled or hornless condition can exclude the requirement of physical dehorning. (Gottardo et al. 2011; Tompson et al. 2017).

India is bestowed with a wide variety of livestock species which forms the backbone of the economy of majority of the farmers. Cattle are one of the important species domesticated by man mainly for their draftability in agricultural operations. Rearing of cattle is an integral part of the Indian agriculture as it is always considered as a subsidiary enterprise of the agriculture farming. The indigenous cattle are well known for their adaptability to the harsh tropical climatic conditions, ability to thrive in the resource poor production systems, better feed efficiency and disease resistance. Barring few dairy breeds, majority of the Indigenous cattle breeds are poor in their genetic potential for milk production. Considering the ever increasing demand from milk , the country has implemented many cattle improvement programmes like Central Herd Registration Scheme (CHRS), Intensive Cattle Development Programme (ICDP), All India Coordinated Research Project (AICRP) on Cattle National Programme for Bovine Breeding and Dairy Development (NPBBD), National Livestock Mission, National Project for Cattle and Buffalo Breeding (NPCBB), Rashtriya Gokul Mission (RGM) etc., for improving the milk productivity of cattle.

Energy is essential for each and every single biological reaction in the body of an individual. Production, reproduction and physiological functions of an animal depend on its body state and utilization of energy from dietary source and its body reserves. Energy reserves are determined primarily by the relative amount of fat accessible as an energy source and are indicative of health condition. Adipose tissue (AT) is a primary reservoir of energy and recognized as an immunologically and endocrinologically active tissue. Cattle have the ability to utilize body reserve to meet energy demand due to negative energy balance during peripartum period, which is crucial for maintaining their health lactation and neonates. There are several methods to measure tissue reserves like body weight, metabolic and hormonal factors, respiratory calorimeter body water by dilution with D2 O, estimation of fat cells diameter, ultrasound techniques etc. Body weight is not a good indicator as it is affected by different factors such as; age, parity, gestation, body frame, gastrointestinal contents weight of vital organs and shows a greater variation in measuring fat stores. Other methods are inapplicable in field conditions as they are costly, time consuming and need laboratory facilities and skilled technicians. However Body Condition Score (BCS) is an easier and the most practical method, which is an assessment of thickness of fat cover, prominence of bone of tail and head region.

Introduction

Raising milk and meat production are long-standing global issues. Researchers are learning that present breeding efforts won't be sufficient to meet anticipated future food demands given the current climate scenario. The animals that influence the overall yield of the field must be screened as soon as possible. In order to build more successful modern breeding programmes, high-throughput phenotyping is currently being included into conventional breeding operations. Despite the public accessibility of their genetic information online, there is still a lack of phenotypic data on the genomes of various animal breeds because environmental factors make it more difficult to define phenotypes and increase the likelihood of measurement error (Rahaman et al., 2015). Genomic selection (GS) is a strategy that predicts the genomic estimated breeding values of lines in a breeding population using information from genome-wide markers (Meuwissen et al., 2001). When compared to other conventional methods like marker-assisted selection (MAS), genomic selection has some inherent advantages. These include boosting genetic gain by reducing breeding cycles and acquiring minor effect loci based on markers dispersed throughout the entire target genome. Reliable phenotypes and genotyping are both necessary for the training of accurate prediction models for genomic selection. Phenotyping is regarded as a significant factor restricting genetic improvements in animal breeding due to high labour and time expenditures. Traditional approaches of phenotyping are prohibitively expensive, time-consuming, and slow.

Introduction

The sex of the animal is one of the most easily observable attributes of a livestock population. The importance of the sex ratio lies in the fact that it sets the future rates of fertility, mortality, and migration. In livestock, male animals are required in fewer numbers compared to females for breeding. So, for profitable management of a farm, the sex ratio has been fixed for each species. But because of the natural 50:50 chance of both types of sperms to fertilize an ovum, this preferred sex ratio is never achieved. In order to reach this economical ratio, additional efforts must be done in the form of culling. Moreover, in monotocous species with nearly one year gestation period, a long wait is sometimes required for getting the offspring of particular sex.

In dairy farming, the number of female offspring born is always an asset to the farm. For the species reared for meat, the males are often avoided due to the intense odor of their meat and handling difficulty while rearing. But when there is shortage of good quality breeding bulls, the sorted sperms will be helpful for producing the elite bulls for breeding. If we can produce only the animal of the desired gender, we can eliminate split-sex feeding, reduce problems related to animal welfare and castration, improve production efficiencies. Additionally, the costs of the progeny testing programme and embryo transfer are reduced as a result, and the value of genetic markers is increased. Apart from the livestock species, sex pre-selection is also important in breeding of companion animals, zoo animals and endangered species.

Artificial Intelligence (AI) is a discipline of computer science that now days affecting evary aspect of day to day life. It has the potential to greatly improve animal breeding programs in India by providing more accurate and efficient selection methods. Some of the avenues and possibilities of using AI in animal breeding in India includes Predictive analytics: AI can be used to develop optimization models that take into account a variety of factors, such as genetics, phenotypic traits, and environmental conditions, to identify the best breeding strategies. AI can be used to analyze large amounts of data on animal genetics, phenotypic traits, and environmental factors to predict the likelihood of an animal producing offspring with desired traits. This can help breeders make more informed decisions about which animals to be selected for breeding. AI algorithms can be trained to accurately identify diseases in animals by analyzing imaging data, such as X-rays and MRI scans, as well as blood and tissue samples which in turn facilitate veterinarians to make more accurate diagnoses, improving treatment outcomes. AI can also improved feed efficiency by analyzing the feed consumption and nutrient utilization data to identify patterns and trends that can be further utilized to improve feed efficiency, reduced feed costs and increased production efficiency.

Artificial intelligence (AI) uses multiple technologies that equip machines to sense, comprehend, plan, act, and learn with human-like levels of intelligence. Fundamentally, AI systems perceive environments, recognize objects, contribute to decision making, solve complex problems, learn from past experiences, and imitate patterns. AI technologies such as deep learning allow computer systems to understand a problem, learn from examples, and make predictions.

The AI has a tremendous potential to solve the diverse application problems in the field of domestic animal breeding and management. Till date, most of the studies have been focused on animal behaviour (Valletta, et al., 2017), cognition (Lake et al., 2017), animal welfare (Neethirajan, 2021), individual identification (Norouzzadeh et al., 2018), growth or body condition scoring (Zin et al., 2020), disease detection and its monitoring (Kumar et al., 2021), precision farm management (Radun et al., 2021) etc. particularly in the pigs, poultry and cattle species. These AI based applications primarily involves data generation, data processing, use of gadgets / IoT devices, development of smart machine learning algorithms and their integration to attain precision to solve various issues in animal husbandry. Having said that, very few works have been carried out with respect to applications of AI in domestic animal breeding, and major problems like breed identification, genomics- based animal selection criteria and breeding decision, are yet to be automated. Moreover, there are some bottlenecks in application of AI in animal breeding, like the lower accuracy of a decision/outcome and large cost involved in creating AI based infrastructure.

Background

Sheep and goats are the poor man’s cow because of the lower capital investment, and production costs. Also supplies milk quantities that are suitable for immediate household consumption thereby reducing problems of milk storage and marketing. Small ruminants, goats and sheep, mainly localized in the arid, semi-arid and mountainous areas of the country, have multi-faceted utility in terms of wool, meat, milk, skins, (mo)hair/pelts, manure and have also acquired socio-cultural niches in many communities (Kosgey and Okeyo, 2007). Goat and sheep milk has many advantages over other livestock species’ milk being easy in digestion, non-allergic, naturally homogenized, improves immunity as it has antifungal and anti-bacterial properties. However, rearing small ruminants for meat is more popular among farmers as price of chevon and mutton are very high, continuously increasing over the years and sale of male for meat is easy, steady and accessible at farmer’s place or local places unlike milk, skin and fibre. Thus, small ruminants (SR) occupy a promising agrarian and economic niche in low to medium input production systems, not suitable for growing crops and dairy farming (Devendra and Chantalakhana, 2002), mostly driven by small and marginal farmers and landless laborers. Their meat and milk production represents 4.8% and 3.4% of the total meat and milk produced, respectively, in the world.

People all around the world have been conducting genetic association studies for a long time. Still the literature to practically understand the statistical analysis of such data using software packages is scarce. Statistical analysis of molecular data is a vast topic. So we will be undertaking one of the important basic and preliminary topics “Statistical analysis of genetic association studies among unrelated individuals” in this chapter. Overall, we will be discussing population association studies in which qualitative and quantitative data on unrelated individuals for various economic traits is collected and these individuals are also typed at a number of Single Nucleotide Polymorphism (SNP) markers. This excludes family-based association studies, admixture mapping or linkage studies. Various software packages used in this chapter to analyze molecular data of a population are given below in Table 1.

Livestock is an integral component of Indian agriculture which is primarily a mixed crop-livestock farming system and plays an important role in the socio- economic life of India. Livestock contributes significantly to the growth and development of agricultural sector by providing a rich source of high quality products such as milk, meat and eggs and by supporting livelihood of more than two third of rural population. Livestock has a crucial and rapidly increasing role infood security and economic stability worldwide Livestock sector contributes for 4.11% of GDP and 25.6% of total Agriculture GDP. The importance of livestock has been undergoing a steady transformation with the contribution of livestock in total agriculture and allied sector Gross Value Added increasing from 24.32% in 2014-15 to 28.63% in 2018-19. Owing to factors such as population and economic growth, urbanization, improvements in transportation and storage practices,its future importanceformeeting human nutritional requirements of food and fiberand a major contributor to agricultural GDP is evident.

To alleviate the concerns raised by a rapidly growing demand of food security and the need of ensuring sustainability of natural resources, we need to better understandthe ways which wouldspeed up commercialization of livestock production so that it can contribute effectively to the bio-economy. Livestock performance and productivity can be improved by adopting proper diet and feeding practices, improved farm management and disease controlstrategies.

The overall number of animals kept as livestock in India comes to 535.78 million, making it the country with the greatest livestock population. According to the 20th Livestock Census, India has a total bovine population of 302.79 Million. This includes Cattle, Buffalo, Mithun, and Yak. There are a total of 109.85 million buffaloes living in the country. The number of goats in the country currently stands at 148.88, while the total number of sheep in the country is 74.26 Million. Most of the breeds in India have evolved naturally through adaptation to varied agro-ecological conditions and have generally been named after their place of origin or on the basis of prominent morphological characteristics. The number of registered breeds in India has increased over time. Majority of livestock breeds are reared by smallholder farmers are of non-descript type. Indiscriminate crossbreeding is extensively occurs resulting in herds of females that may have very complex ancestries.

Introduction

Due to global population growth, rising wages, and urbanisation, the demand for animal products has been expanding quickly in many areas of the world (FAO, 2018). Meeting the rising demand for animal products, which is expected to reach 8.6 billion by 2030 (FAO, 2018) as the world’s population is projected to increase by 80 million per year (Preisinger, 2012), is one of the biggest difficulties facing modern farm animal industry (Eggen, 2012). Animal products and value-added foods are being consumed as a result of urbanisation and income growth (Hoffmann, 2005; FAO, 2011). By 2050, the world’s population will be close to 10 billion, even as the economic conditions continue to improve the demand for animal products will significantly rise. In order to boost animal production, it will be necessary to acquire a more in-depth understanding of animal biology through genomics and other related f ields of study. Understanding animal physiology remains a significant problem in the context of sustainable agriculture and animal husbandry, particularly for developing animal farming systems that cater to the new and diversified consumer demand. Livestock and poultry productivity has been greatly increased through traditional selection based on genetic merit estimated from phenotypic and pedigree data. Most breeding plans do not take population impacts on genetic diversity into consideration, and selection is geared more towards the best genetic response for the upcoming generation than the best long-term response (Meuwissen, 1997). Breeders have employed genetic analyses to find superior animals for more than 40 years.

Introduction

The expanding number of people around the world necessitates an increase in the amount of food that is yielded. As stated by the Food and Agriculture Organization of the United Nations (FAO), global food production ought to be ramped up by a factor of two in the next few years in to meet the requirements of the growing global population in terms of consumption (FAO, 2006). This is because the global population is expected to continue growing at a rate of approximately one person every two seconds until the year 2050. It is possible that the predicted production disparity could be filled by making improvements in genetics, animal health, and the excellence of animal husbandry.

The production of animals has expanded significantly over the course of the last several decades as a direct result of the application of quantitative genetics in animal breeding. However, due to technological limitations, the use of genetic markers in breeding programmes has only been implemented to a relatively small extent (Deng et al., 2016). The concept of genomic prediction, which was first introduced approximately twenty years ago, has completely transformed the planning and execution of animal breeding operations.

Genetic improvement of farm animal species is accelerating in developed countries with adoption of Genomic selection (GS) due to availability of complete reference genome sequence i.e. gene sequences that can be used to compare and study animal genetic traits. GS has been considered most promising for genetic improvement of the complex traits controlled by many genes (Quantitative traits) each with minor effects as using the conventional methods of selection and breeding the rate of genetic gain per generation is very slow with respect to human demand for livestock products. With this method, animals or plants can be selected for selective breeding on the basis of their genetic merit predicted by whole genome molecular markers spanning over the entire genome. Genomic selection may allow the identification of superior individuals for traits such as increased disease resistance which are not currently considered in animal breeding plans because of technical difficulties. The method can predict the genetic merit of young bulls with greater accuracy as compared to convention methods of genetic merit estimation. Genetic gain (ΔG) in animal breeding programs depends upon the intensity of selection (i), accuracy of predictions (r), genetic variance (σ2g) and generation interval (IG): ΔG = i * r * σ2g / IG (Ibañez Escriche & Gonzalez-Recio, 2011).

Genomics is the study of whole genomes of organisms, it uses a combination of DNA sequencing methods, bioinformatics to sequence, assemble, analyse the structure and function of genomes. In another words, it can be defined as it is the study of the structure, function, and inheritance of the genome of an organism. Moreover, genomics focuses on interactions between loci and alleles within the genome and other interactions such as epistasis, pleiotropy and heterosis. Genomics is divided into two basic areas: structural genomics, characterizing the physical nature of whole genomes; and functional genomics, characterizing the transcriptome (the entire range of transcripts produced by a given organism) and the proteome (the entire array of encoded proteins).

Most biological traits are controlled by a large number of genes, which, in addition to their additive effects, may interact with each other, and their expression might be altered based on a variety of environmental effects. Researchers who were among the first to use molecular genetics to the study of cattle began by employing DNA markers to locate genes or sections of the genome affecting features of interest. For instance, identifying a group of genes based on Genome wide association study (GWAS) provides evidence that a causal relationship between a phenotype and a single nucleotide polymorphisms (SNPs) may exist. These findings of GWAS, however, do not improve our understanding of complex traits in which many pathways may be involved. The growing use of genotyping technologies has generated a large quantity of genomic information on the dairy population. Since the draft sequence of the bovine genome was published in 2009 (Zimin et al., 2009), whole-genome sequence data of cattle have also become available.

The systematic identification, evaluation, and integration of the body of published work produced by researchers, scholars, and practitioners is achieved through a rigorous and repeatable method called the review of the literature. It acts as a comprehensive resource, incorporating the most recent information, important discoveries, and theoretical breakthroughs linked to a certain field. The literature review is a useful compilation of important discoveries as well as methodological and theoretical contributions within a certain topic that is frequently seen in academic and scholarly journals.

In all academic areas, the review of literature is a crucial component of research. Its main goal is to assess, evaluate, and make links between our findings and previous research on a particular subject of interest. In addition, the literature review acts as a point of reference and offers helpful insights in the following ways:

i. Approaches

ii. Methods

iii. Variables

Location

Bundelkhand is a geographical and cultural region and also a mountain range in central & North India. The hilly region is now divided between the states of Uttar Pradesh and Madhya Pradesh with the larger portion lying in the latter state. Bundelkhand region is situated between Vindhya range in south and Indo-Gangetic plain in north and lies between 23º10’ and 26º27’ N Latitude and 78º4’ and 81º34’ E Longitude, covering an area of 70,747 sq km. It spread over two states viz. Uttar Pradesh and Madhya Pradesh and comprises of 14 districts. It is spreading over of seven districts of Uttar Pradesh viz. Jhansi, Lalitpur, Jalaun, Hamirpur, Mahoba, Banda and Chitrakoot and similarly seven districts of Madhya Pradesh viz. Sagar, Panna, Tikamgarh, Chhatarpur, Damoh, Datia and recently formulated Niwari district (Fig. 1). The language spoken in Bundelkhand is Bundelkhandi and Hindi. The total population of Bundelkhand as 2011 census is 1,83,35,044.

The study, which was conducted for nature and dynamics of farm ecology in occupational migration in some areas of West Bengal with the stipulated objectives, the following course of action can be considered in future while conduction repeating study.

• Gender dimensions on occupational migration is the future research area.

• Educational issues for families on transit could have been a very interesting area of research.

• Climate refuge; that is migration due to climate change can be an important area of research.

• Application of data analytics could be effective for modelling and simulation on occupational migration.

• The social ecology of migration itself, is a zone of future research.

Summary

It has been found from the study that for the independent variable Family size (x1 ), the maximum is 9.00, and minimum is 2.00 where Coefficient of variation of this variable is 38.124 per cent, which shows that the level of consistency in the distribution is high. For Average family education (x2 ), the maximum is 6.00, and minimum is 1.250 where Coefficient of variation of this variable is 33.074, which shows that the level of consistency in the distribution is high. Average age (x3 ) of the respondents, the maximum is 58.00, and minimum is 12.500 where Coefficient of variation of this variable is 35.341, which shows that the level of consistency in the distribution is high. The study reveals that Average family income (x4 ), the maximum is 10833.00, and minimum is 3666.00 where Coefficient of variation is 30.796, which shows that the level of consistency in the distribution is high and Family land holding (x5 ), the maximum is 5.500, and minimum is 1.00 where Coefficient of variation of this variable is 38.241, which shows that the level of consistency in the distribution Family land of holding is high. In the study maximum and minimum House type (x6 ) of the respondents are 9.00 and 2.00 respectively where Coefficient of variation of this variable is 30.399, which shows that the level of consistency in the distribution is high. In case of material possession (x7 ), the maximum is 13.00, and minimum is 1.00 where Coefficient of variation of this variable is 70.780, which shows that the level of consistency in the distribution is medium. Source of information for migration (x8 ), the maximum is 4.00, and minimum is 1.00 where Coefficient of variation of this variable is 35.679, which shows that the distribution of the variable is high. It has been found from the study that for the independent variable money required for migration (x9 ), the maximum is 5.00, and minimum is 1.00 where Coefficient of variation of this variable is 26.639 per cent, which shows that the level of consistency in the distribution is high.

This chapter deals with the findings of the study along with the discussion based on the analysis. This study tried to represent its findings as per the objectives of the study. At the end of this chapter, interrelation has been made, explanation has been tried to put out down and attempt has been done to reveal the cause behind it. The results and their pertaining discussion are presented according to the specific objectives of the study.

This table 6.1 presents the distribution of 15 independent variables (x1-x15 ) in terms of their Minimum, Maximum, Mean, Variance, Standard deviation, and Coefficient of variation.

The deliberation on the methodology has been made to understand the concept, methods and techniques which are utilized to design the study, collection of information, analysis of data and interpretation of the findings for revelation of truths and formulation of theories. These chapter deals with the method and a procedure used in the study an consist of eight main parts-

A. Locale of research.

B. Pilot study.

C. Sampling Design.

D. Empirical measurement of the variables.

Research setting refers to the detailed information of an area where the study was conducted. The study area generally comprises of a particular geographical area viz. a state, district, block, or gram panchayat area selected according to the convenience of the investigator who possess adequate knowledge regarding the location, communication facility etc. of the locality so that he can easily approach each and every corner of the area for data collection. Besides the investigators must also have the basic knowledge about the socio demographic background of the people so as to have an easy understanding of their knowledge, attitude and behavior. This chapter is intended to present a brief description of the area in terms of social, economic, and agricultural aspects where the present study has been conducted.