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Aquatic plants are recognized as a valuable forage crop, ideally utilized in their fresh state, dried as hay, or preserved as silage. Their suitability and profitability vary depending on the type of livestock being fed. These crops do not occupy arable land and require no investment for cultivation; however, there are costs associated with harvesting. Feeding aquatic plants directly in their natural habitat is infrequently feasible due to factors such as water depth, risks posed by mud and pathogens, and potential contamination of the water by livestock.
1. Water Hyacinth (Eichhornia crassipes): Water hyacinth is a perennial herb that floats freely on the surface of freshwater, including rivers, lakes, canals and ponds. In India, the dried form of water hyacinth or its ensilage is utilized as feed for cattle, owing to its high protein content. The amino acid composition of water hyacinth renders it an appropriate feed option for pigs as well. Typically, the plant is chopped and fed directly to livestock; however, its palatability is compromised by the presence of oxalate crystals in the leaves, which can cause oral irritation in animals. Additionally, cattle may experience adverse effects such as diarrhea and increased urination when consuming water hyacinth. This issue can be mitigated by supplementing the diet of adult cattle with groundnut and paddy straw alongside water hyacinth. Ensiling is an effective preservation technique that improves the palatability of water hyacinth. Due to its high moisture content, it is advisable to wilt the plant in the shade for 48 hours, or alternatively, prepare silage by mixing it with straw in a 4:1 ratio. The addition of molasses is to enhance the soluble carbohydrate content. The DCP and TDN in the silage are measured at 5.64% and 40.26%, respectively. The nutrient composition of water hyacinth includes 5.80% DM, 18.30% CP, 22.60% CF, 2% EE, 21.10% TA, 9.50% Ca and 6.30% P. The nutritive value of fresh water hyacinth is 7.66% DCP and 43.73% TDN, with oxalic acid content ranging from 2.50% to 3.60%

Spindle bug: Carvalhoia arecae :Miridae

Spindle bug is a serious pest multiplying rapidly with the close of monsoon. The adults are red and black and nymphs are greenish in colour with reddish brown patches. Both these stages colonize the top-most leaf axils at the base of the spindle. Adults and nymphs suck the sap from emerging spindle, tender leaves and other tender parts. For feeding they move out and later return to the axils again. At the site of feeding a longitudinal narrow, decolourised zone develops rapidly on either side of the puncture, along the length of the leaf blade. The decolourised patch gradually turns yellowish, then brownish, become stunted, twisted and malformed in a few days and dries up. In this way the tissues may break away and drop off in the wind leaving shot holes on the leaves. In cases of severe infestation the leaves get shred, stand erect and the palms become stunted.

Aphids: Aphis gossypii :Aphididae

The aphids congregate on growing points and suck the sap. Honey dew secreted by the aphids can cause sooty mould in severe infestation. Attack leads to yellowish speckling and curling of leaves.
 
Thrips: Caliothrips indicus: Thripidae

Characteristic silvery white specks with black dots which are mostly faecal pellets, develop on leaves. Consequently, the leaves dry up.

Artificial insemination (AI) is a technique in which sperm cells loaded in straws and stored in liquid nitrogen are thawed and manually deposited into the reproductive tract of a female animal at estrus. The recto-vaginal technique is the most commonly used method for artificial insemination in cattle. In order to increase the probability of pregnancy, the animal in estrus should be inseminated at proper time not too early or late.

Artificial insemination (AI) is the deposition of the semen or male germ cells (spermatozoa) in the female genital tract by artificial means (instruments). Artificial insemination includes collection of semen from the male, preservation, handling and deposition into the female reproductive tract hygienically replacing natural mating by a male. In India this technique is gaining momentum in chickens due to improved animal husbandry practices and economic considerations, initiated by IVRI, Izatnagar and JNKVV, Jabalpur. In many parts of the world, turkey, ducks, goose and guinea fowl are bred solely by AI. Chicken species are endowed with the behaviour and capacity of each male to mate several females and also 25 to 40 times a day. Further, the process of ovulation in birds is almost daily and stimulated by intensity and duration of light.

In modern poultry managemental practices of using cages, environmentally controlled houses and breeding and hybridization techniques employed for developing highly economical chickens, selection for faster growth and heavy body weight in broilers, which has led to loss of fertility and hatchability and use of dwarf female parents in broiler industry have demanded the use of AI in poultry.

At a compound annual growth rate (CAGR) of 7.6%, the global poultry industry expanded from $352.02 billion in 2022 to $378.84 billion in 2023. Global production of chicken meat was projected to reach 103.4 million metric tons in 2023, primarily as a result of rising output in China, India, Brazil, and the US. India is currently the world’s second-largest egg producer (138.3 billion eggs in 2022–2023), trailing only China. It is also the world’s fifth-largest broiler producer (producing 4.99 metric tons (MT) in 2022–2023), behind China, the United States, Brazil, and the Russian Federation.

Climate change affects livestock through heat stress, water scarcity, unstable feed supplies, altered disease patterns and extreme weather. This chapter examines how artificial intelligence supports climate-smart and sustainable animal husbandry. Machine learning, predictive analytics and IoT-enabled monitoring can optimize feeding, detect disease, assess welfare and improve the use of water, energy and other resources. Intelligent technologies can also assist in reducing greenhouse-gas emissions and developing adaptive production strategies. The chapter evaluates the contribution of AI to productivity, climate resilience and environmental responsibility while addressing problems such as insufficient data, limited infrastructure, implementation costs and ethical concerns. Future integration with sustainable agricultural frameworks is also discussed.

Genetic improvement creates permanent, heritable gains in milk production, growth, fertility, disease resistance and environmental adaptation. This chapter explains how artificial intelligence complements conventional phenotypic and pedigree-based selection by analysing large genomic and performance datasets. Machine-learning models reveal genotype-phenotype relationships, predict breeding values and support earlier, more reliable selection. Applications include genomic selection, precision breeding, reproductive technologies, bioinformatics and digital twins. AI can reduce generation intervals and improve the efficiency of breeding programmes, but its success depends on data quality, representative populations and interpretable models. Ethical concerns, genetic diversity and long-term sustainability must also be considered when designing AI-supported breeding systems.

Genetic improvement creates permanent, heritable gains in milk production, growth, fertility, disease resistance and environmental adaptation. This chapter explains how artificial intelligence complements conventional phenotypic and pedigree-based selection by analysing large genomic and performance datasets. Machine-learning models reveal genotype-phenotype relationships, predict breeding values and support earlier, more reliable selection. Applications include genomic selection, precision breeding, reproductive technologies, bioinformatics and digital twins. AI can reduce generation intervals and improve the efficiency of breeding programmes, but its success depends on data quality, representative populations and interpretable models. Ethical concerns, genetic diversity and long-term sustainability must also be considered when designing AI-supported breeding systems.

Currently, the milk production of country is 221.06 million tonnes (2021 22) and the target is 300 million tonnes by 2023-24. The livestock sector contributed nearly 5.21% of total gross value added (GVA) and 28.36% of the agriculture and allied sectors GVA. Thus, there is a huge gap between demand and supply, therefore with the requirements of better yield from the dairy animals, we need more better and advanced options. Artificial intelligence (AI) is one of such options which can be exploited in dairy industry. Artificial Intelligence can be a game-changer for the dairy farming in India and it can emerge as a tool that empowers farmers in monitoring, forecasting as well as optimizing the farm animal growth. It can predominantly change the scenario of dairy farmers by maintaining the health, physiological and physical conditions of dairy-cows. This knowledge-based technology has a huge potential and could confront the loopholes in dairy farming and thus indirectly can strengthen the dairy industry. In dairy farming AI has multiple applications like monitoring the activities of the dairy-cows, boosting the milk production and farm productivity, detection of mastitis in dairy-cows and developing the smart cow houses powered by image analysis.

AI enables the dairy farmers to determine whether the cow is ill, ready to breed or has become less productive. The AI also sends alerts to the farmer about the change in the cow’s behavior allowing human intervention where needed. Regular 24x7 monitoring of dairy animals is the key for successful dairy farming, however, traditional methods of monitoring relied on visual observation, but it was not very efficient due to the lack of time and human resources. Without AI, it would be almost impossible for the farmer to keep a watchful eye on every cow in the herd. Artificial Intelligence components of the dairy automation system process the collected data to provide insights on the heat stress, change in feeding efficiency and the estrus of the cow. Diseases like sub-clinical mastitis, one of the more common diseases in the dairy industry, cost the Indian dairy industry one billion dollars annually. Eventually, it provides new hope and open prospects for the overall quality and progress in the dairy industry through a profitable business approach in dairy farming

Various indicators like range of behavioural, physiological, pathological and carcass-quality parameters can be used to assess the welfare of animals. Whenever, animals undergo painful handling or any other managerial operation, they are likely to face short-term stress. In this condition an increased physiological responses, behavioural responses, injury or mortality are most commonly used; however, some animals which are kept in improper housing with less floor space may cause chronic stress leading to increased disease incidence and suppression of normal development. Therefore, the following techniques can be used to assess the animal welfare at farm level in any given situation.

Assessment of nutrient requirements for ruminants is essential in order to maintain good health and optimal production levels in these animals. Ruminants have a unique digestive system that allows them to digest plant-based feed, such as grass and hay, through a process called fermentation. This process produces volatile fatty acids which are then absorbed by the animal and serve as their main source of energy. Therefore, it is important to ensure that the diet provided to ruminants contains enough nutrients to support both their metabolic needs as well as their production demands. This assessment includes factors such as age, weight, stage of lactation or pregnancy, level of activity, and environmental conditions. In addition, the quality and quantity of available forage should also be considered when determining the nutrient requirements of ruminants. Proper assessment can help prevent deficiencies or excesses of certain nutrients which can lead to health issues and decreased productivity in these animals. Ultimately, by accurately assessing the nutrient requirements for ruminants, producers can develop appropriate feeding programs that promote overall well-being and performance in their herds.

Scientists rely on a variety of endocrine, behavioral, autonomic nervous system and immunological end points to measure stress. Unfortunately, none of these measures has proved to be a litmus test for stress. Increased secretion of the adrenal glucocorticoids and cortisol has been found to be associated with stress and investigators frequently cite an increase in circulating cortisol as a proof of stress. Colborn et al., (1991) found that stallions secreted similar amounts of cortisol whether the stallions were restrained, exercised or permitted to mate with a mare. Serum cortisol concentrations are often used to evaluate stress, but due to the marked variability, faecal corticosterone has been used to evaluate stress in cattle (Morrow et al., 2002). Dairy cattle secrets cortisol during restrained and when approached by strangers. So it is difficult to simply use secretion of cortisol or any other hormone to differentiate between non threatening stress and distress. Further, complicating is inter animal variability in stress response. Even among the same breed some cows may produce more cortisol to the same amounts of thermal stressors.

Withania somnifera, also known as Ashwagandha, Indian ginseng, Winter cherry, Ajagandha, Kan-aje Hindi, Amukkara in Tamil and Samm Al Ferakh, is a plant in the Solanaceae or nightshade family.

Grasshoppers : Trilophida an- nulata : Acrididae

The nymphs and adults of this grasshopper feed on the margins of leaves of Aswagandha. It is only a minor pest, nibbling on the leaves.

The potential of atomic absorption spectrometry/spectrophotometry/ spectroscopy for determination of metallic elements was first realized by Alan Walsh during 1950. The standard equipment termed as atomic absorption spectrometer/ spectrophotometer (AAS) has now gained a reputation in the field of analytical chemistry for determination of very small concentrations of metallic elements and metalloids. As little as 0.01 ppm of many elements can be determined through this tool. Recently, the Zeeman background correction technique has further enhanced the quality of the results obtained from the flame-less graphite furnace atomizer. Combining the very latest in AA technology with the most powerful computing and software available many manufacturers have developed several designs/models of AAS based on flame or flame-less technique.

Introduction

The first application of atomic absorption spectra to chemical analysis was made just over 100 years ago by Kirchoff (1860), who demonstrated the presence of various elements in the solar atmosphere. He and Bunsen, demonstrated shortly afterwards that atomic spectra, whether in emission or absorpiton, could be the basis of a powerful method of chemical analysis. Walsh (1955) recognized the potential advantages of the absorption method over emission method and devised simple and versatile apparatus applicable to the routine analysis of solutions of a wide range of elements. Alkemade and Milatz (1955) published papers describing the application of atomic absorption  techniques to chemical analysis.

Audio-visual aids may be defined as any device used to aid in the communication of an idea. An audiovisual product is any audiovisual item such as still photography, motion picture, audio or video tape, slide or film strip, that is prepared singly or in combination to communicate information or to elicit a desired audience response. Even though early aids such as maps and drawings are still in use, advances in the audiovisual field have opened up new methods of presenting these aids, such as videotapes and other equipments which allow more professional and entertaining presentations to be presented.

Such aids assist the teacher in communicating information among the learners leading to change in skills, attitudes, knowledge, understanding and appreciation. These aids stimulates the sensory organs like ears, eyes, etc and facilitates quick understanding of the message by the audience. The effective use of these aids depends upon the skillful and imaginative approach of the teacher. Hence, it is necessary that extension worker should know what type of aids will be more suitable for a particular teaching objective. These aids may be used for both literate as well as illiterate people.

The instructional devices through which the messages can only be heard are known as Audio Aids. The instructional devices through which the message can only be seen are known as Visual Aids. The instructional devices through which the message can both be heard and seen simultaneously are known as audio-visual aids.

A mill is a device that breaks solid materials into smaller pieces by grinding, crushing, or cutting. Such communition is an important unit operation in many processes. There are manydifferent types of mills and manytypes of materials processed in them. Historically, mills were powered by hand (e.g., via hand cranks) working animals (horsemill), wind (wind mill) or water (watermill). Today they are usually powered by electricity and are controlled by computer (automatic mills).

The grinding of solid matters occurs under exposure of mechanical forces that trench the structure by overcoming of the interior bonding forces. After the grinding, thestate ofthesolid is changed:thegrain size, thegrain size disposition and the grain shape.

Milling also refers to the process of breaking down, separating, sizing, or classifyingaggregatematerial. For instance rock crushingor grindingto produce uniform aggregate size for construction purposes, or separation of rock, soil or aggregatematerialforthe purposesofstructural fillor land reclamationactivities. Aggregate milling processes are also used to remove or separate contamination or moisture from aggregate or soil and to produce “dry fills” prior to transport or structuralfilling.

Grinding may serve the following purposes in engineering: • Increase of the surface area of a solid

• Manufacturing of a solid with a desired grain size

21.1 Automatic Weather Station

Automatic Weather Station, popularly known as AWS, is an electronic device and an automated version of the traditional weather station. Numerous weather sensors are connected to the system which automatically records and stores weather data. It is quite useful in remote areas where no frequent access is possible. The system requires hardware as well as software to log in, store, display, retrieve and analyze the data. The digital data recorded from AWS can be downloaded to the laptop through the memory device. The same digital data can be converted to the actual values indicating various weather parameters through the software provided along with the AWS. It should be also maintained in the desktop of PC/AT so that the data are doubly assured. Every AWS has its own software depending upon the manufactures. Time interval can be fixed for recording weather data depending upon the purpose since it is a continuous recorder. Continuous AWS data are integrated at hourly or half-hourly interval for monitoring weather data, otherwise enormous data are continuously stored and no way are used. Of course, continuous weather display is possible for monitoring weather conditions spatially and temporarily.

Automatic Weather Station consists of a datalogger, rechargeable battery, telemetry (optional) and the meteorological sensors with an attached solar panel. The system may report in near real time via GPRS or save the data for later recovery. Majority of automatic weather stations possesses normally Thermometer Sensor for measuring temperature; Anemometer for measuring wind speed; Wind vane for measuring wind direction; Hygrometer for measuring relative humidity; Barometer for measuring atmospheric pressure; Rain gauge for measuring rainfall and Pyranometer for measuring solar radiation. Automatic weather stations are based around a programmable datalogger that measures the sensors, then processes, stores, and transmits the data. Dataloggers have wide operating temperature ranges, on-board instructions, programmable execution intervals and input channels for commonly used sensors. Wind vector, wet bulb, histogram and sample on maxima or minima are standard in the datalogger instruction sets. Most sensors can be measured directly without external signal conditioning. Data are typically viewed and stored in the units of your choice(e.g., wind speed in mph, m/s, knots). Measurement rates and data recording intervals are independently programmable, allowing calculation of 15 minute, hourly, and daily data values from 1 minute or 1 second measurements, for example. Conditional outputs, such as rainfall intensity and wind gusts, can also be recorded. The program can be modified at any time to accommodate different sensor configurations or new data processing requirements.

Livestock farms

The veterinarians can start their own livestock farms with their vast technical knowledge; they can infuse scientific management techniques in their own farms. In the WTO (World Trade Organisation) era, GMP (Good Manufacturing Practices) and SPS (Sanitory and Phytosanitory) measures are of great importance for export of livestock commodities, as the emphasis in international trade is on quality and food safety. If veterinarians start their own scientifically managed livestock enterprise, they can exploit this opportunity. Further, practicing proven scientific management techniques will improve productivity of animals that would lead to overall quantitative and qualitative improvement of livestock sector.