Artificial Intelligence(AI): Future of Livestock farming in India
Applying artificial intelligence to modern animal husbandry and aquaculture technology can intelligently identify animals of different weights and stages, feed differently, and improve the output rate of high-quality feeding animals. With the huge growth in the world population, the farmers are transferring to smarter techniques that can aid in regulating the appropriate use of land, water, and energy to feed the planet and elude the global food disaster. Researchers believe that the answer lies in sensors, robots and artificial intelligence. The AI technology has been successfully adopted by several industries, and now it is set to revolutionize the future of farming with drones, robots and intelligent monitoring systems. A technique for monitoring the health of farm animals and dairy cattle with a high degree of accuracy uses a camera and artificial intelligence (AI) to achieve a “smart” cow house. AI for detailed observation, powered image analysis could enable early detection of injuries and illnesses that could impact the quantity and quality of milk production. In the recent times, with requirements of the better yield of farm animals. Various uses of AI 1. Artificial Intelligence in automated milking: Milk booth is a section of animal husbandry which has an increasing application of artificial intelligence system. With AI enabled smart sensors, the automated milking units can analyze the milk quality and flag for abnormalities in the product. 2. Precision livestock farming: Latest Dairy is implementing cow, milk and herd intelligence through their sensors and artificial intelligence technologies. They offer sensors ranging from heat detection and calving to health monitoring sensorsincluding the Sense Time Solution sensor, which detects and charts a cow’s daily activities, such as ruminating, eating and walking patterns. Today, there are numerous sensors available that can help farmers track alterations in animal movements, food intake, sleep cycles and even air quality in animal shelters. When paired with artificial intelligence software, this sensor provides users with early, proactive solutions to problems. Along with the capability to record information about reproduction, health and nutrition, the sensor also provides farmers with solutions for each individual cow. 3. Artificial Intelligence for health monitoring: The AI also sends alerts to the farmer about the change in the cow’s behaviour allowing human intervention where needed. Without AI, it would be almost difficult for the farmer to keep a attentive eye on every cow in the herd. By using advanced AI and machine learning algorithms to predict deviations or abnormalities, farmers can now identify, predict and prevent disease outbreaks, even before a large-scale outbreak. 4. Artificial Intelligence for Detection of Oestrus: The collar (with motion sensors) tied to on the cow neck for collects all types of data related to cow 24 hours a day. 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 oestrus of the cow. The occurrence of oestrus cycle results in the release of special hormones that affect the cow’s behaviour and movement. 5. Robotic System to Deliver Vaccines: For a sustainable economic future of dairy farms and to achieve 100 per cent compliance rate, modern dairy farms use a robotic injection system to deliver vaccines and reproductive medicines to domestic animals on the dairy farm. The robotic system is incorporated with a dairy automation system, now a day. The robotic injection system reads the RFID tags attached to the cow’s ear and gets health-related information and vaccination record for the cow. If the cow needs an injection, it is directed to the injection site and the injection mechanism position itself to deliver the medication in the cow’s neck. 6. Artificial Intelligence in food supply chain: Blockchain can connect all aspects of the supply chain from producer to consumer and allow for food traceability and safety. From an agriculture and food perspective, proposing this type of evidence to consumers will become a competitive advantage and may not prove as challenging in dairy as in other areas of agriculture, such as beef, which exchanges ownership more frequently. 7. Artificial Intelligence in data collection: Previously, collected data was generalized for an entire dairy farm. Through the use of sensors, AI and other technologies can provide individual data for each cow, allowing farmers to improve precision and accuracy when making managerial decisions. 8. Artificial Intelligence in improvement of feed quality: With the use of robotics is quite efficient and speeds up harvesting time, when compared to traditional harvesting by hands. Moreover, the automated machinery indefinitely calculates moisture in the cereals harvest as well as overall yield.
- Improving animal health using facial recognition systems: Several useful applications, such as helping us learn more about the animal’s emotional and attentional state. For example, by studying the ear and eye movements of an animal, we can now understand its mood and excitement level with reasonable accuracy. It might help us regulate pain symptoms of animals. On further exploration, we may find injuries, diseases or even signal of predator attacks. 10. Gains in optimizing feed efficiency & energy intake: RGB-D camera can help farmers measure feed intake for individual cows and optimize feed expenses according to their animal needs. Technology can help us estimate performance of farm animals accurately. Their energy expenditure during lactation can be assesses based on parity, milk yield component, and body condition score.
The day is not far when a drone will knock your door step to deliver milk with the desired fat and SNF percentage. The milk composition will exactly match as per your health requirement. Technology has redefined farming over the years and technological advances have affected the agriculture and livestock industry in more ways than one. Agriculture is the mainstay occupation in many countries worldwide and with rising population, which as per UN projections will increase from 7.5 billion to 9.7 billion in 2050, there will be more pressure on land as there will be only an extra 4% of land, which will come under cultivation by 2050. This means that farmers will have to do more with less. According to the same survey, the food production will have to increase by 60% to feed an additional two billion people. However, traditional methods are not enough to handle this huge demand. This is driving farmers and agro companies to find newer ways to increase production and reduce waste. As a result, Artificial Intelligence (AI) is steadily emerging a part of the agriculture industry’s technological evolution. The challenge is to increase the global food production by 50% by 2050 to feed an additional two billion people.AI-powered solutions will not only enable farmers to improve efficiencies but they will also improve quantity, quality and ensure faster go-to-market for crops and livestock products.
Basically, machines powered by Artificial Intelligence can not only act, but also understand and analyze. It has the potential to revolutionize human lifestyle. As a matter of fact, AI is still at a very nascent stage and the opportunities it could unravel, is still ambiguous. It is projected that eventually, AI will bring about qualitative progress and innovation, enhancing individual and societal well-being and the common good.Introduced in the 1950s, many AI methods have been developed or extended recently with the improvement of computer performance. Recent developments have been fueled by the interfaces created between AI and other disciplines, such as bio-medicine, as well as massive data from different fields, particularly those associated with healthcare. We are moving from the information era to artificial intelligence era. It is not data or information that will be used but the intelligence extracted from data to build solutions for the common citizens’ use. The strengths we have in India are that we have a vast IT talent pool, freedom from legacy assets, highest rate of data consumption and growth and rapid digitization across sectors. We need a significant focus to exploit this technology for disruptive growth to move from the existing economy to the new digital economy. Being one of the few global economies to have implemented and perfected automated AI processes across diverse sectors, India is definitely leading in the AI usage trends. As per a study by Salesforce, India ranks third after Singapore and Hong-Kong in the Asia Pacific region, in terms of artificial intelligence readiness
Businessmen looking to invest in the Livestock industry have noted the increased spending power of the consumers and their willingness to pay a premium in order to have fresh and hygienic livestock products. As a result, it is expected that there will be investments made in this sector which will aid the introduction of technological advancements both in logistics and farm management. AI is one such technology which needs immediate implementation in the livestock industry. AI will help livestock farms accumulate and analyze data to accurately predict consumer behavior, like buying patterns, leading trends, etc. With increased investments, farms will be enabled to automate processes, reduce major costs and improve the quality of livestock products like milk. Artificial Intelligence, will be a disrupting inclusion into this industry. Today local farmers and large dairy farms use fodder without much understanding of its impact on the milk. Changes in the fodder content and lifestyle of the animal, the weather and atmosphere, all of it have an impact on the production of milk and the quality as well.As Artificial intelligence and machine learning become more common and easily available, it is expected, that the use of such technology in the dairy industry will automate most of the farm processes while at the same time produce information based on the farm’s operational history.Researchers believe that the future is in sensors, robots and artificial intelligence (AI).
The AI technology has been successfully adopted by several industries, and now it is set to revolutionize the future of farming with drones, robots and intelligent monitoring systems.A technique for monitoring the health of farm animals / dairy cattle with a high degree of accuracy uses a camera and artificial intelligence (AI) to achieve a “smart” cowhouse. Detailed observation by AI-powered image analysis could enable early detection of injuries and illnesses that could impact the quantity and quality of milk production.Have you ever thought how emerging technologies will affect agriculture in the long run to optimize management and profitability? We have seen the implementation of robotic milking machines, brushes for added cow comfort, and automatic calf feeders on dairy farms across the country and world. But, imagine a data system that monitors your cows’ activities 24 hours a day, 7 days a week from lameness and estrous detection to dry matter intake (DMI). With a new technology that recognizes each cow in the barn, this dairy farmer’s dream becomes a reality.
In the recent times, with requirements of the better yield of farm animals, AI has emerged as a tool that empowers farmers in monitoring, forecasting, as well as optimizing the farm animal growth. Tackling parasites, biosecurity, and diseases, monitoring farm animal along with farm management are some of the thrust areas in livestock industry where the use of AI technology can pay rich dividends.There is a school of thought that associates AI with a dystopian future, where machines will take over or completely replace humans. However, countering such theories, there are others who believe AI to be a revolutionary technology that has immense potential, if used vigilantly and appropriately.No doubt Artificial intelligence is the future.
As we learn more about the diverse value of AI today, we envision self-driving cars and robots put to use to improve our human lives. Yet animal welfare is another valuable area of application to appreciate. Animal farming is becoming a data-centric business. AI in animal husbandry is used for raising animals for meat, fiber, milk, eggs and other products. With AI, providing day-to-day care and raising livestock has become easier for animal farmers. For example, farmers are making use of wearable AI devices to collect real-time data about them to make necessary decisions. The wearables are helping farmers to get important alerts like when their animals are sick, when they should be vaccinated and when they are ready for insemination. There are numerous ways that AI and machine-learning algorithms are now used to benefit the animal husbandry industry.
How farmers can leverage the use of AI in animal husbandry
The core focus of a farmer in animal husbandry is to improve animal welfare, improve the efficiency of end products and create better production monitoring. Let’s explore how AI in animal husbandry helps to achieve these objectives.
AI in Dairy Farm Barns
Milk production per cow is a metric that is well tracked in a dairy farm, but there are bigger questions that need to be asked to maintain the production levels. The feed is the most important factor that affects the production level of a cow. AI systems can provide accurate monitoring of the amount of feed that is provided to the cow and help to increase the production level. For example, there’s an application that uses a motion-sensing device to transmit the movement of the cow to an AI-driven system. The sensor data, when aligned with real-world behavior, can help the AI system detect when the cow is walking, drinking or eating. Small dairy barns can be easily taken care of, but when it comes to huge barns, it becomes impossible to keep up with every cow on an individual basis. With facial recognition, AI can help identify each cow uniquely. Unique identification of cows helps farmers provide better treatment to the cows.
AI in Meat Farming
Meat is a major source of dietary protein around the world. Cattle, sheep, pigs and goats are the main species involved in consumption as meat. Pigs can produce up to 11 piglets a year. Based on the numbers tattooed on the flanks of the pigs, AI systems can monitor vulnerable piglets for squeals of distress. An AI system is also being used to recognize facial expressions to detect if a sheep is in pain. The seriousness of the pain can also be determined by the system. The AI system detects different parts of a sheep’s face and compares them with standardized facial patterns provided by veterinarians to diagnose the pain.
Robots can be used to debone an animal to optimize the amount of meat produced. A robot can analyze the difference between the density of the meat and bone, thereby making the most accurate cut possible.
AI in Poultry Farming
Like humans, even animals suffer from nutritional deficiencies. AI machines can help identify the decreased growth of a chicken. The machines can be trained to differentiate between healthy and infected chickens. AI-enabled robots can help poultry farmers in many ways. Robots can do repetitive work like feeding birds, collecting eggs and removing manure. Tasks like collecting, counting and packing eggs are becoming completely automated, reducing the need for close supervision by humans. Another task that a robot can perform is shifting a hatched chick from a broiler shed to the layer shed. Robots can also keep the birds moving for an added health benefit. Thus, a robot can perform various duties for poultry farming and prove to be a cost-saving attribute to the farmers. AI systems can monitor the environment of a shed and adjust conditions accordingly. AI systems can determine the accuracy of fertility in the early stage of incubation. AI can first learn which eggs are fertile and which are not by scanning the eggs, and then algorithms can be created that can determine the accuracy of fertility.
AI in Insect Farming
Edible insects are becoming a growing part of food production because insect farming can help to meet future demand for protein consumption. Bees have been kept in hives and humans have been harvesting honey for a long time. Sensors can be incorporated in hives to monitor hive weight, temperature and humidity. AI systems have been developed that can track the sound waves made by a swarm of bees and can anticipate future changes to the swarm. With the help of anticipation, a beekeeper can plan for the swarm changes ahead of time. Insects such as crickets like it hot (90 °F) and humid (50-90%) and need different temperatures and humidity over their lifetimes. AI systems that allow artificial environmental changes with voice commands can be useful in growing insects like crickets. The AI system can provide features like analytics on smartphones, and alerts for temperature increases. Detecting the perfect breeding time can be achieved through AI monitoring. Companies in China are breeding 6 billion cockroaches a year with the use of 80 different types of big data being collected by AI systems. The cockroaches are then used as an ingredient for medicine that cures stomachaches and other ailments.
AI in Aquaculture
Fish are being depleted faster than they can be generated. The use of AI in aquaculture provides actionable insights to optimize the expenses on fish farms. Fish farms provide half of all the fish for human consumption. Free-floating aquapods are used for farming fish. The aquapods can accommodate thousands of fish. However, what happens when the aquapods need repair? To repair the aquapod manually is a time-consuming task. However, robots can complete the task of repairing aquapods in a safer and more cost-effective way. Underwater robots can easily examine and repair the nets of aquapods. Drones can provide applications for aquaculture both above and beneath the water. Monitoring offshore fish farms and inspecting underwater nets for damage and holes can be easily done by drones. Drones can also provide fish stock information and track environmental changes.
Sensors can be used in aquaculture to collect data such as oxygen levels, pH, salinity and pollution level of water. Detection of the hunger level of the fish by sensors can help farmers or even robots to feed them accordingly. Automated recirculation systems can circulate the water according to the information collected by sensors.
The consumption of animals and animal goods is increasing. The increased demand can be fulfilled by increasing the productivity and longevity of the animals. Therefore, the animal healthcare market size is demonstrating tremendous growth. The animal healthcare market size is expected to grow up to $69.44 billion by 2026, with a CAGR of 5%.
AI in animal husbandry can help detect symptoms of any disease in animals by monitoring the daily behavior of the animal. For example, a drone can be used to collect images of the animal throughout the day. The images can then be fed into the AI machine to determine any behavioral changes. AI can help recognize a disease at an early stage and help provide better treatment to the animal. Thus, AI is not only improving the health of humans, it’s also helping improve the medication and health services provided to animals.
Fast forward and imagine we are in 2030. Somewhere in the world, a pig farmer wakes up and opens a personal assistant on their smartphone. Still in bed, they already know whether anything extraordinary happened in their automated barn overnight. Way before breakfast, this farmer checks information collected in real time, processed and analyzed. They can access an accurate panorama of current conditions, define their priorities for the day and optimize time management. Picture this: full understanding of every animal movement, feed and water consumption, unusual activity levels or any increased coughing. An increased respiratory distress that eventually triggered an automated rope-sample taking for advanced diagnostics. How about having results of those samples already available? This future vision is possible – all thanks to Boehringer Ingelheim’s integrated health management services.
This efficient future is actually happening right now. Digitalization is coming to farms all around the world in an expanding veterinary digital market, which is expected to be worth US$ 4.6 billion by 2024. Tools such as microphones, cameras, sensors, data sets and mobile devices are no strangers to a swine team eager to bring this connected scenario to life. Artificial intelligence is just one technology among others to be used in order to push the industry from simple prevention to prediction… and beyond!
“What we are delivering is an increased support in decision-making and automation, and information transparency for suppliers and consumers,” explains Stephan Lange, Global Head of Swine. “Actually it’s even more. We are not merely preventing disease; we are building the capacities to precisely predict diseases – and better still ensure that the pigs stay healthy in the first place.”
Precision livestock farming: the fourth Industrial Revolution
Market research suggests a few trends. Not only are farms becoming larger and driven to reduce costs and improve competitiveness, but also societal concerns are playing a bigger role in shaping the future of precision livestock farming. Together with an increasing demand for animal protein, there are equally growing concerns on the environmental footprint left behind – and vocal pleas for more transparency about animal welfare.
Artificial intelligence, data collection and monitoring in real time offer solutions to these issues. That is why Boehringer Ingelheim Animal Health’s teams are working towards bringing integrated health management systems to the market, able to provide smart identification and tracking of the animals: smart sensing and detection to record data; analysis platforms and even smart dosing mechanisms.
“Integrated health management is embedded within precision livestock farming, which is animal agriculture’s version of the fourth Industrial Revolution. It is about integrating smart technologies, hardware, software and intelligent analytics into the daily routine of livestock protein production businesses,” shares Dale Polson, Global Technical Manager, Diagnostics and Monitoring. “All of these technologies serve one overriding purpose: to enable more informed, more confident and real-time decision making; both in the barn and the farm management.”
Collecting data to improve farming efficiency
No good decision-making occurs without reliable data. As connected barns and services are increasing new data streams across the swine production chain, it becomes easier for producers to identify potential health issues, better manage farm resources, and increase efficiency in both costs and quality. Moreover, these tools add transparency to final customers interested in knowing more about the meat they consume.
Big chunks of important information can be clustered into three core areas: barn data, health data and genetic data. Under barn data, producers can evaluate factors such as feed, temperature and piglets’ movements. Health data relate to developments such as coughing, body temperature and disease diagnosis. By combining clinical signs and pathogen detection, herd veterinarians can make better-informed decisions. Finally, genetic data, which provide insightful information on the origin of the animals, from which parents and which farms, in order to map previous breeding and eventual problematic outcomes.
Integrated health management system for sustainability and animal well-being
Artificial Intelligence will analyze complex data from all these sources to detect trends, signals or actionable information to support those making daily decisions on the farm. By using an integrated health management system, pork production can deliver better outcomes. For the farmer, in terms of a more predictable and profitable enterprise. Pork consumers have the confidence of transparent and verifiable sources of their food. The planet also wins, as precious resources are managed sustainably – and most importantly: pigs under our care can live with their well-being put at the center of a fully integrated farm.
The agriculture sector, currently valued at US$ 370 billion, is one of the major sectors in the Indian economy. According to the Economic Survey 2020-21, GDP contribution by the agriculture sector is likely to be 19.9% in 2020-21, increasing from 17.8% recorded in 2019-20. Over the years, the government has taken major steps to aid and enhance the agriculture sector with proven farming technologies and supportive policies. The recent evolution of digital technology in farming will further accelerate growth by ensuring higher crop yields and enhance sustainability by reducing water consumption and the use of agrochemicals.
Digital technologies, such as artificial intelligence (AI) and machine learning (ML), remote sensing, big data, block chain and IoT, are transforming agricultural value chains and modernizing operations. While several countries, such as the Netherlands, the US, Australia and Israel, have successfully adopted and exploited digital solutions to revolutionise agriculture, their adoption in India is still in its infancy. The future adoption of digital agriculture in India is anticipated to nurture under the Public-Private Partnership (PPP) mode.
Current Initiatives under Digital Agriculture in India
The demand for digitisation in Indian agriculture is well understood and acknowledged, likewise efforts have also been made towards digitising the prevailing value chain.
In September 2021, the Union Minister of Agriculture & Farmers Welfare, Mr. Narendra Singh Tomar, announced the initiation of the Digital Agriculture Mission 2021–2025, while signing five memorandum of understandings (MoUs) with CISCO, Ninjacart, Jio Platforms Limited, ITC Limited and NCDEX e-Markets Limited (NeML), to forward digital agriculture through pilot projects. The Digital Agriculture Mission 2021–2025 aims to support and accelerate projects based on new technologies, like AI, block chain, remote sensing and GIS technology and use of drones and robots.
Cisco developed an Agricultural Digital Infrastructure (ADI) solution in August 2019, that enhances farming and knowledge sharing. This ADI is likely to play a vital role in the data pool that will be created by the Department of Agriculture under the National Agri Stack. The pilot project for this initiative will take place at Kaithal (Haryana) and Morena (Madhya Pradesh).
The Jio Agri (JioKrishi) platform launched in February 2020, digitises the agricultural ecosystem along the entire value chain to empower farmers. The core function of the platform uses stand-alone application data to provide advisory, the advanced functions use data from various sources, feed the data into AI/ML algorithms and provide accurate personalised advice. The pilot project for this initiative will take place at Jalna and Nashik (Maharashtra).
ITC has proposed to create a personalized ‘Site Specific Crop Advisory’ service to turn conventional crop-level generic advice into a personalised site-specific crop advisory for farmers, using a digital crop monitoring platform, hosted on ITC’s e-Choupal 4.0 digital platform. The pilot project for this initiative will take place at Sehore and Vidisha (Madhya Pradesh).
The Ministry of Agriculture & Farmers Welfare has developed major digital applications in order to boost technology adoption among farmers: –
- National Agriculture Market (eNAM): – Launched in April 2016, the National Agriculture Market (eNAM) is a pan-India electronic trading portal that links the existing Agricultural Produce Market Committee (APMC) mandis, to create a unified national market for agricultural commodities. eNAM helps farmers sell products without the interference of any brokers or mediators, by generating competitive returns from their investment
- Direct Benefit Transfer (DBT) Central Agri Portal: – Launched in January 2013, the DBT Agri Portal is a unified central portal for agricultural schemes across the country. The portal helps farmers adopt modern farm machineries through government subsidies
In June 2021, The Ministry of Agriculture and Farmers Welfare signed an MoU with Microsoft to run a pilot programme for 100 villages in 6 states. Under the MoU, Microsoft will create a ‘Unified Farmer Services Interface’ through its cloud computing services. This is a major part of the ministry’s future plan to create ‘AgriStack’ – a unified platform to provide end-to-end services across the agriculture food value chain to farmers. For this the government is planning to create unique farmer IDs for farmers across the country to integrate it with various government schemes and create digital agricultural ecosystems.
Future of Digital Agriculture in India
Application of Digital Agriculture
Technological interventions based on remote sensing, soil sensors, unmanned aerial surveying and market insights, etc., permit farmers to gather, visualise and assess crop and soil health conditions at different stages of production, in a convenient and cost-effective approach. They can act as an initial indicator to identify potential challenges and provide options to deal with them in a timely manner.
Artificial Intelligence/Machine Learning (AI/ML) algorithms can generate real-time actionable insights to help improve crop yield, control pests, assist in soil screening, provide actionable data for farmers and reduce their workload.
Blockchain technology offers tamper-proof and precise data about farms, inventories, quick and secure transactions and food tracking. Thus, farmers don’t have to be dependent on paperwork or files to record and store important data.
Benefits of Digital Agriculture
Implementing these technological solutions enable reliable management and monitoring of farms. As farmers get a complete digital analysis of farms in real-time, they can act accordingly and don’t have to apply excess pesticides, fertilizers and reduce overall water consumption.
Other benefits include: –
- Increases agriculture productivity and lowers production cost
- Inhibits soil degradation
- Lessens chemical application in crop production
- Promotes effective and efficient use of water resources
- Uplifts socio-economic statuses of farmers
- Reduces environmental and ecological impacts
- Augments worker safety
Implementation of Digital Agriculture in India
The main factor behind the gradual acceptance of digital farming in India is the prominence of segregated small-holder farms in the country, this complicates data gathering. Additionally, limited penetration of mechanisation tools and frequent natural calamities, like droughts, floods and excessive monsoon rains, have negatively impacted the deployment of digital solutions in the sector. Thus, a customised approach would be needed to implement digital agriculture to a typical Indian small farm, this can be later be scaled up and made available to many Indian farms. Following measures could be implemented to make digital agriculture a success in India: –
Low cost technology: – The average annual income of an Indian farmer is >US$ 1,000. This low income explains the precarious financial circumstances in which a typical farmer operates in India. Thus, lowering the cost of technology will help.
Portable hardware: – As typical Indian farms are small, plug and play hardware has a better opportunity in the Indian market. Also, agricultural land leasing is widely prevalent under various farming arrangements, therefore a farmer farming on a specific plot of land may move to another farm plot next season. In such scenarios, investing in portable equipment is better for farmers.
Renting and sharing platforms for agriculture equipment and machinery: – Owing to both constrained financial resources and small farm plots, opportunity exists for digital platforms that offer equipment renting and sharing services instead of outright purchases. A few agritech start-ups like Farmkart (rent4farm), EM3 AgriServices and Trringo, are already providing equipment rental services.
Academic support: – The local agricultural organisation and academic institutes regularly interact with farmers through various locally conducted programs and government initiatives. Training facilities provided by various academic institutes and agricultural organisations will improve digital adoption among farmers.
Conclusion
As the Indian Agriculture and Allied sector is on the verge of adopting modern technologies, such as IoT, AI/ML and agri-drones for unmanned aerial surveying, Indian and foreign agritech players can play a vital role in supplying these advanced technologies to farmers. Currently, there are few players in the market, but catering to ~267 million farmers in a country exhibits a huge opportunity for private and foreign entities to expand their footprint in the country. However, influential factors that will define the success of digital agriculture in India are technology affordability, ease of access and operations, easy maintenance of systems and supportive government policies.
Adopting a holistic ecosystem approach to address challenges faced by the Indian agriculture sector is of national interest, to achieve objectives, like doubling farmer incomes and sustainable development. Thus, a multi-stakeholder approach will be required for the wide-scale adoption of digital agriculture in India, with the government playing a key enabler’s role in the ecosystem.
We can conclude that artificial intelligence allows easy data entry on farm records, monitoring farm activities, analysing economic performance, improving animals’ health, improving soil richness. All these features and solutions endeavour towards ‘smart farming’. Artificial intelligence will use data to improve the quality and clarity of decision making across all levels of the agricultural industry. Artificial intelligence has the potential to be better than humans at determining if individual animals meet market specifications through forecast of individual animal condition. However, as more farms get connected to technology, artificial intelligence and sensing technologies will start playing a more crucial role in helping farmers see patterns and solutions to tenacious problems in the modern animal farming.
DR AMIT TRIPATHY, DIRECTOR
LIVESTOCKMART
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