Introduction
Agriculture plays a growing and going role in everyone’s life and the economy at large. Its importance for an individual can be as his/her livelihood, for the country, its economy, and as a means of survival for the human hood. Agricultural exports account for 10% of India’s total exports and are the country’s fourth-largest exported major commodity category. Agriculture is so important, yet this low output-to-input ratio reveals massive systemic problems in India’s agronomy, causing considerable misery for agriculture and allied labourers who face the impact of growing input costs, diminishing productivity, climate variability, resource depletion, inadequate market access, technological immobility, and so on. The agriculture sector is increasingly looking at methods to harness technology for improved crop yields in order to stimulate innovation and entrepreneurship in agriculture. Technological advances are helping to boost agriculture overall productivity much further. AI and other disruptive technologies are having a significant positive impact on Indian agriculture.
While India’s farming crisis requires attention on numerous levels, this article stresses the importance of innovation – specifically, artificial intelligence (AI) – in raising agricultural productivity and, as a result, farmer livelihoods.
PepsiCo’s entry
In 1989, PepsiCo set up a Tomato processing plant in Hoshiarpur, Punjab. The company planned to make packed tomato ketchup and for that, they required good quality tomatoes. When the company executive researched the Indian tomato market, they found that it is challenging to get their required homogeneous quality of tomatoes from the market as every farmer grows a different variety and quality of tomatoes at the farm.
Impact of Artificial Intelligence on the Agriculture Sector
Artificial intelligence in agriculture is divided into three categories: robotics, soil and crop management, and livestock farming. Its goal is to make farming simpler, more precise, lucrative, and fruitful for farmers. The global AI in the agriculture market was worth US$ 240 million in 2017 and is predicted to grow to US$ 1.1 billion by 2025. In addition, challenges like population expansion, climate change, and food security necessitate novel approaches to increasing crop output. As a result, comprehending AI’s application in agriculture becomes essential. By 2050, the globe will have to grow 50% more food. To accommodate this goal, unfortunately, only 4% of extra land will be put under production. At a time where the global needs to produce more food with fewer resources, AI has the potential to drive an agricultural revolution. Essential Artificial intelligence in agriculture at various phases of the agricultural process can pay off for farmers in terms of increased profitability and revenue.
AI in Indian agriculture has the potential to improve farm production, alleviate supply chain restrictions, and expand market access. It has the potential to benefit the entire agriculture value chain. By 2026, AI in global agriculture is expected to be a $4 billion opportunity.
Main Areas where AI can Benefit Agriculture
The Benefits of Using AI in Agriculture
Farmers may better grasp data insights such as temperature, precipitation, wind speed, and sun radiation by using artificial intelligence in agriculture. Data analysis of historical values allows for a more accurate comparison of planned results. The greatest part about deploying AI in agriculture is that it won’t take away human farmers’ jobs; instead, it will help them better their operations.
Given the advantages of artificial intelligence for sustainable farming, adopting this technology may appear to be a natural next step for any farmer. However, there are still some significant limitations.
Problems farms can face while adopting AI
Artificial intelligence expectations vs. reality for sustainable farming
The advantages of artificial intelligence in agriculture are apparent. Smart farming solutions can automate simple, repeatable, and time-consuming chores, allowing farm employees to focus on more strategic activities that require human intellect. It’s crucial to note, though, that, unlike a tractor, AI cannot be purchased and started. AI isn’t something that can be touched. It’s a collection of technologies that are automated through the use of the software.
Artificial intelligence is a computer simulation of thinking that uses data to learn and solve problems. AI is only the next stage in the growth of smart farming, and its successful implementation needs the employment of additional technologies. To put it another way, before farmers can gain the full benefits of AI, they will require a technological infrastructure. Infrastructure work will take months, if not years, to complete. Farmers, on the other hand, will be able to build a solid technology ecosystem that will last the test of time.
Conclusion
Farmers tend to think of AI as something that only applies in the digital world. They may be unable to see how it can assist them in working the real land. This isn’t because they’re fearful of the unknown or conservative. Their resistance stems from a lack of awareness of how AI tools can be applied in the real world.
For the time being, technology providers must consider a few things: how to enhance their tools, how to assist farmers in addressing their concerns, and how to communicate how machine learning can help solve real-world problems, such as lowering manual labour. AI’s future in agriculture is certain to be beneficial.
FAQ
Our AI/ML modules are trained with a credible secondary and primary database upon which we run the algorithm to create actionable insights and inputs for improving farming practices. This model can be trained for any crops provided that sufficient database (includes images) is available with you to provide high accuracy. KhetiBuddy does not take any responsibility or liability for variances in output in such cases, however we will provide support and guidance in order to help you train the model with right inputs.
The three most popular applications of AI in agriculture are:
Precision agriculture:using AI to analyze data from sensors, drones, and other sources to optimize crop production, reduce waste, and improve resource efficiency.
Agricultural robotics:using AI to develop autonomous robots and machines for tasks such as planting, harvesting, and crop monitoring.
Crop and livestock monitoring:using AI to analyze data from satellite imagery, cameras, and sensors to monitor crop growth and health, detect pests and diseases, and monitor the health and well-being of livestock.
The impact of AI on agriculture can be significant, including:
Increased productivity:AI can help farmers optimize their operations, improve decision-making, and increase efficiency, resulting in higher yields and greater profitability.
Improved sustainability:AI can help farmers reduce their environmental impact by improving resource management, reducing waste, and promoting sustainable practices.
Better crop quality:AI can help farmers monitor crops more effectively, detect issues early, and take corrective action, resulting in better crop quality and higher yields.
Improved animal welfare:AI can help farmers monitor animal health and behavior, detect issues early, and take preventive action, resulting in improved animal welfare.
Enhanced food safety:AI can help identify potential risks in the food supply chain, such as contamination or spoilage, and help prevent outbreaks of foodborne illness.
Reduced labor costs:AI can automate repetitive or time-consuming tasks, such as monitoring crops or livestock, reducing the need for manual labor and potentially lowering labor costs.Overall, the use of AI in agriculture has the potential to improve efficiency, productivity, and sustainability, leading to greater food security and economic growth in rural communities.
In India, AI is being used in agriculture in several ways, including:
Crop monitoring:AI-powered drones and satellite imagery are being used to monitor crop health and identify areas that require attention, such as irrigation or pest control.
Weather forecasting:AI is being used to provide farmers with accurate weather forecasts, enabling them to plan their operations and reduce the risk of crop failure.
Pest and disease detection:AI is being used to detect pests and diseases early, allowing farmers to take timely action and minimize crop damage.
Soil analysis:AI-powered sensors are being used to analyze soil health and provide farmers with insights into fertilization and irrigation.
Market analysis:AI is being used to provide farmers with real-time information on market prices, helping them make informed decisions about crop selection and pricing.
Farm automation:AI-powered robots and machines are being used to automate repetitive tasks such as seeding, weeding, and harvesting, reducing the need for manual labor and potentially lowering labor costs.Overall, the use of AI in Indian agriculture has the potential to improve productivity, reduce costs, and promote sustainable farming practices, helping to address the country's food security challenges and supporting rural economic development.
AI is used in agriculture in various ways, such as crop monitoring, weather forecasting, pest and disease detection, soil analysis, market analysis, and farm automation. The use of AI in agriculture benefits several stakeholders, including:
Farmers:AI helps farmers improve productivity, reduce costs, and increase efficiency, resulting in higher yields and greater profitability.
Consumers:AI helps ensure food safety and quality by detecting contamination, spoilage, and other potential risks in the food supply chain.
Agribusinesses:AI helps agribusinesses make data-driven decisions and reduce risk, improving operational efficiency and profitability.
Governments:AI helps governments monitor and regulate agricultural practices, ensuring compliance with environmental and food safety standards.
The environment:AI helps promote sustainable farming practices by reducing resource waste and minimizing environmental impact.Overall, the use of AI in agriculture benefits various stakeholders and contributes to the goal of achieving sustainable, productive, and profitable agriculture.
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