In order to fulfill the rising food demand, great emphasis is being given to efficient farming through automation in the field and need-based resource management in farm operations to improve crop productivity. Though the scientific advances help us in understanding the crop, soil, weather, and in what conditions it can grow better, some aspects of agriculture can become more efficient by monitoring and predictive analysis for understanding the accurate status of crops, input requirements, and possible yield output. Artificial Intelligence (AI) and remote sensing can help us in this area. AI and advanced satellite imagery, along with weather forecasts provide a unique dataset that allows prediction of harvest, tracking the presence and spread of pests. This improves crop productivity, address food production issues without degrading environment, enhance farm incomes and can help tackle climate change effectively.
Written by Dr. Shivendra Bajaj, Executive Director, Federation of Seed Industry of India and Alliance for Agri Innovation
Dr Shivendra Bajaj
At present, there are several challenges that the agriculture sector is facing. Increase in production cost, lack of required water for irrigation, higher labor cost, fall in farm remuneration, frequent incidences of droughts and floods due to climate change are some of the major issues. To make it worse, the ongoing Covid-19 pandemic has disrupted the food production system and supply chains significantly.
India has seen rapid adoption of technological innovations in the agriculture sector in the recent past. Also, internet services are penetrating the rural areas at a fast pace. This sounds encouraging for the propagation of Artificial Intelligence-based tools for better farm management. One such example is AI tool being used to regulate water flow intelligently and prevent unrequired dampness in soil and thus rules out the possibility of pests that thrive under excessive moisture.
Precision choices
AI enables farmers to carry out farming activities with great precision as they can make informed choices on deciding the right crops and the right process to cultivate for better returns. Higher yields, healthier crops, effective pest control, soil monitoring are some of the major benefits. Artificial intelligence in agriculture involves sensors, robots, and drones to collect different kinds of information and perform tasks such as weeding, irrigation, spraying pesticides, and fertilizers without human intervention. The greenhouse emissions are decreased by 20 percent thanks to new ways of farming AI brings in. This is a significant contribution to the efforts being taken to cut carbon emissions.
At present, a major obstacle farmers face is a lack of timely and accurate data. Remote sensing, which gives valuable insights into various agronomic parameters, and AI facilitate farmers to micromanage standing crops by taking into account the weather conditions, market dynamics. These technological interventions capture green data from multiple sources, analyze it and turn into valuable insights to help stakeholder use fewer resources, manage farming activities accurately and efficiently.
The adoption of AI has so far been driven primarily from a commercial perspective thus we need to focus on how to benefit the agriculture sector at a large scale. NITI Aayog has sought to embrace AI to reduce our dependence on resource-intensive farm practices in order to boost agriculture value chain. There has been substantial rise of agricultural tech start-ups in the past few years. Yet, the adoption of AI has remained limited. NITI Aayog has narrowed down on some problem areas such as difficulty in access to data, high cost and low availability of computing infrastructure, lack of collaborative approach and public awareness.
Agriculture as a backbone
There is no doubt that agriculture is the backbone of India and supports the livelihood of over 50 percent of India’s population. Besides ensuring food security, the demand for healthy, chemical-free food from consumers, which is produced in a sustainable manner, all require the digital transformation in the agriculture sector. What we need to do is to ensure the availability of affordable hardware such as sensors and other communication devices, farm machinery, and equipment and software. Similarly, agriculture research institutes, universities must extend their support, build expertise and create awareness for the adoption of AI and remote sensing in agriculture. One such University in Andhra Pradesh, Acharya NG Ranga Agriculture University (ANGRAU) is using drones in the agriculture sector for various agri related activities. The university is now urging farmers to use drone technology to minimize the input cost on agriculture workers apart from effective practices of seed sowing and spraying pesticides. More colleges and universities should follow this suit.
We will have to start with building AI-enabling infrastructure that has region-specific, crop-specific databases. It will be followed up by capacity building and training of farmers on digital technologies including AI and remote sensing. These technologies may not be affordable to individual farmers so in such cases intermediaries such as FPOs or start-ups can address the problem. Using technology for efficient resources usage, we can achieve higher yields.