The agricultural ministry has decided to use specialised agencies to carry out pilot studies to estimate crop yield at village/gram panchayat level using innovative technology, so that claim settlement of farmers under the existing crop insurance scheme may be accelerated. The move is also aimed at cutting down the cost of farming and increasing productivity, better prices for farmers, providing information and advisory services to farmers.
In this regard, the government has invited experienced agencies for pilot studies and has identified eight crops—paddy, soyabean, cotton, sorghum, guar, bajra, maize, and groundnut. Depending on yield estimation results, the scheme will be adopted in the Pradhan Mantri Fasal Bima Yojana (PMFBY) to quickly settle insured farmers’ claims. The studies will be done during the 2019 kharif (summer sown crop) season and the findings are to be delivered by mid-February 2020.
The technological methods to be employed in estimating the crop yield include the use of high spatio-temporal remote sensing data, unmanned aerial vehicles, machine learning, advanced intelligent crop simulation models, and artificial intelligence (AI).
The pilot project would be overseen by the Mahalanobis National Crop Forecast Centre (MNCFC), which is at present involved in crop yield estimation studies at district level covering over four-fifths of the agricultural area in the country.
Departure from Traditional Farming
Since ages, farmers have been dependent on monsoon rains, the failure of which has often resulted in suicides of farmers. Therefore, departing from the traditional farming, the government has decided to begin use of artificial intelligence (AI) on pilot basis for providing myriad benefits to farmers such as weather forecasting, crop and price forecasting, and crop yield estimation. Announced in July 2019, the attempt is to reduce the cost of farming, help in crop selection, ensure better prices for farmers and provide information to farmers, thus improving productivity.
Modi launched Prime Minister’s Crop Insurance Scheme, called Pradhan Mantri Fasal Bima Yojana (PMFBY), in February 2016, to provide comprehensive coverage to farmers against any crop failure. The scheme (i) covers risks vis-a-vis sowing and germination, loss of standing crop, post-harvest loss, crop protection against calamities, and an add-on coverage for crop loss by animals; (ii) gives comprehensive coverage to farmers against crop failure.
The recent decision to use AI under the PMFBY scheme as well as introduction of modern techniques in farming like soil health cards and assistance for farmers using modern irrigation methods are attempts to modernise agriculture through the use of cutting-edge technology.
India is keenly pushing forward research and programmes to use cutting-edge technology in agriculture (the budget has outlined establishing 20 technology business incubators to develop over 75,000 skilled agro-rural entrepreneurs). The Union Ministry of Earth Sciences and Agricultural Meteorology Division, India Meterological Department (IMD) has proposed in its Mission 2030 to form to give a fillip to modernisation in agro-meteorological activities. It would involve an integrated unit in a phased manner. IMD and the Indian council of Agricultural Research (ICAR) and institutions like agricultural universities, the state agricultural, information technology and space departments, MS Swaminathan Research Foundation (MSSRF) and non-governmental organisations in a collaboration that can be strengthened at the national and international levels. The National Mission on Agricultural Extension and Technology (NMAET) is keen on strengthening agricultural mechanisation and crop protection activities by restructuring them so that improved agronomic practices can contribute to sustainable development. The farmer producer organisations (FPOs) have been established to ensure a conducive atmosphere between the centre and the states, which would help farmers get fair price for their crops and experience ease in agricultural business. The Pradhan Mantri Matsya Sampada Yojana (PMMSY) has been boosted by allocation of ` 805 crore to deal with critical issues in the agricultures value chain by integrating latest technology. The issues relate to infrastructure, modernisation, traceability, productivity, management in the post-harvest phase, and control of quality.
As agriculture has been recognised as the core of the union budget, there have been efforts to improve the agricultural sector through adoption of various means: The plan is to invest widely in improving agricultural infrastructure to ensure an assured income for small and marginal producers. Niti (National Institute for Transforming India) Aayog is to conduct research and programmes on use of technologies in agriculture, such as machine learning and AI. As per Food and Agriculture Organisation (FAO) estimates, India has to double its agricultural output by 2050. Besides, initiatives are aimed at doubling the farmer’s income by 2022.
Use of AI in Agriculture
In the twenty-first century, when technology is seen as the key driver, giving a big push to a rather neglected sector—agriculture—by leveraging AI, is imperative. Artificial Intelligence (AI) may reduce the cost of production through precise application of agricultural inputs like fertilisers, chemicals, irrigation, etc. Apparently, agriculture is an unlikely field for AI, but Indian farmers have already started using digital tools in deciding which crops to grow, and selecting pesticides and fertilisers.
However, making successful use of technology will have to undergo certain tests like required skill tests at individual farmer level to operationalise it and behavioural test of individual farmers. And the solution to all these problems is AI with less human interface.
Improving Production through AI
Improving agricultural productivity involves many things, from crop decision to harvesting and marketing, and precise information to the farmer. So, having a self-guided automatic model that understands the behaviour of various stakeholders for the benefit of all is a must.
Artificial Intelligence (AI) can be described as simulated algorithmic computer models that mimic the human behaviour. A robotic ‘friend’ or installed application guides farmers regarding when to grow, harvest, and sell the produce. It links agriculture resource persons with farmers: the former can track the most pressing problems faced by farmers by examining the searches on internet (google analystics) made by the latter. For policymakers also, it would provide digital data and help them explore various policy options and interventions. The collection of data by digitalisation of agriculture would aid in developing and implementing artificial intelligence in agriculture. In 2018, farmers in Andhra Pradesh and Karnataka sowed crops relying on messages delivered by Microsoft and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) using artificial intelligence.
Marketing And Supply through AI
Marketing is the most important factor in bringing about prosperity in rural areas. Modern marketing system is based on grading and price prediction. Crops have to be graded as per physical parameters through automated quality analysis of images both at farm level and at market level. Thus, farmers can know the exact parameters to upload their produce parameters online on platforms like e-NAM and e-GraMS, and can do marketing at reduced cost even without a middleman. Also, the process of buying and selling can be done from anywhere, far from the point of production as well.
Forecasting market price helps producers in receiving remunerative price, and algorithmic models tell us the possible price using the previous years’ price data, leaving no scope of price manipulation and errors which happen in feeding false prices.
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IT&C in Sustainable Farming
Use of developments in information technology and communication (IT&C) is a worldwide trend today to achieve long-term sustainable agriculture goals of economic profitability, social and economic equality, and environmental health.
IOT Internet of Things (IOT) has been integrated in farming to facilitate soil-less culture, solution control technology, intelligent irrigation practices, and environmental control through manipulation of carbon dioxide intensity, humidity, wind speed, and pressure of winds. Such integration of IOT in farming has helped in the development of plant factory technology. Use of lighting and video sensors, for instance, can show how light intensity is distributed in real time and they can be used to monitor plant size. Spectral analysis of plant images can help ascertain the health of plants in real-time.
GPS and WSN Use of global positioning systems (GPS) and wireless sensor nodes (WSN) are used as monitoring tools to oversee parameters and correlate among them, for instance, to help farmers make decision in crop management and monitor and control on-field sensors, such as for switching off/on irrigation pumps when the required water level is reached.
Smart farms Smart farming projects are being pursued in Brazil and South Korea (the country’s largest smart farm was set up in an abandoned road tunnel). The idea involves the digital revolution, artificial intelligence, and the use of remote sensing solutions for crop cultivation and management. Using satellite images, a global study was done in 1980–83 and the Normalised Difference Vegetation Index (NDVI) was deduced. The NDVI correlates with vegetation parameters like green-leaf biomass and areas, and indicates the amount of photosynthetically active vegetation in a region. The NDVI curve has been established and its relationship with variables like sunlight, humidity, rainfall, and temperature has been identified. This has helped in the formulation of data-driven models. As India has high NDVI values, such models can help sustainable farming practices.
Crop grown in indoor smart farms can be safeguarded from extreme weather conditions. They also reduce insect infestation, as the crops are in a closed environment.
Artificial intelligence has provided more opportunities to share data useful for farmers. In 2018, farmers in South India could rely on messages for sowing crops delivered using AI by Microsoft and ICRISAT. In Tanzania, using Google’s open source, farmers discovered diseases in crops with over 90 per cent accuracy and used robotics to pluck the weeds.
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Supply chain management is another important factor in predicting price. AI-aided software can manage commodity exchange among the stakeholders in the market. Apart from that, integration of value chains-stocks/storage space, procurement, and ICT-enabled banking service helps bring globalisation in value chains.
Soil and Water Management Through Reactive AI
Soil and water are facing severe threats under modern agricultural practices. The use of inorganic chemicals affects the productivity. In this situation, Reactive AI would be the most preferable type of AI, which works on the principle of perception of surrounding conditions and acts on what it sees. Thus, it can be used to recognise any deviation to the health of soil and water and ensure fertility status and quality of water. Integrated data signals from satellites can also be used and compared with local farm image, thus reducing the high cost of laboratory testing infrastructure. PEAT, a Berlin-based agricultural tech start-up, has developed a application, viz, Plantix, which identifies potential defects and nutrient deficiencies in the soil. It also correlates particular foliage pattern with certain soil defects, etc., and immensely saves on cost. India should adopt a resilient resource strategy and should increase the yield of cereals like in USA and China. Reactive AI models store the crop-specific moisture requirement and using the remote sensing satellite, they help in examining the moisture content in the field and informing the farmer through text messages. The same technique can also be used in laying of auto-irrigation from borewell, which will help in curbing the indiscriminate use of water in farming (nearly 89 per cent of groundwater is used for agriculture in an inefficient manner, resulting in water wastage).
Given the chemical residues in the Indian soils, AI must be given leverage to maintain soil health for future generations. About 70 per cent of water is contaminated, which may cause a severe water crisis in the next decade.
Emergence of Agri-Start-ups
Certain agri-startups have come into being and have proved successful in unleashing the farm potential through technology. Intello Labs, Aibono, Thrithi robotics, and Satsure are some of the AI start-ups which are successfully using AI in predicting yield, stabilising soil analysis, and even in predicting future economic value. The start-ups will also generate considerable employment for the people.
Digital Scenario in India
Though digitalisation is keeping pace in the country, the agricultural sector is somewhat lagging. Through the Digital India programme, the drive is reaching rural areas. Currently, 30 million farmers are using smartphones and the number is expected to reach 315 millions by 2020. This increase in digital literacy will further boost AI as a game changer.
In this connection, NITI Aayog and IBM have signed a statement of Intent (SoI) to develop a crop yield prediction model using AI to produce real-time advisory to farmers.
Technology has touched the lives and aspirations of 1.3 billion Indians. Use of technology in agriculture has shown progress. By assessing demand and supply situations, farming has now become easy. Therefore, deployment of AI should be a part of the AI policy to solve problems on priority basis. Early adoption of AI can bring in a much-needed second Green Revolution. And to materialise this dream, synergy between the centre and the states is a must.