Indigenous agriculture in India was guided by the Krishi-Panchangam, the traditional Vedic almanac. However, with political shifts and rapid industrialization, availability of farmland additives and rampant use of various crop growth enhancers, there is a dynamic change in how the quality of farm produce is professed.
With largely marginalized farmlands and a paucity of adequate agriculture-specific information, it is difficult to ensure consistent commercial successes for farmers and reliable quality to consumers. The shift from traditional agriculture to digitization precisely addresses these challenges by adding a layer of transparency to the farmlands.
Like any other business of staples and produce, the core agriculture business depends on the economy of scale to establish commercial success; work that can be measured is more likely to have a higher success rate. AI and IoT in agriculture help transcend the challenges of managing scattered marginalized farmlands and improve the efficacy of larger farm holdings. Data collection, data monitoring and specific sensors for critical data parameters help the farmers get real-time information about the situation at hand and find solutions to fix any challenges which could impair crop productivity.
Data is pure power in the space of agriculture, both pre-harvest and post-harvest management. Digital connectivity helps us network and use this power to improve the food security and nutrition security of the world. Sensors to monitor soil health and water quality, sensors to monitor the sound of the crop (yes, some bugs can bore into a standing crop and eat the stalk from within destroying produce of acres overnight), sensors to monitor transpiration rates and overall crop management can be integrated into an IoT system for a farmer to know what is going on remotely. From minor things like management of irrigation to major changes based on market demand can be done using this system.
Furthermore, digitization of agriculture is instrumental in reducing manpower demand in agriculture. Often cited by farmers is a problem of not having enough manpower to manage the fields. Today with robotics, one can have assistance in harvesting fruits/ vegetables like strawberries, brinjals etc. with camera imagery determining if the produce is at the right stage of ripening to be picked or otherwise. Drones can be used to scan and analyze large acres of crops for their wellness, produce efficacy and overall agricultural parameters for profit. Soil analysis can indicate if the soil needs any attention and devices can be used to identify and spray specifically on weeds whilst being mounted on a regular tractor which runs on the field for allied cropping activities.
Beyond the farm, the produce needs to be maintained in good condition till it reaches the market. After harvest, the produce continues to exchange gases and evolve ethylene. Ethylene helps ripen the produce but in the case of long-distance shipping, this may not be ideal. There is hence a need to monitor and control temperature, humidity and ethylene production which can be achieved with technologies such as AI and IoT.
Moreover, in the case of products such as cereals, pulses, and oil seeds that require large, long-term storage under a controlled environment, there is a heightened need for monitoring and regulation of temperature, humidity and moisture.
In the post-harvest stage, quality is a major checkpoint to ascertaining profitability. Grading as per size and colour is a set norm the world over. This demands large manpower and long man-hours and needless to say excessive handling. Camera systems integrated with AI to help in the grading of produce, having a tool that is mounted on the sorting table and using simple gravity helps the processing house greatly.
While India is one of the largest producers of agricultural goods in the world with a sizeable export share, the Indian farmers still face challenges in the areas of quality standards and buyer confidence. It is these gaps that can be addressed by bringing technology into the picture. With IoT and AI technologies, the produce can be traced back to its origins with surety that it complies with every quality requirement along the way. Traceability adds to the export value of the produce and can become the farmers’ key to hassle-free export proceedings. Technology application in farming can even go one step ahead to form a marketplace where buyers and sellers can collaborate with complete transparency, thereby ensuring farmers’ ease of access to the market.
AI is also an essential tool for the Dairy Industry. Understanding milk quality at the source, ensuring temperature-controlled storage of milk, internet-enabled milk analyzers, monitoring cattle health and being an imaging partner for telemedicine tool support with veterinarians, the solutions which can be brought to the table can help places where cattle farms are scattered and small scale too.
The food industry no longer seeks to be blind to the origin of ingredients. Be it straight ingredients like staples, produce, meat, etc. to processed ready-to-cook and ready-to-eat foods, people seek to know that the ingredients are safe and produced according to norms of set quality standards. The world is moving to a system where a minor traceable digital code on the package would tell the story of the rolling farmlands where the ingredients were produced, with an assurance of quality compliance steps followed during crop production, pre-harvest management, post-harvest management and food processing. Transparency is a sign of integrity. The integrity of processes in farming and food processing will certainly bring incredible strength to all stakeholders developing consistent quality standards and economic progress.
