We are faced with a global food security challenge today, and there is a growing need to boost agricultural productivity with a minimal impact on the environment. Using technology in the agricultural sector is a necessary intervention to feed the global population, which is likely to reach 9.3 billion by 2050. New technology has the potential to make agri-businesses more productive and profitable, and enhance the income of farmers. Declining crop quality, debilitation of arable land, and newer crop pests and diseases are some of the other major problems the sector is currently grappling with.
While the majority of farmers and agri-businesses remain technologically handicapped, government and agtech start-ups are working incessantly to change this. Thanks to their efforts, modern agriculture now employs cutting-edge technology such as artificial intelligence (AI), machine learning (ML), internet of things (IoT), robotics and big data to meet the world’s growing food and fibre needs.
Big data for efficient decision-making
Farmers walk through their fields to keep a close eye on plant and soil health through the crop cycle. However, this manual process can be subjective and time-consuming, and adversely impact the efficiency of the food production process. Modern agricultural practices use big data-based sensors and devices, which swiftly and precisely collect real-time crop information for hectares of farmland, and then process it into insightful data. Big data has been a revolutionary force in the agricultural sector; besides giving farmers a better understanding of crops and farming practices, it has given them incomparable decision-making capabilities at every step of the way.
AI and ML for predictive crop analysis
Farmers choose crops based on their marketability, profitability as well as on the farm’s biotic factor and topographic features, such as soil quality and weather compatibility. So far, with traditional agricultural practices, crop predictions have been unreliable and farmers keep hypothesising results during the entire crop cycle. However, farmers today have access to AI and ML tools that can inform them of the best time to sow seeds, alert them about impending pest diseases, etc.
AI algorithms leverage big data tools that collect and analyse years of weather and crop information about any given farmland to accurately forecast crop yields – all this even before planting a seed. Meanwhile, ML is being used to identify crop disease, instead of the traditional way of visual inspection. A trained computer can accurately spot affected plants within minutes compared to manual inspection, which can be cumbersome and subjective. The holistic insight obtained through AI can help farmers get the best harvest possible by suggesting the optimal time for planting and harvesting.
Robotics and IoT for monitoring farms
Agri-businesses around the world are using various IoT-based drones to keep tabs on the crop and soil health of their farms. These drones are equipped with compact multispectral imaging sensors for scanning farms, or cameras for creating GPS maps, or cameras with thermal imaging for monitoring livestock. Farmers in China are using drones to pollinate apple orchards and fight weather changes. Considering the rapid growth of robotics and IoT, a future where drones will be able to take care of end-to-end crop cycles isn’t far away.
Government’s role in encouraging digital innovation in agriculture
Subsidies have been the Indian government’s preferred tool for encouraging technology adoption amongst farmers. Given that agriculture is one of the oldest professions, farmers are reluctant to change their traditional ways. The Digital India initiative introduced by the Government of India in 2015 has improved digital literacy amongst farmers, thereby accelerating technology adoption. The government is also partnering with agtech start-ups to bring about change at the grassroots level.
One such initiative was undertaken by the Karnataka government , in collaboration with Bengaluru-based agtech start-up CropIn Technology Solutions. The project aims to boost the socio-economic development of farmers across 30 districts of Karnataka through the adoption of technology. They plan to equip farmer producer organisations (FPOs) and farm managers with complete farm advisory services covering climate-smart farming, right package of practices, and pest and disease management. In a similar collaboration, the Andhra Pradesh government partnered with CropIn to digitise farms under two FPOs in the districts of Chittoor and Krishna, with the goal of doubling farming income by 2022.
With agriculture becoming more and more vulnerable to weather extremes, the Food and Agriculture Organization of the United Nations recommends the adoption of climate-smart agriculture. The central and state governments of India are working with the World Bank on Sustainable Livelihoods and Adaptation to Climate Change to bring climate-smart practices to the doorstep of the Indian farmer. The project uses a comprehensive end-to-end advisory model developed by CropIn to assist village representatives in disseminating information amongst the local farming community. Currently, over 90,000 farm plots have been digitised in the states of Madhya Pradesh and Bihar, with the aim of creating climate sustainability and boosting productivity. S