Research Projects

Agriculture and related sectors are crucial to India's economy, employing over half of the population. India is the world's second-largest producer of rice and the largest exporter of rice, providing food and nutrition security for most of the Indian people. Rice is India's most important staple crop, with a record average productivity of 4100 kg/ha in the financial year 2020. However, there are no existing guidelines and pricing mechanisms for damaged food grains that are based on scientific standards and provide a quality-based market pricing. The current Agri market faces challenges in handling and trading damaged food grains due to the lack of a quality assessment tool that quantifies damage type and severity, and hence, the market value of a damaged grain. The national policy on biofuels, 2018, has laid down targets to achieve 20 blending of Ethanol in petrol by 2030, envisioning the utilization of surplus and damaged food grains available with Food Corporation of India FCI for production of Ethanol. However, there are no existing guidelines and pricing mechanisms for damaged food grains that are based on scientific standards and provide a quality-based market pricing. The AIDD device proposed in this project would provide an AI-based quality evaluation of damaged food grains, aiding in ascertaining their market value, benefiting both farmers and traders. Food and agricultural product quality control is complex and time-consuming, with traditional operations being mostly manual. Quality has historically been measured by hand, which is time-consuming, expensive, and inaccurate due to human decision making in identifying quality factors such as appearance, taste, nutrient, texture, and more. Another option is to conduct lab tests, which are expensive, time-consuming, and require relying on labs for reports. Flatbed scanners are often used to evaluate the consistency of food grains but do not provide high fidelity results or have a dependent processing time on the dpi of the images used. The state-of-the-art color sortex machine is expensive, not portable, and only sorts good/bad grains without providing quantitative data of good/bad grain. To address these challenges, the project aims to develop a portable device that helps in instant quality evaluating food grains, ensuring a quality index-based market pricing of food grains. The device is expected to require minimal installation procedure with little learning for end users.