Unlocking the Power of Deep Learning for Nutrient Profiling of Black Rice in Goalpara, Assam: Discoveries and Perspectives

Technological developments in recent years, especially in the area of deep learning, have completely changed how we evaluate and identify nutrients in food products. Black rice, revered for its rich nutritional profile and distinctive color, holds significant promise as a staple crop in Goalpara, Assam . The health benefits of black rice, a grain with excellent nutritional value and cultural significance, are becoming more widely recognized. Deep learning algorithms, taking advantage of black rice's distinct molecular makeup, provide a revolutionary way to precisely detect and measure nutrients in the grain. In the majority of emerging nations, the main cereal crop is black rice (Oryza sativa L.). Given that rice is an integral grain for billions of people worldwide, it is extremely important for nutrition and food security. Its nutritious content must be accurately assessed in order to combat hunger and improve farming methods. With its accurate and economical procedures, DL has become a potent tool for nutritional analysis in recent years. Black bran covers the endosperm of the rice kernel in black rice, a form of colored rice. Due to its many health advantages, the aromatic and colored black rice type known as "Chakhao" is becoming more and more popular in India and throughout the world. Due to its elevated anthocyanin concentration that serves as a significant bioactive component, it is not eaten as a staple food but rather as a functional food. Rice grains become black due to the accumulation of anthocyanins (Cyanidin-3-glucoside, Cyanidin-3-rutinoside, and Peonidin-3-glucoside) in the pericarp, tegmen, and aleurone layer. The water-soluble pigment known as anthocyanins gives black rice its anti-inflammatory and antioxidant qualities. It might be applied to the formulation of functional or neutraceutical foods. This paper methodically examines current developments in the field of research on the identification of nutritional values in black rice from Goalpara, Assam, using several DL approaches and makes comparison with that of white rice. It covers a range of approaches, developments, difficulties, and potential future directions in this area, illuminating the significance of black rice as a nutrient-dense food source and its possible effects on human health comparing with the white rice.