Currently, quality inspection and nutrients estimation of rice grains is very important for evaluating the grade of the food grains. Artificial Intelligence and image processing algorithms play an extensive role in agriculture for assessing the nutrients present in three types of rice grains. The three types of rice varieties include Brown Rice (BR), White Rice (WR) and Enriched White Rice (EWR). One among them is the analysis of the quality and nutrients present in the rice grains. The main difficulty in trading rice grains based on quality and nutrients is presently done by a human inspector. In this paper, a strategy is presented to estimate the quality of rice grains based on the nutrients content in it. The major nutrients for assessing the quality of the rice grains include Manganese, Niacin, Thiamine, Selenium and Magnesium. The proposed method is an application of image processing with Artificial Neural Networks (ANN) trained with Back Propagation Algorithm (BPA) to offer a cost effective solution using Artificially Intelligent (AI) Sensor to assess quality, rating and nutrient based categorization of rice grains based on the colour of the rice grains.