Soft Computing applications in predicting Palatability Preferences in Rice Varieties

Rice is the only cereal consumed as staple food mainly as whole grains by more than 50 percent people of the world. The overall cooking and eating quality of such a significant crop determines its widespread preference, acceptance and consumption. The varieties, hybrids, landraces of rice are immense in diversity not only in morphological traits but also in end-use qualities. Hence, the choice for palatability relies on many cooking and eating quality parameters such as grain shape, chalkiness, gelatinization temperature, gel consistency, amylose content etc., Based on the combinational composition of these parameters, all the known varieties of rice have been classified, identified and promoted. For such quality classification, soft computing technique –fuzzy logic has been employed supported with correlation studies as the criteria for determining the cooking and eating quality preference includes both discrete and non discrete parameters. The output results in sorting 11 varieties into 5 preferential groups based on combination of 6 palatability parameters. Keywords—cooking and eating quality, soft computing, fuzzy logic, rice varieties, palatability