Rice Quality Analysis After Drying

Paddy rice, as a grain sensitive to high temperature, is apt to display degradation phenomena including cracking and inferior taste during the drying process. It is necessary to analyze and calculate the taste value of the post-drying paddy for paddy processing and dryer designing.Many terms, such as crack rate, head rice yield, taste value, based on individually desired requirement from researchers are used to evaluate rice quality. In this research, rice quality in terms of head rice yield, taste value were synthetically analyzed for the after drying paddy rice.The samples of moisture conditioned paddy rice, from 3 varieties, were processed on a thin-layer drying table under different drying conditions including initial moisture content, drying temperature and surface velocity. Milling quality and taste value were obtained according to the standards method from Chinese Department of Agriculture. Near Infrared Radiation (NIR) technology and Neural Network (NN) method were applied to measure rice constituents and predicate rice quality.The conclusions were obtained as following:The essential factors on rice quality were analyzed after drying paddy. A regression equation was developed to express the relation between drying constant K and drying parameters in terms of drying temperature, surface velocity, relative humidity and initial moisture content, which describes the effect of each parameter on drying rate during paddy rice drying process.The significant effects of drying conditions on rice milling quality were found that milling quality i n t erms o f whole kernel amount, total rice yield, and head rice yield decrease with the increase of drying temperature and surface velocity under high initial moisture content. The result from taste analysis of dried rice indicated that the rice taste value is subject to the main constituents content which including the moisture, protein, amylose and fatty acid and drying temperature.On the basis of the experiment, the rice taste value of post-drying paddy was evaluated. Firstly, the main constituents content (A) of the rice was measured in near-infrared grain analyzer. Then, the rice taste value (B) was determined in panel sensory evaluation. The mathematical model was built involving in the A and B base on the Neural Network software (NeuroShell2,V3.0) which has one input layer (five input nodes) and three hidden layer and one output layer (one output node).A validated experiment indicates that the synthesis grade from neural network model for the dried rice make a good agreement with experimental results. The analysis of results leads to a conclusion that neural network model can evaluate the rice taste value of the post-drying paddy.