Rresearch On Detection Method Of Rice Storage Quality

Rice is the staple food for the most residents. So it is related to people's livelihood to research whether rice is suitable for storage. The nation have expressly provided that the poor quality of rice stored for many years should not be used directly as food ,but be sold to the holders of feed processing with specific qualification and brewing companies through legal auction. In a word, the nation strictly prohibits the poor rice into the market. Currently, we have more and more awarded of the importance of testing to quality of rice stored, and many researchers had been working on the quality of stored rice, but most current detection methods are based on subjective judgment. Purpose of this study is to develop inspection system of stored rice quality with high-convenient and rapid, a higher degree of recognition and low-cost and meet consumers demand for quality assessment of stored rice.Improve the detection method of the fatty acid value of rice in this paper by using a new hybrid colour-developing agent (bromophenol blue - bromophenol green - potassium permanganate) that show the color of rice extract, gain color value through color sensor.1. Optimize ratio of the mixed reagent bromophenol blue - bromocresol green, potassium permanganate - sodium carbonate and consider 9:1 as the best color ratio, and ultimately determine adding 100μL reagent in the 5mL test samples. Select ultraviolet - visible spectrophotometer wavelength 610nm.2. Discuss experimental factors impacting the fatty acid value of rice; determine the different degree of impacts in the extraction time, extraction temperature and centrifugation time on the rapid determination of fatty acids in rice; design the experiment for above three factors by using surface analysis; use Design Expert Statistical software for data analysis on the experimental results, and the optimal level of experimental factor: 0.31, -0.06 and 1.00,the best experimental conditions: extraction time is 16min, the extraction temperature is 20℃and Centrifugation time is 3min.3. Do the experiments for the fine and coarse rice samples with national standard titration and respectively use LCS011 color sensor, JDCL-003 fiber optic sensor recognizing color to capture color value. Pick out the good color single value relating with the fatty acid, then use fatty acid value and color single value to build GRNN neural network. Use the remaining 30 groups of rice sample to test accuracy of the neural network. Based on the data got form the two color sensors to respectively construct GRNN neural network and the accuracy rate reach 96.7%.4. Comparing and analyzing two color sensors, finally, select JDCL-003 fiber optic sensor recognizing color as the improved equipment for detection of fatty acid value. Based on Near Infrared Spectroscopy, improve the detection method of rice tasting value, and test accuracy of the near-infrared spectroscopy.1. Get 110 rice samples of different tasting values by artificially cultivating fresh rice.2. Using dichotomous method to optimize the grinding fineness, the amount of sample, the weight of imposing on the sample, and ultimately determine the optimal grinding fineness 120 holes, the amount of sample 12g, the weight of imposing on the sample 500g.3. Randomly select 80 rice samples to determine tasting values and using near infrared spectroscopy measure the optical value. Finally, use testing values obtained and different optical wavelengths to build the GRNN neural network .4. Randomly select 20 rice samples to determine tasting values and get optical value, and use the data of GRNN neural network to test .The result show that the accuracy rate of GRNN neural network was 95%.Based on the fatty acid value of rice and tasting value to construct the GRNN neural network and build evaluation system of rice storage quality, a lot of tests show that the predicting accuracy rate reaches 80%...