Cooking is an important process before rice is consumed and constitutes the key process for rice flavor formation. In this paper, dynamic changes in aroma- and sweetness-related compounds were tracked during the entire cooking process (including washing with water, presoaking, and hydrothermal cooking). The volatiles, fatty acids, and soluble sugars in raw rice, washed rice, presoaked rice, and cooked rice were compared. After being washed with water, the total volatiles decreased while aldehydes and unsaturated fatty acids increased. Meanwhile, oligosaccharides decreased and monosaccharides increased. The changes in fatty acids and soluble sugars caused by the presoaking process were similar to those in the water-washing process. However, different changes were observed for volatiles, especially aldehydes and ketone. After hydrothermal cooking, furans, aldehydes, alcohols, and esters increased while hydrocarbons and aromatics decreased. Moreover, all fatty acids increased; among these, oleic acids and linoleic acid increased most. Unlike with washing and presoaking, all soluble sugars except fructose increased after hydrothermal cooking. Principal component analysis showed that cooked rice possessed a volatile profile that was quite different from that of uncooked rice, while washed rice and presoaked rice possessed similar volatile profiles. These results indicated that hydrothermal cooking is the pivotal process for rice flavor formation.

Binary nanocomposite has become an excellent modification material for sensors and biosensors, which is superior to single nanomaterial. Multiple electrochemical sensors with four types of binary nanocomposites and biosensors with four biological elements were presented in the application of food safety. Different sensors for the detection of the same food analyte were contrasted. The synergistic effects and interactions of nanocomposites, and analytical performance of modified (bio)sensors are elaborated. The future perspectives for binary nanocomposites used on food (bio)sensors are discussed.

Fragrant rice has various flavor types, mainly the popcorn flavor, corn flavor and lotus root flavor. Chinese fragrant rice from China and Thai fragrant rice from Thailand were analyzed. GC-MS was used to determine the volatile compounds of fragrant rice. It was found that there were 28 identical volatile compounds between Chinese and Thai fragrant rice. The key compounds of different flavor types of fragrant rice were obtained by comparing the common volatile compounds. The key compounds of the popcorn flavor were 2-butyl-2-octenal, 4-methylbenzaldehyde, ethyl 4-(ethyloxy)-2-oxobut-3-enoate and methoxy-phenyl-oxime. The key compounds of the corn flavor were 2,2′,5,5′-tetramethyl-1,1′-biphenyl, 1-hexadecanol, 5-ethylcyclopent-1-enecarboxaldehyde and cis-muurola-4(14), 5-diene. By using a combination of GC-MS and GC-O, the flavor spectrogram of fragrant rice was constructed, and the characteristic flavor compounds of each flavor type were identified. It was found that the characteristic flavor compounds of the popcorn flavor were 2-butyl-2-octenal, 2-pentadecanone, 2-acetyl-1-pyrroline, 4-methylbenzaldehyde, 6,10,14-trimethyl-2-pentadecanone, phenol and methoxy-phenyl-oxime. The characteristic flavor compounds of the corn flavor were 1-octen-3-ol, 2-acetyl-1-pyrroline, 3-methylbutyl 2-ethylhexanoate, methylcarbamate, phenol, nonanal and cis-muurola-4(14), 5-diene. The characteristic flavor compounds of the lotus root flavor were 2-acetyl-1-pyrroline, 10-undecenal, 1-nonanol, 1-undecanol, phytol and 6,10,14-trimethyl-2-pentadecanone. The resistant starch content of lotus root flavor rice was relatively high (0.8%). The correlation between flavor volatiles and functional components was analyzed. It was found that the fat acidity of fragrant rice was highly correlated (R = 0.86) with the characteristic flavor compounds, such as 1-octen-3-ol, 2-butyl-2-octenal and 3-methylbutyl-2-ethylhexanoate. The characteristic flavor compounds had an interactive contribution to the production of the different flavor types of fragrant rice.

An approach for improving the identification and discrimination ability of electronic tongue multi-sensor array was developed. The detail signal was obtained by decomposing the original voltammetric signal using wavelet packet decomposition, and the feature value was extracted by Fast Fourier transform in which the influence of collinearity was eliminated. Based on the principle of information entropy, the sensing entropy of single electrode and between electrodes in the multi-sensor array were defined, and the unit sensing vector and interactive sensing vector were constructed. The results showed that 6 unit sensing entropies could be effectively used for the identification of rice origin, and all interactive sensing vectors for the discrimination of rice type. SVM and KNN classifiers were employed. The results showed that the training and prediction accuracy of SVM with interactive sensing vector as the input for identifying rice origin were 89.0% and 82.9% respectively, and that for distinguishing rice type were 96.0% and 88.6% respectively. In conclusion, the SVM model with interactive sensing vector could be an approach to accurately identify rice origin and distinguish rice type. The identification and discrimination ability of multi-sensor array could be enhanced by using the sensing interaction information based on information entropy.