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(1) Background: To achieve the rapid, non-destructive detection of corn freshness and staleness for better use in the storage, processing and utilization of corn. (2) Methods: In this study, three varieties of corn were subjected to accelerated aging treatment to study the trend in fatty acid values of corn. The study focused on the use of hyperspectral imaging technology to collect information from corn samples with different aging levels. Spectral data were preprocessed by a convolutional smoothing derivative method (SG, SG1, SG2), derivative method (D1, D2), multiple scattering correction (MSC), and standard normal transform (SNV); the characteristic wavelengths were extracted by the competitive adaptive reweighting method (CARS) and successive projection algorithm (SPA); a neural network (BP) and random forest (RF) were utilized to establish a prediction model for the quantification of fatty acid values of corn. And, the distribution of fatty acid values was visualized based on fatty acid values under the corresponding optimal prediction model. (3) Results: With the prolongation of the aging time, all three varieties of corn showed an overall increasing trend. The fatty acid value of corn can be used as the most important index for characterizing the degree of aging of corn. SG2-SPA-RF was the quantitative prediction model for optimal fatty acid values of corn. The model extracted 31 wavelengths, only 12.11% of the total number of wavelengths, where the coefficient of determination RP2 of the test set was 0.9655 and the root mean square error (RMSE) was 3.6255. (4) Conclusions: This study can provide a reliable and effective new method for the rapid non-destructive testing of corn freshness. [ABSTRACT FROM AUTHOR]

Stored rice susceptible to environmental influences may induce quality deterioration. To clarify the optimal storage condition for rice, the quality indicators including microbial counts and fatty acid values (FAVs) under different relative humidity (RH) and brown rice (BR) rates were monitored, and lipid composition and fungal community of three freshness rice were explored by liquid chromatography mass spectrometry (LC-MS) and internal transcribed spacer (ITS) sequencing. The results showed the fastest increase of microbial counts and FAVs at 80% RH and 8% BR, indicating the better rice quality stored at 60% RH and with a BR rate of less than 2%. During storage, Aspergillus significantly increased by 99.0%, while Alternaria decreased by 99.5%. Moreover, 927 lipid species belonging to 6 classes and 50 subclasses were identified, including glycerolipids (GLs, 40.45%), sphingolipids (SPs, 22.22%), and glycerophospholipids (GPs, 14.46%). The major differentially abundant metabolites (DAM), including SHexCer, PE-Cer, PMEOH, and SMGDG, can be identified as key markers in rice deterioration. Notably, glycerophospholipid metabolism and glycerolipid metabolism were the main pathways for poor-quality rice in contrast with sphingolipid metabolism for mild-quality rice. Additionally, the degradation of GLs, SPs, and GPs significantly correlated with the changes of Aspergillus , Wallemia , Fusarium during rice deterioration. [Display omitted] • Rice should be stored at 60% relative humidity with a brown rice rate <2%. • SHexCer, PE-Cer, PMEOH, and SMGDG were the markers of rice deterioration. • Sphingolipid metabolism was the primary pathway for mild-quality rice. • Poor-quality rice was involved in glycerophospholipid and glycerolipid metabolisms. • Lipids degradation significantly correlated with Aspergillus , Wallemia and Fusarium. [ABSTRACT FROM AUTHOR]

A fatty acid value determination method in grain was developed by using automatic photometric titrator with KOH as standard titration solution in this paper, in which magnetic stirring apparatus was selected as extraction device, anhydrous ethanol was used as extraction solvent, and thymol blue was used to control directing terminal. Finally, the fatty acid value was calculated by combining the consumed volume of KOH's standard titration solution. The instrument can automatically complete the whole process of extraction, filtration,quantitative transfer, titration and calculation. The results showed that the determination method has high precision, and the repeatability, accuracy and stability can meet the requirements of the national standard method, the consistency between instruments can meet the repeatability requirement of national standard method, the measuring time of paddy and wheat flour were one-third and one-half respectively of those by potentiometric or manual titration, and the measuring time of maize was two-fifths of the potentiometric titration and one-half of the manual titration. With a wide application range, the method was easy to operateand less to be disturbed by human factors, it is very suitable for batch and rapid determination of fatty acid value in grain. In a word, this method provided a suitable method for strict quality control in the grass-roots grain storage companies when purchasing grain and detection of large quantities fatty acid value in grain inspection agency.

A more stable and reliable method of the fatty acid values determination in grain was studied based on the establishment of manual titration method associated with the automatic potentiometric titration.The GB/T 20569—2006 Guidelines for evaluation of paddy storage character for the sample pre-treatment was used, and the manual titration was replaced by automatic potentiometric titration to determine the free fatty acid in grain with KOH as the standard titration solution.At the same time, the change of pH values in test solution were determined during titration, following by the corresponding real time change curves of pH-titration volume which will be stopped at the set terminal PH values, and phenolphthalein indicator was used as the finish monitoring in the process of the titration.The results showed that the titration processes were not affected by man-made factors, and the accuracy has no significant difference compared with manual titration method, thus ensuring the determination results has better repeatability, reproducibility and stability,and with the wider application scope.

(1) Background: To achieve the rapid, non-destructive detection of corn freshness and staleness for better use in the storage, processing and utilization of corn. (2) Methods: In this study, three varieties of corn were subjected to accelerated aging treatment to study the trend in fatty acid values of corn. The study focused on the use of hyperspectral imaging technology to collect information from corn samples with different aging levels. Spectral data were preprocessed by a convolutional smoothing derivative method (SG, SG1, SG2), derivative method (D1, D2), multiple scattering correction (MSC), and standard normal transform (SNV); the characteristic wavelengths were extracted by the competitive adaptive reweighting method (CARS) and successive projection algorithm (SPA); a neural network (BP) and random forest (RF) were utilized to establish a prediction model for the quantification of fatty acid values of corn. And, the distribution of fatty acid values was visualized based on fatty acid values under the corresponding optimal prediction model. (3) Results: With the prolongation of the aging time, all three varieties of corn showed an overall increasing trend. The fatty acid value of corn can be used as the most important index for characterizing the degree of aging of corn. SG2-SPA-RF was the quantitative prediction model for optimal fatty acid values of corn. The model extracted 31 wavelengths, only 12.11% of the total number of wavelengths, where the coefficient of determination R P 2 of the test set was 0.9655 and the root mean square error (RMSE) was 3.6255. (4) Conclusions: This study can provide a reliable and effective new method for the rapid non-destructive testing of corn freshness.