Refrigeration is considered a prime technology for preserving meat products. Temperature alterations are commonly ignored by industry during refrigeration, which have impacts on product quality. Thus, we conducted research on pork loin and salmon fillets that were preserved for 0, 5, 9, 12, and 15 d, where different temperature fluctuations and shocks were established on 4 °C. Data revealed that several meat parameters such as total volatile basic nitrogen, total viable count, and lipid oxidation were significantly changed in the ±2 °C fluctuations group compared with the constant temperature group. Additionally, both the temperature fluctuations and shocks groups had accelerated myofibril protein degradation, while desmin expression and species richness/diversity of bacteria were significantly reduced in the ±2 °C fluctuations group compared with the constant temperature group. Briefly, temperature fluctuations and shocks accelerated the destruction of muscle structural integrity. Furthermore, both conditions accelerated meat spoilage by progressively expanding the water-loss channels, which can reduce meat edibility. This study provides a new theoretical basis for the proper use of refrigerated temperatures for storing meat products.

Milk fatty acids significantly contribute to human nutrition and clinical health. However, previous evidence for changes in the fatty acid profiles of different dairy species following homogenization and heat treatment is lacking. Here, changes in fat globule particle size and fatty acids in samples of Holstein, goat, buffalo, yak, and camel milk following homogenization (20 MPa) and heat treatment (63 °C for 30 min and 90 °C for 15 min) were investigated using a laser particle sizer and gas chromatography approach. The results indicated that the milk fat globule particle size of all studied dairy species significantly decreased after homogenization and heat treatment, in which there was no difference. The fatty acid composition of C10:0 and medium-chain fatty acid in goat milk, C18:0 and long-chain fatty acid in camel milk, and C16:0 in buffalo and yak milk served as the characteristic traits of these milks. Changes in the relative contents of several fatty acids (C4:0, C10:0, C16:0, C18:0, C18:1n9c, and C18:3n3) were dependent on homogenization, heat treatment, and the type of dairy species. In particular, C18:3n3 significantly decreased in goat and camel milk after homogenization and heat treatment. These findings provide new insights into how homogenization and heat treatment affect the fatty acid profile and can be used to further improve the heat treatment of milk from minor dairy species.

Detection of fruit traits by using near-infrared (NIR) spectroscopy may encounter out-of-distribution samples that exceed the generalization ability of a constructed calibration model. Therefore, confidence analysis for a given prediction is required, but this cannot be done using common calibration models of NIR spectroscopy. To address this issue, this paper studied the Gaussian process regression (GPR) for fruit traits detection using NIR spectroscopy. The mean and variance of the GPR were used as the predicted value and confidence, respectively. To show this, a real NIR data set related to dry matter content measurements in mango was used. Compared to partial least squares regression (PLSR), GPR showed approximately 14% lower root mean squared error (RMSE) for the in-distribution test set. Compared with no confidence analysis, using the variance of GPR to remove abnormal samples made GPR and PLSR showed approximately 58% and 10% lower RMSE on the mixed distribution test set, respectively (when the type 1 error rate was set to 0.1). Compared with traditional one-class classification methods, the variance of the GPR can be used to effectively eliminate poorly predicted samples.

Although surface-enhanced Raman spectroscopy (SERS) substrates have achieved high sensitivity, it is still difficult to apply these SERS protocols to the on-site detection of real samples due to the SERS substrate being fabrication-complexed, unstable, reproducible, or unable to be applied in batch production. Here, a large-scale ordered two-dimensional array of Au nano-hemispheres was developed through electron beam vaporization of Au onto the easy-available commercialized anodic aluminum oxide (AAO) template with two-layer nanostructures of different diameters. The uniform Au nano-hemisphere is reliable for SERS detection of malachite green (MG) due to the relative standard deviation (RSD) of the SERS intensities at different locations less than 10%. With the optimized excitation wavelength, solvent effect and pH environment, the linear range of MG detection spans from 10–10 to 10–6 mol/L with a limit of detection (LOD) of 4×10–10 mol/L. The enhancement factor can reach 1.2×106. After extraction with acetonitrile and dichloromethane, MG in the spiked tilapia was detected with satisfactory recovery. The results indicate that the Au nano-hemisphere array can be expected to greatly facilitate SERS practical applications in detecting harmful food additives and chemicals due to the advantages of chemical inertness, physical robustness, simple fabrication, controllability, large-area uniformity, and large-batch production.

Background Wheat flour maturation affects the aggregation and structural stability of proteins. The number of high-molecular-weight glutenin subunits (HMW-GSs) differs in various wheat varieties. The effects of Dx2 absence on the protein aggregation characteristics and thermal stability of flour were investigated during 120 d of maturation using near-isogenic lines (NILs). Results The absence of Dx2 delayed and decreased the protein aggregation of flours during maturation, i.e. the maturation-induced increases were later and smaller for glutenin, glutenin macropolymer (GMP), glutenin/gliadin ratio, β-sheets, and β-sheet/α-helix ratio in HMW-D1a without Dx2 than in HMW-D1p with Dx2; these differences were ascribed to the weaker interactions between the sulfhydryl (-SH) groups, disulfide bonds (-S-S-), and hydrophobicity in the flours without Dx2. Flour maturation caused the dough microstructures to be more compact and denser, thereby increasing the flour thermal stability as observed by a higher denaturation peak temperature (Tp), enthalpy of thermal transition (ΔH), and degradation temperature (Td), These changes led to better dough properties such as dough development time, dough stability time, and protein weakening, but the optimal stage in HMW-D1a without Dx2 was reached later. Conclusion These findings deepen the understanding of how HMW-GS Dx2 modifies protein structures during flour maturation.