Marine protein hydrolysates and peptides have grown in popularity due to their biological activities and robust properties. They are increasingly studied in the functional food, pharmaceutical, and cosmeceutical sectors. This article discusses the current knowledge about preparing protein hydrolysates and peptides from seaweed, seafood, and seafood processing byproducts. Gaps in knowledge and technical expertise required for their industrial integration have been identified. The desire for natural substances to use as functional food has gained prevalence as consumers have become more aware of the adverse side effects of synthetic drugs. Aging-related chronic diseases, including cancer, arteriosclerosis, and diabetes, can be prevented by actively introducing food-based functional ingredients. Marine-derived proteins and peptides still face several hurdles to commercialization, such as scaling up production and maintaining a sustainable supply of raw materials. Further understanding of the physiological functionalities, action mechanisms, and clinical efficacy of these peptides and proteins would facilitate their use in biomedical applications and as functional ingredients in food and cosmetics.

Not from concentrate (NFC) fruit juice is the crucial clean label ingredient for new-style tea-making due to its pleasant color and fresh aroma. Here, we compared the effects of mild heating (MH) and high pressure processing (HPP) on physicochemical characters and phytochemicals in NFC spine grape juice based on metabolomics analysis. Similar compound profiles were observed between HPP-treated and fresh juices. The richer phytochemical compounds comprised malvidin-3-O-glucoside, malvidin-3,5-di-O-glucoside, quercetin-3-O-rhamnoside, quercetin-3-O-glucuronide, catechin, caffeic acid, ferulic acid, procyanidin B1, procyanidin B2 were obtained after MH treatment. Nine marker phenolics and two marker tripeptides (i.e., Glu-Val-Phe and Leu-Leu-Tyr) were identified to differentiate MH from HPP treatment, of which higher contents occurred in the MH group. Storage time experiments showed that the Glu-Val-Phe could serve as potential markers for monitoring storage of spine grape juice. These results provide new insights into the effects of processing on individual phytochemical changes and the guide for commercial application of production of spine grape NFC juice.

While high-hydrostatic pressure (HHP) has successfully been applied to the pasteurization of fruit and vegetable juice beverages, their quality-stable shelf life during storage has not been fully elucidated. Therefore, we investigated the effect of HHP (550 MPa/10 min) treatment on polyphenols, carotenoids, ascorbic acids, and antioxidant capacity in tomato juice and their changes during 4-week refrigerated storage. High-temperature short-time (HTST, 110 °C/8.6 s) treatment was used as a control. The results revealed a significantly greater presence of polyphenols, carotenoids, ascorbic acid content, and antioxidant capacity in tomato juice after HHP processing than after HTST processing. However, the total carotenoids and total phenolic content in HHP-treated tomato juice decreased dramatically and approached that in the HTST-treated tomato juice after 1 week of storage. Therefore, HHP’s advantage in maintaining antioxidant compounds and capacity was only evident during the first week of storage in tomato juice. Nevertheless, the post-storage caffeic acid, quercetin, ferulic acid, and p-coumaric acid concentrations were 8.31, 4.77, 1.86, and 6.84 μg/g higher in the HHP-treated than in HTST-treated tomato juice, respectively. This study provides a new perspective for predicting HHP products' quality-stable shelf life.

High hydrostatic pressure has become a non-thermal alternative to thermal pasteurization in dairy product processing. In this study, we investigated the effects of the treatment of high hydrostatic pressure on the bacterial composition in donkey milk using high-throughput sequencing technology and culture-dependent methods. Compared with the microbial composition in the untreated donkey milk, the relative percentage of Pseudomonas and Acinetobacter in donkey milk after high hydrostatic pressure was significantly decreased by 4.92% and 4.82%, respectively. Beta diversity analysis demonstrated that the treatment of high hydrostatic pressure affected the microbial composition in donkey milk significantly. The potential probiotic Enterococcus casseliflavus isolated from the untreated donkey milk has a good acidifying ability. This study revealed the effects of high hydrostatic pressure treatment on the microbial composition in donkey milk, exhibiting its practical industrial application and the potential use of biological resources in the future.

In the process of post-harvest storage and transportation, the quality of fresh fruits and vegetables are decreased due to the autogenetic physiological effect and microbial pollution, which causes great losses to the food industry. Food packaging using edible film and coatings is an emerging environmentally friendly method of fruits and vegetable preservation. This review provides an overview of various film fabrication techniques, including solution casting, extrusion, electrospinning, and 3D printing, while examining the advantages and limitations of each method. A detailed analysis is offered on the key performance parameters of these films, such as mechanical strength, water vapor permeability, antioxidant activity, antimicrobial properties, and their effectiveness in preserving fruits and vegetables. Additionally, strategies to enhance the performance of edible films through incorporating nanoparticles, natural additives, and crosslinking methods are explored. The review aims to establish a comprehensive theoretical foundation and offer practical insights to support the further development and application of edible film technology in fruits and vegetables preservation.

The soluble solid content (SSC) in grapes significantly influences their flavour and plays an integral role in evaluation of the quality and consumer acceptance. This study employed visible near-infrared (Vis-NIR) spectroscopy to rapidly quantify SSC in table grapes during storage. A predictive model was developed to construct a correlation between the spectral data and the measured SSC, while a comparative analysis was undertaken to assess the effects of various spectral preprocessing techniques. Successive projection algorithms (SPA), uninformative variable elimination (UVE), and the competitive adaptive reweighting algorithm (CARS) were adopted to eliminate redundant variables from both the original and preprocessed spectral data. The partial least squares regression (PLSR), and support vector regression (SVR) algorithms were adopted to establish a predictive model. Comparing the modelling results derived from whole-band spectral data with those obtained from selected spectral variables, the optimal spectral prediction model was formulated utilizing PLSR. The model, which incorporated filtered characteristic wavelength spectral data obtained through CARS following standard normal variate (SNV) preprocessing yielded optimum results with the correlation coefficients of the calibration set (RC), and the prediction set (RP) were 0.956 and 0.940, respectively. The root mean square errors of the calibration set (RMSEC), and prediction set (RMSEP) were 0.683 and 0.769, respectively, while the ratio of prediction to deviation (RPD) was 2.899. These results suggest that the application of Vis-NIR spectroscopy technology could effectively detect the SSC in grapes during storage, and it can provide a valuable reference for the rapid assessment of the table grape quality.

The potential of employing hyperspectral imaging (HSI) in the near-infrared (NIR) range (386.82−1,004.50 nm) for predicting the firmness of 'Fuji' apples cultivated in Aksu has been evaluated. The performance of seven preprocessing algorithms and two feature selection algorithms was evaluated. The coefficient of determination (R2) and root mean square error (RMSE) of Partial Least Squares (PLS) models are contrasted using various inputs. These results confirm that the Multiplicative Scatter Correction (MSC) preprocessing algorithm was the optimal choice (\begin{document}$ {R}_{p}^{2} $\end{document} = 0.7925, RMSEP = 0.6537), and the Competitive Adaptive Reweighted Sampling (CARS) feature selection algorithm demonstrated superior performance (\begin{document}$ {R}_{p}^{2} $\end{document} = 0.8325, RMSEP = 0.6257). Based on the aforementioned findings, PLS, Multiple Linear Regression (MLR), Heterogeneous Transfer Learning (HTL), and Back Propagation Neural Network (BPNN) models were constructed for cross-validation purposes. The experimental results indicate that the CARS-BPNN model exhibits the optimal prediction performance, with an \begin{document}$ {R}_{p}^{2} $\end{document} value of 0.9350 and an RMSEP value of 0.4654. The results of the research indicated that a deep learning method combined with hyperspectral imaging technology could be utilized to non-destructively detect the firmness of 'Fuji' apples, which will be beneficial and potentially applicable for post-harvest fruit firmness monitoring. This research provides a reference point for the non-destructive detection of apple in the selection of preprocessing, feature selection algorithms, and predicting firmness model.

MicroRNAs (miRNAs) play important roles in various physiological activities in plants. However, their role in protecting grapes against gray mold (Botrytis cinerea) invasion remains largely unexplored. This study focuses on the phenotypic and physiological responses of 'Shine Muscat' (Vitis vinifera × V. labrusca) to gray mold infestation. High-throughput sequencing implicates several miRNAs, including miR398 and miR319, involved in the plant's defense mechanisms. Notably, miR395 emerges as a key player, positively influencing grape disease resistance. Specifically, miR395 downregulated the expression of its target gene APS1, which encodes ATP sulfurylase, a crucial enzyme in the plant's sulfur metabolic pathway. Concurrently, ATP sulfurylase downregulation increased the content of sulfate ions and glutathione (GSH). These findings were corroborated by our study of APS1. Collectively, these results suggest that miR395-APS1 modulates sulfur metabolism in grapes, thereby enhancing resistance to B. cinerea. The observed miRNA-mediated interactions between grapes and B. cinerea elucidate the role of miR395 in grape resistance to gray mold and offer new insights into the molecular mechanisms of grape disease resistance.

Machine learning, in combination with optical sensing, extracts key features from high-dimensional data for non-destructive food quality assessment. This approach overcomes the limitations of traditional destructive and labor-intensive methods, facilitating real-time decision-making for food quality profiling and robotic handling. This mini-review highlights various optical techniques integrated with machine learning for assessing food quality, including chemical profiling methods such as near-infrared, Raman, and hyperspectral imaging spectroscopy, as well as visual analysis such as RGB imaging. In addition, the review presents the application of robotics and computer vision techniques to assess food quality and then drives the automation of food harvesting, grading, and processing. Lastly, the review discusses current challenges and opportunities for future research.

Protected cultivation is an effective measure for high-end grape production. Nevertheless, the long-time application of plastic film negatively influences the light environment, and results in a certain decrease in berry quality. In this study, six different light treatments, including white (W), red (R), blue (B), and three different combinations with different ratios of red and blue light (1:1, 4:1, 1:4, respectively), were applied to monitor the quality and sensory properties of 'Queen Nina' grapes. Compared to the control group (without supplemental light), all light treatments significantly increased the size and weight of berries, as well as improved their sugar, anthocyanins, flavonoids, and volatile organic compounds (VOCs) content, whereas all light treatments decreased the levels of chlorophylls and organic acids. Furthermore, the R1B4 treatment improved the content of cyanidin-3-O-glucoside (Cy) and peonidin-3-O-glucoside (Pn), which are the dominant anthocyanin compounds in red grape berry. Additionally, esters, accounting for more than 42% of the VOCs, are the main volatile compounds in 'Queen Nina' grape, and R1B4 treatment was the most favorable treatment for VOCs accumulation. The combination of red and blue light at the 1:4 ratio (R1B4) obtained the highest composite and sensory scores and had the most positive impact on berry coloration, sugars, anthocyanins, flavonoids, and VOCs accumulation, followed by the blue light treatment. In summary, the present results highlight the effective strategy of R1B4 light treatment to increase the berry quality of 'Queen Nina' grape berries.