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.

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.

Aronia melanocarpa is a fruit rich in antioxidant compounds with notable health benefits; however, its astringency limits its widespread consumption. This study examined the effects of fermentation with Lactiplantibacillus plantarum 1243 and Lacticaseibacillus paracasei 139 on the microbiological dynamics, quality indicators, and flavor profile of Aronia melanocarpa juice. The results showed that, compared to the unfermented juice, the microbial count reached 7.03 lg CFU/mL at 24 h of fermentation, followed by a decline to 3.90 lg CFU/mL at 96 h. Soluble sugars experienced an initial decline, subsequently increased, and then decreased again. Acidity firstly reduced and then increased, while pH increased initially and then decreased. Total phenolic and flavonoid contents remained relatively stable at 24 h before showing a significant reduction. The DPPH radical scavenging activity significantly increased during fermentation, reaching a peak of 71.7% at 48 h. Overall improvement was observed in color and sensory acceptance of the juice. Flavor analysis demonstrated an increase in aromatic organic compounds, aliphatic aromatics, and methyl compounds, contributing to aroma enhancement in Aronia melanocarpa juice. These findings establish a basis for the use of lactic acid bacteria fermentation to enhance the quality, flavor, and functionality of Aronia melanocarpa juice, supporting the development of functional beverages.

Aronia melanocarpa is a fruit rich in antioxidant compounds with notable health benefits; however, its astringency limits its widespread consumption. This study examined the effects of fermentation with Lactiplantibacillus plantarum 1243 and Lacticaseibacillus paracasei 139 on the microbiological dynamics, quality indicators, and flavor profile of Aronia melanocarpa juice. The results showed that, compared to the unfermented juice, the microbial count reached 7.03 lg CFU/mL at 24 h of fermentation, followed by a decline to 3.90 lg CFU/mL at 96 h. Soluble sugars experienced an initial decline, subsequently increased, and then decreased again. Acidity firstly reduced and then increased, while pH increased initially and then decreased. Total phenolic and flavonoid contents remained relatively stable at 24 h before showing a significant reduction. The DPPH radical scavenging activity significantly increased during fermentation, reaching a peak of 71.7% at 48 h. Overall improvement was observed in color and sensory acceptance of the juice. Flavor analysis demonstrated an increase in aromatic organic compounds, aliphatic aromatics, and methyl compounds, contributing to aroma enhancement in Aronia melanocarpa juice. These findings establish a basis for the use of lactic acid bacteria fermentation to enhance the quality, flavor, and functionality of Aronia melanocarpa juice, supporting the development of functional beverages.

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.

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.

Skeletal muscle atrophy resulting from glucolipid metabolic disorders poses a serious challenge to human health with the rapidly increasing prevalence of diabetes and obesity. Clinical trials investigating treatment interventions against skeletal muscle atrophy yielded limited success. This article addressed novel phytochemicals, such as polyphenols, flavonoids, terpenoids, alkaloids, and plant extracts, that modulated muscle atrophy and suggested avenues for future treatment. Several studies demonstrated an inverse relationship between dietary phytochemical supplementation and the onset of skeletal muscle atrophy caused by glucolipid metabolic disorders, as evidenced by improved muscle quality and function. Insulin-like growth factor 1/protein kinase B signaling pathway activation, protein ubiquitination inhibition, enhancement of mitochondrial function and inflammatory response, reduction of oxidative stress, and regulation of gut microbiota represent the mechanisms underlying the anti-skeletal muscle atrophy effect of phytochemicals. The manuscript also contains the clinical trials and filed patents regarding the beneficial effects of phytochemicals on skeletal muscle health. This review provided fresh perspectives on potentially effective therapeutic or preventive measures (dietary phytochemical intervention) for clinically managing skeletal muscle atrophy associated with diabetes or obesity.

Skeletal muscle atrophy resulting from glucolipid metabolic disorders poses a serious challenge to human health with the rapidly increasing prevalence of diabetes and obesity. Clinical trials investigating treatment interventions against skeletal muscle atrophy yielded limited success. This article addressed novel phytochemicals, such as polyphenols, flavonoids, terpenoids, alkaloids, and plant extracts, that modulated muscle atrophy and suggested avenues for future treatment. Several studies demonstrated an inverse relationship between dietary phytochemical supplementation and the onset of skeletal muscle atrophy caused by glucolipid metabolic disorders, as evidenced by improved muscle quality and function. Insulin-like growth factor 1/protein kinase B signaling pathway activation, protein ubiquitination inhibition, enhancement of mitochondrial function and inflammatory response, reduction of oxidative stress, and regulation of gut microbiota represent the mechanisms underlying the anti-skeletal muscle atrophy effect of phytochemicals. The manuscript also contains the clinical trials and filed patents regarding the beneficial effects of phytochemicals on skeletal muscle health. This review provided fresh perspectives on potentially effective therapeutic or preventive measures (dietary phytochemical intervention) for clinically managing skeletal muscle atrophy associated with diabetes or obesity.

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.

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.

Vibrational spectroscopy is a green, rapid, and affordable analytical tool for analysing the quality, safety, and origin of biological materials in agri-food sectors. Pre-processing spectral data is crucial to removing instrumental interferences and physical artifacts when developing a classification model. However, there has yet to be a consensus on which spectral pre-processing method, settings, and decision parameters to use to optimise pre-processing for different spectroscopy tools. Using an arbitrary criterion poses a risk of applying the wrong type or too severe pre-processing that removes valuable information or affects the model's performance for prediction studies. Matthew's Correlation Coefficient (MCC) - a statistic for parameterising classification performance, accounts for data set imbalance and improved decisions on model selection to express uncertainty on future predictions. Four vibrational spectroscopy instruments [near-infrared (NIR), hyperspectral (HSI), mid-infrared (FTIR), and Raman] were compared using different pre-processing methods to understand the performance using MCC to classify coffee from four countries (Indonesia, Ethiopia, Brazil and Rwanda). Key decision parameters were evaluated for the development of reliable classification models. The best pre-processing for NIR was extended multiplicative scatter correction with mean centering (MNCN), and for HSI, Savitzky-Golay (1st derivative, 15 points) with MNCN. NIR performed the best across all four instruments, with FTIR performing the worst. Raman showed potential for coffee origin classification using the right pre-processing. Pre-processing with weighted least squares, normalisation, and MNCN eliminated the fluorescence effect on Raman spectral data. These findings show the feasibility of using MCC for classification problems.

Vibrational spectroscopy is a green, rapid, and affordable analytical tool for analysing the quality, safety, and origin of biological materials in agri-food sectors. Pre-processing spectral data is crucial to removing instrumental interferences and physical artifacts when developing a classification model. However, there has yet to be a consensus on which spectral pre-processing method, settings, and decision parameters to use to optimise pre-processing for different spectroscopy tools. Using an arbitrary criterion poses a risk of applying the wrong type or too severe pre-processing that removes valuable information or affects the model's performance for prediction studies. Matthew's Correlation Coefficient (MCC) - a statistic for parameterising classification performance, accounts for data set imbalance and improved decisions on model selection to express uncertainty on future predictions. Four vibrational spectroscopy instruments [near-infrared (NIR), hyperspectral (HSI), mid-infrared (FTIR), and Raman] were compared using different pre-processing methods to understand the performance using MCC to classify coffee from four countries (Indonesia, Ethiopia, Brazil and Rwanda). Key decision parameters were evaluated for the development of reliable classification models. The best pre-processing for NIR was extended multiplicative scatter correction with mean centering (MNCN), and for HSI, Savitzky-Golay (1st derivative, 15 points) with MNCN. NIR performed the best across all four instruments, with FTIR performing the worst. Raman showed potential for coffee origin classification using the right pre-processing. Pre-processing with weighted least squares, normalisation, and MNCN eliminated the fluorescence effect on Raman spectral data. These findings show the feasibility of using MCC for classification problems.

Plant seeds from the Fabaceae (Leguminosae) family are commonly edible. However, little has been done to study the phytochemicals of red clover (Trifolium pratense) seeds. Our study aims to obtain comprehensive and novel findings on red clover seeds and supercritical fluid extraction (SFE)-extracted oil, with the purpose of exploring their potential as a new source of functional ingredients for food and health care products. In our study, red clover seed oil was extracted by supercritical CO2. Forty-four phytochemical compounds were preliminarily identified in red clover seeds and the extracted oil by UPLC-ESI-MS/MS metabolomics method. These compounds mainly belong to lipids, phenolic compounds, terpenoids and phytosterols. Red clover seeds contain fatty acids (4,676.1 mg/100 g dried seeds) and bioactive components such as phenolic compounds (228.4 mg/100 g) and tocopherols (94.9 mg/100 g). In red clover seed oil, unsaturated fatty acids are over 83% and are rich in linoleic acid (54.7 g/100 g oil) and oleic acid (14.0 g/100 g oil). These findings provide important guidance for introducing red clover seed oil into pharmaceutical products or as functional foods.

Plant seeds from the Fabaceae (Leguminosae) family are commonly edible. However, little has been done to study the phytochemicals of red clover (Trifolium pratense) seeds. Our study aims to obtain comprehensive and novel findings on red clover seeds and supercritical fluid extraction (SFE)-extracted oil, with the purpose of exploring their potential as a new source of functional ingredients for food and health care products. In our study, red clover seed oil was extracted by supercritical CO2. Forty-four phytochemical compounds were preliminarily identified in red clover seeds and the extracted oil by UPLC-ESI-MS/MS metabolomics method. These compounds mainly belong to lipids, phenolic compounds, terpenoids and phytosterols. Red clover seeds contain fatty acids (4,676.1 mg/100 g dried seeds) and bioactive components such as phenolic compounds (228.4 mg/100 g) and tocopherols (94.9 mg/100 g). In red clover seed oil, unsaturated fatty acids are over 83% and are rich in linoleic acid (54.7 g/100 g oil) and oleic acid (14.0 g/100 g oil). These findings provide important guidance for introducing red clover seed oil into pharmaceutical products or as functional foods.

Umami peptides, the flavor compounds mainly derived from natural proteins, provide a pleasant taste for humans and exhibit a variety of biological activities, such as antioxidant and lipid-lowering properties. Marine proteins, which serve as excellent sources of umami peptides, have become a focal point of research. This review introduces the research progress on reported marine umami peptides. Firstly, it discusses the structural characteristics of umami peptides and the mechanism behind their formation to create an umami taste. It then presents several commonly used techniques for preparing and regulating umami peptides while summarizing the advantages and disadvantages of each technique. Finally, this review describes the potential application prospects for core technologies within Industry 4.0—such as molecular simulation, artificial intelligence, big data analysis, cloud computing, and blockchain technology—which could bring new opportunities for the development of marine umami peptides.

Umami peptides, the flavor compounds mainly derived from natural proteins, provide a pleasant taste for humans and exhibit a variety of biological activities, such as antioxidant and lipid-lowering properties. Marine proteins, which serve as excellent sources of umami peptides, have become a focal point of research. This review introduces the research progress on reported marine umami peptides. Firstly, it discusses the structural characteristics of umami peptides and the mechanism behind their formation to create an umami taste. It then presents several commonly used techniques for preparing and regulating umami peptides while summarizing the advantages and disadvantages of each technique. Finally, this review describes the potential application prospects for core technologies within Industry 4.0—such as molecular simulation, artificial intelligence, big data analysis, cloud computing, and blockchain technology—which could bring new opportunities for the development of marine umami peptides.

Carotenoids are colored bioactive substances increasingly used due to their antioxidant properties, vitamin A precursor role, and ability to function as a natural food color. Knowledge of carotenoid behavior during high-heat processing and subsequent storage in emulsified food matrix is essential to expand their application natural food colors and neutraceuticals. Firstly, the physical, thermal, and colloidal stability of emulsions constructed from octenyl succinic anhydride-modified starch (OSA starch)-chitosan multilayered interfaces were investigated. Results of charge reversal from −32.4 ± 1.9 mV to +38.0 ± 0.8 mV indicate that multilayered interfaces were formed in emulsions. As measured by Z-average size, the emulsions were stable after the thermal treatment at 121 °C for 60 min, thus demonstrating a novel heat-stable multilayered emulsion. Subsequently, a select multilayered emulsion was loaded with β-carotene, and its storage stability was assessed. The degradation of β-carotene in an oil-in-water emulsion was better described with zeroth order kinetics; β-carotene dissolved in bulk oil was better described using a second-order kinetic equation. The presence of an encapsulating material around the oil droplets loaded with β-carotene enhanced its stability, which makes it instrumental in extending shelf-life and maintaining a consistent appearance. The results can be used to predict the availability of β-carotene during storage.

Carotenoids are colored bioactive substances increasingly used due to their antioxidant properties, vitamin A precursor role, and ability to function as a natural food color. Knowledge of carotenoid behavior during high-heat processing and subsequent storage in emulsified food matrix is essential to expand their application natural food colors and neutraceuticals. Firstly, the physical, thermal, and colloidal stability of emulsions constructed from octenyl succinic anhydride-modified starch (OSA starch)-chitosan multilayered interfaces were investigated. Results of charge reversal from −32.4 ± 1.9 mV to +38.0 ± 0.8 mV indicate that multilayered interfaces were formed in emulsions. As measured by Z-average size, the emulsions were stable after the thermal treatment at 121 °C for 60 min, thus demonstrating a novel heat-stable multilayered emulsion. Subsequently, a select multilayered emulsion was loaded with β-carotene, and its storage stability was assessed. The degradation of β-carotene in an oil-in-water emulsion was better described with zeroth order kinetics; β-carotene dissolved in bulk oil was better described using a second-order kinetic equation. The presence of an encapsulating material around the oil droplets loaded with β-carotene enhanced its stability, which makes it instrumental in extending shelf-life and maintaining a consistent appearance. The results can be used to predict the availability of β-carotene during storage.

The promising future of natural colors in the food industry aligns with the shift in consumer preference toward healthier food options. These naturally derived ingredients gradually replace their artificial counterparts and find applications in a wide range of food categories, and aquatic products have emerged as one of them. In this work, we introduced the characteristics and extraction of several main types of natural pigments and also explored the positive outcomes of integrating the pigments, such as carotenoids, curcumin, anthocyanins, and betalains, in aquatic product processing and preservation. Their outstanding antioxidant and dyeing properties contribute to the production and storage of various aquatic products. This review aims to provide a comprehensive understanding of the current state of natural pigment applications in aquatic products and to provide inspiration for future research and industry practices.

The promising future of natural colors in the food industry aligns with the shift in consumer preference toward healthier food options. These naturally derived ingredients gradually replace their artificial counterparts and find applications in a wide range of food categories, and aquatic products have emerged as one of them. In this work, we introduced the characteristics and extraction of several main types of natural pigments and also explored the positive outcomes of integrating the pigments, such as carotenoids, curcumin, anthocyanins, and betalains, in aquatic product processing and preservation. Their outstanding antioxidant and dyeing properties contribute to the production and storage of various aquatic products. This review aims to provide a comprehensive understanding of the current state of natural pigment applications in aquatic products and to provide inspiration for future research and industry practices.