Raisins, known for their delicious taste and high nutritional value, are among the most widely consumed dried fruits globally. The natural waxy layer on the surface of grapes impedes water migration, making pretreatment necessary before drying. This study evaluated the effects of various pretreatment methods on the nutritional and functional quality of seedless purple raisins. By using non-pretreated dry seedless purple raisins as a control, the impact of physical and chemical pretreatment methods on the nutritional and functional qualities of seedless purple raisins was assessed through the analysis of nutrient content, phenolic compounds, and antioxidant activity. Our results demonstrate that physical pretreatment significantly increases the levels of vitamin C, fructose, glucose, total acid, total phenolics, total flavonoids, total anthocyanins, and antioxidant activity compared to chemical pretreatment and the control group. The correlation analysis revealed that phenolic substances were closely linked to antioxidant capacity. Additionally, phenolic compounds, including resveratrol, ferulic acid, chlorogenic acid, ethyl coumarate, and cinnamic acid, were more abundant following physical pretreatment. The OPLS-DA model effectively differentiated the three groups of processed samples, showing that different pretreatments significantly affect the nutritional and functional quality of seedless purple raisins. These findings suggest that physical pretreatment offers considerable potential for improving the drying quality of seedless purple raisins.

Wheat is a major staple crop in Xinjiang, China; however, comprehensive data on Fusarium mycotoxin contamination in wheat from this region remain limited. Despite recent observations of Fusarium head blight (FHB), few studies have characterized the mycotoxin profiles in wheat from Xinjiang, especially regarding emerging mycotoxins. This study aimed to systematically investigate the occurrence of both conventional and emerging mycotoxins in freshly harvested wheat from Xinjiang, to evaluate the effects of sampling year and geographical region on mycotoxin contamination levels, and to identify the Fusarium species responsible for mycotoxin production. A total of 151 freshly harvested wheat samples were collected from Southern and Northern Xinjiang in 2023 and 2024. Mycotoxins were quantified using high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS). Fusarium isolates were obtained and identified through the translation elongation factor 1-alpha (TEF-1α) gene sequencing. Genotyping was assessed by genotype-specific multiplex PCR, and mycotoxigenic potential was detected by rice culture assays. A high incidence (72.9%) of co-contamination with multiple mycotoxins was observed. Conventional mycotoxins such as deoxynivalenol (DON) and zearalenone (ZEN) were detected in 31.1% and 41.1% of samples. Notably, emerging mycotoxins, including enniatins (ENNs) and beauvericin (BEA), were present at significantly higher concentrations than those reported in some regions of China. Significant spatiotemporal variation was observed, with markedly higher contamination levels of emerging mycotoxins in 2024, particularly in Northern Xinjiang, where the symptoms of FHB epidemic occurred due to the humid climate and maize–wheat rotation system. Fusarium graminearum was identified as the primary producer of conventional mycotoxins, while F. acuminatum and F. avenaceum were mainly associated with emerging mycotoxins except BEA. This study provides the first comprehensive dataset on the co-occurrence of conventional and emerging Fusarium mycotoxins in wheat from Xinjiang and highlights significant spatiotemporal variations influenced by environmental factors. These findings underscore the necessity for continuous, region-specific monitoring and effective risk management strategies to address the evolving mycotoxin threat in Xinjiang’s wheat. Future research should focus on characterizing the populations of Fusarium toxin-producing fungi and the long-term impacts of mycotoxin exposure on food safety.

Almond-derived peptide fractions (APs) represent a promising yet underexplored class of plant-based bioactive compounds for ulcerative colitis (UC) management. This study investigated the protective effects of APs against dextran sulfate sodium (DSS)-induced colitis in male BALB/c mice using integrated 16S rRNA sequencing and transcriptomic analysis. Mice received low-dose (200 mg/kg) or high-dose (400 mg/kg) APs during 7-day DSS administration. Both doses significantly attenuated body weight loss, disease activity index, colon shortening, and histopathological damage. Compared with the DSS group, low-dose and high-dose APs reduced disease activity index by 65.9% and 52.4%, increased colon length by 30.0% and 26.5%, decreased histopathological scores by 39.6% and 55.1%, and lowered colonic myeloperoxidase activity by 13.9% and 34.1%, respectively. APs also modulated inflammatory cytokines, improved mucus-barrier-related indices, and enhanced continuous ZO-1 localization at epithelial junctions. Additionally, 16S rRNA sequencing indicated that AP treatment was associated with altered genus-level microbiota profiles after DSS exposure, including changes in Ligilactobacillus, Escherichia-Shigella, and Parabacteroides-related taxa. Transcriptomic analysis suggested dose-associated response patterns: low-dose APs were associated with broader immune-related transcriptional changes, whereas high-dose APs were more closely associated with extracellular matrix organization, focal adhesion, and genes enriched in the PI3K-Akt signaling pathway. These findings support the protective effects of APs in DSS-induced acute colitis and suggest potential associations among microbiota alterations, host transcriptional responses, and mucosal repair.

Reliable potato quality monitoring during postharvest handling requires compact sensing systems that can acquire chemically relevant information while operating on irregular tuber surfaces. In this study, a Flexible Spectral Sensing Gripper (FSSG) was developed by integrating a low-cost 12-channel visible/near-infrared (Vis/NIR) spectral sensor array, electronic components, and an ESP32-S microcontroller onto a flexible printed circuit (FPC) substrate encapsulated with PDMS. By embedding the sensing units into the grasping interface, the FSSG enables conformal, multi-point spectral acquisition during potato handling, reducing optical-coupling uncertainty associated with unstable contact. Spectral reflectance data were collected from potato tubers, and dry matter content (DMC) and starch content (SC) were determined by standard chemical analysis as reference values. Multiple linear regression (MLR) and partial least squares regression (PLSR) models were compared under Norm, SNV, MSC, SNV-Norm, and MSC-Norm preprocessing conditions, and support vector machine (SVM) classification was used to distinguish healthy and artificially induced deteriorated samples. Normalization combined with MLR provided the best performance among the evaluated regression approaches, achieving cross-validation coefficients of determination ($R_{CV}^2$) of 0.847 and 0.817 and RPD values of 2.557 and 2.345 for DMC and SC, respectively. The SVM model achieved 98.67% accuracy for healthy versus artificially induced deteriorated potato samples. Overall, the FSSG demonstrates the value of combining gripper-integrated spectral sensing with interpretable chemometric modeling for potato quality screening. The FSSG enables real-time non-destructive quality prediction and disease-detected classification of potatoes, improves sorting accuracy and production efficiency, and provides general sensing solutions for controlled-environment agriculture, cold-chain logistics, and value-added processing of agricultural products.

A flexible visible/near-infrared (Vis/NIR) sensing system (FVNS) was developed for the non-destructive assessment of almond composition. Almonds from four distinct varieties were measured under non-contact conditions, and the acquired spectra were preprocessed using Savitzky–Golay (S–G) smoothing and standard normal variate (SNV). Based on the spectral data captured by the FVNS, random forest (RF) regression models were established to quantify protein and fat contents. The optimized RF models achieved prediction coefficients of determination (R²_p) of 0.91 for protein and 0.86 for fat, with corresponding residual predictive deviation (RPD) values of 3.32 and 2.67, respectively. These results demonstrate that the FVNS possesses reliable quantitative capability and can accurately capture compositional variations in almonds while maintaining low cost, portability, and real-time wireless operation.

LBP (300 μg/mL) partially restores glucose consumption and glycogen content. Transcriptomic analysis suggests that these protective effects are potentially associated with the upregulation of glycerophospholipid–DAG-PtdOH signaling and ULK1-dependent autophagy. These preliminary findings provide transcriptional insights into a potential dual botanical mechanism, though further protein-level validation is required. Objective: The objective of this study was to investigate the ameliorative effects of LBP on palmitic acid (PA)-induced cellular dysfunction (or insulin signaling impairment) in HepG2 cells and the potential molecular mechanisms. Methods: LBP was extracted by hot water extraction–ethanol precipitation and characterized by the phenol-sulfuric acid method, Fourier-transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR) spectroscopy for content determination and structural characterization. The CCK-8 assay was used to determine the safe concentrations of PA and LBP. Glucose consumption and glycogen content were measured by the glucose oxidase method. Transcriptome sequencing combined with GO and KEGG enrichment analyses was performed to screen key pathways and differentially expressed genes (DEGs). RT-qPCR was used to validate the mRNA expression of DGKA, LPIN1, and ULK1. Results: LBP was identified as a pyranose-type acidic heteropolysaccharide containing uronic acid. Compared with the control group, PA treatment significantly decreased glucose consumption and glycogen content (p < 0.05), both of which were significantly ameliorated by 300 μg/mL LBP intervention (p < 0.05). Transcriptome sequencing identified 1752 DEGs, and KEGG enrichment analysis indicated that LBP treatment was associated with transcriptional changes in glycerophospholipid metabolism, AMPK signaling, and autophagy pathways. RT-qPCR further showed that LBP significantly upregulated the mRNA expression of DGKA, LPIN1, and ULK1 (p < 0.05). However, these mechanistic insights are limited to the transcriptional level and require further protein-level validation. Conclusions: LBP exhibited protective effects against PA-induced insulin signaling impairment in HepG2 cells, which were potentially associated with the transcriptional regulation of the DAG-PtdOH metabolic axis and AMPK/ULK1 pathway-related genes. However, these mechanistic inferences are speculative and require validation via protein and inhibitor experiments.