Geographical relocation can alter flavor quality in marine crops. Here, the same cultivar of Pyropia haitanensis ("ZHEDONG 1") was cultivated at six sites spanning northern to southern China, and taste- and odor-active compounds were characterized by LC-MS and GC×GC-TOFMS together with environmental measurements. Inosine monophosphate was identified as the major contributor to umami intensity and showed a strong positive association with nitrate levels. A conserved core aroma profile dominated by heptanal, 2-pentylfuran, nonanal, and 2-ethyl-1-hexanol was consistent across regions, whereas differences in their relative abundances led to distinct regional sensory nuances. Correlation analyses further indicated that phosphate, temperature, and pH shaped volatile composition. These results demonstrate that while P. haitanensis retains a genetically determined intrinsic flavor, environmental conditions modulate flavor intensity and aromatic complexity during cross-regional cultivation.

Compositional heterogeneity of oil bodies (OB) from nine high-oleic peanut (HOP) cultivars was systematically characterized. The results demonstrated that nine OB samples exhibited variability in R, G, and B values (red, green, and blue color channels), with the B channel values significantly differing among cultivars, while no significant color variation was observed in their overall appearance. Fats and proteins dominated the dry matter composition of OB, consistent with typical plant OB structural profiles. The high-fat OB of cultivars J572-O, J6-O, Z215-O, and H985-O exhibited outstanding efficiency in loading lipophilic bioactive compounds. OBs from J16-O, G37-O, Z215-O, J572-O, Y37-O, and Y65-O had a distinctive fatty acid profile: high-oleic acid and monounsaturated fatty acids (MUFAs), with reduced linoleic acid, palmitoleic acid, and saturated fatty acids (SFAs). All OB samples contained four tocopherol isomers (α-, β-, γ-, δ-), with α-tocopherol (5.07-12.59 mg/100 g) and γ-tocopherol (6.36-14.81 mg/100 g) as the predominant forms. Essential amino acids (EAAs) and hydrophobic amino acids were detected, with leucine, phenylalanine, and valine being highly abundant. TEAA/TAA and TEAA/TNEAA ratios complied with FAO/WHO standards. J16-O stood out with a balanced fatty acid profile, high tocopherols, and quality protein, making it a promising candidate for functional foods.

Sweeteners are commonly blended to exploit synergistic effects, enabling the desired sweetness to be attained while reducing total usage. However, establishing a quantitative relationship between mixed sweeteners' concentration and sweetness intensity remains a key challenge. This study developed a sensory evaluation-machine learning approach to construct prediction models for binary/ternary mixtures of five sweeteners (sucrose, glucose, fructose, mannitol, and sorbitol). After feature selection of molecular descriptors and comparison of seven machine learning regression models, the Multilayer Perceptron achieved superior performance for the binary mixtures (R2 = 0.9828), while the Support Vector Regression exhibited optimal performance for the ternary mixtures (R2 = 0.9825). Concentration-sweetness intensity curves of mixed sweeteners at specific concentrations were generated using these two optimal prediction models. Results showed that at low concentrations, ternary blends of one sugar and two polyols (mannitol and sorbitol) exhibited stronger synergism than binary mixtures in the same concentration range. Specifically, blending the composite system of 1% mannitol and 2% sorbitol with 1% sucrose, 1% glucose, and 1% fructose separately increased the sweetness intensity by 39.6%, 42.8%, and 37.4%, respectively. This work confirms that machine learning can establish a quantitative relationship between multi-component sweeteners' concentration and sweetness intensity, reveal their complex interactions, and provide a novel approach for intelligent sensory assessment and formulation design.

Pulsed electric field technology possesses a high potential and a bright future in food processing to inactivate microorganisms and reduce enzymatic activity. Processed food shows a higher retention of health-related compounds and an extension of the shelf-life compared to conventional pasteurization methods. This technology is gradually moving from the laboratory and pilot-plant scale to the commercial scale. In the current review, we focus on the way existing knowledge on mathematical modeling and computational approaches is structured, connected, and interpreted across scales. We start with the electroporation models, progressing from those that are derived from simple physical and chemical considerations to those that are based on more complex probabilistic approaches. They attempt to predict how electric pulses create pores in cell membranes and form the basis of kinetic inactivation models. Subsequently, we examine the most common kinetic models of microorganism inactivation, from first-order models to models based on random and probabilistic considerations. We then review the works carried out on the numerical simulations of the electric field in a continuous PEF chamber and the works related to coupled simulations of the electric, fluid flow, temperature, and inactivation kinetic field. Finally, we conclude the manuscript with a section dedicated to the current applications of the PEF process to demonstrate its effectiveness.

Fusarium oxysporum-induced soft rot severely threatens postharvest pitaya quality and storage life, and while vanillin shows promise in the disease management, its mechanisms for controlling pitaya decay remain incompletely understood. In this study, we systematically investigated the molecular mechanism by which vanillin inhibits soft rot in postharvest pitaya, employing physiological and biochemical characterization, bioinformatics analysis, and molecular biology techniques. Compared with control fruit on 10 d, vanillin treatment significantly reduced disease index and lesion area by 27.12% and 67.43%, respectively. Meanwhile, vanillin treatment delayed the degradation of total soluble solids (TSSs) and titratable acidity (TA) and promoted the accumulation of total phenolics and flavonoids. Additionally, vanillin enhanced the activities of defense-related enzymes, such as catalase (CAT), superoxide dismutase (SOD), phenylalanine ammonia-lyase (PAL), β-1,3-glucanase (GLU), chitinase (CHI), peroxidase (POD) and polyphenol oxidase (PPO), and increased antioxidant capacity, as evidenced by increased DPPH radical scavenging capacity and ascorbic acid content. This resulted in reduced oxidative damage, as indicated by decreased levels of malondialdehyde (MDA), H2O2 and O2•-. Yeast one-hybrid (Y1H), dual-luciferase reporter (DLR) and subcellular localization revealed that HuTGA1, a nuclear-localized transcriptional activator, specifically bound to the as-1 cis-acting element and activated expression of HuNPR1 and HuNPR5-1. Transient overexpression of HuTGA1 reduced reactive oxygen species (ROS) accumulation and upregulated related genes. These findings suggest that vanillin treatment might enhance pitaya resistance by activating the HuTGA1-HuNPR signaling module, providing insights into the molecular mechanisms underlying vanillin-induced resistance.

This study investigated the effects of Auricularia auricula Polysaccharide (AAP) concentrations on the rheological and thermal properties of gluten and its subunit components. We used multiple techniques, including dynamic rheology, differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FT-IR), free thiol group analysis, and scanning electron microscopy (SEM). The results revealed that AAP increased the storage (G') and loss (G″) modulus of gluten, glutenin, and gliadin, promoting compact elastic protein networks. DSC and free thiol group analysis demonstrated that AAP enhanced thermal stability and disulfide bond cross-linking in gluten and glutenin, but reduced thermostability and inhibited disulfide formation in gliadin. Secondary structure analysis showed 31.93% and 17.72% increases in α-helix and β-sheet content, respectively, in glutenin at 8% AAP, thereby enhancing the orderliness of the gluten structure and improving structural rigidity, while reducing gliadin's structural order. Microscopy confirmed AAP narrowed gluten matrix pores, forming uniform honeycomb structures (though high concentrations caused disruption). In summary, AAP primarily stabilizes gluten conformation by modulating glutenin structure, thereby enhancing rheological and thermal properties.

Polygonatum sibiricum polysaccharide (PsP), one of the main components of Polygonatumsibiricum used in traditional Chinese food and medicine, has important bioactive functions, but it is difficult to fully utilize PsP because of the degradative effect of digestive gastric juices. This study aimed to innovatively synthesize a new food formulation for PsP, namely, a PsP-hydroxyapatite (HAP) sustained-release system, so as to reduce its degradation. The new food formulation was optimized and evaluated by the response surface method (RSM) and by in vitro experiments. The optimal stirrer temperature, reaction pH, etching pH, and loading time for synthesizing PsP-HAP were 85.62 °C, pH 11.12, pH 8.40, and 5.10 h, respectively, all of which were different from the findings of other similar research studies. The average encapsulation rate of PsP-HAP reached (40.16 ± 1.54)%, and the content of PsP was 8.98%. Additionally, PsP-HAP appeared to be pH-responsive, and its continuous antioxidative effect was first proven by the DPPH assay and then cytologically by a total antioxidative capacity assay. The CCK-8 assay indicated that PSP-HAP did not induce toxicity. This study successfully developed a new food formulation for PsP which appears to have the potential to reduce the degradative effect of digestive gastric juices. Thus, it is possible to achieve full utilization of PsP by using this new sustained-release food formulation.

The use of a portable near-infrared (NIR) spectrometer for detecting sea buckthorn juice SSC has not been explored. In this study, spectral data of 180 juice samples were collected using a portable NIR spectrometer. An SSC prediction model based on a mixture of experts convolutional neural network (MoE-CNN) was proposed. The MoE-CNN model was compared with traditional chemometric models in terms of prediction performance and feature extraction capability. The results showed that detecting the SSC of sea buckthorn juice using a portable NIR spectrometer combined with the MoE-CNN model is feasible. The optimal chemometric model, CARS-PLS, achieved RMSEP and RPD values of 1.42% and 2.67, respectively. The MoE-CNN model outperformed chemometric models and the CNN model, achieving an RMSEP of 1.26% and RPD of 3.02. Compared with CARS-PLSR, MoE-CNN adaptively weighted spectral features through MoE and feature fusion modules, effectively suppressing spectral noise and improving detailed feature extraction. These findings demonstrate that combining a portable NIR spectrometer with MoE-CNN is effective for rapid SSC detection in sea buckthorn juice. This study provides a new approach for the rapid detection of sea buckthorn juice SSC.

Type 2 diabetes mellitus (T2DM) is an endocrine-metabolic disorder characterized by pancreatic islet dysfunction-induced hyperglycemia, which triggers hepatic injury, intestinal microbiota dysbiosis, and systemic complications. Fagopyrum tararicum seeds exhibit various biological activities, including antioxidant, hypolipidemic, and antihypertensive effects. However, there is limited research exploring how supernatants derived from the water extraction-ethanol precipitation of Fagopyrum tararicum seeds (SWEPFT) modulate the intestinal microbiota and their potential link to T2DM. This study evaluates SWEPFT's effects on hyperglycemia and intestinal microbiota in T2DM mice. After a 4-week therapeutic period, SWEPFT markedly ameliorated hyperglycemia, as evidenced by reduced body weight (BW), fasting blood glucose (FBG), and glycated serum protein (GSP) and improved insulin sensitivity/resistance indicators (HOMA-IS/IR) and β-cell function (HOMA-β). Furthermore, the levels of both Akt1 and Slc2a2 transcription displayed notable enhancement. SWEPFT-H (high-dose SWEPFT) exhibited superior effects to SWEPFT-L (low-dose SWEPFT) in improving BW, FBG, and HOMA-IS. Moreover, SWEPFT modulated the intestinal microbiota by decreasing the Firmicutes/Bacteroidetes ratio, augmenting the proportion of Intestinimonas and Ruminiclostridium, and increasing the short-chain fatty acid content. A correlation analysis identified Candidatus_Arthromitus, Anaeroplasma, Candidatus_Stoquefichus, and Harryflintia as potential T2DM biomarkers linked to glycemic regulation. These findings elucidate SWEPFT's critical role in microbiota modulation and hyperglycemia alleviation, providing a novel perspective for T2DM pathogenesis research and therapeutic development.

The effects of grape-seed proanthocyanidins (GSP) and malic acid (MA) on the multiscale structure and digestibility of starch in a bread model were investigated. Fourier transform infrared (FTIR), Raman spectroscopy analyses, long-range order (crystallinity), amylolytic release of glucose, as well as the effect on α-amylase activity of starch in the bread, were determined. The combination of GSP and MA increased the molecular order but decreased the crystallinity of the starch. Amylase fluorescence spectra showed that the α-amylase was notably quenchable by adding GSP and MA, and the inhibition rate of α-amylase reached 10.3%. Confocal Laser Scanning Microscopy (CLSM) imaging confirmed the digestion data in vitro showing that in the presence of 0.3% GSP and 0.5% MA in the bread, the glucose release of the bread was reduced to 5.43%. These findings demonstrate that GSP and MA can effectively modulate starch structure and digestibility in bread, offering a strategy to control glucose release in baked foods.