Prior studies on Ganoderma lucidum spore oil (GLSO) rarely systematically explored its storage oxidative deterioration mechanism via multi-marker combined characterization. This study innovatively integrated the Schaal oven accelerated storage test and dual-NMR detection (LF-NMR and 1H NMR) to evaluate the oxidative stability of GLSO over 60 d. Dynamic changes in routine oxidation indices, glycerol core aldehydes (GCAs), phytosterols and their triterpenoid biosynthetic precursors, fatty acids and volatile compounds were synchronously tracked. Results revealed complex fluctuating accumulation of primary and secondary oxidation products; non-volatile GCAs exhibited continuous monotonic growth and acted as reliable markers for severe GLSO oxidation. Unsaturated fatty acids and phytosterols and their triterpenoid biosynthetic precursors degraded in a structure-dependent pattern, with phytosterols and their triterpenoid biosynthetic precursors degradation sensitivity ranked as squalene > lanosterol > β-sitosterol. Correlation analysis clarified the intrinsic linkage between fatty acid substrates and oxidation derivatives. This work innovatively reveals the complete lipid oxidation pathway of GLSO, offering novel theoretical references and multi-index evaluation strategies for quality control and preservation of high-grade GLSO products.

Ganoderma lucidum spore oil (GLSO) is a fat-soluble bioactive substance extracted from cell-wall-broken Ganoderma lucidum spore powder, and it holds broad application prospects in the fields of functional foods and pharmaceuticals. This paper provides a systematic review of research progress regarding its preparation technology, bioactive components, and multidimensional pharmacological mechanisms. Supercritical CO2 extraction has become the mainstream method for industrial production due to its green and efficient nature and the absence of solvent residues. GLSO is rich in monounsaturated fatty acids, triglycerides, steroids, and triterpenoids, among which, monounsaturated fatty acids, primarily oleic acid, serve as the key molecular basis for its immunomodulatory and antitumor activities. Although triterpenoid components are regarded as important indicators for evaluating Ganoderma quality, existing detection technologies still have limitations, and it is currently inappropriate to use them as the sole standard for quality control. In terms of pharmacological mechanisms, GLSO exhibits significant multiple biological activities, including antitumor, immunomodulatory, and antioxidant effects. Its antitumor mechanism demonstrates multi-target synergistic characteristics. Although GLSO holds promising prospects for application, it still faces challenges such as technical bottlenecks in triterpenoid detection, a lack of clinical evidence, and limited product forms. In the future, the realization of the industrialization of GLSO will require the establishment of standardized production processes and precise quality monitoring systems. Through clinical trials, this will drive high-quality development in both precision nutrition and pharmaceutical-grade applications.

Button mushrooms (Agaricus bisporus) are highly perishable, undergoing rapid browning and moisture loss during postharvest cold storage. These physicochemical degradations can be sensitively captured by visible-near-infrared (Vis-NIR) spectral characteristics. In this study, a rapid and non-destructive analytical strategy integrating Vis-NIR hyperspectral imaging (400–1000 nm) with a novel deep learning framework was developed to accurately evaluate postharvest freshness dynamics. Hyperspectral data from 400 mushroom cap samples were collected over a 9-day refrigerated storage period at 2-day intervals. To overcome the challenges of mining high-dimensional spectral-spatial data, a patch-aligned multimodal interaction fusion network (PAMIF-Net) was proposed. This end-to-end architecture dynamically fuses global Vis-NIR spectral features-reflecting internal compositional changes-with spatial morphological features characterizing surface deterioration, thereby preventing the information loss typical of traditional stepwise modeling. A gated attention mechanism was introduced to adaptively weight the contributions of spectral and spatial representations. This significantly enhanced the interpretability, stability, and robustness of the model in processing complex Vis-NIR hyperspectral data. Across 10 independent trials, the optimized PAMIF-Net achieved 100.00% classification accuracy and a 0.00 mean absolute error for five-class storage time recognition. Furthermore, it exhibited superior performance over conventional machine learning and classical deep learning architectures regarding spectral feature extraction, convergence speed, and inference efficiency. This study demonstrates that Vis-NIR hyperspectral imaging, when coupled with the proposed multimodal deep learning framework, provides a reliable, interpretable, and highly efficient tool for non-destructive freshness monitoring. It also offers a valuable methodological reference for applying advanced chemometric-spectral analyses to the quality evaluation of horticultural products.

Accurate and non-destructive assessment of plant nutritional status remains a key challenge in precision agriculture, particularly under dynamic physiological conditions such as dehydration. Therefore, this study focused on developing an integrated nutritional assessment framework for avocado (Persea americana Mill.) leaves across progressive dehydration stages using spectral analysis. A novel nutritional function index (NFI) was innovatively constructed using an entropy-weighted multi-criteria decision-making approach. This unified assessment metric integrated critical physiological indicators, such as moisture content, nitrogen content, and chlorophyll content estimated from soil and plant analyzer development (SPAD) readings. To enhance the prediction accuracy and interpretability of NFI, innovative vegetation indices (VIs) specifically tailored to NFI were systematically constructed using exhaustive wavelength-combination screening. Optimal wavelengths identified from short-wave infrared regions (1446, 1455, 1465, 1865, and 1937 nm) were employed to build physiologically meaningful VIs, which were highly sensitive to moisture and biochemical constituents. Feature wavelengths selected via the successive projections algorithm and competitive adaptive reweighted sampling further reduced spectral redundancy and improved modeling efficiency. Both feature-level and algorithm-level data fusion methods effectively combined VIs and selected feature wavelengths, significantly enhancing prediction performance. The stacking algorithm demonstrated robust performance, achieving the highest predictive accuracy (R2V = 0.986, RMSEV = 0.032) for NFI estimation. This fusion-based modeling approach outperformed conventional single-model schemes in terms of accuracy and robustness. Unlike previous studies that focused on isolated spectral predictors, this work introduces an integrative framework combining entropy-weighted feature synthesis and multiscale fusion learning. The developed strategy offers a powerful tool for real-time plant health monitoring and supports precision agricultural decision-making.

Starch digestibility is a key factor influencing postprandial glycemic response. This study compared the effects of hydrolyzed endogenous proteins from corn flour, treated with different proteases, on starch digestibility. Results showed that the papain-treated group (CF-Pa) had significantly higher resistant starch (RS) content (32.01%) than other groups, while the deproteinized corn flour (CF-Pr) exhibited the lowest RS content (8.43%), highlighting the crucial role of endogenous protein components in modulating starch digestibility. Further analysis revealed enhanced short-range order and double-helix structure in CF-Pa starch, along with relatively high inhibitory activity of its protein hydrolysates against amyloglucosidase (up to 30%). Multiscale structural characterization suggested that papain hydrolysis modestly altered protein secondary structure—most notably increasing the proportion of β-turns—and delayed starch gelatinization, changes that may collectively reduce the accessibility of amylolytic enzymes to starch substrates. Compared to the corn flour group (CF), the protein hydrolysates further reduced the resistant starch content on the basis of the protein barrier, highlighting the role of protein hydrolysates in delaying starch digestion. The research results provide a theoretical basis for the development of low-glycemic-index starch-based foods, and confirm that the treatment with papain is an effective strategy for delaying the digestion of starch.

The real-time, non-destructive freshness monitoring of highly perishable Agaricus bisporus was identified as a critical task for postharvest supply chains. While hyperspectral imaging (HSI) demonstrated strong capabilities in capturing physiologically plausible quality assessments, its practical deployment was frequently hindered by high hardware costs and environmental constraints. To bridge the gap between advanced spectral analysis and accessible edge devices, an asymmetric cross-modal knowledge distillation (CMKD) framework was proposed. Initially, a hyperspectral teacher network, integrating a differentiable spectral gate-compression (DSGC) module and a bidirectional selective state-space (Mamba) encoder, was designed to extract physiological deterioration patterns from paired HSI-RGB observations. Subsequently, the learned spectral representations were distilled into a highly efficient RGB-only student network (LiteMobileStudent, 0.2 M parameters) via an annealed feature alignment and delayed logit-matching strategy. Operating exclusively on standard digital RGB images, the distilled student network achieved a classification accuracy of 81.11% and a regression root-mean-square error of 1.37 days. This performance effectively outperformed several standard lightweight convolutional architectures while maintaining a low computational footprint. To evaluate its practical feasibility, the framework was integrated into a smartphone-based edge computing application. Supported by a robust four-level hierarchical segmentation pipeline to mitigate complex background interferences in retail environments, the edge engine achieved an inference latency of 18.6 ms on a standard mobile CPU. By transferring spectrally-informed features into a mobile RGB interface, this study presented a scalable and computationally efficient AI solution, demonstrating practical potential for postharvest quality management in agricultural Internet of Things ecosystems.

Button mushrooms (Agaricus bisporus) are highly perishable and undergo rapid browning, moisture loss, and quality degradation during postharvest cold storage, which can be sensitively reflected by the changes in Vis-NIR spectral characteristics. In this work, a rapid, non-destructive analytical strategy based on Vis-NIR hyperspectral imaging (400–1000 nm) combined with a novel deep learning framework was developed for the accurate evaluation of postharvest freshness and quality changes in button mushrooms. Hyperspectral data were collected from 400 mushroom cap samples stored under refrigerated conditions for up to 9 days, with parallel sampling performed at 2-day intervals. To address the difficulty of effective information mining from high-dimensional infrared hyperspectral data, a patch-aligned multimodal interaction fusion network (PAMIF‐Net) was proposed. This end-to-end architecture dynamically fused global Vis-NIR spectral features reflecting the compositional changes of mushrooms, and spatial texture/morphological features characterizing surface quality deterioration, avoiding information loss caused by traditional stepwise modeling methods. A gated attention mechanism was introduced to adaptively weight the contributions of infrared spectral and spatial features, which significantly improved the interpretability, stability, and robustness of the model in infrared spectral data processing. The optimized PAMIF‐Net achieved 100.00% classification accuracy and 0.00 mean absolute error for five-class storage time recognition across 10 independent repeated trials. It also exhibited superior performance over conventional machine learning approaches and classical deep learning architectures in terms of infrared feature extraction efficiency, convergence speed, and inference efficiency. This study demonstrates that Vis-NIR hyperspectral imaging combined with the proposed multimodal deep learning model provides a reliable, interpretable, and high-efficiency technical tool for non-destructive monitoring of postharvest freshness dynamics. The proposed method also offers a valuable reference for the application of infrared spectral imaging technology in the non-destructive quality analysis of horticultural products.

Ganoderma lucidum, a medicinal and edible fungus with active components possessing antioxidant, anti-inflammatory, and anti-cancer properties, has attracted global attention and been extensively cultivated since the 1970s. Its cultivation and active component extraction methods affect yield and active ingredient content. Traditional segmented wood cultivation of fruiting bodies faces continuous cropping obstacles (e.g., cellulose degradation, soil physical-chemical changes, reduced enzyme activity, increased microorganisms, and higher endogenous organic acids in G. lucidum), while substitute cultivation avoids such issues and utilizes agricultural by-products. Active ingredients are extracted via solvent, ultrasonic-assisted, or enzyme-assisted methods. Though deep eutectic solvents (e.g., ethanolamine-o-cresol) achieve high polysaccharide content (92.35mg/g), they raise food safety concerns, making natural deep eutectic solvents (e.g., betaine-lactic acid, choline chloride-lactic acid) potential substitutes. Extracted active components are mainly used as functional food ingredients but have limited addition due to bitterness; emerging technologies (e.g., multi-sensory integration, encapsulation technology) can reduce bitterness while maintaining nutritional activity. This review summarizes G. lucidum cultivation and extraction methods to facilitate high-yield, high-quality production and promote its food industry development.

The frying process is an effective method for producing food with desirable sensory attributes. However, this process may also lead to the formation of deleterious compounds. This study primarily investigates the inhibitory effects of anti-foaming agent (AFA, a silicone-based compound), tert-butylhydroquinone (TBHQ), and tea polyphenols (TP) on the generation of lipid oxidation products during the frying process. AFA offers superior protection against triacylglycerol degradation during frying compared to TP and TBHQ. In the AFA group, the degradation rates of LLL, OLL, and LLP remained below 30

Iron deficiency is a global health issue, making the development of novel iron supplements to enhance iron absorption critically important. In this study, low molecular weight donkey-hide gelatin peptides (LMW DHGP) were enzymatically hydrolyzed from donkey-hide gelatin. Experimental results demonstrated that the iron chelating capacity of LMW DHGP reached 249.98 μg/mg. Key amino acids (Asn, Gly, Cys, Lys) may participate in chelation. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis showed rough, porous amorphous structures of LMW DHGP-iron complexes. The results of circular dichroism spectroscopy (CD) indicated that the self-assembly of LMW DHGP-iron complexes appears to be primarily mediated by peptide α-helical structural conformations. Fourier transform infrared (FTIR) spectroscopy further indicated that the interaction between LWM DHGP and Fe2+ likely occurs through carboxyl and amino functional groups. In vitro digestion stability studies demonstrated that LMW DHGP-iron complexes exhibited superior iron ion solubility compared to FeSO4 in simulated gastrointestinal conditions. PGPAG-iron complexes exhibited the highest antioxidant activity, with scavenging rates of 71.64% (DPPH radical) and 88.79% (ABTS radical). These findings collectively suggest that LMW DHGP-iron complexes possess significant potential as a novel iron supplement in food applications, which provides valuable theoretical insights for the development of innovative iron supplementation strategies.

Steam explosion (SE) was applied to enhance the grinding performance and physicochemical properties of Ganoderma lucidum (GL), and the effects of steam-exploded Ganoderma lucidum powders (SGL) on quality characteristics of wheat dough were investigated. Results showed that SE significantly improved the grindability and functional properties of GL at 0.7 MPa for 5 min. Compared to native GL, SE effectively disrupted the GL structure, reducing the average particle size by 64.87% and power consumption during grinding by 8.95%. Additionally, SE increased the cell wall breakage rate by 129.51%, water solubility index by 79.27%, and crude polysaccharides content by 7.99 times, as well as total phenolics content by 46.30%. Aqueous, ethanol, and acetone extracts of SGL exhibited significant DPPH radical scavenging activity. A guidance table for incorporating SGL (0.7 MPa, 5 min) into dough was developed, showing that the strength and tolerance of dough mixing were enhanced or maintained with the addition of 8% and 10% SGL. The inclusion of 8% SGL in dough resulted in a higher Delta pH during fermentation. Furthermore, SGL improved the dough's elasticity by increasing the elastic modulus and reducing the tan delta. This study contributes to the increased utilization of GL resources and the development of functional food.

The deterioration of frying oil significantly affects the quality of fried foods, leading to the formation of harmful oxidation products. This study examined how triacylglycerol (TAG) degradation influences both non-volatile and volatile oxidation products in frying oils. The sn-1/3 position of unsaturated fatty acyl chains was key to TAG degradation during frying. After 32 h, soybean oil showed higher levels of polymerized TAG products, 2,4-decadienal, (E)-2-heptenal, (E,E)-conjugated dienes, 4-oxo-alkanals, and epoxides compared to other oils. Rapeseed oil, however, had higher levels of glycerol core aldehydes, (E,E)-2,4-alkadienals, and n-alkanals. Correlation analysis suggested that thermal oxidation was more pronounced in the unsaturated TAGs of soybean and rapeseed oils, likely due to their abundant free radicals and low short-chain fatty acid content. The polar compound composition of TAG heating systems further supported the above conclusions. These results provide a better understanding of oxidative degradation in frying oils, focusing on TAG profiles.

Polar compounds are complex, heterogeneous substances associated with various chronic diseases. In this study, we applied kinetic models to characterise the formation of total polar compounds (TPC), triacylglycerol oligomers (TGOs), triacylglycerol dimers (TGDs), oxidized triacylglycerol monomers (OxTGs), and diacylglycerols (DGs) under different frying conditions. After 32 h of frying, the contents of TPC, OxTGs, TGDs, TGOs, and DGs in the oils ranged from 3.95 % to 35.70 %, 1.63 % to 5.95 %, 2.82 % to 10.87 %, 1.08 % to 9.50 %, and 2.93 % to 16.34 %, respectively. The results revealed variable degradation kinetics across frying systems. Elevated temperatures, frying of chicken nuggets, ferric sulfate addition, and discontinuous frying promoted the formation of OxTGs, TGDs, and TGOs. In contrast, the addition of tert-butylhydroquinone inhibited their formation. These findings provide a kinetic basis for controlling the formation of polar compounds during frying

In order to improve the poor mechanical properties and strong hydrophilicity of soluble soybean polysaccharide (SSPS) based films, licorice residue extract (LE) was introduced into the film-forming matrix. In this study, the effect of the amount of LE on the microstructure, physical and functional performances of the SSPS-based films, and its antioxidant activity and practical application in delaying the oxidation of oil-fried peanuts were investigated. The results showed that the compounding of LE increased the tensile strength (TS) by 4.39 times, decreased the WVP to 62 %, and increased the contact angle by 17.77 %, respectively. FTIR and SEM analyses verified the formation of intermolecular hydrogen bonds among LE, glycerol and SSPS. Furthermore, radical scavenging activity experiments proved that the films possessed a superior capacity to scavenge DPPH and ABTS•+ radicals up to 63.51 % and 93.10 % respectively, when the LE dosage was at 10 %. It is worth noting the shelf life of oil-fried peanut was extended by about 3.25 d at 60 °C (~65 d at 20 °C) with the packaging of SSS-LE8 film. The preparation of SSPS-LEx film could promote the development of biomass-based packaging materials and their preservation applications in nuts and other products.

Gelatin from bovine hide, especially yak hide, is valued in the food and pharmaceutical industries; however, as the most common domestic cattle in China, gelatin made from yellow cattle hide remains unexplored. Thus, the physicochemical properties, nutritional components, and flavor characteristics of gelatin produced from yellow cattle hides and yak hides, both before and after hair removal, were analyzed. It was found that yellow cattle hide gelatin (YCHG) not only had a higher protein content (68.45–71.51%) than yak hide gelatin (YHG) (66.81–67.56%) but also had a higher Fe content (86.75 ± 1.650 mg/kg). Additionally, 17 amino acids were detected in the four bovine hide gelatin samples; among them, dehaired yellow cattle hide gelatin (DYCHG) was richer in sweet-tasting amino acids than the others. Notably, non-dehaired yellow cattle hide gelatin (NDYCHG) featured 4-methyl-3-penten-2-one (with a honey aroma), whereas non-dehaired yak hide gelatin (NDYHG) featured β-pinene, 1-nonanal, acetic acid-D, (E)-2-pentenal, and allyl sulfide. Therefore, yellow cattle hide gelatin (YCHG) exhibits prominent nutritional and flavor properties, suggesting its potential as an alternative raw material for food industry applications.

Canning substantially alters fruit aroma, yet the integrated dynamics of these changes remain unelucidated. This study employed comprehensive two-dimensional gas chromatography-olfactometry-time of flight mass spectrometry (GC × GC-O-TOF MS), sensory analysis, and multi-omics to elucidate the dynamic evolution of 31 key aroma-active compounds (odor activity value, OAV ≥ 1) and their precursors during yellow peach canning. Partial least squares-discriminant analysis (PLS-DA, R2 > 0.65, Q2 > 0.46) validated 41 discriminative metabolites (variable importance in projection, VIP > 1), while Spearman correlations (|r| > 0.5, p < 0.05) highlighted linolenic acid, linoleic acid, leucine, phenylalanine, and fructose as pivotal precursors. Thermal processing shifted aroma generation from enzymatic to non-enzymatic pathways, producing "roasted, fruity" notes via Maillard reactions, lipid and carotenoid degradation. Supplemental sucrose enhanced aroma complexity by derivatizing substrates and modulating viscosity/moisture activity. This work establishes a detailed aroma-metabolic map for canned yellow peaches, providing insights to support quality control in fruit processing.

This study examines the effects of four rapeseed varieties, differing in erucic acid (EA) and glucosinolate (GSL) levels, on the flavor profile of fragrant rapeseed oil (FRO). Total phenolic content and β-tocopherol serve as indicators of FRO's nutritional quality during roasting. Notably, GSLs had a greater effect on the flavor profile than EA. The stronger pungent-like odor in FROs derived from high-GSL rapeseed varieties (LEHG and HEHG) is likely attributed to elevated concentrations of methallyl cyanide, 2,4-pentadienenitrile, 5-(methylthio)-pentanenitrile, benzenepropanenitrile, 6-(methylthio)-hexanenitrile, 5-cyano-1-pentene, 3-methylcrotononitrile, 2-pentenenitrile, and 4-isothiocyanato-1-butene. Additionally, the fatty-like odor was most pronounced in HEHG samples due to increased levels of hexanal, (E,E)-2,4-heptadienal, and nonanal. For LELG and HEHG, the duration of roasting had a more significant impact on the development of FRO flavor than the roasting temperature did. These results may facilitate the selection of rapeseed varieties for FRO production.

Broken Ganoderma lucidum spore powder (BGLSP) is abundant in nutrients and bioactive compounds, rendering it a suitable functional raw material for food applications. This study examined the impact of incorporating BGLSP (ranging from 0.5% to 10%) on the physicochemical properties of flour blends, dough, and the quality of Chinese steamed bread (CSB). The results indicated that with increasing BGLSP content, the a* value, onset temperature, peak temperature, water absorption, development time, and dough stability all exhibited an upward trend in the flour blends and dough, while the L* value and protein network weakening decreased. When compared to the control sample, the inclusion of 10% BGLSP resulted in a reduction in the spread ratio, specific volume, cohesiveness, and springiness of CSB, while simultaneously increasing its hardness, chewiness, and gumminess. The observed odor variations among samples were primarily ascribed to the proportions of aldehydes and ketones. Notably, sensory evaluation demonstrated that the flavor attributes of BGLSP-enhanced samples were superior to those of the control sample. In conclusion, the incorporation of BGLSP at concentrations ranging from 0.5% to 1% is deemed optimal for CSB, offering novel insights into the application of BGLSP within the food industry.

Steam explosion (SE, at 0.3-0.7 MPa for 3-7 min) was employed to modify the physicochemical properties of Tartary buckwheat (TB) flour, and the eating quality and starch digestibility of corresponding gluten-free wholegrain TB cookies was assessed. The results illustrated that SE enhanced the water-extractable arabinoxylans content in TB flour by 24%-152%. SE increased the random coil content while decreasing the alpha-helix content, and starch of SE flours had lower relative crystallinity and degree of short-range order. The water-holding capacity significantly increased with SE at moderate conditions. Additionally, SE flours enhanced the spread ratio of the cookies. Compared to cookies made with native TB flour, the digestibility of starch in cookies made with SE flour was significantly lower, and their resistant starch content was higher. The sensory evaluation attributes of SE cookies were superior to those of native cookie in terms of texture, smell, and form attributes. This study elucidates the action mechanism of SE modification on the properties of TB flours and cookies, offering a reference for the application of SE treatment on whole grain processing.

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