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A novel allele of Sh1 facilitates the development of waxy-sweet corn from waxy corn.

Waxy corn and sweet corn represent 2 major classes of fresh-eating corn, each with distinct sensory attributes and nutritional compositions. Developing a new variety that combines both waxy and sweet traits would address rising consumer demand and expand new market potential. From a fast neutron-mutagenized population of the waxy corn inbred line HB522, we isolated a novel mutant, designated as wx-sweet, whose kernels simultaneously exhibit waxy and sweet characteristics at the milk-filling stage. Through bulked segregant analysis combined with fine mapping, we mapped the causal locus to SHRUNKEN1 (Sh1) on chromosome 9, which was confirmed by an allelism test with a characterized Mu-insertion allele of Sh1. A 7,227-bp Copia-type long terminal repeat retrotransposon insertion was identified in exon 2 of Sh1 in the wx-sweet mutant by long-read sequencing. Consistently, the novel sh1 allele significantly reduced sucrose synthase activity. Genetic and physiological analyses demonstrate that sh1 and wx1 act synergistically to fine-tune carbohydrate metabolism in the endosperm. Integrated transcriptomic and metabolomic profiling uncover extensive transcriptional reprogramming and redirected metabolic flux, leading to substantial accumulation of sucrose and a range of oligosaccharides. These metabolic shifts underlie the unique simultaneous dual waxy-sweet texture in fresh-eating wx-sweet kernels. In summary, our work not only provides valuable genetic resources for breeding next-generation fresh-eating corn but also, for the first time, elucidates the molecular mechanism by which the sh1 and wx1 mutations cooperatively shape the waxy-sweet endosperm phenotype.

Zea mays

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas

The transcription factor PavERF28 promotes fruit softening by regulating cell wall degradation in sweet cherry (Prunus avium L.).

Fruit softening is a critical determinant of shelf life and marketability in sweet cherry (Prunus avium L.). This process is predominantly driven by cell wall disassembly, which is tightly regulated by transcription factors. Despite evidence for ethylene's role in sweet cherry softening, how these signals are transduced to regulate the expression of cell wall-modifying genes is unclear. Here, we identified the ethylene-responsive transcription factor PavERF28 as a key regulator in this process. Overexpression of PavERF28 significantly upregulated the transcriptional levels of genes involved in pectin degradation (including genes encoding polygalacturonase, pectin methylesterase inhibitor, and pectate lyase), thus effectively enhancing fruit softening. Moreover, heterologous overexpression of PavERF28 in tomato confirmed its function in promoting fruit softening. At the molecular level, PavERF28 was shown to directly activate the expression of two polygalacturonase genes (PavPG1 and PavPL5) by binding to their promoters, which catalyze pectin depolymerization and thus drive softening. Collectively, our work provides an in-depth elucidation of the regulatory mechanism by which ERF family members control fruit softening in sweet cherry and offers potential targets for the manipulation of fruit ripening, especially softening.

Cell Wall

Multiomics analyses provide insights into the genomic basis of differentiation among four sweet osmanthus groups.

Sweet osmanthus (Osmanthus fragrans) is famous in China for its flowers and contains four groups: Albus, Luteus, Aurantiacus, and Asiaticus. Understanding the relationships among these groups and the genetic mechanisms of flower color and aroma biosynthesis are of tremendous interest. In this study, we sequenced representative varieties from two of the four sweet osmanthus groups. Multiomics and phylogenetic analyses of varieties from each of the four groups showed that Asiaticus split first within the species, followed by Aurantiacus and the sister groups Albus and Luteus. We show that the difference in flower color between Aurantiacus and the other three groups was caused by a 4-bp deletion in the promoter region of carotenoid cleavage dioxygenase 4 (OfCCD4) that leads to expression decrease. In addition, we identified 44 gene pairs exhibiting significant structural differences between the multiseasonal flowering variety "Rixianggui" in the Asiaticus group and other autumn-flowering varieties. Through correlation analysis between intermediate products of aromatic components and gene expression, we identified eight genes associated with the linalool and α- and β-ionone biosynthesis pathways. Overall, our study offers valuable genetic resources for sweet osmanthus, while also providing genetic clues for improving the flower color and multiseasonal flowering of osmanthus and other flowers.

Oleaceae

Dual-gRNA CRISPR/Cas9 Deletion of CsDMR6 in Sweet Orange Supported by Improved In Vitro Regeneration.

Huanglongbing (HLB), caused by Candidatus Liberibacter spp., remains the most destructive disease affecting citrus worldwide. To support host-directed genome-editing strategies aimed at reducing susceptibility, we optimized key regeneration steps in Citrus sinensis and validated a dual-gRNA CRISPR/Cas9 approach targeting the susceptibility gene CsDMR6. Juvenile explants of 'Valencia' and hybrid genotypes (CsH1-CsH3) were successfully established in vitro, and shoot elongation was markedly improved by supplementing Citrus Shoot Multiplication (CiSM) medium with 1 mg L-1 GA3. Callus induction was most efficient in Citrus Callus Induction (CiCM) medium under dark conditions, while a 48 h NAA pulse (100 µM) significantly enhanced rooting, increasing efficiencies to 37.1% in 'Valencia' and 52.9% in CsH1. Two guide RNAs targeting conserved regions of CsDMR6 were designed and shown to be identical across all evaluated genotypes. The dual-gRNA cassette was assembled into a CRISPR/Cas9 geminivirus-based vector and transiently delivered into sweet orange leaf tissue via Agrobacterium. GFP fluorescence verified construct expression, and PCR amplification across the target region produced a diagnostic ~447 bp fragment corresponding to the expected ~5.8 kb deletion. Sanger sequencing confirmed precise junction formation between the two cut sites. These results demonstrate efficient large-fragment deletion of CsDMR6 in sweet orange and establish an experimentally validated, genotype-compatible regeneration and editing platform. This study provides a transient validation of the dual-gRNA system and establishes the technical foundation required for future stable, non-transgenic edited lines. Together, these advances support the downstream functional evaluation of CsDMR6 loss-of-function alleles under HLB pressure.

CRISPR/Cas9

The TANG cluster comprising ten nitrate transporter genes controls fruit sweetness and size in tomato.

Sucrose is a major transport form of photoassimilated carbon in tomato, Arabidopsis, and many other plant species, and plays a critical regulatory role in plant growth, development, and fruit quality. Plant vacuoles function as storage organelles, accumulating substantial quantities of metabolically inactive nitrates as a nitrogen reserve and soluble sugars as a carbon reserve. Consequently, the balance between nitrate and sucrose accumulation determines plant growth dynamics and fruit taste. In this study, we identified a gene cluster designated TANG (Total soluble solidsAccumulation viaNitrate transporterGene cluster), comprising ten nitrate transporter genes that are significantly associated with sucrose accumulation in tomato. This gene cluster mediates the transport of nitrate between the cytoplasm and vacuole, thereby influencing its storage. Functional disruption of TANG8, a member of the gene cluster, results in either enhanced sugar accumulation or increased fruit size. Selective disruption of multiple TANG cluster members yields fruits with elevated sweetness and increased fruit size in S. pimpinellifolium. The interaction between the TANG members and a tonoplast localized Sucrose Transporter 4 provides insight into the competitive accumulation of nitrate and sugar. The multiplex editing of a gene cluster provides a successful example of engineering crops with high quality and yield.

Gene cluster

EST-SSR based genetic polymorphism among Lablab (Lablab purpureus L. Sweet) accessions contrasting for drought stress at seedling stage.

Lablab is a multipurpose and the most drought-tolerant (DT) crop compared with its relatives. Despite its potential, Lablab is still an underutilized crop with a lack of improved varieties in many countries. The DT (D349, D147, HA4, D363, D352, D359, D348, D311, D55 and D250) and drought-susceptible (DS) (D271, D66, D106, D6, D26, D255, D28, D186, D95, and D258) accessions were earlier identified according to their morphological and biochemical responses to moisture stress at the seedling stage. These accessions were used to establish genetic polymorphism among the accessions contrasting for drought stress based on the Expressed Sequence Tag-Simple Sequence Repeats (EST-SSR) markers. The CTAB protocol was employed for the genomic DNA extraction. After DNA quality and quantity verification, the PCR was conducted using 16 EST-SSR primer pairs specific to the Lablab. The products were separated through the horizontal polyacrylamide gel electrophoresis (hPAGE). Discriminating ability of the markers and primers' efficiency were evaluated based on various genetic parameters. Principal Coordinate Analysis (PCoA) was performed to estimate the distance matrix among the population and among the accessions. While cluster analysis was processed to trace the genetic relationship among the accessions, dendrogram was constructed to decipher their genetic relationship. Analysis of Molecular Variance (AMOVA) was finally computed to quantify the diversity level and genetic relationship among the population, and among the accessions. A low polymorphism (GD = 0.19) was observed between the DT and DS accessions, likely due to limited discriminatory power of the EST-SSR markers. However, the PCoA, cluster analysis and AMOVA identified DT (D147, HA4, and D349) and DS (D106, D95, and D271) accessions as strongly contrasting populations under drought stress, with D147, HA4, D349, D363, D359, D352, and D348 further recommended as DT accessions. Given the low polymorphism observed, further validation using more informative molecular markers and advanced genomic approaches is recommended to improve the identification of drought-tolerance genes and related QTLs to support Lablab breeding programs.

Expressed Sequence Tags

Low-burden metrics for monitoring healthy diets among nonpregnant females aged 15 to 49 years: a multicountry validation analysis using quantitative 24-hour dietary intake data.

BACKGROUND: Limited nationally representative quantitative dietary intake data and a lack of consensus on lower-burden tools and metrics hinder high-frequency monitoring of healthy diets globally. OBJECTIVES: This study aimed to evaluate the comparative construct validity and potential complementarity of low-burden metrics of a healthy diet among nonpregnant females aged 15 to 49 y. METHODS: Quantitative 24-h dietary intake data collected from 77,118 adolescent and adult females across 27 countries were used to construct low-burden metrics and reference metrics of dietary intake. Associations between mean-standardized low-burden measures or indicators and reference metrics were assessed using linear and logistic mixed-effect models, with Spearman's &#x3c1; used for survey-level rank correlations. Test characteristics identified low-burden indicators best differentiated adherence to reference indicators. RESULTS: An indicator reflecting nonconsumption of sweet foods and/or sweet beverages was most robustly associated with greater adherence to <10% energy from free sugars in upper-middle-income countries {odds ratio [OR] [95% confidence interval (CI)]: 5.35 [5.05, 5.66]}. Food group diversity score (FGDS) was most strongly associated with and differentiated higher mean adequacy ratio of micronutrients [&#x3b2; of 1-standard deviation (SD) change: &#x223c;11 percentage points (9, 12); &#x3c1;: 0.79], whereas noncommunicable disease-Protect score best reflected consumption of &#x2265;400 g/d of fruits and vegetables [range OR of 1-SD changes (95% CI): 2.56-3.01 (2.40, 3.13) in lower-middle and high-income countries, respectively; &#x3c1;: 0.56]. FGDS and Global Diet Quality Score Positive were most consistently associated with achieving &#x2265;25 g/d of fiber and &#x2265;3510 mg/d of potassium across contexts. CONCLUSIONS: Low-burden data collection tools yield valid metrics, enabling high-frequency monitoring of healthy diets across contexts. Specifically, avoiding sweet foods and/or sweet beverages is an indicator for adherence to WHO free sugar guidelines among nonpregnant females in upper-middle-income countries, whereas metrics reflecting nutritious food group diversity strongly reflect better micronutrient adequacy and adherence to WHO guidelines for fruits and vegetables, fiber, and potassium intakes within and across contexts.

Humans

E-cigarette product characteristics and packaging features and interest in e-cigarette use: Results from a randomized within-person trial nested in three prospective cohorts.

BACKGROUND: Product characteristics and packaging may be key targets for regulation to reduce e-cigarette use among youth, but existing data are limited. METHODS: Data are from an experimental study (2018-2020) nested within three prospective cohorts (age 14-26) in southern California (N&#x2009;=&#x2009;3565). Participants were shown five e-cigarette (e-liquid) packages in a random order that varied in flavor (sweet vs. tobacco), flavor name (descriptive ["blueberry cheesecake"] vs. concept ["smurf cake"] vs. none [number only]), and cartoon image on package (yes/no). For each stimuli, survey items assessed the following outcomes: product appeal (self-enjoyment, others' enjoyment; Likert scale [1-5]), susceptibility to use (use if friends offered, curiosity; 4 ordered responses [definitely not-definitely yes]), peer acceptability (definitely not-definitely yes), and perceived harm (definitely not-definitely yes). Mixed effects proportional odds models evaluated within-person effects of each factor (flavor, flavor name, cartoon) with each outcome. RESULTS: Participants reported greater appeal, susceptibility, and peer acceptability (OR range=3.7-16.9; ps<0.05), and lower perceived harm (OR=0.61; 95%CI=0.53, 0.70) for sweet (vs. tobacco-flavored) e-cigarettes; effects were progressively stronger for younger cohorts. The descriptive flavor name rated higher than the concept flavor (OR range=1.13-2.02; ps<0.05) or number only (OR range=1.18-1.69; ps<0.05) for appeal and susceptibility measures; no differences for concept vs. number were found. The cartoon image rated higher for appeal, curiosity, and peer acceptability (OR range=1.24-1.51; ps<0.05). CONCLUSIONS: Sweet flavors, descriptive flavor names, and cartoon images may increase the appeal of e-cigarettes among youth and young adults with no history of e-cigarette use, and are key targets for regulation.

Humans

Genomic and functional characterization of sugar transporters reveals potential roles in sugar accumulation in a modern sugarcane cultivar.

Sugarcane (Saccharum spp.) is a globally important sugar crop whose productivity depends on efficient sugar transport from source to sink organs. However, systematic identification and functional characterization of sugar transporters (STs) in sugarcane cultivars remain limited. Here, we identified 190 non-redundant ST genes in sugarcane cultivar Guitang 42 (GT42) and phylogenetically classified them into nine groups within the Monosaccharide Transporter (MST), Sucrose Transporter (SUT), and Sugars Will Eventually be Exported Transporters (SWEET) families. Comparative evolutionary analysis revealed significant lineage-specific expansions in the PMT, STP subfamilies, and SWEET families compared to diploid and wild relatives, likely driven by polyploidization and intensive selection for sugar yield. Transcriptomic profiling across tissues and internode elongation stages demonstrated marked tissue-specific and developmental expression patterns. Yeast complementation assays confirmed the transport activity of candidate MSTs, SUTs and SWEETs, with confocal microscopy verifying their distinct subcellular localization at the plasma membrane, tonoplast, or endoplasmic reticulum. Furthermore, transient overexpression of several candidate transporters (ScSWEET4-T2, ScSWEET15, and ScTST4-T1) in Nicotiana benthamiana modulated soluble sugar accumulation, and their expression in sugarcane protoplasts activated key sugar-responsive marker genes (ScGPT2 and ScWIP4). Together, our study establishes a systematic genomic framework and identifies candidate functional transporters that govern sugar partitioning and storage, providing valuable genetic targets for molecular breeding and quality enhancement in sugarcane.

Functional characterization

Predicting food taste with bound-driven optimization.

The prediction of sensory attributes from ingredient-level formulations is an emerging challenge at the intersection of food science and artificial intelligence. We address the fundamental question of whether the taste of a food can be predicted from its ingredients by treating recipes as composite materials. We apply Hashin-Shtrikman (HS) and Reuss-Voigt (RV) bounds, techniques originally developed for elastic moduli, as a null-hypothesis additive baseline for five taste dimensions (sweetness, sourness, bitterness, umami, saltiness) on a curated dataset of 70 recipes decomposed into 115 distinct ingredients scored against a library of 209 ingredient-level taste references with trained-panel ground truth. This baseline systematically under-predicts perceived taste: 77% of actual taste values exceeded the HS upper bound, with the exceedance rate ranging from 26% (bitterness) to 97% (saltiness). We traced this gap to specific processing chemistry (Maillard reactions, caramelization, evaporative concentration, protein hydrolysis, and nucleotide synergy) and introduced a hybrid model that augments the HS baseline with eight chemistry-proxy features encoding these mechanisms. Our results show that our interpretable hybrid model eliminates the systematic bias and reduces mean absolute error by 27%-62% for sweetness, sourness, umami, and saltiness while using only 10 interpretable features, achieving performance comparable to a black-box Lasso regression on 115 per-ingredient features. We further demonstrate constrained inverse design via Differential Evolution, recovering ingredient formulations that match target taste profiles subject to compositional bounds. Our work demonstrates how key chemical processes during food preparation can inform and augment physics-based and machine learning models, providing a quantitative fingerprint of processing chemistry's contribution to taste perception and paving the way for model-driven food formulation with targeted sensory characteristics.

Composite material bounds

Ancient DNA reveals early use of melons in China's Song dynasty.

Melon (Cucumis melo L.) domestication is thought to have occurred independently once in Northeast Africa and twice in India, but archaeobotanical seed remains point to a possible additional domestication event in China. Because Cucumis seeds are difficult to diagnose morphologically, genomic data from archaeological material are needed to evaluate these scenarios and reconstruct ancient melon traits. We sequenced two Song Dynasty (960-1279 CE) melon seeds from Shuomen Gugang (China), recovering 5.5&#xd7; and 2.1&#xd7; nuclear genome coverage. Nuclear and chloroplast analyses place both seeds within cultivated C. melo from China, within the "agrestis" East Asian gene pool. To assess whether these seeds carried traits associated with sweet dessert melons, we examined loci underlying fruit phenotypes. Neither seed carried alleles for orange flesh; one harbored an allele linked to yellow/orange peel, the other possessed alleles associated with green flesh and reduced acidity. Since wild melons are monoecious, the presence of the derived andromonoecy allele in one seed, associated with rounder fruit shape, suggests early selection on fruit morphology. Together, these findings indicate that Song Dynasty melons were likely consumed as fresh or culinary fruits rather than sweet dessert melons. Their flesh coloration resonates with Song-period aesthetic sensibilities, exemplified by jade-green celadon ceramics frequently crafted in melon-shaped forms. By anchoring East Asian archaeobotanical remains within modern melon genomic variation, this study provides a temporal framework for melon cultivation in China and shows how ancient genomics can illuminate past crop use.

China

Dissecting genetic architecture and improving machine learning&#x2011;based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.

Sweet osmanthus (Osmanthus fragrans), a traditional ornamental plant in China, exhibits substantial variation in autumn flowering time, which significantly affects landscape application and cultivation efficiency. Here, we performed a genome-wide association study on 127 resequenced accessions classified into early, intermediate, and late flowering types, using a set of 2,325,410 single-nucleotide polymorphisms (SNPs) and 246,824 structural variants (SVs). By integrating SNP/insertion and deletion (Indel) and SV data with weighted gene co-expression network analysis, machine learning, and genomic prediction, we dissected the genetic architecture of flowering time. We identified 24 associated SNP/Indels and six SVs, mapping to 30 candidate genes, including known flowering regulators FLK, LOS1, Y14, MIF2, and GID1B. These genes showed tissue-specific expression, with some responding to low temperature. The two hub genes, GUX1 and LYG027904, were located within modules of the co-expression network associated with low-temperature treatment. Haplotype analysis revealed a specific three-SNP haplotype associated with late flowering and linked to LOS1, and epistatic interactions among combined genotypes contributed to phenotypic variation. Notably, integrating SVs with SNP/Indels improved genomic prediction accuracy; the gradient boosting decision tree model outperformed other machine learning algorithms, achieving a mean accuracy of 0.859 and an AUC&#xa0;>&#xa0;0.8 (where AUC is area under receiver operating characteristic curve) for all flowering types. These findings provide insights into the genetic mechanisms underlying flowering time variation in O. fragrans, offer candidate genes and haplotypes for molecular breeding, and highlight the value of integrating SVs with machine learning for genomic prediction in woody ornamentals.

Machine Learning

The relationship between food intake and outdoor temperature in a longitudinal study: a public health perspective in the context of global warming.

BACKGROUND: Climate change affects human health and nutrition. Rising temperatures may significantly impact diets, but research on their influence on dietary habits in large populations remains limited. OBJECTIVES: We aimed to study the link between outdoor temperature and energy-adjusted food consumption across profiles in a longitudinal study. METHODS: This study included 100,851 participants from the NutriNet-Sant&#xe9; study (2009-2023) with 1,716,046 24-h dietary records linked to daily maximum outdoor temperature at the residence, from the nearest M&#xe9;t&#xe9;o-France station. Associations were analyzed using linear mixed models with interactions tested for sex and 6 socioeconomic profiles (employees, privileged, intermediate, young, disadvantaged, and retirees) derived from clustering. RESULTS: Across all subgroups, higher outdoor temperature was associated with higher consumption of fruits, vegetables, processed meats, sweet products, water, alcoholic beverages, and sugar-sweetened beverages, whereas consumption of red meat, pulses, and dairy products decreased. From 25&#xb0;C to 35&#xb0;C, the increase in alcohol consumption with temperature was more pronounced in males {150 g/d [95% confidence interval (CI): 147 g/d, 153 g/d] to 166 g/d [95% CI: 162 g/d, 171 g/d], +11%} than in females [101 g/d (95% CI: 98 g/d, 103 g/d) to 107 g/d (95% CI: 104 g/d, 109 g/d), +6%]. Across socioeconomic profiles, changes shared similar directions, but some trends were more marked, notably for alcoholic beverages among employees (95% CI: 114 g/d, 130 g/d; +14%) and sugar-sweetened beverages in young (95% CI: 56 g/d, 72 g/d; +29%). Consumption of fruits increased more modestly in the young (95% CI: 227 g/d, 248 g/d; +9%) than in employees (95% CI: 194 g/d, 227 g/d; +17%). These changes, although variable in magnitude, were not accompanied by substantial modifications in energy intake or overall diet quality scores. CONCLUSIONS: These results emphasize the importance of targeted prevention messages when temperatures exceed 25&#xb0;C, especially concerning alcoholic and sugar-sweetened beverages, and offer insight into potential long-term food consumption patterns (beyond seasonal changes) in the context of global warming.

Humans

Water intake, switching between bites and sips, and drinking behavior are associated with food intake across meals varying in spiciness: A secondary analysis of two randomized crossover studies.

Widespread nutrition advice instructs consumers to drink water with meals to increase fullness and reduce energy intake. However, recent data indicates greater water intake is associated with more food intake at a meal, not less. Switching between meal components (e.g., alternating between food and water), has also been associated with increased food intake at a pasta meal, but it remains unclear whether this applies to other foods. In a secondary analysis, we pooled existing data from 2 crossover experiments (total n&#xa0;=&#xa0;86) where adults ate an ad libitum lunch consisting of 650&#xa0;g of beef chili (n&#xa0;=&#xa0;52) or chicken tikka masala (n&#xa0;=&#xa0;34) with 450&#xa0;g of water twice in the laboratory while being video-recorded. For both experiments, the spiciness of the lunch was varied by adding different ratios of hot:sweet paprika. Videos were coded to measure sip number, sip size (g/sip), drinking rate (g/min), and number of switches between bites of food and sips of water. As we previously reported, increasing spiciness slowed eating rate and reduced food intake; in secondary analyses described here, the reduction in food intake was not moderated by water intake, switching, or drinking behaviors (all p&#xa0;>&#xa0;0.73). Notably, across all meals, greater water intake (p&#xa0;<&#xa0;0.001) and switching (p&#xa0;=&#xa0;0.02) associated with greater food intake. Overall, individuals ate more when they drank more and switched between bites and sips more often, highlighting the potential influence of water and drinking behaviors on food consumption. This finding challenges the widespread dietary advice to drink water with meals to reduce food intake.

Humans

Elucidation of microbial community structure, small-molecule metabolic and flavor profile characteristics in Xuanwei ham under different processing techniques.

This study systematically compared the impacts of traditional (TH) and modern (MH) processing techniques on the physicochemical properties, microbial community structure, metabolome, and volatile aroma compounds of Xuanwei ham. The results showed that the TH group had higher moisture content and water activity, along with a more tender texture, whereas the MH group exhibited greater hardness and chewiness. Microbiological analysis revealed that the interior of the MH group had higher species richness of both fungi and bacteria, while the TH group maintained higher fungal diversity. Metabolomic analysis identified 112 differential metabolites, with sweet amino acids and certain lipids being more enriched in modern ham, whereas traditional ham contained higher levels of umami amino acids, polyunsaturated fatty acids, and flavor compounds such as carnosine. KEGG pathway enrichment indicated that the differences were primarily concentrated in amino acid biosynthesis and metabolism-related pathways. Volatile flavoromics analysis identified 45 odor-active compounds and screened 15 key aroma-active substances. Among them, modern processed ham was significantly enriched in fatty aldehydes such as (E)-2-nonenal, hexanal, nonanal, and octanal, whereas traditional processed ham was characterized by 1-octen-3-ol, (E,E)-2,4-decadienal, methional, acetoin, and benzeneacetaldehyde. Correlation analysis confirmed that dominant microbes in Xuanwei ham were significantly associated with differential metabolites and characteristic aroma compounds, respectively. This study provides a scientific basis for standardizing production processes, enabling precise quality control, and promoting high-quality industrial development of Xuanwei ham.

Animals

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV&#xa0;>&#xa0;100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation