Psychrotrophic Gram-negative bacteria and thermophilic or thermoduric spore-forming bacteria are major causes of quality deterioration and shelf-life loss in milk and dairy products. Their impact is mediated primarily by heat-stable peptidases and lipases, heat-resistant spores and biofilms that persist in processing environments; with the notable exception of toxigenic members of the Bacillus cereus group, most of these organisms are spoilage rather than safety hazards. Culture-based methods remain the reference standard but are slow and provide single time-point information. This review critically evaluates molecular and sensing methods, including quantitative and digital PCR, isothermal amplification, CRISPR-Cas assays, biosensors, viability assays, spectroscopy and (meta)omics, with explicit attention to whether performance has been demonstrated in naturally contaminated dairy matrices rather than in buffer or spiked samples, and examines how their outputs could inform predictive microbiology and machine learning. A classification framework based on growth-temperature range, heat resistance, sporulation and dairy relevance is provided, and each detection-to-prediction pathway is graded as demonstrated in dairy, partly demonstrated or proposed. Validated dairy applications currently exist mainly for individual detection assays and for mechanistic or stochastic shelf-life models driven by culture-derived data; prospective, validated workflows in which molecular or biosensor outputs are used as model inputs to forecast spoilage have not yet been reported. Because heat-stable enzymes can spoil ultra-high-temperature products after the producing cells have been inactivated, viable counts alone are insufficient predictors of such defects. Key barriers include matrix effects, small and imbalanced datasets, domain shift, limited external validation and poorly defined intended use. Detection-to-prediction integration should therefore be regarded as an emerging research direction rather than an established industrial capability.
Maize is frequently contaminated by toxigenic fungi, mainly Fusarium spp. and Aspergillus section Flavi, which produce several mycotoxins and represent a major food safety concern. Climate change is expected to alter fungal communities in agroecosystems, potentially modifying mycotoxin contamination patterns in maize. This study compared mycotoxin accumulation and the mycotoxigenic potential of fungal isolates between two consecutive growing seasons characterized by contrasting climatic conditions (2023, hot/dry, and 2024, mild/wet) in maize samples from northeastern Spain.From 2023 and 2024, 853 Fusarium and 210 Aspergillus section Flavi isolates were obtained, and their toxigenic potential for fumonisins (FBs), deoxynivalenol (DON), zearalenone (ZEN), T-2/HT-2 toxins and aflatoxins (AFs) was assessed by HPLC, while natural mycotoxin contamination in the maize samples was determined by ELISA.The 2024 season was associated with a higher proportion of mycotoxin-producing Fusarium isolates and higher DON and ZEN concentrations in maize. DON and ZEN concentrations were positively correlated in both growing seasons, and the relative proportion of F. graminearum was positively associated with DON. F. proliferatum showed high FBs-producing potential in both seasons and a higher proportion of FBs-producing isolates than F. verticillioides. Although AFs-producing isolates were more frequent in 2023, AFs remained below the analytical LOD in all maize samples from both seasons. A. parasiticus showed high AF-producing capacity in vitro despite its relatively low occurrence.No significant correlations were detected between the in vitro toxigenic potential of fungal isolates and mycotoxin concentrations in the corresponding maize samples.Overall, contrasting seasonal conditions were associated with differences in toxigenic fungal profiles and mycotoxin accumulation in maize.
This study characterizes genomic and phenotypic diversity among Vibrio parahaemolyticus isolates from shrimp aquaculture by integrating phenotypic profiling with pangenomic analysis. Growth was quantified under temperature, salinity, pH, nutrient, and ethanol stresses, together with motility, hemolysis, and antibiotic susceptibility. Core-genome SNP phylogeny identified genetic differentiation among representative isolates, with relationships not consistently associated with sampling location, sample type, or collection period. Comparative genomics showed variation in accessory-gene composition and isolate-specific distributions of blaCARB variants, whereas tet(34), tet(35), and several motility and chemotaxis genes were widely detected. Phenotypic assays showed isolate- and condition-dependent variation in stress responses, antimicrobial susceptibility, hemolysis, and motility. Neither tdh nor trh was detected by PCR or WGS-based screening. No clear hemolytic zones were observed on Columbia blood agar, whereas Ref, 1P1, 2P2, 3P2, 4 M2, and 4 N2 showed hemolytic activity on Wagatsuma agar, indicating a discrepancy between the Wagatsuma phenotype and molecular detection of these hemolysin genes. Isolate 1 M1 exhibited greater swimming without increased swarming activity. Accessory-genome principal coordinate analysis (PCoA) and phenotypic principal component analysis (PCA) showed partial correspondence between genomic and phenotypic relationships. The close accessory-genome relationship between 2P2 and 3P2 was not reflected phenotypically, whereas 2Q2 and 3P2 showed phenotypic similarity despite greater accessory-genome separation. These contrasting relationships indicate that accessory-gene presence and absence alone did not reproduce the measured multivariate phenotypic patterns. These findings indicate that genomic and phenotypic variation represent related but non-equivalent dimensions of strain-level diversity and support integrated genomic and phenotypic characterization for surveillance in aquaculture environments.
Antagonistic microorganisms have gained increasing attention for the control of postharvest fruit diseases due to their safety, low risk of resistance development, and capacity to activate the fruit's innate defense responses. This study evaluated the biocontrol potential of Bullera alba against major tomato diseases and elucidated its underlying mechanisms. The results indicated that Bullera alba effectively reduced disease incidence and lesion diameter in tomato fruit and significantly inhibited conidial germination and germ tube elongation of Alternaria alternata and Botrytis cinerea. The strain rapidly colonized tomato wounds at both 25 °C and 4 °C. Furthermore, Bullera alba markedly enhanced the activities of POD, PPO, SOD, APX, and PAL, and significantly promoted the accumulation of total phenolics, flavonoids, and lignin. Transcriptomic analysis indicated that Bullera alba treatment significantly upregulated the expression of genes associated with several defense-related pathways in tomato fruit, including plant–pathogen interactions, phenylpropanoid biosynthesis, glutathione metabolism, and MAPK signaling pathways. Overall, these findings suggest that Bullera alba may enhance tomato fruit resistance to two major postharvest diseases by inducing the expression of defense-related genes, increasing defense enzyme activities, and promoting the accumulation of bioactive secondary metabolites.
