Tea is one of the most popular beverage in the world and may be contaminated by fungi and mycotoxins during processing. To analyse aflatoxin B₁ (AFB₁) and sterigmatocystin (STC) in three types of tea, a simple, fast, sensitive and reliable method of these two myxotoxins was developed. Recoveries obtained ranged from 95.9% to 118.0% and the RSDs were between 0.3% and 11.2%. The range of LODs was 0.2–0.45 µg/kg for AFB₁ and 0.04–0.12 µg/kg for STC. The range of LOQs was 0.67–1.73 µg/kg for AFB₁ and 0.13–0.40 µg/kg for STC. The optimised procedure was applied to analyse 126 tea samples randomly collected from different markets in China. AFB₁ was not detected, but STC was determined in 17 samples with concentrations ranging from 0.13 to 4.48 µg/kg. The detection rate of STC was 5%, 8.9% and 33.3% in black tea, green tea and Oolong tea, respectively.

Pesticide residues are one of the key factors affecting food safety and human health. This study systematically monitored the pesticide residue levels in pineapples from major production regions in China and assessed the dietary exposure risks. A total of 387 samples were collected during the pineapple harvesting seasons from 2023 to 2025. The residues of 88 pesticides were detected using GC, GC-MS, and LC-MS/MS. The results showed that 20 pesticides were detected, with detection rates of cypermethrin, carbendazim, and gibberellic acid exceeding 10%. Based on the Chinese National Standard GB 2763, the compliance rate of the samples was 98.71%. In the worst-case scenario, the ADI % for all population subgroups was less than 1%, the %ARfD was less than 60%, and the Hazard Index was less than 1.5%, far below the 100% risk threshold, indicating that the pesticide residue risk in pineapples is low and at an acceptable level.

Fresh milk quality deterioration during processing is a major dairy challenge, with microbial-driven protein degradation mechanisms unclear. This study pioneers an integrated microbiome-proteome approach to systematically elucidate the dynamic interplay between microbial succession and protein quality changes during industrial processing. Microbial community analysis revealed oscillatory richness, with 2.3-fold and 1.8-fold increases during pre-treatment (PL) and refrigerated transport (RC), respectively. Pseudomonas (12.4 % → 31.7 %) and Acinetobacter (8.1 % → 19.3 %) dominated key phases, with proteomics showing significant nutrient loss (IgM: -69.8 %; IgG: -54.15 %). Integrating microbial metagenomics with proteolytic pathway analysis identified proteases from Pseudomonas and Acinetobacter as key drivers of protein degradation (68 % activity). Pasteurization cut microbial load by 82 % but paradoxically intensified nutrient loss via protein denaturation. Crucially, our data establish a time-dependent degradation model, revealing that combined microbial enzymatic action and thermal effects account for 76 % of total protein hydrolysis, providing a theoretical framework for developing targeted intervention strategies in dairy processing optimization.