Full
Outline
To establish an efficient and accurate analytical method to track the transfer and distribution patterns of pesticide residues from brewing raw materials to the final Baijiu products, and to assess their potential risks.
Raw materials (rice and glutinous rice) from different sources and their corresponding Baijiu products were collected. Samples were extracted and purified with acetonitrile, then analyzed using ultra performance liquid chromatography-Orbitrap-high resolution mass spectrometry. Compounds were identified through a pseudo-targeted screening approach with database matching and quantified using reference standards.
The established quantitative analytical methods for 5 kinds of pesticide residues, including triazophos,alloxydim, isoprothiolane, bufencarb and pebulate, exhibited good linearity in the range of 1.0–50.0 ng/mL(correlation coefficient, r>0.998). The method limits of detection and limits of quantitation were 0.12–0.32 ng/mL and 0.48–1.05 ng/mL, respectively. The spiked recoveries ranged from 88.60% to 95.60% with relative standard deviations below 3%. Analysis of distribution characteristics revealed that pesticide residues were primarily concentrated in raw materials from scattered household farming. Triazophos, alloxydim and isoprothiolane were commonly detected in both rice and glutinous rice samples, whereas butacarb (detected in both rice and glutinous rice) and pebulate (detected only in glutinous rice) were specifically found in samples collected after October 30,indicating significant spatio-temporal distribution differences. No high-risk pesticide residues were detected in raw materials from base cultivation or in any Baijiu products. The risk assessment indicated that the levels of all detected pesticide residues were below the GB 2763—2021 National food safety standards-Maximum residue limits of pesticides in food, suggesting that the overall risk is controllable.
This study successfully reveals the key distribution nodes and characteristics of pesticide residues throughout the Baijiu production chain, identifying that the risk primarily originates from raw materials of specific sources and procurement batches. It provides crucial data support and a scientific basis for implementing targeted source control and whole-process risk early warning in the Baijiu industry.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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