College of Biological Engineering, Henan University of Technology, Zhengzhou, China.
College of Food Science and Technology, Henan University of Technology, Zhengzhou, China.
J Sci Food Agric. 2021 Sep;101(12):4980-4986. doi: 10.1002/jsfa.11141. Epub 2021 Feb 22.
Mycotoxins are among the most severe food contaminants. Deoxynivalenol and aflatoxin contamination are predominant in wheat and rice, respectively. Nowadays, there are no standardized and approved grain-sampling schemes worldwide. This study aimed to develop a scientific grain-sampling scheme to investigate the regularity of mycotoxin distributed in wheat and rice fields. The data were analyzed with analysis of variance and cluster analysis to select a better sampling scheme.
Considering the influences of the weather before harvest (temperature, humidity, wind direction, and other conditions), we sampled grains from different places in different farmlands and detected the mycotoxin content of the sampled grains. The mycotoxin content had extremely significant differences in the area of rice fields (P<0.01) and significant differences in the area of wheat fields (P<0.05). The filtering effect existed peripheral the field areas, especially peripheral the humid areas, where the fungi were filtered and the toxin were easily produced. Furthermore, the upwind direction peripheral the field areas cause more filterature effect than other wind direction. Although 97% of mycotoxins in wheat can be removed through the shelling process, the toxin content were not obviously affected by rice lodging in the field. According to the cluster analysis, the peripheral and middle areas were divided into the same group with higher mycotoxin content.
This paper developed a sampling scheme to detect the mycotoxin content of wheat and rice in the field, considering the temperature and humidity of the weather, locations, and other grain contamination conditions before harvest. Meanwhile, the sampling rule of lodging and wind direction in the field was also assayed. © 2021 Society of Chemical Industry.
霉菌毒素是最严重的食品污染物之一。脱氧雪腐镰刀菌烯醇和黄曲霉毒素分别是小麦和水稻的主要污染物。目前，全世界没有标准化和批准的粮食采样方案。本研究旨在制定科学的粮食采样方案，以研究小麦和稻田中霉菌毒素的分布规律。采用方差分析和聚类分析对数据进行分析，以选择更好的采样方案。
考虑到收获前的天气影响（温度、湿度、风向等条件），我们从不同农田的不同地点采样，并检测了采样谷物中的霉菌毒素含量。稻田面积的霉菌毒素含量差异极显著（P<0.01），小麦田面积的霉菌毒素含量差异显著（P<0.05）。田间周边地区存在过滤效应，特别是在潮湿地区，真菌被过滤，毒素容易产生。此外，田间周边的上风方向比其他风向产生更多的过滤效应。尽管小麦中的 97%的霉菌毒素可以通过脱壳过程去除，但毒素含量不受田间倒伏的明显影响。根据聚类分析，将周边和中部地区分为同一组，具有较高的霉菌毒素含量。
本文制定了一种采样方案，用于检测田间小麦和水稻的霉菌毒素含量，考虑了收获前天气的温度和湿度、位置以及其他粮食污染条件。同时，还分析了田间倒伏和风向的采样规律。 © 2021 英国化学学会。
