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Cui H, Wang S, Yang X, Zhang W, Chen M, Wu Y, Li S, Li L, Cai D, Guo B, Ye J, Wang S. Predictive models for assessing the risk of Fusarium pseudograminearum mycotoxin contamination in post-harvest wheat with multi-parameter integrated sensors. Food Chem X 2022; 16:100472. [PMID: 36304207 PMCID: PMC9593717 DOI: 10.1016/j.fochx.2022.100472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 09/28/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022] Open
Abstract
Water activity plays a significant role in affecting CO2 and mycotoxin levels. Models were developed to predict contamination with ZEN and DON in stored wheat. These models + multi-parameter integrated sensors for real-time mycotoxin monitoring.
Reliable prediction of the risk of mycotoxin contamination in post-harvest wheat will aid in improvement of the quality and safety. To establish the relationship between Fusarium pseudograminearum mycotoxins and CO2 production, changes in their respective concentrations were monitored for the artificial contamination of wheat under different values of water activities (0.84 aw, 0.92 aw, and 0.97 aw) and temperatures (20 ℃, 25 ℃, and 30 ℃). Water activity played a significant role in all these processes. CO2 concentration together with moisture content and temperature were used as the main parameters to establish DON and ZEN contamination prediction models. The prediction accuracy for DON was 98.15 % (R2 = 0.990) and 90.74 % for ZEN (R2 = 0.982). These models were combined with T/RH/MC/CO2 multi-parameter integrated sensors to form an early warning system, which offers a great prospect to minimise the risk of DON/ZEN contamination in post-harvest wheat.
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Affiliation(s)
- Hua Cui
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Songshan Wang
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Xu Yang
- Baoding Qingyuan District National Grain Reserve Co., Ltd., No. 2866-500, Lianchi South Str, Qingyuan District, Baoding City, Hebei 071100, China
| | - Wei Zhang
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Mengze Chen
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Yu Wu
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Sen Li
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Li Li
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Di Cai
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Baoyuan Guo
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
| | - Jin Ye
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China,Corresponding author.
| | - Songxue Wang
- Academy of National Food and Strategic Reserves Administration, No. 11 Baiwanzhuang Str, Xicheng District, Beijing 100037, China
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