Quantitative assessment of zearalenone in maize using multivariate algorithms coupled to Raman spectroscopy. (15th July 2019)

• Record Type: Journal Article
• Authors: Guo, Zhiming; Wang, Mingming; Wu, Jingzhu; Tao, Feifei; Chen, Quansheng; Wang, Qingyan; Ouyang, Qin; Shi, Jiyong; Zou, Xiaobo
• Is Part Of: Food chemistry. Volume 286(2019)
• Page Start: 282
• Page End: 288
• Publication Date: 2019-07-15
• Subjects: Food safety -- Raman spectroscopy -- Zearalenone -- Chemometrics -- Quantitative determination -- Ant colony optimization; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2019.02.020
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Zearalenone was screened in maize using Raman spectroscopy. Raman spectroscopy combined with chemometrics was applied to screen zearalenone. ACO-siPLS algorithm proved effective for zearalenone screening in maize. This technique proved an in-situ for the detection of toxins in food. Abstract: Zearalenone is a contaminant in food and feed products which are hazardous to humans and animals. This study explored the feasibility of the Raman rapid screening technique for zearalenone in contaminated maize. For representative Raman spectra acquisition, the ground maize samples were collected by extended sample area to avoid the adverse effect of heterogeneous component. Regression models were built with partial least squares (PLS) and compared with those built with other variable selection algorithms such as synergy interval PLS (siPLS), ant colony optimization PLS (ACO-PLS) and siPLS-ACO. SiPLS-ACO algorithm was superior to others in terms of predictive power performance for zearalenone analysis. The best model based on siPLS-ACO achieved coefficients of correlation (Rp ) of 0.9260 and RMSEP of 87.9132 μg/kg in the prediction set, respectively. Raman spectroscopy combined multivariate calibration showed promising results for the rapid screening large numbers of zearalenone maize contaminations in bulk quantities without sample-extraction steps.