Title:	Determination of fumonisin content in maize using near-infrared hyperspectral imaging (NIR-HSI) technology and chemometric methods.
Authors:	CONCEIÇÃO, R. R. P. QUEIROZ, V. A. V. MEDEIROS, E. P. de ARAUJO, J. B. de SILVA, D. D. da MIGUEL, R. de A. STOIANOFF, M. A. R. SIMEONE, M. L. F.
Affiliation:	UNIVERSIDADE FEDERAL DE MINAS GERAIS; VALERIA APARECIDA VIEIRA QUEIROZ, CNPMS; EVERALDO PAULO DE MEDEIROS, CNPA; JOABSON BORGES DE ARAUJO, CNPA; DAGMA DIONISIA DA SILVA ARAUJO, CNPMS; RAFAEL DE ARAUJO MIGUEL, CNPMS; UNIVERSIDADE FEDERAL DE MINAS GERAIS; MARIA LUCIA FERREIRA SIMEONE, CNPMS.
Date Issued:	2024
Citation:	Brazilian Journal of Biology, v. 84, e277974, 2024.
Description:	Maize (Zea mays L.) is of socioeconomic importance as an essential food for human and animal nutrition. However, cereals are susceptible to attack by mycotoxin-producing fungi, which can damage health. The methods most commonly used to detect and quantify mycotoxins are expensive and time-consuming. Therefore, alternative non-destructive methods are required urgently. The present study aimed to use near-infrared spectroscopy with hyperspectral imaging (NIR-HSI) and multivariate image analysis to develop a rapid and accurate method for quantifying fumonisins in whole grains of six naturally contaminated maize cultivars. Fifty-eight samples, each containing 40 grains, were subjected to NIR-HSI. These were subsequently divided into calibration (38 samples) and prediction sets (20 samples) based on the multispectral data obtained. The averaged spectra were subjected to various pre-processing techniques (standard normal variate (SNV), first derivative, or second derivative). The most effective pre-treatment performed on the spectra was SNV. Partial least squares (PLS) models were developed to quantify the fumonisin content. The final model presented a correlation coefficient (R2) of 0.98 and root mean square error of calibration (RMSEC) of 508 µg.kg-1 for the calibration set, an R2 of 0.95 and root mean square error of prediction (RMSEP) of 508 µg.kg-1 for the test validation set and a ratio of performance to deviation of 4.7. It was concluded that NIR-HSI with partial least square regression is a rapid, effective, and non-destructive method to determine the fumonisin content in whole maize grains.
Thesagro:	Zea Mays Micotoxina
Keywords:	Fumonisina Análise não-destrutiva Imagem hiperespectral Infravermelho próximo Mínimos quadrados parciais
DOI:	https://doi.org/10.1590/1519-6984.277974
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CNPMS)