Academic Journal
Determination of fumonisin content in maize using near-infrared hyperspectral imaging (NIR-HSI) technology and chemometric methods
| العنوان: | Determination of fumonisin content in maize using near-infrared hyperspectral imaging (NIR-HSI) technology and chemometric methods |
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| المؤلفون: | R. R. P. Conceição, V. A. V. Queiroz, E. P. Medeiros, J. B. Araújo, D. D. S. Araújo, R. A. Miguel, M. A. R. Stoianoff, M. L. F. Simeone |
| المصدر: | Brazilian Journal of Biology, Vol 84 (2024) |
| بيانات النشر: | Instituto Internacional de Ecologia, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Science LCC:Biology (General) LCC:Zoology LCC:Botany |
| مصطلحات موضوعية: | Zea mays L., mycotoxins, fumonisins, non-destructive analysis, hyperspectral image near infrared, partial least squares (PLS), Science, Biology (General), QH301-705.5, Zoology, QL1-991, Botany, QK1-989 |
| الوصف: | Abstract 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1678-4375 1519-6984 |
| Relation: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000101139&tlng=en; https://doaj.org/toc/1678-4375 |
| DOI: | 10.1590/1519-6984.277974 |
| URL الوصول: | https://doaj.org/article/fca158b793ba42559b6d1337c6d3109b |
| رقم الانضمام: | edsdoj.fca158b793ba42559b6d1337c6d3109b |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 16784375 15196984 |
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| DOI: | 10.1590/1519-6984.277974 |