中文摘要：本研究运用短波红外（SWIR）高光谱成像系统(1000-2500 nm)，结合化学计量学数据分析，检测美国不同州（乔治亚州、伊利诺伊州、印第安纳州及内布拉斯加州）的四个黄玉米品种600粒籽粒表面的黄曲霉毒素B1（AFB1）。研究表明，SWIR光谱结合化学计量学及光谱预处理检测表面受AFB1污染的不同品种玉米籽粒具有可行性。进一步建议，合并样本中玉米样品的水分、蛋白质、淀粉和脂类等成分的增加会影响AFB1污染检测的准确性。
外文摘要：A short-wave infrared (SWIR) hyperspectral imaging system (1000-2500 nm) combined with chemometric data analysis was used to detect aflatoxin B, (AFB(1)) on surfaces of 600 kernels of four yellow maize varieties from different States of the USA (Georgia, Illinois, Indiana and Nebraska). For each variety, four AFB(1) solutions (10, 20, 100 and 500 ppb) were artificially deposited on kernels and a control group was generated from kernels treated with methanol solution. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA) and factorial discriminant analysis (FDA) were applied to explore and classify maize kernels according to AFB, contamination. PCA results revealed partial separation of control kernels from AFBi contaminated kernels for each variety while no pattern of separation was observed among pooled samples. A combination of standard normal variate and first derivative pre treatments produced the best PLSDA classification model with accuracy of 100% and 96% in calibration and validation, respectively, from Illinois variety. The best AFB, classification results came from FDA on raw spectra with accuracy of 100% in calibration and validation for Illinois and Nebraska varieties. However, for both PLSDA and FDA models, poor AFB1 classification results were obtained for pooled samples relative to individual varieties. SWIR spectra combined with chemometrics and spectra pre treatments showed the possibility of detecting maize kernels of different varieties coated with AFB(1). The study further suggests that increase of maize kernel constituents like water, protein, starch and lipid in a pooled sample may have influence on detection accuracy of AFB(1) contamination.
外文关键词：Aflatoxin B-1；Factorial discriminant analysis (FDA)；Maize kernel；Partial least squares discriminant analysis (PLSDA)；Short-wave infrared hyperspectral imaging
作者：Kimuli, D；Wang, W；Wang, W；Jiang, HZ；Zhao, X；Chu, X
作者单位：China Agr Univ
期刊名称：INFRARED PHYSICS & TECHNOLOGY
期刊影响因子：1.588
出版年份：2018
出版刊次：3
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