College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada.
College of Animal and Veterinary Sciences, Southwest Minzu University, Chengdu 610041, China.
Toxins (Basel). 2023 Feb 13;15(2):151. doi: 10.3390/toxins15020151.
The objectives of this study were to explore the possibility of using near infrared (NIR) and Fourier transform mid-infrared spectroscopy-attenuated total reflectance (ATR-FT/MIR) molecular spectroscopic techniques as non-invasive and rapid methods for the quantification of six major ergot alkaloids (EAs) in cool-season wheat. In total, 107 wheat grain samples were collected, and the concentration of six major EAs was analyzed using the liquid chromatography-tandem mass spectrometry technique. The mean content of the total EAs-ergotamine, ergosine, ergometrine, ergocryptine, ergocristine, and ergocornine-was 1099.3, 337.5, 56.9, 150.6, 142.1, 743.3, and 97.45 μg/kg, respectively. The NIR spectra were taken from 680 to 2500 nm, and the MIR spectra were recorded from 4000-700 cm. The spectral data were transformed by various preprocessing techniques (which included: FD: first derivative; SNV: standard normal variate; FD-SNV: first derivative + SNV; MSC: multiplicative scattering correction; SNV-Detrending: SNV + detrending; SD-SNV: second derivative + SNV; SNV-SD: SNV + first derivative); and sensitive wavelengths were selected. The partial least squares (PLS) regression models were developed for EA validation statistics. Results showed that the constructed models obtained weak calibration and cross-validation parameters, and none of the models was able to accurately predict external samples. The relatively low levels of EAs in the contaminated wheat samples might be lower than the detection limits of the NIR and ATR-FT/MIR spectroscopies. More research is needed to determine the limitations of the ATR-FT/MIR and NIR techniques for quantifying EAs in various sample matrices and to develop acceptable models.
本研究旨在探索近红外(NIR)和傅里叶变换中红外光谱-衰减全反射(ATR-FT/MIR)分子光谱技术作为非侵入性和快速方法定量测定冷季小麦中六种主要麦角生物碱(EAs)的可能性。共采集了 107 个小麦籽粒样本,采用液相色谱-串联质谱技术分析六种主要 EAs 的浓度。六种主要 EAs(麦角新碱、麦角胺、麦角酸、麦角隐亭、麦角柯宁和麦角卡宁)的总含量分别为 1099.3、337.5、56.9、150.6、142.1、743.3 和 97.45μg/kg。采集 NIR 光谱的范围为 680-2500nm,MIR 光谱的记录范围为 4000-700cm。对光谱数据进行了多种预处理技术(包括:FD:一阶导数;SNV:标准正态变量;FD-SNV:一阶导数+SNV;MSC:乘法散射校正;SNV-Detrending:SNV+去趋势;SD-SNV:二阶导数+SNV;SNV-SD:SNV+一阶导数)的变换,并选择了敏感波长。建立了用于 EA 验证统计的偏最小二乘(PLS)回归模型。结果表明,构建的模型得到了较弱的校准和交叉验证参数,没有一个模型能够准确预测外部样本。污染小麦样本中 EAs 的含量相对较低,可能低于 NIR 和 ATR-FT/MIR 光谱的检测限。需要进一步研究确定 ATR-FT/MIR 和 NIR 技术在各种样品基质中定量测定 EAs 的局限性,并开发可接受的模型。