黄曲霉毒素是广泛存在于玉米中且具有剧毒的一种代谢产物，以美国农业部农业研究署（USDA-ARS） Toxicology and Mycotoxin Research Unit提供的2010年先锋玉米为研究对象，验证了高光谱成像技术对玉米中黄曲霉毒素检测的可行性。以甲...黄曲霉毒素是广泛存在于玉米中且具有剧毒的一种代谢产物，以美国农业部农业研究署（USDA-ARS） Toxicology and Mycotoxin Research Unit提供的2010年先锋玉米为研究对象，验证了高光谱成像技术对玉米中黄曲霉毒素检测的可行性。以甲醇为溶剂制备四种不同浓度的黄曲霉毒素溶液，并将其逐一滴在等量的4组共120粒玉米颗粒表面，以未处理的30粒洁净玉米作为一组对照样本，将大小、形状相似的150个样品随机分为训练集103个，验证集47个；对获取的400～1000 nm波段范围内的高光谱图像，先进行标准正态变量变换（standard normal variate transformation ，SNV）预处理，然后引入基于 Fisher判别最小误判率的方法选择最优波长，并以所选波长作为Fisher判别分析法的输入建立判别模型，对玉米颗粒表面不同浓度的黄曲霉毒素进行识别，最后对模型判别正确率进行了验证。结果表明，选取四个最优波长（812.42，873.00，900.36和965.00 nm ）时Fisher判别分析模型对训练集与验证集的准确率分别为87.4％和80.9％。该方法为含黄曲霉毒素玉米颗粒便携式检测仪器的开发，以及对田间霉变玉米自然代谢产生毒素的检测奠定了技术基础。展开更多
A novel systematic quality monitoring and prediction method based on Fisher discriminant analysis (FDA) and kernel regression is proposed. The FDA method is first used for quality monitoring. If the process is un-der ...A novel systematic quality monitoring and prediction method based on Fisher discriminant analysis (FDA) and kernel regression is proposed. The FDA method is first used for quality monitoring. If the process is un-der normal condition, then kernel regression is further used for quality prediction and estimation. If faults have oc-curred, the contribution plot in the fault feature direction is used for fault diagnosis. The proposed method can ef-fectively detect the fault and has better ability to predict the response variables than principle component regression (PCR) and partial least squares (PLS). Application results to the industrial fluid catalytic cracking unit (FCCU) show the effectiveness of the proposed method.展开更多
文摘黄曲霉毒素是广泛存在于玉米中且具有剧毒的一种代谢产物，以美国农业部农业研究署（USDA-ARS） Toxicology and Mycotoxin Research Unit提供的2010年先锋玉米为研究对象，验证了高光谱成像技术对玉米中黄曲霉毒素检测的可行性。以甲醇为溶剂制备四种不同浓度的黄曲霉毒素溶液，并将其逐一滴在等量的4组共120粒玉米颗粒表面，以未处理的30粒洁净玉米作为一组对照样本，将大小、形状相似的150个样品随机分为训练集103个，验证集47个；对获取的400～1000 nm波段范围内的高光谱图像，先进行标准正态变量变换（standard normal variate transformation ，SNV）预处理，然后引入基于 Fisher判别最小误判率的方法选择最优波长，并以所选波长作为Fisher判别分析法的输入建立判别模型，对玉米颗粒表面不同浓度的黄曲霉毒素进行识别，最后对模型判别正确率进行了验证。结果表明，选取四个最优波长（812.42，873.00，900.36和965.00 nm ）时Fisher判别分析模型对训练集与验证集的准确率分别为87.4％和80.9％。该方法为含黄曲霉毒素玉米颗粒便携式检测仪器的开发，以及对田间霉变玉米自然代谢产生毒素的检测奠定了技术基础。
基金Supported by the National Natural Science Foundation of China (60504033)the Open Project of State Key Laboratory of Industrial Control Technology in Zhejiang University (0708004)
文摘A novel systematic quality monitoring and prediction method based on Fisher discriminant analysis (FDA) and kernel regression is proposed. The FDA method is first used for quality monitoring. If the process is un-der normal condition, then kernel regression is further used for quality prediction and estimation. If faults have oc-curred, the contribution plot in the fault feature direction is used for fault diagnosis. The proposed method can ef-fectively detect the fault and has better ability to predict the response variables than principle component regression (PCR) and partial least squares (PLS). Application results to the industrial fluid catalytic cracking unit (FCCU) show the effectiveness of the proposed method.
