【摘要】：以豆粕和3種抗生素菌渣為研究對(duì)象,通過(guò)傅里葉變換近紅外顯微成像系統(tǒng)采集樣品近紅外顯微圖像;對(duì)采集到的近紅外顯微圖像進(jìn)行光譜重構(gòu),并對(duì)所有樣品光譜進(jìn)行預(yù)處理,利用Duplex算法分別從不同的樣品預(yù)處理光譜中篩選具有代表性的光譜建立豆粕和抗生素菌渣的特征光譜庫(kù)。使用偏最小二乘判別分析(PLS-DA)與支持向量機(jī)判別分析(SVM-DA)結(jié)合不同的光譜預(yù)處理方法,構(gòu)建豆粕與不同種類(lèi)抗生素菌渣的近紅外顯微成像定性判別模型。結(jié)果表明:構(gòu)建的2種模型均能有效對(duì)試驗(yàn)中所用豆粕和抗生素菌渣樣品進(jìn)行鑒別分析,正確率均在99.4%以上。進(jìn)一步比較研究發(fā)現(xiàn),一階導(dǎo)數(shù)+SNV的預(yù)處理方式優(yōu)于無(wú)預(yù)處理、一階導(dǎo)數(shù)、二階導(dǎo)數(shù);SVM-DA的模型效果優(yōu)于PLS-DA,SVM-DA中特征提取方法 PLS優(yōu)于PCA。
[Abstract]:Taking soybean meal and three kinds of antibiotic bacteria dregs as research objects, the near infrared microscopic images of samples were collected by Fourier transform near infrared microscopic imaging system, and the acquired near infrared microscopic images were reconstructed by spectral analysis. All the sample spectra were pretreated and the characteristic spectrum library of soybean meal and antibiotic residue was established by Duplex algorithm from different sample pretreatment spectra. Using partial least squares discriminant analysis (PLS-DA) and support vector machine discriminant analysis (SVM-DA) combined with different spectral pretreatment methods, a qualitative model of near-infrared microscopic imaging of soybean meal and antibiotic residue was established. The results showed that the two models could be used to identify and analyze soybean meal and antibiotic bacteria residue effectively, and the accuracy was over 99.4%. Furthermore, it is found that the pretreatment of first derivative SNV is better than that of no pretreatment, and the model effect of first derivative and second derivative SVM-DA is better than that of PLS-DA-SVM-DA.
【作者單位】： 中國(guó)農(nóng)業(yè)大學(xué)工學(xué)院;中國(guó)農(nóng)業(yè)科學(xué)院農(nóng)業(yè)質(zhì)量標(biāo)準(zhǔn)與檢測(cè)技術(shù)研究所;
【基金】：中國(guó)農(nóng)業(yè)科學(xué)院基本科研業(yè)務(wù)費(fèi)專(zhuān)項(xiàng)(1610072017001)和中國(guó)農(nóng)業(yè)科學(xué)院“飼料質(zhì)量安全檢測(cè)與評(píng)價(jià)”創(chuàng)新團(tuán)隊(duì)經(jīng)費(fèi)項(xiàng)目
【分類(lèi)號(hào)】：O657.3;S816

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