【摘要】：為了研究快速無損鑒別雞蛋產(chǎn)地的可行性,利用可見-近紅外光譜技術(shù),采集4種湖北不同產(chǎn)地雞蛋的透射光譜(500~900 nm),利用中心化、歸一化、標準正態(tài)變量(SNV)、Savitzky-Golay平滑濾波(SG)和多元散射校正(MSC)、直接正交信號校正(Direct Orthogonal Signal Correction,DOSC)算法對光譜數(shù)據(jù)進行預(yù)處理,采用t分布式隨機鄰域嵌入(t-distributed stochastic neighbor embedding,t-SNE)、主成分分析(PCA)方法對預(yù)處理后的數(shù)據(jù)降維,并將降維后的數(shù)據(jù)分別輸入極限學習機(extreme learning machine,ELM)和隨機森林(random forest,RF),建立雞蛋產(chǎn)地溯源模型。比較兩種方法建立的模型,發(fā)現(xiàn)運用DOSC預(yù)處理及t-SNE提取的光譜特征信息建立的RF模型鑒別效果最好,訓(xùn)練集和預(yù)測集的鑒別正確率分別為100%和98.33%。研究結(jié)果表明基于可見-近紅外光譜技術(shù)對雞蛋產(chǎn)地溯源是可行的,為進一步研究與開發(fā)雞蛋產(chǎn)地溯源便攜式儀器提供技術(shù)支持。
[Abstract]:In order to study the feasibility of fast and nondestructive identification of egg origin, the transmission spectra of four kinds of eggs from different areas in Hubei province were collected by using visible near infrared spectroscopy (500 ~ 900 nm),) using centralization, normalization and standard normal variable (SNV),. Savitzky-Golay smoothing filter (SG) and multivariate scattering correction (MSC), direct orthogonal signal correction (Direct Orthogonal Signal Correction,DOSC) algorithm are used to preprocess the spectral data. T distributed random neighborhood embedding (t-distributed stochastic neighbor embedding,t-SNE) is used to preprocess the spectral data. The principal component analysis (PCA) was used to reduce the dimension of pretreated data, and the reduced dimension data were input into the extreme learning machine (extreme learning machine,ELM) and random forest (random forest,RF), respectively, and a traceability model of egg origin was established. Comparing the two models, it is found that the RF model based on DOSC pretreatment and t-SNE extraction is the best, and the accuracy of training set and prediction set are 100% and 98.33%, respectively. The results show that it is feasible to trace the origin of eggs based on visible near infrared spectroscopy, which provides technical support for further research and development of portable instrument for tracing the origin of eggs.
【作者單位】： 華中農(nóng)業(yè)大學工學院;華中農(nóng)業(yè)大學國家蛋品加工技術(shù)研發(fā)分中心;
【基金】：國家自然科學基金(31371771) 湖北省科技支撐計劃項目(2015BBA172) 國家科技支撐計劃項目(2015BAD19B05) 公益性行業(yè)(農(nóng)業(yè))科研專項(201303084)
【分類號】：O657.33;TS253.7
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本文編號：2373703