本文選題：雞肉 + 近紅外光譜��； 參考：《農(nóng)業(yè)機(jī)械學(xué)報(bào)》2017年08期

【摘要】：假單胞菌是雞肉腐敗最主要的致腐菌,為了快速識別雞肉中的假單胞菌,首先從腐敗雞肉中分離并篩選出致腐菌,進(jìn)一步利用聚合酶鏈反應(yīng)技術(shù)對目標(biāo)菌株進(jìn)行生物學(xué)鑒別(分別為蓋氏假單胞菌、嗜冷假單胞菌、莓實(shí)假單胞菌和熒光假單胞菌);配置鑒定的4種假單胞菌和等體積混合的4種假單胞菌菌液,采集菌液近紅外透射光譜信息;然后運(yùn)用標(biāo)準(zhǔn)正態(tài)變量變換對光譜進(jìn)行預(yù)處理,利用聯(lián)合區(qū)間偏最小二乘法篩選出特征波段;最后有比較地運(yùn)用K最近鄰法、最小二乘支持向量機(jī)和反向傳播人工神經(jīng)網(wǎng)絡(luò)建立5種假單胞菌菌液的近紅外光譜分類識別模型。其中反向傳播人工神經(jīng)網(wǎng)絡(luò)模型預(yù)測效果最佳,其訓(xùn)練集和預(yù)測集的識別率分別為99.17%和95.00%。研究結(jié)果表明,近紅外光譜結(jié)合反向傳播人工神經(jīng)網(wǎng)絡(luò)可以快速識別雞肉中的假單胞菌。
[Abstract]:Pseudomonas is the most important spoilage fungus in chicken. In order to quickly identify Pseudomonas in chicken, the spoilage fungi were isolated and screened. The target strains were further identified by polymerase chain reaction (Pseudomonas Gaysoni, Pseudomonas thermophilus). Pseudomonas raspberry and Pseudomonas fluorescens, four Pseudomonas species and four pseudomonas mixed with the same volume were configured to collect near-infrared transmission spectrum information, and then the spectrum was pretreated by standard normal variable transformation. The characteristic bands were screened by using the joint interval partial least square method, and the near infrared spectrum classification and recognition models of five pseudomonas liquid were established by using K-nearest neighbor method, least squares support vector machine and backpropagation artificial neural network. The back propagation artificial neural network model has the best prediction effect, and the recognition rates of training set and prediction set are 99.17% and 95.00% respectively. The results show that near infrared spectroscopy combined with back propagation artificial neural network can quickly identify Pseudomonas in chicken.
【作者單位】： 江蘇大學(xué)食品與生物工程學(xué)院;
【基金】：國家自然科學(xué)基金面上項(xiàng)目(31371770) 江蘇省高校自然科學(xué)研究面上項(xiàng)目(16KJB550002) 江蘇大學(xué)高級人才基金項(xiàng)目(15JDG169)
【分類號】：O657.33;TS251.7

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