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雞肉中假單胞菌的近紅外光譜快速識(shí)別
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國(guó)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)和江蘇大學(xué)高級(jí)人才基金項(xiàng)目(15JDG169)


Rapid Identification of Pseudomonas spp. in Chicken by Near-infrared Spectroscopy
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    摘要:

    假單胞菌是雞肉腐敗最主要的致腐菌,為了快速識(shí)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(duì)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(duì)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(lèi)識(shí)別模型。其中反向傳播人工神經(jīng)網(wǎng)絡(luò)模型預(yù)測(cè)效果最佳,其訓(xùn)練集和預(yù)測(cè)集的識(shí)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(shí)別雞肉中的假單胞菌。

    Abstract:

    Pseudomonas spp. is the main bacteria involved chicken degradation which ultimately affects the meat quality and the potential of posing health public health threats. The use of near infrared spectroscopy (NIRS) for rapid identification and monitoring of four strains of Pseudomonas spp. in degrading chicken was attempted. Initially, four Pseudomonas strains namely Pseudomonas gessardii, Pseudomonas psychrophila, Pseudomonas fragi and Pseudomonas fluorescens were isolated from samples of degrading chicken and identified via polymerase chain reaction (PCR) technology. The different isolated Pseudomonas spp. were cultured in trypticase soy broth (TSB) and incubated at 30℃ for 12 h to growth. The four isolates of Pseudomonas spp. and their combined mixture in equal proportions were all prepared from the incubated inoculum by using 100mL∶5mL and each replicated 40 times. The preprocessed data outcomes of the 200 samples using standard normal variable transformation (SNV) exhibited superiority compared with other deployed data preprocessing algorithms such as multiplicative scatter correction (MSC), calibration standard score, first derivative (DB1) and second derivative (DB2). Synergy interval partial least squares (SiPLS) was employed to select relevant characteristics wavelengths such as 3999.64~4597.46cm-1, 6406.37~7004.19cm-1, 8211.41~8805.38cm-1 and 8809.24~9403.20cm-1. Principal component analysis (PCA) was performed prior to the model development with loadings of 97.02% in PC1, 2.47% in PC2 and 0.27% in PC3 which indicated the possibility of developing models for the classification of the different samples of Pseudomonas spp. The recognition rates for KNN (65.00%, 63.75%), SVM (91.67%, 86.25%) and BP-ANN (99.17%, 95.00%) were obtained in the training and prediction sets. The model results obtained for SVM was sufficiently high and may be combined with NIRS system for the possible Pseudomonas spp. classification. However, the best result was obtained with BP-ANN built model. These high recognition rates implied near-infrared spectroscopy combined with BP-ANN can be deployed for the rapid detection of different Pseudomonas spp. strains in chicken for the purpose of safeguarding its deteriorating chicken quality.

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陳全勝,王名星,郭志明,范沖,孫浩,趙杰文.雞肉中假單胞菌的近紅外光譜快速識(shí)別[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2017,48(8):328-334. CHEN Quansheng, WANG Mingxing, GUO Zhiming, FAN Chong, SUN Hao, ZHAO Jiewen. Rapid Identification of Pseudomonas spp. in Chicken by Near-infrared Spectroscopy[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(8):328-334.

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  • 收稿日期:2016-12-16
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  • 在線發(fā)布日期: 2017-08-10
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