低温杀菌黄焖鸡中菌落总数生长预测模型的比较和货架期预测
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摘要
为比较不同生长预测模型对低温杀菌黄焖鸡中菌落总数生长情况的拟合效果,使用修正的Gompertz模型、修正的Logistic模型和Baranyi模型描述其在4、15、25℃贮藏期间菌落总数的变化情况,使用Belehradek模型和Arrhenius模型描述菌落总数生长参数与贮藏温度之间的关系,通过计算各模型拟合所得的参数值及回归相关系数R~2、均方误差平方根、赤池信息准则和贝叶斯信息准则等指标评价模型的拟合优度,以最优组合建立产品的货架期预测模型。结果表明:在一级模型中,修正的Logistic模型拟合所得的生长参数值最接近实测值,模型的评价指标最优;在二级模型中,Arrhenius模型的拟合优度最高,其R~2均在0.97以上;对修正的Logistic模型的偏差因子、准确因子和Arrhenius模型的残差值进行分析,表明建立的一级、二级模型可被接受;以此为基础建立低温杀菌黄焖鸡的货架期预测模型,经过验证,模型预测值与实测值的相对误差值均在±10%以内,表明所建立的货架期预测模型能够比较准确地预测低温杀菌黄焖鸡在4～25℃范围内的货架期。
In order to compare the goodness-of-fit of different prediction models for the aerobic bacterial count in pasteurized braised chicken stored at 4, 15 and 25 ℃, three primary models, the modified Gompertz, modified Logistic and Baranyi models, were applied to fit the change of aerobic bacterial count, and the secondary models, Belehradck and Arrhenius models, were used to construct the relationship between the parameter eigenvalues and temperature. The goodness-offit of the models were evaluated by comparing the parameter eigenvalues and the evaluation indexes such as correlation coefficient(R~2), root mean square error(RMSE), Akaike information criterion(AIC) and Bayesian information criterion(BIC),and a predictive model for the shelf life of pasteurized braised chicken was established. Results showed that the parameter eigenvalues fitted with the modified Logistic model were closest to the measured values, and the model exhibited the best goodness-of-fit. The Arrhenius model fitted best with a R~2 above 0.97 between the secondary models. It was found that the bias and accuracy factor of the modified Logistic model and the absolute residual values of the Arrhenius model were both at acceptable levels. On the basis of the microbial growth prediction models, the predictive model for the shelf life of pasteurized braised chicken was established and was verified. The relative errors between the predicted and observed values were within ± 10%, which indicated that the predictive model was reliable for the shelf life of pasteurized braised chicken stored at a temperature ranging from 4 to 25 ℃.
In order to compare the goodness-of-fit of different prediction models for the aerobic bacterial count in pasteurized braised chicken stored at 4, 15 and 25 ℃, three primary models, the modified Gompertz, modified Logistic and Baranyi models, were applied to fit the change of aerobic bacterial count, and the secondary models, Belehradck and Arrhenius models, were used to construct the relationship between the parameter eigenvalues and temperature. The goodness-offit of the models were evaluated by comparing the parameter eigenvalues and the evaluation indexes such as correlation coefficient(R~2), root mean square error(RMSE), Akaike information criterion(AIC) and Bayesian information criterion(BIC),and a predictive model for the shelf life of pasteurized braised chicken was established. Results showed that the parameter eigenvalues fitted with the modified Logistic model were closest to the measured values, and the model exhibited the best goodness-of-fit. The Arrhenius model fitted best with a R~2 above 0.97 between the secondary models. It was found that the bias and accuracy factor of the modified Logistic model and the absolute residual values of the Arrhenius model were both at acceptable levels. On the basis of the microbial growth prediction models, the predictive model for the shelf life of pasteurized braised chicken was established and was verified. The relative errors between the predicted and observed values were within ± 10%, which indicated that the predictive model was reliable for the shelf life of pasteurized braised chicken stored at a temperature ranging from 4 to 25 ℃.
引文
[1]卢君逸,罗瑞明,刘莹莹,等.五香牛肉品质变化及安全贮藏期的界定研究[J].安徽农业科学,2013,41(11):5034-5036.DOI:10.3969/j.issn.0517-6611.2013.11.118.
[2]BATT C A,TORTORELLO M L.Encyclopedia of food microbiology[M].2nd ed.Manhattan:Academic Press,2014:59-68.
[3]金鑫,周光宏,徐幸莲,等.预测食品微生物学在肉品安全领域的应用[J].肉类研究,2010,24(7):3-7.
[4]DELHALLE L,DAUBE G,ADOLPHE Y,et al.A review of growth models in predictive microbiology to ensure food safety[J].Biotechnology,Agronomy,Society and Environment,2012,16(3):369-381.DOI:10.1080/10889868.2012.687417.
[5]陈睿,徐幸莲,周光宏,等.真空包装鸡肉早餐肠中细菌总数生长预测模型的拟合优度比较[J].食品科学,2014,35(15):113-117.DOI:10.7506/spkx1002-6630-201415023.
[6]朱彦祺,郭全友,李保国,等.不同温度下腐败希瓦氏菌(Shewanella putrefaciens)生长动力学模型的比较与评价[J].食品科学,2016,37(13):147-152.DOI:10.7506/spkx1002-6630-201613026.
[7]YANG S,PARK S Y,HA S D.A predictive growth model of Aeromonas hydrophila on chicken breasts under various storage temperatures[J].LWT-Food Science and Technology,2016,69:98-103.DOI:10.1016/j.lwt.2016.01.016.
[8]常思盎,惠腾,刘毅,等.杀菌和复热工艺对黄焖鸡挥发性风味物质的影响[J].肉类研究,2018,32(4):20-26.DOI:10.7506/rlyj1001-8123-201804004.
[9]中华人民共和国国家卫生和计划生育委员会,国家食品药品监督管理总局.食品安全国家标准 食品微生物学检验菌落总数测定:GB 4789.2-2016[S].北京:中国标准出版社,2016.
[10]张昭寰,娄阳,杜苏萍,等.分子生物学技术在预测微生物学中的应用与展望[J].食品科学,2017,38(9):248-257.DOI:10.7506/spkx1002-6630-201709040.
[11]YE Keping,WANG Huhu,ZHANG Xinxiao,et al.Development and validation of a molecular predictive model to describe the growth of Listeria monocytogenes in vacuum-packaged chilled pork[J].Food Microbiology,2013,32(1):246-254.DOI:10.1016/j.foodcont.2012.11.017.
[12]GONZáLEZ-FANDOS E,GARCíA-LINARES M C,VILLARINO-RODRíGUEZ A,et al.Evaluation of the microbiological safety and sensory quality of rainbow trout (Oncorhynchus mykiss) processed by the sous vide method[J].Food Microbiology,2004,21(2):193-201.DOI:10.1016/S0740-0020(03)00053-4.
[13]SAITO K,JIN D H,OGAWA T,et al.Antioxidative properties of tripeptide libraries prepared by the combinatorial chemistry[J].Journal of Agricultural and Food Chemistry,2003,51(12):3668-3674.DOI:10.1021/jf021191n.
[14]BARANYI J,ROBERTS T A.A dynamic approach to predicting bacterial growth in food[J].International Journal of Food Microbiology,1994,23(3/4):277-294.DOI:10.1016/0168-1605(94)90157-0.
[15]KREYENSCHMIDT J,CHRISTIANSEN H,ALBRECHT A,et al.A novel photochromic time-temperature indicator to support cold chain management[J].International Journal of Food Microbiology,2010,45(2):208-215.DOI:10.1111/j.1365-2621.2009.02123.x.
[16]HONG Y K,HUANG L H,YOON W B.Mathematical modeling and growth kinetics of Clostridium sporogenes in cooked beef[J].Food Control,2016,60(7):471-477.DOI:10.1016/j.foodcont.2015.08.035.
[17]李秋庭,吴建文.盐焗鸡贮藏品质变化及货架期预测模型[J].食品科技,2015,40(2):157-162.DOI:10.13684/j.cnki.spkj.2015.02.033.
[18]FENG C H,DRUMMOND L,SUN D W,et al.Modeling the growth parameters of lactic acid bacteria and total viable count in vacuumpackaged Irish cooked sausages cooled by different methods[J].International Journal of Food Science and Technology,2014,49(12):2659-2667.DOI:10.1111/ijfs.12603.
[19]姜颖.真空包装烤肠货架期预测及保鲜技术研究[D].北京:中国农业科学院,2016:19-32.
[20]DURACK E,ALONSO-GOMEZ M,WILKINSON M G.The effect of thawing and storage temperature on the microbial quality of commercial frozen ready meals and experimental reduced salt frozen ready meals[J].Journal of Food Research,2012,1(2):99-112.DOI:10.5539/jfr.v1n2p99.
[21]中华人民共和国国家卫生和计划生育委员会,国家食品药品监督管理总局.食品安全国家标准 熟肉制品:GB 2726-2016[S].北京:中国标准出版社,2016.
[22]陈睿,徐幸莲,周光宏.真空包装鸡肉早餐肠货架期预测模型的建立[J].食品科学,2014,35(6):209-213.DOI:10.7506/spkx1002-6630-201406045.
[23]陈鹏,程镜蓉,杨禹新,等.冷鲜黄羽肉鸡货架期预测模型的建立与评价[J].食品工业科技,2016,37(12):144-148.DOI:10.13386/j.issn1002-0306.2016.12.020.
[24]胡洁云,林露,王彤,等.熟鸡肉中金黄色葡萄球菌生长预测模型的建立[J].微生物学通报,2016,43(9):1999-2009.DOI:10.13344/j.microbiol.china.150738.
[25]张婉.鲜熟面贮藏品质及货架期预测模型研究[D].烟台:烟台大学,2012:23-29.
[26]陈睿.真空包装鸡肉早餐肠腐败进程分析及货架期预测模型研究[D].南京:南京农业大学,2014:47-56.
[27]丁婷,李婷婷,励建荣,等.冷藏三文鱼片微生物生长动力学模型适用性分析及货架期模型的建立[J].中国食品学报,2015,15(5):63-73.DOI:10.16429/j.1009-7848.2015.05.009.
[28]MATHIAS S P,ROSENTHAL A,GASPAR A,et al.Prediction of acid lactic-bacteria growth in turkey ham processed by high hydrostatic pressure[J].Brazilian Journal of Microbiology,2013,44(1):23-28.DOI:10.1590/S1517-83822013005000014.
[29]YOON Y,GEOMARAS I,SCANGA G A,et al.Probabilistic models for the prediction of target growth interfaces of Listeria monocytogenes on ham and turkey breast products[J].Journal of Food Science,2011,76(6):450-455.DOI:10.1111/j.1750-3841.2011.02273.x.
[30]胡聪.清真牛羊肉产品微生物预测软件开发[D].银川:宁夏大学,2014:21-38.
[2]BATT C A,TORTORELLO M L.Encyclopedia of food microbiology[M].2nd ed.Manhattan:Academic Press,2014:59-68.
[3]金鑫,周光宏,徐幸莲,等.预测食品微生物学在肉品安全领域的应用[J].肉类研究,2010,24(7):3-7.
[4]DELHALLE L,DAUBE G,ADOLPHE Y,et al.A review of growth models in predictive microbiology to ensure food safety[J].Biotechnology,Agronomy,Society and Environment,2012,16(3):369-381.DOI:10.1080/10889868.2012.687417.
[5]陈睿,徐幸莲,周光宏,等.真空包装鸡肉早餐肠中细菌总数生长预测模型的拟合优度比较[J].食品科学,2014,35(15):113-117.DOI:10.7506/spkx1002-6630-201415023.
[6]朱彦祺,郭全友,李保国,等.不同温度下腐败希瓦氏菌(Shewanella putrefaciens)生长动力学模型的比较与评价[J].食品科学,2016,37(13):147-152.DOI:10.7506/spkx1002-6630-201613026.
[7]YANG S,PARK S Y,HA S D.A predictive growth model of Aeromonas hydrophila on chicken breasts under various storage temperatures[J].LWT-Food Science and Technology,2016,69:98-103.DOI:10.1016/j.lwt.2016.01.016.
[8]常思盎,惠腾,刘毅,等.杀菌和复热工艺对黄焖鸡挥发性风味物质的影响[J].肉类研究,2018,32(4):20-26.DOI:10.7506/rlyj1001-8123-201804004.
[9]中华人民共和国国家卫生和计划生育委员会,国家食品药品监督管理总局.食品安全国家标准 食品微生物学检验菌落总数测定:GB 4789.2-2016[S].北京:中国标准出版社,2016.
[10]张昭寰,娄阳,杜苏萍,等.分子生物学技术在预测微生物学中的应用与展望[J].食品科学,2017,38(9):248-257.DOI:10.7506/spkx1002-6630-201709040.
[11]YE Keping,WANG Huhu,ZHANG Xinxiao,et al.Development and validation of a molecular predictive model to describe the growth of Listeria monocytogenes in vacuum-packaged chilled pork[J].Food Microbiology,2013,32(1):246-254.DOI:10.1016/j.foodcont.2012.11.017.
[12]GONZáLEZ-FANDOS E,GARCíA-LINARES M C,VILLARINO-RODRíGUEZ A,et al.Evaluation of the microbiological safety and sensory quality of rainbow trout (Oncorhynchus mykiss) processed by the sous vide method[J].Food Microbiology,2004,21(2):193-201.DOI:10.1016/S0740-0020(03)00053-4.
[13]SAITO K,JIN D H,OGAWA T,et al.Antioxidative properties of tripeptide libraries prepared by the combinatorial chemistry[J].Journal of Agricultural and Food Chemistry,2003,51(12):3668-3674.DOI:10.1021/jf021191n.
[14]BARANYI J,ROBERTS T A.A dynamic approach to predicting bacterial growth in food[J].International Journal of Food Microbiology,1994,23(3/4):277-294.DOI:10.1016/0168-1605(94)90157-0.
[15]KREYENSCHMIDT J,CHRISTIANSEN H,ALBRECHT A,et al.A novel photochromic time-temperature indicator to support cold chain management[J].International Journal of Food Microbiology,2010,45(2):208-215.DOI:10.1111/j.1365-2621.2009.02123.x.
[16]HONG Y K,HUANG L H,YOON W B.Mathematical modeling and growth kinetics of Clostridium sporogenes in cooked beef[J].Food Control,2016,60(7):471-477.DOI:10.1016/j.foodcont.2015.08.035.
[17]李秋庭,吴建文.盐焗鸡贮藏品质变化及货架期预测模型[J].食品科技,2015,40(2):157-162.DOI:10.13684/j.cnki.spkj.2015.02.033.
[18]FENG C H,DRUMMOND L,SUN D W,et al.Modeling the growth parameters of lactic acid bacteria and total viable count in vacuumpackaged Irish cooked sausages cooled by different methods[J].International Journal of Food Science and Technology,2014,49(12):2659-2667.DOI:10.1111/ijfs.12603.
[19]姜颖.真空包装烤肠货架期预测及保鲜技术研究[D].北京:中国农业科学院,2016:19-32.
[20]DURACK E,ALONSO-GOMEZ M,WILKINSON M G.The effect of thawing and storage temperature on the microbial quality of commercial frozen ready meals and experimental reduced salt frozen ready meals[J].Journal of Food Research,2012,1(2):99-112.DOI:10.5539/jfr.v1n2p99.
[21]中华人民共和国国家卫生和计划生育委员会,国家食品药品监督管理总局.食品安全国家标准 熟肉制品:GB 2726-2016[S].北京:中国标准出版社,2016.
[22]陈睿,徐幸莲,周光宏.真空包装鸡肉早餐肠货架期预测模型的建立[J].食品科学,2014,35(6):209-213.DOI:10.7506/spkx1002-6630-201406045.
[23]陈鹏,程镜蓉,杨禹新,等.冷鲜黄羽肉鸡货架期预测模型的建立与评价[J].食品工业科技,2016,37(12):144-148.DOI:10.13386/j.issn1002-0306.2016.12.020.
[24]胡洁云,林露,王彤,等.熟鸡肉中金黄色葡萄球菌生长预测模型的建立[J].微生物学通报,2016,43(9):1999-2009.DOI:10.13344/j.microbiol.china.150738.
[25]张婉.鲜熟面贮藏品质及货架期预测模型研究[D].烟台:烟台大学,2012:23-29.
[26]陈睿.真空包装鸡肉早餐肠腐败进程分析及货架期预测模型研究[D].南京:南京农业大学,2014:47-56.
[27]丁婷,李婷婷,励建荣,等.冷藏三文鱼片微生物生长动力学模型适用性分析及货架期模型的建立[J].中国食品学报,2015,15(5):63-73.DOI:10.16429/j.1009-7848.2015.05.009.
[28]MATHIAS S P,ROSENTHAL A,GASPAR A,et al.Prediction of acid lactic-bacteria growth in turkey ham processed by high hydrostatic pressure[J].Brazilian Journal of Microbiology,2013,44(1):23-28.DOI:10.1590/S1517-83822013005000014.
[29]YOON Y,GEOMARAS I,SCANGA G A,et al.Probabilistic models for the prediction of target growth interfaces of Listeria monocytogenes on ham and turkey breast products[J].Journal of Food Science,2011,76(6):450-455.DOI:10.1111/j.1750-3841.2011.02273.x.
[30]胡聪.清真牛羊肉产品微生物预测软件开发[D].银川:宁夏大学,2014:21-38.
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