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食品研究与开发:2019,40(19):1-7
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货架温度对西兰花品质影响及预测模型建立
SHI Meng,LIU Jing,YANG Pei-jie,CHEN Ai-qiang,YAN Rui-xiang,LIU Bin,GUAN Wen-qiang
(1.College of Biotechnology and Food Sciences,Tianjin University of Commerce,Tianjin 300134,China;2.College of Mechanical Engineering,Tianjin University of Commerce,Tianjin 300134,China;3.School of Packaging and Printing Engineering,Tianjin University of Science&Technology,Tianjin 300222,China)
Influence of Shelf Temperatures on Broccoli Quality and the Establishment of Prediction Models
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投稿时间:2018-12-18    
中文摘要: 为更好监测不同货架温度对西兰花品质的影响,将西兰花分别放置于4、10、20 ℃下测定失重率、叶绿素、呼吸强度、乙烯释放量,并进行感官评价和特征指标动力学分析。结果表明,低温(4、10 ℃)可明显抑制西兰花货架期感官指标变化,延缓叶绿素下降速度,并推迟呼吸和乙烯峰值的出现时间。其中4 ℃保鲜效果最好,能有效延长货架期至21 d。应用Arrhenius 方程与化学动力学反应,可拟合确定以叶绿素为变量的货架期预测模型(shelf life prediction model of chlorophyll,SLChlo)、失重率为变量的货架期预测模型(shelf life prediction model of weight loss,SLWL)。其中,SLChlo在低温条件下预测更准确,SLWL 平均相对误差较小。二者结合可得到更准确的预测参数,进而为西兰花货架期监测提供理论基础。
中文关键词: 西兰花  Arrhenius方程  品质  货架期  预测模型
Abstract:In order to monitor the effect of different shelf temperatures on the quality of broccoli,the broccoli were placed under 4,10,20 ℃ conditions,and the rate of weight loss,chlorophyll content,respiration rate and ethylene emission were measured.The sensory evaluation and characteristic index dynamic analysis were performed.It was found that cryopreservation significantly inhibited sensory index changes and the decline rate of chlorophyll content,delayed the appearance of respiratory and ethylene peaks.Above all,4 ℃ was the optimal storage temperature,which effectively extended the shelf life to 21 days.The study also combined the Arrhenius equation with chemical kinetic reaction to fit the shelf-life prediction modelshelf life prediction model of chlorophyl (SLChlo),shelf life prediction model of weight loss (SLWL)with chlorophyll and weight loss rate variables.The verification results showd that SLChlo was more accurate under lower temperature conditions,while the SLWL had low average relative error.The combination of these two equations could obtain more accurate prediction parameters and provide a theoretical basis for the monitoring of broccoli shelf life.
文章编号:201919001     中图分类号:    文献标志码:
基金项目:国家重点研发计划项目(2018YFD0401304-4);天津市高等学校创新团队建设项目(TD13-5087)
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