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Development of predictive models for egg freshness and shelf-life under different storage temperatures

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摘要 The objective of the present study was to develop models for egg freshness and shelf-life predictions for the selected evaluation indicators including egg weight,Flaugh unit(HU),and albumen height.Experiments were carried out at different storage temperatures for a total period of 29-32 d.All data were collected and fitted in to Arrhenius equation for egg freshness,while the HU data were applied to a probability model for shelf-life prediction.The results showed that egg weight,albumen height,and HU decreased significantly,while albumen pH increased with the extension of storage time.The higher the storage temperature,the faster the egg quality decreased.In addition,the bias factor,accuracy factor,and the standard error of prediction were selected to verify the developed quality models.Maximum rescaled R-square statistic,the Hosmer-Lemeshow goodness-of-fit statistic,and the receiver operating characteristic curve were used to evaluate the goodness-of-fit of the developed probability model for the shelf-life of eggs,which indicated that the presented predictive models can be used to assess egg freshness and predict shelf-life during different storage temperatures.
作者 权春丽 奚倩 史雪萍 韩荣伟 都启晶 Fereidoun Forghani 薛传运 张佳程 王军 Chunli Quan;Qian Xi;Xueping Shi;Rongwei Han;Qijing Du;Fereidoun Forghani;Chuanyun Xue;Jiacheng Zhang;Jun Wang(College of Food Science and Engineering,Qingdao Agricultural University,Qingdao,China;College of Life Science,Tarim University,Alar,China;College of Animal Science and Technology,Qingdao Agricultural University,Qingdao,China;Shandong Engineering Technology Research Center of Food Quality and Safety Control,Qingdao,China;Molecular Epidemiology,Inc.,Lake Forest Park,WA,USA)
出处 《Food Quality and Safety》 SCIE CSCD 2021年第4期344-350,共7页 食品品质与安全研究(英文版)
基金 supported by the Key Research and Development Program of Shandong Province(No.2019GNC106024) the Shandong Poultry Industry Innovation Team Construction Project(SDAIT-11-14) the High-level Talent Research Fund of Qingdao Agricultural University(No.6631120080/1111317),China.
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