食品科学 ›› 2021, Vol. 42 ›› Issue (1): 264-271.doi: 10.7506/spkx1002-6630-20200103-029

• 包装贮运 • 上一篇    下一篇

温度对金针菇贮藏品质的影响及货架期的预测模型

牛耀星,王霆,毕阳,张雨,刘宏,贠建民   

  1. (甘肃农业大学食品科学与工程学院,甘肃 兰州 730070)
  • 发布日期:2021-01-18
  • 基金资助:
    “十三五”国家重点研发计划重点专项(2018YFD0400205)

Effect of Storage Temperature on the Quality of Flammulina velutipes and Shelf Life Predictive Modeling

NIU Yaoxing, WANG Ting, BI Yang, ZHANG Yu, LIU Hong, YUN Jianmin   

  1. (College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China)
  • Published:2021-01-18

摘要: 为了研究采后流通贮藏销售过程中金针菇子实体品质的变化以及快速预测金针菇子实体的货架期,本实验模拟了金针菇子实体的3 种货架贮藏流通温度(4、15、25 ℃),并定期对其感官品质和理化品质进行测定。采用一级动力学模型结合Arrhenius方程建立基于金针菇子实体品质指标的货架期预测模型,并对模型的预测精确度进行验证及评价。结果表明:低温可明显减缓金针菇子实体品质的下降并且延长了贮藏期,具体表现为抑制金针菇子实体质量损失率、褐变度以及丙二醛含量的上升,减缓可溶性固形物质量分数的下降,保持较高的游离脯氨酸含量。根据质量损失率、病害指数、褐变度、可溶性固形物质量分数构建的金针菇子实体货架期预测模型精确度都较高,决定系数R2均在0.90以上,实测值与预测值的相对误差都低于10%,尤其是通过可溶性固形物质量分数构建的货架期预测模型效果更好。所建立的模型能够快速可靠地预测金针菇子实体的剩余货架期,可为通过实时控制贮藏流通条件延长金针菇子实体的货架期提供实践指导。

关键词: 金针菇;动力学模型;货架期预测;Arrhenius方程

Abstract: In order to study the quality change of Flammulina velutipes during postharvest storage and to quickly predict the shelf life, we kept the mushroom under three temperature conditions simulating those occurring during storage and circulation (4, 15 and 25 ℃). The sensory and physicochemical qualities of the samples were evaluated at regular intervals. The first-order kinetic model combined with the Arrhenius equation was used to establish shelf life prediction models based on quality indexes. The prediction accuracy of these models were verified and evaluated. The results showed that low temperature could remarkably slow down the spoilage and extend the shelf life of postharvest F. velutipes. More specifically, low temperature inhibited the mass loss, browning and the increase in malondialdehyde content, slowed down the decline in soluble solid content and maintained high free proline content. The shelf life prediction models based on mass loss rate, disease index, browning degree, and soluble solid content all exhibited high accuracy with determination coefficients R2 higher than 0.90. The relative errors between the predicted and actual values were less than 10%. Particularly, soluble solid content was a more accurate indicator to predict the shelf life. Therefore, the established models can quickly and reliably predict the remaining shelf life of F. velutipes, which will provide a practical guidance to control the storage and circulation conditions in real time so as to extend the shelf life of F. velutipes.

Key words: Flammulina velutipes; kinetic model; shelf life prediction; Arrhenius equation

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