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林业科学 ›› 2022, Vol. 58 ›› Issue (8): 117-125.doi: 10.11707/j.1001-7488.20220812

• 研究论文 • 上一篇    下一篇

冰温状态下蓝莓质量损失率与质构参数变化规律及相关分析

李庆鹏,李洋*,霍若冰,徐曈晖,李馨男   

  1. 东北林业大学工程技术学院 哈尔滨 150040
  • 收稿日期:2022-02-28 出版日期:2022-08-25 发布日期:2022-12-19
  • 通讯作者: 李洋
  • 基金资助:
    黑龙江省自然科学基金项目(LH2021C016);中央高校基本科研业务费专项资金项目(2572017CB05)

Quality Loss Rate and Change Pattern of Texture Parameters of Fresh Blueberry Under Ice Temperature and Their Correlation

Qingpeng Li,Yang Li*,Ruobing Huo,Tonghui Xu,Xinnan Li   

  1. College of Engineering and Technology, Northeast Forestry University Harbin 150040
  • Received:2022-02-28 Online:2022-08-25 Published:2022-12-19
  • Contact: Yang Li

摘要:

目的: 研究冰温状态下蓝莓鲜果质量损失率与质构参数随时间的变化规律及其相关性,为蓝莓鲜果采后品质预测及感官评价提供理论依据。方法: 以‘北村’蓝莓为试验材料,(-1±0.5)℃为冰温组,(4±0.5)℃为对照组,分别对2种温度状态下蓝莓鲜果质量损失率及硬度、脆性、弹性、咀嚼性、内聚性和黏附性等6项质构参数进行测定,通过数据拟合与线性回归反映出蓝莓鲜果质量损失率与质构参数随时间的变化规律,进行相关性分析确定与蓝莓鲜果质量损失率呈显著相关的质构参数。结果: 冰温状态下,蓝莓鲜果质量损失率Y与时间X0的拟合模型为Y=0.197 36exp(X0/5.850 47)-0.184 5,呈指数式增长,增长趋势明显小于对照组;蓝莓鲜果各项质构参数在试验期间随时间呈不同程度的下降趋势,且均优于对照组。蓝莓鲜果冰温下质量损失率Y与硬度X1、脆性X2、咀嚼性X3等3项质构参数呈显著负相关(P<0.05),构建回归方程为Y=4.772-0.011X1-0.017X2-0.306X3结论: 冰温贮藏更有助于蓝莓鲜果品质的保持。冰温状态下,蓝莓鲜果质量损失率及各质构参数与时间构建的回归模型拟合精度较高。确定了冰温状态下蓝莓鲜果的硬度、脆性和咀嚼性是与蓝莓鲜果质量损失率变化相关的主要质构参数。

关键词: 冰温, 蓝莓, 质量损失率, 质构参数, 相关性分析

Abstract:

Objective: This study aims to provide a theoretical basis for blueberry quality prediction and sensory evaluation of fresh blueberry fruit after harvest by investigating the change pattern of quality loss rate and texture parameters of blueberry fresh fruit under ice temperature condition with time and their correlation. Methods: The 'Beicun' blueberry was used as the test object, and subjected to different temperatures. The (-1±0.5) ℃ was for the ice temperature group, and (4±0.5) ℃ for the control group. The quality loss rate of fresh blueberry fruit and six texture parameters, namely hardness, brittleness, elasticity, chewiness, cohesion and adhesion, were measured at the two temperatures. The changes of quality loss rate and texture parameters with time were reflected by data fitting and linear regression. The texture parameters that were significantly related to blueberry fresh fruit quality loss rate were determined through correlation analysis. Results: Under ice temperature condition, the fitted model for the quality loss rate Y of blueberry fresh fruit versus time X0 was Y=0.197 36 exp (X0/5.850 47)-0.184, which showed an exponential growth, and the growth trend was significantly smaller than that of the control group. The quality parameters of blueberry fresh fruit showed to different degrees decrease with time during the experiment and but were all better than the control group. The mass loss rate Y of blueberry fresh fruit at ice temperature was significantly negatively correlated with hardness X1, brittleness X2 and Chewiness X3 (P < 0.05), and the regression equation was constructed as Y=4.772-0.011 X1-0.017 X2-0.306 X3. Conclusion: Ice temperature storage is more helpful to maintain the quality of fresh blueberries. The regression models constructed for the quality loss rate of fresh blueberry fruit and each texture parameter with time under the ice temperature condition are fitted with high accuracy. The chewiness, crispness and hardness of fresh blueberry fruit under ice temperature are identified as the main qualitative indicators related to the change of quality loss rate of fresh blueberry fruit, which would provide a theoretical basis for the prediction of postharvest storage time and qualitative quality change of fresh blueberry fruit.

Key words: ice temperature, blueberries, quality loss rate, qualitative parameters, correlation analysis

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