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Scientia Silvae Sinicae ›› 2022, Vol. 58 ›› Issue (8): 117-125.doi: 10.11707/j.1001-7488.20220812

• Research papers • Previous Articles     Next Articles

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

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

CLC Number: