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Basic Research | Publishing Language: Chinese | Open Access

Fruit Quality Evaluation and Optimal Selection of 16 Lines of Feijoa (Acca sellowiana)

Shiqi YANG1 , Yumin LIU1, Yamin LIU1 ( ), Ju LI1, Chengxiang LI2, Bingli GAO2
College of Resources and Environment, Southwest University, Chongqing 400715, China
Chongqing Hemu Qianli Ecological Agriculture Technology Co. Ltd., Chongqing 402760, China
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Abstract

In order to comprehensively evaluate the difference in fruit quality among 16 different feijoa lines, this study determined the external and internal quality indicators and antioxidant activities of 16 feijoa lines. Variability analysis, correlation analysis and principal component analysis were used to identify core indicators. The weights of these indicators were determined by analytic hierarchy process, and a comprehensive evaluation model for fruit quality was established by grey relational analysis. The accuracy of the model was verified by sensory evaluation. The results indicated a significant variation in fruit quality across feijoa lines. Four core fruit quality indexes were selected, including single fruit mass (X1), juice yield (X2), sugar/acid ratio (X3), and total phenol content (X4). The comprehensive evaluation model was described as follows: weighted grey relational grade = 0.3810X1 + 0.2982X2 + 0.2108X3 + 0.1100X4. The model results were correlated well with those of sensory evaluation (R2 = 0.869), indicating high accuracy of the model. Two excellent lines, Y4 and Y1, were selected for promotion. The findings provide a reference for the establishment of a comprehensive evaluation system for feijoa quality and offer scientific guidance for feijoa breeding.

CLC number: TS255.2 Document code: A Article ID: 1002-6630(2025)10-0031-08

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Food Science
Pages 31-38

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Cite this article:
YANG S, LIU Y, LIU Y, et al. Fruit Quality Evaluation and Optimal Selection of 16 Lines of Feijoa (Acca sellowiana). Food Science, 2025, 46(10): 31-38. https://doi.org/10.7506/spkx1002-6630-20240716-161

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Received: 16 July 2024
Published: 25 May 2025
© Beijing Academy of Food Sciences 2025.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).