Development of a texture analyzer-based method for waxiness evaluation and its application to phenotypic variation analysis in postharvest Chinese chestnut kernels

Waxiness is a critical textural factor determining the taste and consumer preference of postharvest Chinese chestnut ( Castanea mollissima Blume) kernels. However, its genetic improvement is hindered by the lack of an accurate, high-throughput phenotyping method and a clear understanding of its inheritance. In this study, a texture analyzer-based method was developed to objectively evaluate waxiness and analyze the associated phenotypic variations. Sensory waxy scores, starch composition, and texture parameters of 43 chestnut germplasms were evaluated. Notably, high-waxiness germplasms (waxy score > 80) exhibited significantly higher amylopectin content but had lower hardness and chewiness after steaming. Integrated analyses, including UPGMA clustering, principal component analysis, and Pearson correlation, convergently identified hardness as the optimal parameter for predicting waxiness. A robust regression model (Waxiness = 106.3041 - 0.3055 × Hardness) was established to quantify waxiness based on instrumental hardness measurements. Notably, the method effectively quantified continuous waxiness variation among 20 F 1 hybrid kernel populations and uncovered significant parental effects, thereby demonstrating its power as a reliable phenotyping tool when breeding for chestnut quality. This study is an important exploration of the phenotypic variation characteristics of the chestnut waxiness trait and lays a foundation for breeding high-quality chestnut cultivars. • A novel, instrumental method for objective waxiness evaluation in postharvest Chinese chestnut kernels was developed. • Kernel hardness after steaming was identified as the optimal parameter for predicting sensory waxiness. • A robust regression model was established to convert instrumental hardness into a reliable waxiness index. • The method enabled high-throughput phenotyping, revealing continuous waxiness variation in F 1 hybrid populations. • Significant maternal effects on kernel waxiness were uncovered, providing crucial insights for breeding strategies.

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Publication Details

Journal
Journal of Food Composition and Analysis
Published
2026-02-04
DOI
https://doi.org/10.1016/j.jfca.2026.108972
Primary Topic
Nuts composition and effects
Type
article
Field-Weighted Citation Impact
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article

Development of a texture analyzer-based method for waxiness evaluation and its application to phenotypic variation analysis in postharvest Chinese chestnut kernels

Lan Liu, Mengjie Shi, Yaqi Fan, Yan Liu et al.
Journal of Food Composition and Analysis
Nuts composition and effects
article

Development of a texture analyzer-based method for waxiness evaluation and its application to phenotypic variation analysis in postharvest Chinese chestnut kernels

Lan Liu, Mengjie Shi, Yaqi Fan, Yan Liu, Dongsheng Wang, Jing Liu, Haie Zhang, Xuan Wang, Liyang Yu
article en

Abstract

Waxiness is a critical textural factor determining the taste and consumer preference of postharvest Chinese chestnut ( Castanea mollissima Blume) kernels. However, its genetic improvement is hindered by the lack of an accurate, high-throughput phenotyping method and a clear understanding of its inheritance. In this study, a texture analyzer-based method was developed to objectively evaluate waxiness and analyze the associated phenotypic variations. Sensory waxy scores, starch composition, and texture parameters of 43 chestnut germplasms were evaluated. Notably, high-waxiness germplasms (waxy score > 80) exhibited significantly higher amylopectin content but had lower hardness and chewiness after steaming. Integrated analyses, including UPGMA clustering, principal component analysis, and Pearson correlation, convergently identified hardness as the optimal parameter for predicting waxiness. A robust regression model (Waxiness = 106.3041 - 0.3055 × Hardness) was established to quantify waxiness based on instrumental hardness measurements. Notably, the method effectively quantified continuous waxiness variation among 20 F 1 hybrid kernel populations and uncovered significant parental effects, thereby demonstrating its power as a reliable phenotyping tool when breeding for chestnut quality. This study is an important exploration of the phenotypic variation characteristics of the chestnut waxiness trait and lays a foundation for breeding high-quality chestnut cultivars. • A novel, instrumental method for objective waxiness evaluation in postharvest Chinese chestnut kernels was developed. • Kernel hardness after steaming was identified as the optimal parameter for predicting sensory waxiness. • A robust regression model was established to convert instrumental hardness into a reliable waxiness index. • The method enabled high-throughput phenotyping, revealing continuous waxiness variation in F 1 hybrid populations. • Significant maternal effects on kernel waxiness were uncovered, providing crucial insights for breeding strategies.

Journal of Food Composition and AnalysisVol. 151
Hebei Normal University of Science and Technology (CN)
Openalex Percentile: Top 68%
Nuts composition and effects
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