基于叶片表型特征的文冠果生物柴油品质预测模型

In the realm of crop improvement, it is commonly employed the strategy of indirect selection,which relies on the identification of germplasm exhibiting favorable agronomic traits through their correlation with other intuitive traits. The plant yellowhorn (Xanthoceras sorbifolia bunge) is an ideal oil woody species for the production of biodiesel due to the high composition of oleic acid (C18:1) and linoleic acid (C18:2). Nevertheless, the knowledge about the correlation between the biodiesel characteristics and agronomic traits in yellowhorn remains to be elucidated. In this study, the leaf morphological structure, biodiesel characteristics and fatty acid composition of 206 yellowhorn germplasm resources were measured and calculated. The coefficients of variation for 25 leaf quality traits, 8 biodiesel characterization indexes, and 13 fatty acids composition of yellowhorn exhibited a ranged of -2.91 % ~1591.61 %, -0.11 % ~ 0.10 % and 2.89 % ~ 19.54 %, respectively. The correlation analysis showed that SPAD, FN, LRWC, LSI, δ15N and W/L showed stronger correlations with the biodiesel characterization indexes of yellowhorn, making them valuable indicators for assessing the relationship between leaf traits and biodiesel. Meanwhile, SPAD, LRWC, SLW, δ13C and FN (leaf photosynthetic index) also exhibited advantage significant associations with the majority of fatty acids. Finally, the key attributes of biodiesel (CN, IV, OS, and CFPP) were utilized as a foundation for constructing a prediction diagram for biodiesel characteristics, with the five primary leaf indicators (SPAD, FN, LRWC, LSI and W/L) serving as the vertices. This study provided valuable insights into the prediction of intricate biodiesel traits using easily measurable leaf traits.