Analysis of the causes of mastication trait of Chinese olives (Canarium album) based on sensory evaluation and establishment prediction model for mastication trait

• Sensory evaluation combined with texture profile analysis to achieve identification of differences in mastication trait. • AIR and SDF content play an important role in mastication trait. • Differences in cell wall organization exist in different varieties (lines). • Development of a regression prediction model for mastication trait. Mastication trait is an important quality indicator for evaluating Chinese olives, which affects consumer preference and market demand for Chinese olives. In order to investigate the factors influencing mastication trait in Chinese olives, this study examined 44 different varieties (lines). The mastication trait were assessed through sensory evaluation, texture profile analysis, ultrastructural, and biochemical analyses. Results indicated that Chinese olives with higher total sensory scores exhibited lower levels of hardness, gumminess, and chewiness in the textural characteristics. The cell wall composition of Chinese olive fruit was primarily composed of cellulose at an average percentage of 39.55 %, followed by Na 2 CO 3 -soluble pectin (22.05 %), lignin (17.43 %), chelator-soluble pectin (12.01 %), hemicellulose (5.13 %), and water-soluble pectin (3.84 %). Insoluble dietary fiber was the predominant dietary fiber component in the fruit, accounting for 94.41 % on average, with soluble dietary fiber making up the remaining 5.59 %. The results of the correlation analysis indicated that fruits with lower levels of hardness, gumminess, chewiness, Na 2 CO 3 -soluble pectin, alcohol-insoluble residue, chelator-soluble pectin, hemicellulose, cellulose, lignin, and insoluble dietary fiber, as well as higher levels of soluble dietary fiber, exhibited better mastication trait. The ultrastructure analysis revealed that the mastication trait of Chinese olive may be influenced by the number of cells, their arrangement, and cell thickness. A comprehensive prediction model was developed for the mastication trait total sensory score utilizing multiple stepwise regression, which incorporated textural characteristics and biochemical indexes. The model demonstrated a coefficient of determination of R 2 =0.751 and a relative error of δ=8.10 %. This study provides new insights into identifying differences in mastication trait among Chinese olives, as well as enhancing the selection and development of superior resources.