Location: Healthy Processed Foods ResearchTitle: Texture attributes of a persimmon (Diospyros kaki) chip-style product Author
Submitted to: Annual Meeting of the Institute of Food Technologists
Publication Type: Abstract Only
Publication Acceptance Date: 3/18/2017
Publication Date: N/A
Citation: N/A Interpretive Summary:
Technical Abstract: Asian persimmons (Diospyros kaki) are tree fruits that have not yet been widely commercialized into value-added products. A dried, chip-style product (analogous to banana chips) has been developed for persimmons, and the objectives of this work were to characterize the texture of hot-air dried persimmon chips from both instrumental and sensory perspectives and to determine if the sensory attributes of the chips could be predicted from instrumental measurements alone. Dried chip-style products were prepared from 54 persimmon samples, representing 39 cultivars – some harvested multiple times and from multiple sources/orchard locations. Texture attributes of the products were measured using 2 instrumental procedures: texture profile analysis [TPA] and shear analysis [SA] . A cork borer (3 mm) was used to prepare samples of equal diameter for TPA, and a line segment of 15 mm was used for the slicing area for SA. Astringent cultivars had the greatest fracture and hardness, at 386 and 400 N, respectively. Nonastringent cultivars had the least fracture and hardness, 263 and 295 N, respectively. Variant cultivars were closer to astringent cultivars with fracture and hardness values of 357 and 365 N, respectively. This ranking was similar for adhesiveness and chewiness. Results from the SA also demonstrated that astringent cultivars had the greatest maximum load at 365 N followed by variants at 185 N and least was nonastringent at 137 N. The 8 measured sensory texture attributes were ‘Roughness’, ‘Moistness’, ‘Hardness’, ‘Crispness’, ‘Toughness of Skin’, ‘Fibrousness’, ‘Chewiness’, and ‘Tooth Packing’. Of these, only ‘Tooth Packing’ was not correlated (p < 0.01) with any of the instrumental texture attributes. This is an expected result, since ‘Tooth Packing’ is evaluated after expectoration, which is not a physical situation that can be easily replicated on a laboratory instrument. Partial least squares regression analysis with leave-one-out cross validation was used to generate regression equations for predicting the sensory attributes (except ‘Tooth Packing’) from the instrumental attributes. This work will enable more rapid development of dried persimmon chips that possess specific textural attributes.