The sensory evaluation of cohesiveness, hardness and springiness of 15 solid food samples was performed by eight trained assessors. The rheological response of the 15 samples was estimated by performing cyclic compression tests and stress–relaxation tests. From the force–deformation curves of the first two cycles of the compression test, texture profile analysis parameters related to cohesiveness, hardness and springiness were calculated. Young's modulus (E), strain (di) and stress (si) at peak as well as irrecoverable strain (ri) and irrecoverable work (Li) were monitored during the first five cycles. From the stress–relaxation response, Peleg's linearization model parameters, K1 and K2, were estimated by best-fit regression. These parameters were used for predicting sensory attributes. Hardness and springiness were both accurately predicted by rheological properties, while cohesiveness prediction was less representative.
Predicting sensory cohesiveness, hardness and springiness of solid foods from instrumental measurements / DI MONACO, Rossella; Cavella, Silvana; Masi, Paolo. - In: JOURNAL OF TEXTURE STUDIES. - ISSN 0022-4901. - STAMPA. - 39:(2008), pp. 129-149.
Predicting sensory cohesiveness, hardness and springiness of solid foods from instrumental measurements
DI MONACO, ROSSELLA;CAVELLA, SILVANA;MASI, PAOLO
2008
Abstract
The sensory evaluation of cohesiveness, hardness and springiness of 15 solid food samples was performed by eight trained assessors. The rheological response of the 15 samples was estimated by performing cyclic compression tests and stress–relaxation tests. From the force–deformation curves of the first two cycles of the compression test, texture profile analysis parameters related to cohesiveness, hardness and springiness were calculated. Young's modulus (E), strain (di) and stress (si) at peak as well as irrecoverable strain (ri) and irrecoverable work (Li) were monitored during the first five cycles. From the stress–relaxation response, Peleg's linearization model parameters, K1 and K2, were estimated by best-fit regression. These parameters were used for predicting sensory attributes. Hardness and springiness were both accurately predicted by rheological properties, while cohesiveness prediction was less representative.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.