Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries

• Main Authors: Sebastian Rivera, Huub Kerckhoffs, Svetla Sofkova-Bobcheva, Dan Hutchins, Andrew East
• Format: Article
• Language: English
• Published: Elsevier 2021-10-01
• Series: Data in Brief
• Subjects: Vaccinium spp; Texture Profile Analysis; Mechanical property; Storage humidity
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340921005977

Texture Profile Analysis is a well-established method for assessing mechanical properties of horticultural food products and consists of two compression cycles on a repeated motion to a given strain using a flat surface probe (i.e., compression plate). Input settings of target deformation (strain%) and duration (s) between compression cycles utilized for Texture Profile Analysis could influence output mechanical properties. The article provides data related to the ability of different Texture Profile Analysis operational settings to enable the separation of blueberries with variable mechanical properties. To create variable mechanical parameters of ‘Nui’ and ‘Rahi’ blueberries, fruit was stored in four relative humidity for 21 d at 4°C. For each storage humidity, mechanical properties of hardness (BH, N), hardness slope (BHS, kN m−1), apparent modulus of elasticity (E, MPa), and resilience (BR, -) were determined by utilizing two strain (15% or 30% of berry equatorial height). Meanwhile, mechanical parameters of cohesiveness (BCo, -), and springiness (BSp, -) were obtained by utilizing the combination of two strain (15% or 30%) and two duration between cycles (2 s and 10 s) as TPA operational settings. The statistical evaluation was conducted by one-way ANOVA, and the means of each storage humidity were separated according to the Tukey-HSD test (P = 0.05). The data presented in this article was used to select the Texture Profile Analysis operational settings utilized in the article entitled “Influence of water loss on mechanical properties of stored blueberries” Rivera et al. [1].