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

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%)...

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Autores principales: Rivera, Sebastian, Kerckhoffs, Huub, Sofkova-Bobcheva, Svetla, Hutchins, Dan, East, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8405910/
https://www.ncbi.nlm.nih.gov/pubmed/34485643
http://dx.doi.org/10.1016/j.dib.2021.107313
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author Rivera, Sebastian
Kerckhoffs, Huub
Sofkova-Bobcheva, Svetla
Hutchins, Dan
East, Andrew
author_facet Rivera, Sebastian
Kerckhoffs, Huub
Sofkova-Bobcheva, Svetla
Hutchins, Dan
East, Andrew
author_sort Rivera, Sebastian
collection PubMed
description 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].
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spelling pubmed-84059102021-09-02 Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries Rivera, Sebastian Kerckhoffs, Huub Sofkova-Bobcheva, Svetla Hutchins, Dan East, Andrew Data Brief Data Article 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]. Elsevier 2021-08-20 /pmc/articles/PMC8405910/ /pubmed/34485643 http://dx.doi.org/10.1016/j.dib.2021.107313 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Rivera, Sebastian
Kerckhoffs, Huub
Sofkova-Bobcheva, Svetla
Hutchins, Dan
East, Andrew
Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries
title Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries
title_full Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries
title_fullStr Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries
title_full_unstemmed Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries
title_short Data of texture profile analysis performed by different input settings on stored ‘Nui’ and ‘Rahi’ blueberries
title_sort data of texture profile analysis performed by different input settings on stored ‘nui’ and ‘rahi’ blueberries
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8405910/
https://www.ncbi.nlm.nih.gov/pubmed/34485643
http://dx.doi.org/10.1016/j.dib.2021.107313
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