Finite Element Analysis and Near-Infrared Hyperspectral Reflectance Imaging for the Determination of Blueberry Bruise Grading.
blueberry bruise damage
finite element
hyperspectral reflectance imaging
response surface
uniaxial compression experiment
Journal
Foods (Basel, Switzerland)
ISSN: 2304-8158
Titre abrégé: Foods
Pays: Switzerland
ID NLM: 101670569
Informations de publication
Date de publication:
27 Jun 2022
27 Jun 2022
Historique:
received:
21
05
2022
revised:
10
06
2022
accepted:
13
06
2022
entrez:
9
7
2022
pubmed:
10
7
2022
medline:
10
7
2022
Statut:
epublish
Résumé
Bruising of the subcutaneous tissues of blueberries is an important form of mechanical damage. Different levels of bruising have a significant effect on the post-harvest marketing of blueberries. To distinguish different grades of blueberry bruises and explore the effects of different factors, explicit dynamic simulation and near-infrared hyperspectral reflectance imaging were employed without harming the blueberries in this study. Based on the results of the compression experiment, an explicit dynamic simulation of blueberries was performed to measure the potential locations of bruises and preliminarily divide the bruise stages. A near-infrared hyperspectral reflectance imaging system was used to detect the actual blueberry bruises. According to the blueberry photos taken by the near-infrared hyperspectral reflectance imaging system, the actual bruise rates of blueberries were obtained by using the Environment for Visualizing Images software for training and classification. Bruise grades of blueberries were divided accordingly. Response surface methodology was used to determine the effects of ripeness, loading speed and loading location on the blueberry bruising rate. Under the optimized parameters, the actual damage rate of blueberries was 1.1%. The results provide an important theoretical basis for the accurate and rapid identification and classification of blueberry bruise damage.
Identifiants
pubmed: 35804715
pii: foods11131899
doi: 10.3390/foods11131899
pmc: PMC9265279
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Key-Area Research and Development Program of Guangdong Province
ID : 2020B0202010004
Organisme : National Natural Science Foundation of China
ID : 31901824
Organisme : Natural Science Foundation of Tianjin City
ID : 19JCQNJC13600
Organisme : Scientific Research Project of Tianjin Municipal Education Commission
ID : 2018KJ120
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