A comparative analysis of the discrimination of pepper (Capsicum annuum L.) based on the cross‐section and seed textures determined using image processing. (13th April 2021)
- Record Type:
- Journal Article
- Title:
- A comparative analysis of the discrimination of pepper (Capsicum annuum L.) based on the cross‐section and seed textures determined using image processing. (13th April 2021)
- Main Title:
- A comparative analysis of the discrimination of pepper (Capsicum annuum L.) based on the cross‐section and seed textures determined using image processing
- Authors:
- Ropelewska, Ewa
Szwejda‐Grzybowska, Justyna - Abstract:
- Abstract: The aim of this study was to develop the models based on the texture parameters of images of selected parts of pepper fruit for cultivar discrimination. This study was aimed to compare the usefulness of textures from cross‐sections (slices) and seeds of pepper for distinguishing the different cultivars using the discriminative classifiers. The textures from the cross‐sections and seeds were calculated based on images converted to individual color channels. The texture selections and discriminant analyzes were performed separately for color spaces RGB, Lab, XYZ and color channels R, G, B, L, a, b, X, Y, Z . In the case of pepper cross‐sections, the discriminant models built for color space RGB, color channel G, color space Lab, color channel L, color space XYZ and color channel Y provided the total accuracies reaching 100%. In the case of pepper seeds, the total accuracies reached 89% for models built based on textures selected from color space RGB, 90% for color space Lab and 82% for color space XYZ. Among the color channels from individual color spaces, the highest total accuracies were determined for color channel R (84%), color channel L (81%), and color channel X (83%). Practical Applications: The developed discrimination models can be practically applied for the identification of pepper cultivars in a fast, objective and inexpensive way. Both, in the case of pepper cross‐sections and pepper seeds, the cultivar may be distinguished with a very high probability.Abstract: The aim of this study was to develop the models based on the texture parameters of images of selected parts of pepper fruit for cultivar discrimination. This study was aimed to compare the usefulness of textures from cross‐sections (slices) and seeds of pepper for distinguishing the different cultivars using the discriminative classifiers. The textures from the cross‐sections and seeds were calculated based on images converted to individual color channels. The texture selections and discriminant analyzes were performed separately for color spaces RGB, Lab, XYZ and color channels R, G, B, L, a, b, X, Y, Z . In the case of pepper cross‐sections, the discriminant models built for color space RGB, color channel G, color space Lab, color channel L, color space XYZ and color channel Y provided the total accuracies reaching 100%. In the case of pepper seeds, the total accuracies reached 89% for models built based on textures selected from color space RGB, 90% for color space Lab and 82% for color space XYZ. Among the color channels from individual color spaces, the highest total accuracies were determined for color channel R (84%), color channel L (81%), and color channel X (83%). Practical Applications: The developed discrimination models can be practically applied for the identification of pepper cultivars in a fast, objective and inexpensive way. Both, in the case of pepper cross‐sections and pepper seeds, the cultivar may be distinguished with a very high probability. In order to increase the range of use of the developed procedure, the research may be extended to other cultivars. It may allow to avoid adulteration of pepper fruit and seeds. Abstract : … (more)
- Is Part Of:
- Journal of food process engineering. Volume 44:Number 6(2021)
- Journal:
- Journal of food process engineering
- Issue:
- Volume 44:Number 6(2021)
- Issue Display:
- Volume 44, Issue 6 (2021)
- Year:
- 2021
- Volume:
- 44
- Issue:
- 6
- Issue Sort Value:
- 2021-0044-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-04-13
- Subjects:
- Food industry and trade -- Periodicals
Food -- Analysis -- Periodicals
664.005 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1745-4530 ↗
http://www.blackwell-synergy.com/openurl?genre=journal&issn=0145-8876 ↗
http://onlinelibrary.wiley.com/ ↗
http://www.blackwell-synergy.com/loi/jfpe ↗ - DOI:
- 10.1111/jfpe.13694 ↗
- Languages:
- English
- ISSNs:
- 0145-8876
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4984.545000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 18227.xml