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How does Computer vision compare to standard colorimeter in assessing the seed coat color of common bean (Phaseolus vulgaris L.)?
- Source :
- Journal of Central European Agriculture, Vol 20, Iss 4, Pp 1169-1178 (2019)
- Publication Year :
- 2019
- Publisher :
- Journal of Central European Agriculture, 2019.
-
Abstract
- Common bean (Phaseolus vulgaris L.) exhibits a wide range of seed coat colors and this morphological trait is widely used in cultivar identification and assessment of diversity within this species. With an advancement in technology and informatics, new methods of assessing seed color are emerging in addition to traditionally used visual observation. Due to a great variety of color measuring techniques, the evaluation of the agreement between methods is needed prior to using the methods interchangeably. Seed coat color in terms of CIE L*a*b* color coordinates of 100 common bean accessions belonging to five mono- colored landraces was assessed using two methods, colorimeter and Computer vision. The percentage difference between the two methods across all samples for L* color coordinate was 5.81%, for a* color coordinate 23.32% and for b* color coordinate 44.44%. According to Bland- Altman difference plot there is a considerable lack of agreement between the two methods. However, using stepwise discriminant analysis revealed that colorimeter method correctly classified 97% of accessions into their respective landrace, while the classification success of the Computer vision was 99%.
- Subjects :
- common bean
Coat
biology
business.industry
Stepwise discriminant analysis
Colorimeter
lcsh:S
colorimetry
Computer vision
landrace
biology.organism_classification
computer vision
lcsh:Agriculture
Animal Science and Zoology
Artificial intelligence
Cultivar
Phaseolus
Colorimetry
business
Agronomy and Crop Science
Color coordinates
Morphological trait
Mathematics
Subjects
Details
- ISSN :
- 13329049
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- Journal of Central European Agriculture
- Accession number :
- edsair.doi.dedup.....b8a20b337191722c8894da282dc48fb8
- Full Text :
- https://doi.org/10.5513/jcea01/20.4.2509