Morphological Description and Classification of Wheat Kernels Based on Geometric Models
Modern automated and semi-automated methods of shape analysis depart from the coordinates of the points in the outline of a figure and obtain, based on artificial vision algorithms, descriptive parameters (i.e., the length, width, area, and circularity index). These methods omit an important factor:...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-07-01
|
Series: | Agronomy |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4395/9/7/399 |
id |
doaj-5a112717121c460ba03d0b5b9d1dc44b |
---|---|
record_format |
Article |
spelling |
doaj-5a112717121c460ba03d0b5b9d1dc44b2021-04-02T11:00:26ZengMDPI AGAgronomy2073-43952019-07-019739910.3390/agronomy9070399agronomy9070399Morphological Description and Classification of Wheat Kernels Based on Geometric ModelsJosé Javier Martín-Gómez0Agnieszka Rewicz1Klaudia Goriewa-Duba2Marian Wiwart3Ángel Tocino4Emilio Cervantes5IRNASA-CSIC (Institute of Natural Resources and Agronomy-Consejo Superior de Investigaciones Científicas), Cordel de Merinas, 40, E-37008 Salamanca, SpainDepartment of Geobotany and Plant Ecology, Faculty of Biology and Environmental Protection, University of Lodz, 12/16 Banacha Str., 90-237 Lodz, PolandDepartment of Plant Breeding and Seed Production, University of Warmia and Mazury in Olsztyn, 10-724 Olsztyn, PolandDepartment of Plant Breeding and Seed Production, University of Warmia and Mazury in Olsztyn, 10-724 Olsztyn, PolandDepartamento de Matemáticas, Universidad de Salamanca, Plaza de la Merced 1, 37008 Salamanca, SpainIRNASA-CSIC (Institute of Natural Resources and Agronomy-Consejo Superior de Investigaciones Científicas), Cordel de Merinas, 40, E-37008 Salamanca, SpainModern automated and semi-automated methods of shape analysis depart from the coordinates of the points in the outline of a figure and obtain, based on artificial vision algorithms, descriptive parameters (i.e., the length, width, area, and circularity index). These methods omit an important factor: the resemblance of the examined images to a geometric figure. We have described a method based on the comparison of the outline of seed images with geometric figures. The J index is the percentage of similarity between a seed image and a geometric figure used as a model. This allows the description and classification of wheat kernels based on their similarity to geometric models. The figures used are the ellipse and the lens of different major/minor axis ratios. Kernels of different species, subspecies and varieties of wheat adjust to different figures. A relationship is found between their ploidy levels and morphological type. Kernels of diploid einkorn and ancient tetraploid emmer varieties adjust to the lens and have curvature values in their poles superior to modern “bread” varieties. Kernels of modern varieties (hexaploid common wheat) adjust to an ellipse of aspect ratio = 1.6, while varieties of tetraploid durum and Polish wheat and hexaploid spelt adjust to an ellipse of aspect ratio = 2.4.https://www.mdpi.com/2073-4395/9/7/399geometric curvesJ indexkernelimage analysismorphologyseedshapewheat |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
José Javier Martín-Gómez Agnieszka Rewicz Klaudia Goriewa-Duba Marian Wiwart Ángel Tocino Emilio Cervantes |
spellingShingle |
José Javier Martín-Gómez Agnieszka Rewicz Klaudia Goriewa-Duba Marian Wiwart Ángel Tocino Emilio Cervantes Morphological Description and Classification of Wheat Kernels Based on Geometric Models Agronomy geometric curves J index kernel image analysis morphology seed shape wheat |
author_facet |
José Javier Martín-Gómez Agnieszka Rewicz Klaudia Goriewa-Duba Marian Wiwart Ángel Tocino Emilio Cervantes |
author_sort |
José Javier Martín-Gómez |
title |
Morphological Description and Classification of Wheat Kernels Based on Geometric Models |
title_short |
Morphological Description and Classification of Wheat Kernels Based on Geometric Models |
title_full |
Morphological Description and Classification of Wheat Kernels Based on Geometric Models |
title_fullStr |
Morphological Description and Classification of Wheat Kernels Based on Geometric Models |
title_full_unstemmed |
Morphological Description and Classification of Wheat Kernels Based on Geometric Models |
title_sort |
morphological description and classification of wheat kernels based on geometric models |
publisher |
MDPI AG |
series |
Agronomy |
issn |
2073-4395 |
publishDate |
2019-07-01 |
description |
Modern automated and semi-automated methods of shape analysis depart from the coordinates of the points in the outline of a figure and obtain, based on artificial vision algorithms, descriptive parameters (i.e., the length, width, area, and circularity index). These methods omit an important factor: the resemblance of the examined images to a geometric figure. We have described a method based on the comparison of the outline of seed images with geometric figures. The J index is the percentage of similarity between a seed image and a geometric figure used as a model. This allows the description and classification of wheat kernels based on their similarity to geometric models. The figures used are the ellipse and the lens of different major/minor axis ratios. Kernels of different species, subspecies and varieties of wheat adjust to different figures. A relationship is found between their ploidy levels and morphological type. Kernels of diploid einkorn and ancient tetraploid emmer varieties adjust to the lens and have curvature values in their poles superior to modern “bread” varieties. Kernels of modern varieties (hexaploid common wheat) adjust to an ellipse of aspect ratio = 1.6, while varieties of tetraploid durum and Polish wheat and hexaploid spelt adjust to an ellipse of aspect ratio = 2.4. |
topic |
geometric curves J index kernel image analysis morphology seed shape wheat |
url |
https://www.mdpi.com/2073-4395/9/7/399 |
work_keys_str_mv |
AT josejaviermartingomez morphologicaldescriptionandclassificationofwheatkernelsbasedongeometricmodels AT agnieszkarewicz morphologicaldescriptionandclassificationofwheatkernelsbasedongeometricmodels AT klaudiagoriewaduba morphologicaldescriptionandclassificationofwheatkernelsbasedongeometricmodels AT marianwiwart morphologicaldescriptionandclassificationofwheatkernelsbasedongeometricmodels AT angeltocino morphologicaldescriptionandclassificationofwheatkernelsbasedongeometricmodels AT emiliocervantes morphologicaldescriptionandclassificationofwheatkernelsbasedongeometricmodels |
_version_ |
1724165988976427008 |