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:...

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Main Authors: José Javier Martín-Gómez, Agnieszka Rewicz, Klaudia Goriewa-Duba, Marian Wiwart, Ángel Tocino, Emilio Cervantes
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Agronomy
Subjects:
Online Access:https://www.mdpi.com/2073-4395/9/7/399
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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
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