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1 Definition of seed morphology. General view. From a descriptive to a numerical science. Magnitudes in morphomety. The J index. + 586 word(s) 586 2020-06-23 08:12:47 |
2 Corrected punctuation marks Meta information modification 586 2020-07-02 16:03:12 | |
3 Corrected: morphometry. -2 word(s) 584 2020-10-13 12:52:43 | |
4 format correct -74 word(s) 510 2020-10-28 07:48:39 | |
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Martín-Gómez, J.J.; Gutiérrez Del Pozo, D.; Ucchesu, M.; Bacchetta, G.; Cabello Sáenz De Santamaría, F.; Tocino, �.; Cervantes, E. Seed Morphology. Encyclopedia. Available online: https://encyclopedia.pub/entry/1218 (accessed on 29 March 2024).
Martín-Gómez JJ, Gutiérrez Del Pozo D, Ucchesu M, Bacchetta G, Cabello Sáenz De Santamaría F, Tocino �, et al. Seed Morphology. Encyclopedia. Available at: https://encyclopedia.pub/entry/1218. Accessed March 29, 2024.
Martín-Gómez, José Javier, Diego Gutiérrez Del Pozo, Mariano Ucchesu, Gianluigi Bacchetta, Félix Cabello Sáenz De Santamaría, Ángel Tocino, Emilio Cervantes. "Seed Morphology" Encyclopedia, https://encyclopedia.pub/entry/1218 (accessed March 29, 2024).
Martín-Gómez, J.J., Gutiérrez Del Pozo, D., Ucchesu, M., Bacchetta, G., Cabello Sáenz De Santamaría, F., Tocino, �., & Cervantes, E. (2020, June 29). Seed Morphology. In Encyclopedia. https://encyclopedia.pub/entry/1218
Martín-Gómez, José Javier, et al. "Seed Morphology." Encyclopedia. Web. 29 June, 2020.
Seed Morphology
Edit

Seed morphology is the scientific analysis and description of the shape of seeds.

description geometry morphology seed shape taxonomy

1. Introduction

Traditionally the objective of seed morphology was to provide a concise description, based in qualitative aspects, normally expressed in the form of adjectives.

For example, in the genus Vitis, adjectives used to describe seed shape  include the following: cordate, globose, globular, oblong, oval, ovoid, pear-shaped (pyriform)  rounded, squat and triangular. [1][2][3]

Magnitudes used to measure seed shape in Vitis include seed length, seed breadth, chalazal length, chalazal position and others describing primary aspects of the morphology of pips, as indicated by Jaquat and Martinolli[4] and Mangafa and Kotsakis.[3]

2. Methods

Modern methods of automated vision are based on the coordinates of the points in a bi-dimensional image and permit new approaches to seed morphology. Digital image analysis coupled with morphometric studies of grape seeds is a relatively new application in the plant research field. By using a set of high-resolution digital images, it is possible to obtain measurements of morphometric, colorimetric and textural features, describing the shape, size, color and texture of seeds, and this quantitative information can be correlated with various qualitative aspects of the seeds. The data obtained, corresponding to magnitudes such as area, perimeter, circularity and roundness [3][5][6][7][8], can be combined and subjected to analysis based on diverse algorithms, for example, elliptic Fourier (EFD) and Aralik descriptors. Finally, in all cases, the data are collected in a matrix and can be submitted to Linear Discriminant Analysis (LDA), to classify the seeds in groups.[9][5][6][10][11][12][13].

There is an interest, both theoretical and applied, in joining both aspects of morphology: the descriptive adjectives and the measurements with the objective of testing if the groups defined by artificial vision and statistical analysis correspond to well defined geometric figures. This objective, that we may define as obtaining new measurable adjectives, can be reached by comparing the seed images with geometric models based on mathematical curves. This way, we obtain the J index that gives the percent of similarity between the two images (the bi-dimensional image of the seed and the geometric model). High values of J index were obtained when comparing images of seeds with the cardioid or modified cardioids in the model plant Arabidopsis thaliana (L.) Heynh[14], as well as in the model legumes, Lotus japonicus L. and Medicago truncatula Gaertn. [15], also in Capparis spinosa L.[16], and in species of the Papaveraceae and Malvaceae [17][18].

Other geometric models include the ovoid and the ellipse, that give high values of J index with seeds of species in the Cucurbitaceae[19] and in the Euphorbiaceae, such as Ricinus L. and Jatropha L. [20][21]. Seed shape in wheat kernels was described based on three geometric figures: (1) an ellipse of aspect ratio (AR) = 1.8 fitting the “round varieties” (T. aestivum L. ssp. aestivum cv. Zebra and Torka), (2) a lens of AR = 3.2 for the elongated kernels (T. monococcum L.), and (3) an ellipse of AR = 2.4 that adjusted well the kernels of intermediate-shaped varieties such as T. durum  Desf. cv. Floradur [22]. The adjustment of seed shape to geometrical forms has been reported recently in Vitis sp. [23]

References

  1. Planchon, J. E.; Ampelideae, Monographie des Ampélidées Vraies. In: A. P. De Candolle (ed.): Monographiae Phanerogamarum 5, 305-368. Treuttel et Würtz, Paris, 1887.
  2. Viala, P.; Péchoutre, P. Morphologie externe de la graine In: P. Viala, V. Vermorel (eds.): Ampélographie 1, 156-166. Masson et Cie. Paris, 1910.
  3. Mangafa, M.; Kotsakis, K. A new method for the identification of wild and cultivated charred grape seeds. J Archaeol Sci 1996, 23, 409–418.
  4. Jacquat, Ch.; Martinoli, D.; Vitis vinifera L.: Wild or cultivated? Study of the grape pips found at Petra, Jordan: 150 B.C. - A.D. 40. . Veget Hist Archaeobot 1999, 8, 25-30.
  5. Orrú, M.; Grillo, O.; Lovicu, G; Venora, G.; Bacchetta, G.; Morphological characterisation of Vitis vinifera L. seeds by image analysis and comparison with archaeological remains. . Veget Hist Archaeobot 2013, 22, 231-242.
  6. Orrú, M.; Grillo, O.; Venora, G.; Bacchetta, G.; Seed morpho-colorimetric analysis by computer vision: a helpful tool to identify grapevine (Vitis vinifera L.) cultivars.. Aust J Grape Wine Res 2015, 21, 508–519..
  7. Rovner, I.; Gyulai, F.; Computer-assisted morphometry: a new method for assessing and distinguishing morphological variation in wild and domestic seed populations.. Econ Bot 2007, 61, 154-172..
  8. Sonka, M.; Hlavac, V.; Boyle, R. . Image Processing analysis and machine vision.; Thomson Learning: UK, 2008; pp. 829.
  9. Rivera D.; Miralles, B.; Obón, C.; Carreño, E.; Palazón J.A.; Multivariate analysis of Vitis subgenus Vitis seed morphology. . Vitis 2007, 46, 158-167.
  10. Ucchesu, M.; Orrú, M.; Grillo, O.; Venora , G.; Usai, A.; Serreli, P.F.; Bacchetta, G. Earliest evidence of a primitive cultivar of Vitis vinifera L. during the Bronze Age in Sardinia (Italy). Veget Hist Archaeobot; Earliest evidence of a primitive cultivar of Vitis vinifera L. during the Bronze Age in Sardinia (Italy). Veget Hist Archaeobot. Veget Hist Archaeobot 2015, 24, 587-600..
  11. Ucchesu, M.; Orrú, M.; Grillo, O.; Venora , G.; Paglietti, G.; Ardu, A.; Bacchetta, G.; Predictive Method for Correct Identification of Archaeological Charred Grape Seeds: Support for Advances in Knowledge of Grape Domestication Process. . PLoS ONE 2016, 11, e0149814, doi:10.1371/journal.pone.0149814.
  12. Milanesi, C.; Costantini, L.; Firmati, M.; Antonucci,F.; Faleri, C.; Buracchi, A.; Cresti, M.; Geometric morphometry and archaeobotany: characterisation of grape seeds (Vitis vinifera L.) by analysis of form.. Open Access Library Journal 2014, 1, e634, http://dx.doi.org/10.4236/oalib.1100634..
  13. Mravcsik, Z.; Gyulai, F.; Vinogradov, S.; Emödi, A.; Rovner, I.; Gyulai, G.; Digital seed morphometry for genotype identification case study of seeds of excavated (15th century Hungary) and current vine grape (Vitis v. vinifera) varieties.. Acta Bot Hung 2015., 57, 169–182..
  14. Cervantes, E.; Martín, J.J.; Ardanuy, R.; de Diego, J.G.; Tocino, Á.; Modeling the Arabidopsis seed shape by a cardioid: efficacy of the adjustment with a scale change with factor equal to the Golden Ratio and analysis of seed shape in ethylene mutants. J Plant Physiol 2010, 67, 408-410., https://doi.org/10.1016/j.jplph.2009.09.013.
  15. Cervantes, E.; Martín, J.J.; Chan, P.K.; Gresshoff, P.M.; Tocino, Á.; Seed shape in model legumes: approximation by a cardioid reveals differences in ethylene insensitive mutants of Lotus japonicus and Medicago truncatula. . J Plant Physiol 2012, 169, 1359-1365., https://doi.org/ 10.1016/j.jplph.2012.05.019..
  16. Saadaoui, E.; Martín, J.J.; Cervantes, E.; Seed morphology in Tunisian wild populations of Capparis spinosa L. . Acta Biol Cracov Ser Bot 2013, 55, 99–106., https://doi.org/10.5897/AJB10.1429..
  17. Martín-Gómez, J.J. Rewicz, A.; Cervantes; Seed Shape Diversity in families of the Order Ranunculales. . Phytotaxa 2019, 425, 193–207., https://doi.org/10.11646/phytotaxa.425.4.1.
  18. José Javier Martín Gómez; Diego Gutiérrez Del Pozo; Emilio Cervantes; Seed Shape Quantification in the Malvaceae Reveals Cardioid-Shaped Seeds Predominantly in Herbs. Botanica 2019, 25, 21-31, 10.2478/botlit-2019-0003.
  19. Cervantes, E.; Martín-Gómez, J.J.; Seed shape quantification in the order Cucurbitales. Modern Phytomorphol 2018, 12, 1–13. , https://doi.org/10.5281/zenodo.117487.
  20. José Javier Martín-Gómez; Ezzeddine Saadaoui; Emilio Cervantes; Seed Shape of Castor Bean (Ricinus communis L.) Grown in Different Regions of Tunisia. Journal of Agriculture and Ecology Research International 2016, 8, 1-11, 10.9734/jaeri/2016/23934.
  21. Ezzeddine Saadaoui; José Javier Martín; Rebeh Bouazizi; Chokri Ben Romdhane; Mohamed Grira; Saad Abdelkabir; Med Larbi Khouja; Emilio Cervantes; Phenotypic variability and seed yield of Jatropha curcas L. introduced to Tunisia. Acta Botanica Mexicana 2015, 1, 119-134, 10.21829/abm110.2015.193.
  22. 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 2019, 9, 399, 10.3390/agronomy9070399.
  23. José Javier Martín-Gómez; Diego Gutiérrez Del Pozo; Mariano Ucchesu; Gianluigi Bacchetta; Félix Cabello Sáenz De Santamaría; Ángel Tocino; Emilio Cervantes; Seed Morphology in the Vitaceae Based on Geometric Models. Agronomy 2020, 10, 739, 10.3390/agronomy10050739.
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