Outline analysis of the grapevine (Vitis vinifera L.) berry shape by elliptic Fourier descriptors

Authors

  • E. Somogyi Institute of Viticulture and Oenology, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • J. Lázár Institute of Viticulture and Oenology, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • L. Baranyai Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • P. Bodor-Pesti Institute of Viticulture and Oenology, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • D. A. Nyitrainé Sárdy Institute of Viticulture and Oenology, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary

DOI:

https://doi.org/10.5073/vitis.2022.61.63-70

Keywords:

uvometry, shape description, diversity, machine vision, image processing

Abstract

Grapevine berry morphology is one of the most important features in table grape production. In this study, berry samples of 46 grapevine accessions were investigated for 3 consecutive years with elliptic Fourier descriptors (EFD) to evaluate shape diversity. Ten reference shapes obtained from the OIV descriptor list were involved and principal component (PC) scores summarizing the EFD's were statistically evaluated with Two way ANOVA and discriminant analysis. The cummulative contribution of the five principal components was 96.83 %. Two way ANOVA revealed that berry shape had high variability within the accessions and years. Based on the linear discriminant analysis, reference shapes were compared to those of the accessions and graphic reconstruction was carried out. OIV references were considered as unknown samples and grouped into the accession classes. Overall correct classification of the accessions into their group was 13.88 %. Our results showed that EFD together with reference shapes are a powerful method to discribe berry shape and possibly give the future basis of uvometric evaluation of grapevine cultivars.

Downloads

Published

2022-06-29

Issue

Vol. 61 No. 2 (2022): Vitis

Section

Article

License

Copyright (c) 2022 The Author(s)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The content of VITIS is published under a Creative Commons Attribution 4.0 license. Any user is free to share and adapt (remix, transform, build upon) the content as long as the original publication is attributed (authors, title, year, journal, issue, pages) and any changes to the original are clearly labeled. We do not prohibit or charge a fee for reuse of published content. The use of general descriptive names, trade names, trademarks, and so forth in any publication herein, even if not specifically indicated, does not imply that these names are not protected by the relevant laws and regulations. The submitting author agrees to these terms on behalf of all co-authors when submitting a manuscript. Please be aware that this license cannot be revoked. All authors retain the copyright on their work and are able to enter into separate, additional contractual arrangements.