Automatic image-based determination of pruning mass as a determinant for yield potential in grapevine management and breeding

Kicherer A, Klodt M, Sharifzadeh S, Cremers D, Toepfer R, Herzog K (2017)

Publication Type: Journal article

Publication year: 2017

Journal

Australian Journal of Grape and Wine Research Wiley-Blackwell

Book Volume: 23

Pages Range: 120-124

Journal Issue: 1

DOI: 10.1111/ajgw.12243

Abstract

Background and Aims: Vine balance is defined as a relation between vegetative (mass of dormant pruning wood) and generative (yield) growth. For grapevine breeding, emphasis is usually placed on the evaluation of individual seedlings. In this study, we calculated the mass of dormant pruning wood with the assistance of an automated image-based method for estimating the pixel area of dormant pruning wood. The evaluation of digital images in combination with depth map calculation and image segmentation is a new and non-invasive tool for objective data acquisition. Methods and Results: The proposed method was tested on a set of seedlings planted at the Institute for Grapevine Breeding Geilweilerhof, Germany. All images taken in the field were geo-referenced, and the automated method was validated by manual segmentation. Together with additional yield parameters, the vine balance indices can be used to classify seedlings for breeding purposes. Conclusion: The computed pruning mass obtained using image-based methods is an accurate, inexpensive and easy method to estimate pruning mass compared with the manual time-consuming measurements. Together with the yield parameters, it is a suitable method for seedling evaluation and can also be used in precision viticulture. Significance of the Study: This study demonstrates an image-based evaluation of the pruning mass to be a highly valuable tool for grapevine research and grapevine breeding. Moreover, the tool might be used by industry to monitor vine balance. The key findings reported have the potential to increase grapevine breeding efficiency by using an accurate and objective phenotyping method.

Involved external institutions

Julius Kühn-Institut – Bundesforschungsinstitut für Kulturpflanzen (JKI) DE Germany (DE) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Kicherer, A., Klodt, M., Sharifzadeh, S., Cremers, D., Toepfer, R., & Herzog, K. (2017). Automatic image-based determination of pruning mass as a determinant for yield potential in grapevine management and breeding. Australian Journal of Grape and Wine Research, 23(1), 120-124. https://dx.doi.org/10.1111/ajgw.12243

MLA:

Kicherer, A., et al. "Automatic image-based determination of pruning mass as a determinant for yield potential in grapevine management and breeding." Australian Journal of Grape and Wine Research 23.1 (2017): 120-124.

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