Vineyard yield estimation using 2-D proximal sensing : a multitemporal approach
Date
2020-10-23
Journal Title
Journal ISSN
Volume Title
Publisher
International Viticulture and Enology Society
Abstract
Vineyard yield estimation is a fundamental aspect in precision viticulture that enables a better understanding of the inherent variability within a vineyard. Yield estimation conducted early in the growing season provides insightful information to ensure the best fruit quality for the maximum desired yield. Proximal sensing techniques provide non-destructive in situ data acquisition for yield estimation during the growing season. This study aimed to determine the ideal phenological stage for yield estimation using 2-dimensional (2-D) proximal sensing and computer vision techniques in a vertical shoot positioned (VSP) vineyard. To achieve this aim, multitemporal digital imagery was acquired weekly over a 12-week period, with a final acquisition two days prior to harvest. Preceding the multitemporal analysis for yield estimation, an unsupervised k-means clustering (KMC) algorithm was evaluated for image segmentation on the final dataset captured before harvest, yielding bunch-level segmentation accuracies as high as 0.942, with a corresponding F1-score of 0.948. The segmentation yielded a pixel area (cm2), which served as input to across-validation model for calculating bunch mass (g). The ‘calculated mass’ was linearly regressed against the ‘actual mass’, indicating the capability for estimating vineyard yield. Results of the multitemporal analysis showed that the final stage of berry ripening was the ideal phenological stage for yield estimation, achieving a global r2 of 0.790.
Description
CITATION: Hacking, C., Poona, N. & Poblete-Echeverria, C. 2020. Vineyard yield estimation using 2-D proximal sensing : a multitemporal approach. Oeno One, 4:793-812, doi:10.20870/oeno-one.2020.54.4.3361.
The original publication is available at https://oeno-one.eu
The original publication is available at https://oeno-one.eu
Keywords
Vineyards, Computer vision, Crop estimating, Precision viticulture, Image segmentation, Remote sensing
Citation
Hacking, C., Poona, N. & Poblete-Echeverria, C. 2020. Vineyard yield estimation using 2-D proximal sensing : a multitemporal approach. Oeno One, 4:793-812, doi:10.20870/oeno-one.2020.54.4.3361.