Application of 2D and 3D image technologies to characterise morphological attributes of grapevine clusters

[Background] Grapevine cluster morphology influences the quality and commercial value of wine and table grapes. It is routinely evaluated by subjective and inaccurate methods that do not meet the requirements set by the food industry. Novel two-dimensional (2D) and three-dimensional (3D) machine vision technologies emerge as promising tools for its automatic and fast evaluation. [Results] The automatic evaluation of cluster length, width and elongation was successfully achieved by the analysis of 2D images, significant and strong correlations with the manual methods being found (r = 0.959, 0.861 and 0.852, respectively). The classification of clusters according to their shape can be achieved by evaluating their conicity in different sections of the cluster. The geometric reconstruction of the morphological volume of the cluster from 2D features worked better than the direct 3D laser scanning system, showing a high correlation (r = 0.956) with the manual approach (water displacement method). In addition, we constructed and validated a simple linear regression model for cluster compactness estimation. It showed a high predictive capacity for both the training and validation subsets of clusters (R = 84.5 and 71.1%, respectively). [Conlucion] The methodologies proposed in this work provide continuous and accurate data for the fast and objective characterisation of cluster morphology. © 2016 Society of Chemical Industry.

Bibliographic Details

Main Authors:	Tello, Javier, Cubero, Sergio, Blasco, José, Tardáguila, Javier, Aleixos, Nuria, Ibáñez Marcos, Javier
Other Authors:	Ministerio de Economía y Competitividad (España)
Format:	artículo biblioteca
Published:	John Wiley & Sons 2016-10
Subjects:	Vitis vinifera L, Cluster shape, Machine vision, Cluster compactness, Cluster size,
Online Access:	http://hdl.handle.net/10261/146323 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/100007652 http://dx.doi.org/10.13039/501100000780
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