A Three-dimensional Statistical Reconstruction Model of Grapevine (Vitis vinifera) Simulating Canopy Structure Variability within and between Cultivar/Training System Pairs

Abstract

The parameter values obtained in each situation were consistent with our knowledge of grapevine architecture. Quantitative assessments for the generated virtual scenes were carried out at the canopy and plant scales. Light interception efficiency and local variations of light transmittance within and between experimental plots were correctly simulated for all canopies studied. The approach predicted these key ecophysiological variables significantly more accurately than the classical complete digitization method with a limited number of plants. In addition, this model accurately reproduced the characteristics of a wide range of individual digitized plants. Simulated leaf area density and the distribution of light interception among leaves were consistent with measurements. However, at the level of individual organs, the model tended to underestimate light interception.

A leaf gas exchange model that accounts for intra‐canopy variability by considering leaf nitrogen content and local acclimation to radiation in grapevine (Vitis vinifera L.)

“…2007). We reconstructed 3D mock‐ups with a model for grapevine (TOPVINE, Louarn, Lecoeur & Lebon 2008) available on an open‐source platform for functional‐structural plant modelling (OpenAlea; Pradal et al . 2008).…”

Visualizing and Quantifying Vineyard Canopy LAI Using an Unmanned Aerial Vehicle (UAV) Collected High Density Structure from Motion Point Cloud

“…Although not specifically applied to viticulture, airborne lidar datasets can confidently predict LAI and other biophysical characteristics of tree vegetation by calculating several height-based metrics [16][17][18][19]. Yet another method, that of statistically-based modeling, was implemented by [20] to look at single vine canopy and explore potential light interception for different grapevine varietals. For sake of practicality and cost though, airborne and terrestrial lidar datasets have proven difficult to acquire [21] and repeat acquisitions are usually cost-prohibitive.…”

Simple envelope-based reconstruction methods can infer light partitioning among individual plants in sparse and dense herbaceous canopies

“…If in some cases practical reconstruction solutions might appear tractable by directly applying the "finer scale description" principle (Oker-Blom and Kellomäki, 1983;Sonohat et al,2006;630 Da Silva et al, 2008;Louarn et al, 2008a), in many situations the number of inner scale components still exceeds any reasonable capacity of direct follow-up in the field (e.g. characterisation of all tillers in grass plants for the present study).…”

“…They are based on the coupling of light models with simplified envelope-based plant structures (e.g. envelope-based turbid medium, 115 Norman and Welles, 1983;Johnson and Lakso, 1991;Law et al, 2001) or stochastic 3D-explicit statistical reconstructions (Giuliani et al, 2005;Sonohat et al, 2006;Louarn et al, 2008a). The rationale behind the possible simplifications regarding actual plants within a canopy remains however poorly understood.…”