A Geometric Approach to Kiwifruit Canopy Modelling

Succi, F.; Magnanini, E.; Quadretti, R.; Miserocchi, O.; Costa, Gabriel Brito

doi:10.17660/actahortic.1997.444.26

Cited by 5 publications

(5 citation statements)

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“…In such cases, calculations for stands of plants are generally based on measurements from one to five plants, replicated to represent the field, and microclimatic variables are inferred from this sample, which is assumed to be representative. Although often ignored, plant to plant variability is probably significant in many cases (Casteran et al, 1980;Succi et al, 1997). This is particularly true for vine species, in which the shape of shoots is far from consistent (Carbonneau and Cargnello, 2003).…”

Section: Introductionmentioning

confidence: 99%

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

2007

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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.

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Section: Introductionmentioning

confidence: 99%

“…Several statistical models based on Monte Carlo simulation (Hammerley and Hanscomb, 1964) have been described (Succi et al, 1997;Ross and Ross, 1998;Giuliani et al, 2005). All these models infer the reconstruction rules for the canopy from an extracted data sample.…”

Section: Introductionmentioning

confidence: 99%

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

2007

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“…Recently, probabilistic approaches have been propounded for field use (Poni et al 1996;Succi et al 1997;Kucharik, Norman & Gower 1998) to define canopy architecture and the foliage distribution of fruit trees. There are also new methodologies to configure a three-dimensional canopy by quoting its components (Sinoquet & Rivet 1997;Carboni 1998;Mabrouk & Sinoquet 1998) and to simulate canopy geometry using a volume-rendering technique (Ivanov et al 1995;Tanaka, Yamaguchi & Takeda 1998).…”

Section: Canopy Tomographymentioning

confidence: 99%

Ground monitoring the light–shadow windows of a tree canopy to yield canopy light interception and morphological traits

Giuliani

Magnanini

Fragassa

et al. 2000

Plant Cell & Environment

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Monitoring the light-shadow windows of a tree via a grid system on the ground was performed on sunny summer days at high spatial resolution using a custom-built, inexpensive scanner. The measurements were taken with two goals: (1) to quickly and remotely quantify the overall, short-wave solar radiation (300-1100 nm) intercepted by the tree canopy, and (2) to yield such crown geometric traits as shape, size and the number of theoretical canopy leaf layers (leaf layer index, LLI) in relation to the section orthogonal to sunbeam direction (sun window). The ground readings at each measurement over the day were used to project a digitized shadow image. Image processing was applied and the intercepted radiation was calculated as the difference from the corresponding incoming radiation above the canopy. Tree-crown size and shape were profiled via computer imaging by analysing the different shadow images acquired at the various solar positions during the day. It is notable that these combined images yielded the crown features without having to parameterize such canopy characteristics as foliage extension and spatial distribution.

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“…However, because of the large number of organ to record for each plant and to significant differences in vine architecture between plants (Casteran et al. 1980, Succi et al. 1997), the use of these methods may result in the sampling of a non‐representative number of plants, which hamper their potential to quantitatively compare canopy management options.…”

Section: Introductionmentioning

confidence: 99%

Influence of trellis system and shoot positioning on light interception and distribution in two grapevine cultivars with different architectures: an original approach based on 3D canopy modelling

Louarn

Dauzat

Lecœur

2008

Australian Journal of Grape and Wine Research

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Background and Aims: A 3D modelling approach simulating canopy structure was used in combination with a radiative transfer model to simulate light interception, distribution and microclimate in the fruiting zone. Methods and Results: This model was parameterised for four training systems (two vertical shoot‐positioned systems with one or two pairs of catch wires (VSP‐1W, VSP‐2W); two non‐shoot‐positioned systems, gobelet (GOB) and bilateral free cordon (BFC)) and two cultivars (Syrah and Grenache). Light interception and canopy microclimate depended on the interactions between the intrinsic architecture of the cultivars and canopy manipulations. Shoot vigour and leaf area were the main determinants of canopy radiative balance. However, differences in shoot architecture accounted for up to 25% of the difference in light interception between cultivar × trellis system pairs at a given leaf area index (LAI). Light interception efficiencies and the proportion of sunlit leaf area (SLA) were 25–30% lower for VSP‐2W than for BFC for intermediate LAI values. The genotypic differences in the ability to capture light were mostly induced by the ‘procumbent’ habit of the Syrah shoots. For this cultivar, shoot‐positioned systems resulted in lower levels of fruit illumination at midday than the BFC and GOB systems, whereas the use of a catch wire in VSP‐Grenache canopies made it possible to maintain light penetration in the fruit zone. Conclusions: These results highlight the problem of adapting the training system to both the architectural characteristics of the cultivar and climate. Free‐standing systems had greater light interception and SLA than shoot‐positioned systems. They may enhance fruit illumination for cultivars with ‘procumbent’ shoots. Significance of the Study: Non‐positioned shoot systems offer the possibility of combining a high level of light interception, favourable microclimate and reduced labour‐intensive practices for vineyards in conditions of moderate vigour.

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A Geometric Approach to Kiwifruit Canopy Modelling

Cited by 5 publications

References 0 publications

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

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

Ground monitoring the light–shadow windows of a tree canopy to yield canopy light interception and morphological traits

Influence of trellis system and shoot positioning on light interception and distribution in two grapevine cultivars with different architectures: an original approach based on 3D canopy modelling

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