Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional–structural plant model

Sarlikioti, V.; Visser, P.H.B. de; Marcelis, L.F.M.

doi:10.1093/aob/mcr006

Cited by 150 publications

(127 citation statements)

References 41 publications

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“…The ratio of the shaded or sunlit leaves to the total leaves is associated with the canopy structure, and the diurnal trend varies due to sun position in the different canopy layers (Sarlikioti et al, 2011;Thanisawanyangkura et al, 1997). Therefore, a new upscaling approach (Approach 2) is proposed.…”

Section: Upscaling Approachesmentioning

confidence: 99%

A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance

Zhang

Tian

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract.A multi-scale, multi-technique study was conducted to measure evapotranspiration and its components in a cotton field under mulched drip irrigation conditions in northwestern China. Three measurement techniques at different scales were used: a photosynthesis system (leaf scale), sap flow (plant scale), and eddy covariance (field scale). The experiment was conducted from July to September 2012. To upscale the evapotranspiration from the leaf to plant scale, an approach that incorporated the canopy structure and the relationships between sunlit and shaded leaves was proposed. To upscale the evapotranspiration from the plant to field scale, an approach based on the transpiration per unit leaf area was adopted and modified to incorporate the temporal variability in the relationship between leaf areas and stem diameter. At the plant scale, the estimate of the transpiration based on the photosynthesis system with upscaling was slightly higher (18 %) than that obtained by sap flow. At the field scale, the estimates of transpiration derived from sap flow with upscaling and eddy covariance showed reasonable consistency during the cotton's open-boll growth stage, during which soil evaporation can be neglected. The results indicate that the proposed upscaling approaches are reasonable and valid. Based on the measurements and upscaling approaches, evapotranspiration components were analyzed for a cotton field under mulched drip irrigation. During the two analyzed sub-periods in July and August, evapotranspiration rates were 3.94 and 4.53 m day −1 , respectively. The fraction of transpiration to evapotranspiration reached 87.1 % before drip irrigation and 82.3 % after irrigation. The high fraction of transpiration over evapotranspiration was principally due to the mulched film above the drip pipe, low soil water content in the inter-film zone, well-closed canopy, and high water requirement of the crop.

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Section: Upscaling Approachesmentioning

confidence: 99%

A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance

Zhang

Tian

et al. 2014

Hydrol. Earth Syst. Sci.

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“…Mathematical functions and three-dimensional structures of computer simulation modeling methods are commonly used to simulate the light radiation distribution in the crop canopy [30][31][32]. The Beer-Lambert law proposed by Monsi and Saeki [7] is one of the most popular classical models for simulating light radiation distribution.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Vertical Distribution of Structural Parameters and Light Radiation in Rice Canopies by the Coupling Model and Remote Sensing

Guo¹,

Zhang²,

Qin³

et al. 2015

Remote Sensing

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Canopy structural parameters and light radiation are important for evaluating the light use efficiency and grain yield of crops. Their spatial variation within canopies and temporal variation over growth stages could be simulated using dynamic models with strong application and predictability. Based on an optimized canopy structure vertical distribution model and the Beer-Lambert law combined with hyperspectral remote sensing (RS) technology, we established a new dynamic model for simulating leaf area index (LAI), leaf angle (LA) distribution and light radiation at different vertical heights and growth stages. The model was validated by measuring LAI, LA and light radiation in different leaf layers at different growth stages of two different types of rice (Oryza sativa L.), i.e., japonica (Wuxiangjing14) and indica (Shanyou63). The results show that the simulated values were in good agreement with the observed values, with an average RRMSE (relative root mean squared error) between simulated and observed LAI and LA values of 14.75% and 21.78%, respectively. The RRMSE values for simulated photosynthetic active radiation (PAR) transmittance and interception rates were 14.25% and 9.22% for Wuxiangjing14 and 15.71% and 4.40% for Shanyou63, respectively. In addition, the corresponding RRMSE values for red (R), green (G)

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“…The principles and exploration behind these models are beginning to be detailed in the literature (Godin & Sinoquet, 2005;Vos et. al., 2010) with applications seen within scientific research (Sarlikioti et. al., 2010).…”

Section: D Modelsmentioning

confidence: 99%

An Evaluative Review of Simulated Dynamic Smart 3d Objects

Romeijn

Sheth

Pettit

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Three-dimensional (3D) modelling of plants can be an asset for creating agricultural based visualisation products. The continuum of 3D plants models ranges from static to dynamic objects, also known as smart 3D objects. There is an increasing requirement for smarter simulated 3D objects that are attributed mathematically and/or from biological inputs. A systematic approach to plant simulation offers significant advantages to applications in agricultural research, particularly in simulating plant behaviour and the influences of external environmental factors. This approach of 3D plant object visualisation is primarily evident from the visualisation of plants using photographed billboarded images, to more advanced procedural models that come closer to simulating realistic virtual plants. However, few programs model physical reactions of plants to external factors and even fewer are able to grow plants based on mathematical and/or biological parameters. In this paper, we undertake an evaluation of plant-based object simulation programs currently available, with a focus upon the components and techniques involved in producing these objects. Through an analytical review process we consider the strengths and weaknesses of several program packages, the features and use of these programs and the possible opportunities in deploying these for creating smart 3D plant-based objects to support agricultural research and natural resource management. In creating smart 3D objects the model needs to be informed by both plant physiology and phenology. Expert knowledge will frame the parameters and procedures that will attribute the object and allow the simulation of dynamic virtual plants. Ultimately, biologically smart 3D virtual plants that react to changes within an environment could be an effective medium to visually represent landscapes and communicate land management scenarios and practices to planners and decision-makers.

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Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional–structural plant model

Cited by 150 publications

References 41 publications

A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance

A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance

Exploring the Vertical Distribution of Structural Parameters and Light Radiation in Rice Canopies by the Coupling Model and Remote Sensing

An Evaluative Review of Simulated Dynamic Smart 3d Objects

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