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. 2019 Apr 29;70(9):2479-2490.
doi: 10.1093/jxb/ery430.

A three-dimensional canopy photosynthesis model in rice with a complete description of the canopy architecture, leaf physiology, and mechanical properties

Tian-Gen Chang  1 , Honglong Zhao  1   2 , Ning Wang  3   2 , Qing-Feng Song  1 , Yi Xiao  1 , Mingnan Qu  1 , Xin-Guang Zhu  1
Affiliations

A three-dimensional canopy photosynthesis model in rice with a complete description of the canopy architecture, leaf physiology, and mechanical properties

Tian-Gen Chang et al. J Exp Bot. .

Abstract

In current rice breeding programs, morphological parameters such as plant height, leaf length and width, leaf angle, panicle architecture, and tiller number during the grain filling stage are used as major selection targets. However, so far, there is no robust approach to quantitatively define the optimal combinations of parameters that can lead to increased canopy radiation use efficiency (RUE). Here we report the development of a three-dimensional canopy photosynthesis model (3dCAP), which effectively combines three-dimensional canopy architecture, canopy vertical nitrogen distribution, a ray-tracing algorithm, and a leaf photosynthesis model. Concurrently, we developed an efficient workflow for the parameterization of 3dCAP. 3dCAP predicted daily canopy RUE for different nitrogen treatments of a given rice cultivar under different weather conditions. Using 3dCAP, we explored the influence of three canopy architectural parameters-tiller number, tiller angle and leaf angle-on canopy RUE. Under different weather conditions and different nitrogen treatments, canopy architecture optimized by manipulating these parameters can increase daily net canopy photosynthetic CO2 uptake by 10-52%. Generally, a smaller tiller angle was predicted for most elite rice canopy architectures, especially under scattered light conditions. Results further show that similar canopy RUE can be obtained by multiple different parameter combinations; these combinations share two common features of high light absorption by leaves in the canopy and a high level of coordination between the nitrogen concentration and the light absorbed by each leaf within the canopy. Overall, this new model has potential to be used in rice ideotype design for improved canopy RUE.

Keywords: 3D canopy; Canopy photosynthesis; ideotype; leaf nitrogen concentration; rice; systems model.

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Figures

Fig. 1.
Fig. 1.
Reconstruction of the 2D and 3D architecture of a rice panicle. (A) The simulated 2D architecture of a rice panicle. (B) An illustration of the mechanical model used to simulate the bending of the rachis or one of the primary branches. θi, Initial angle of the ith segment; Δθi, bending angle of the ith segment; Fj, force of gravity generated by the jth branch; si, length of the ith segment; ri, radius of the ith segment; Lj, equivalent length of the base of the jth branch to the ith segment; Y, Young’s modulus of the rachis and branches. (C) Simulated changes of the 3D architecture of a panicle for an indica rice cultivar during the grain filling period. (D) Photograph of a real panicle at harvest.
Fig. 2.
Fig. 2.
Illustration of the workflow for canopy architecture measurement using rice directly taken from the field. The architectural parameters used in the 3D model construction are labelled P1 to P25.
Fig. 3.
Fig. 3.
Relationship between leaf nitrogen concentration (LNC) and leaf photosynthetic parameters. The correlation study was performed for high-nitrogen (HN) treatment (n=17) and low-nitrogen (LN) treatment (n=21). The leaf photosynthetic parameters used include light-saturated photosynthetic rate Asat (A), maximum apparent quantum yield for CO2 (ΦCO2) (B), and curvature factor (θ) of the response of photosynthetic CO2 uptake to incident photosynthetic photon flux density (A-PPFD) (C). LNC was calculated as LNC=(leaf nitrogen dry weight)/(leaf dry weight)×100%.
Fig. 4.
Fig. 4.
Comparison of reconstructed and photographed plant architectures of rice cultivar XS134. The front view of reconstructed and photographed rice plants under low-nitrogen treatment (A, B) and high-nitrogen treatment (E, F) are shown. Counts of the number of ‘plant pixels’ that represent plant tissues in the images of reconstructed and photographed plants were made for plants under low-nitrogen (C, D) and high-nitrogen (G, H) treatment. The bars represent data for photographed plants (mean ±SD, n=5) and the dashed lines represent data for reconstructed plants. (This figure is available in colour at JXB online.)
Fig. 5.
Fig. 5.
Predicted and measured diurnal net canopy photosynthesis rate (Ac) on three different days. The measured hourly average photosynthetic photon flux density (PPFD) (A–C; n=6), Ac under low-nitrogen treatment (D–E; n=3) and high-nitrogen treatment (G–I; n=3) for rice cultivar XS134 during the daytime are shown. The simulation of diurnal Ac assumed all the incident light to be direct light only (DL) or scattered light only (SL). Diurnal light environments from three days with different weather conditions, an overcast day (12 September; A), a cloudy day (18 September; B), and a sunny day (13 September; C), were used in the simulations.
Fig. 6.
Fig. 6.
Optimization of canopy architectural parameters to increase canopy photosynthesis. Optimal plant architectures for high canopy photosynthesis were identified under strong direct light (DL) only (A), strong scattered light (SL) only (F), weak DL only (K), and weak SL only (P). The parameters used to identify the optimal plant architectures are tiller number (TN) (C, H, M, R), tiller angle (TA) (D, I, N, S), and leaf angle (LA) (E, J, O, T). The top 50 plant architectures showing higher daily net canopy photosynthesis (Ac) were used in calculations of relative changes for daily net canopy photosynthetic accumulation (ACP), TN, TA, and LA. The numbers above the bars in panels B, G, L, and Q represent relative change from the respective values for default plants.
Fig. 7.
Fig. 7.
Relationships between simulated daily net canopy photosynthetic accumulation (ACP) and plant architectural parameters under two light conditions, strong direct light only (A–C; see Fig. 6A) and strong scattered light only (D–F; see Fig. 6F), simulated for rice cultivar XS134 under high-nitrogen treatment. The black dots with error bars show the predicted variations of ACP for 2280 plant architectures with different combinations of tiller number, tiller angle, and leaf angle. The red squares denote optimal ACP values. The mean leaf angle is the average value for all leaves on a plant. (This figure is available in colour at JXB online.)
Fig. 8.
Fig. 8.
Relationships between simulated photosynthesis, light interception, and leaf nitrogen concentration. Two light conditions, strong direct light (A–C; see Fig. 6A) and strong scattered light (D–F; see Fig. 6F), were used for rice cultivar XS134 under high-nitrogen treatment. The relationships between daily total canopy leaf-accumulated absorbed light (TLAL) and daily net canopy photosynthetic CO2 uptake (ACP; A, D), between leaf position (LP; counted from bottom to top on a plant) and daily total light absorption by a leaf (LAL; B, E), and between leaf nitrogen concentration (LNC) and leaf daily total photosynthetic CO2 uptake (A; C, F) are illustrated for 2280 plant architectures (All), elite plant architectures (Top 50), and the default plant architecture (CK). ACP, TLAL, LAL, and A were calculated for 1 m2 ground area.
Fig. 9.
Fig. 9.
Relationships between simulated photosynthesis, light interception, and leaf nitrogen concentration. Two light conditions, strong direct light (A–C; see Fig. 6A) and strong scattered light (D–F; see Fig. 6F), were used for rice cultivar XS134 under high-nitrogen treatment. The relationships between daily total canopy leaf-accumulated absorbed light (TLAL) and daily net canopy photosynthetic CO2 uptake (ACP; A, D), between leaf position (LP; counted from bottom to top on a plant) and daily total light absorption by a leaf (LAL; B, E), and between leaf nitrogen concentration (LNC) and leaf daily total photosynthetic CO2 uptake (A; C, F) are illustrated for simulated plant architectures with high TLAL (All), elite plant architectures with high ACP (Top 50), and a plant architecture with high TLAL but low ACP (example). ACP, TLAL, LAL, and A were all calculated for 1 m2 ground area.
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