Can improved canopy light transmission ameliorate loss of photosynthetic efficiency in the shade? An investigation of natural variation in Sorghum bicolor

Variation in shoot architecture traits and their relationship to canopy coverage and light interception in soybean (Glycine max)

BACKGROUND

In soybeans, faster canopy coverage (CC) is a highly desirable trait but a fully covered canopy is unfavorable to light interception at lower levels in the canopy with most of the incident radiation intercepted at the top of the canopy. Shoot architecture that influences CC is well studied in crops such as maize and wheat, and altering architectural traits has resulted in enhanced yield. However, in soybeans the study of shoot architecture has not been as extensive.

RESULTS

This study revealed significant differences in CC among the selected soybean accessions. The rate of CC was found to decrease at the beginning of the reproductive stage (R1) followed by an increase during the R2-R3 stages. Most of the accessions in the study achieved maximum rate of CC between R2-R3 stages. We measured Light interception (LI), defined here as the ratio of Photosynthetically Active Radiation (PAR) transmitted through the canopy to the incoming PAR or the radiation above the canopy. LI was found to be significantly correlated with CC parameters, highlighting the relationship between canopy structure and light interception. The study also explored the impact of plant shape on LI and CO2 assimilation. Plant shape was characterized into distinct quantifiable parameters and by modeling the impact of plant shape on LI and CO2 assimilation, we found that plants with broad and flat shapes at the top maybe more photosynthetically efficient at low light levels, while conical shapes were likely more advantageous when light was abundant. Shoot architecture of plants in this study was described in terms of whole plant, branching and leaf-related traits. There was significant variation for the shoot architecture traits between different accessions, displaying high reliability. We found that that several shoot architecture traits such as plant height, and leaf and internode-related traits strongly influenced CC and LI.

CONCLUSION

In conclusion, this study provides insight into the relationship between soybean shoot architecture, canopy coverage, and light interception. It demonstrates that novel shoot architecture traits we have defined here are genetically variable, impact CC and LI and contribute to our understanding of soybean morphology. Correlations between different architecture traits, CC and LI suggest that it is possible to optimize soybean growth without compromising on light transmission within the soybean canopy. In addition, the study underscores the utility of integrating low-cost 2D phenotyping as a practical and cost-effective alternative to more time-intensive 3D or high-tech low-throughput methods. This approach offers a feasible means of studying basic shoot architecture traits at the field level, facilitating a broader and efficient assessment of plant morphology.

Contrasting leaf-scale photosynthetic low-light response and its temperature dependency are key to differences in crop-scale radiation use efficiency

Radiation use efficiency (RUE) is a key crop adaptation trait that quantifies the potential amount of aboveground biomass produced by the crop per unit of solar energy intercepted. But it is unclear why elite maize and grain sorghum hybrids differ in their RUE at the crop level. Here, we used a non-traditional top-down approach via canopy photosynthesis modelling to identify leaf-level photosynthetic traits that are key to differences in crop-level RUE. A novel photosynthetic response measurement was developed and coupled with use of a Bayesian model fitting procedure, incorporating a C4 leaf photosynthesis model, to infer cohesive sets of photosynthetic parameters by simultaneously fitting responses to CO2 , light, and temperature. Statistically significant differences between leaf photosynthetic parameters of elite maize and grain sorghum hybrids were found across a range of leaf temperatures, in particular for effects on the quantum yield of photosynthesis, but also for the maximum enzymatic activity of Rubisco and PEPc. Simulation of diurnal canopy photosynthesis predicted that the leaf-level photosynthetic low-light response and its temperature dependency are key drivers of the performance of crop-level RUE, generating testable hypotheses for further physiological analysis and bioengineering applications.

Anatomical determinants of gas exchange and hydraulics vary with leaf shape in soybean

BACKGROUND AND AIMS

Leaf shape in crops can impact light distribution and carbon capture at the whole plant and canopy level. Given similar leaf inclination, narrow leaves can allow a greater fraction of incident light to pass through to lower canopy leaves by reducing leaf area index, which can potentially increase canopy-scale photosynthesis. Soybean has natural variation in leaf shape which can be utilized to optimize canopy architecture. However, the anatomical and physiological differences underlying variation in leaf shape remain largely unexplored.

METHODS

In this study, we selected 28 diverse soybean lines with leaf length to width ratios (leaf ratio) ranging between 1.1 and 3.2. We made leaf cross-sectional, gas exchange, vein density and hydraulic measurements and studied their interrelationships among these lines.

KEY RESULTS

Our study shows that narrow leaves tend to be thicker, with an ~30 µm increase in leaf thickness for every unit increase in leaf ratio. Interestingly, thicker leaves had a greater proportion of spongy mesophyll while the proportions of palisade and paraveinal mesophyll decreased. In addition, narrow and thicker leaves had greater photosynthesis and stomatal conductance per unit area along with greater leaf hydraulic conductance.

CONCLUSIONS

Our results suggest that selecting for narrow leaves can improve photosynthetic performance and potentially provide a yield advantage in soybean.

Modelling plants across scales of biological organisation for guiding crop improvement

Grain yield improvement in globally important staple crops is critical in the coming decades if production is to keep pace with growing demand; so there is increasing interest in understanding and manipulating plant growth and developmental traits for better crop productivity. However, this is confounded by complex cross-scale feedback regulations and a limited ability to evaluate the consequences of manipulation on crop production. Plant/crop modelling could hold the key to deepening our understanding of dynamic trait-crop-environment interactions and predictive capabilities for supporting genetic manipulation. Using photosynthesis and crop growth as an example, this review summarises past and present experimental and modelling work, bringing about a model-guided crop improvement thrust, encompassing research into: (1) advancing cross-scale plant/crop modelling that connects across biological scales of organisation using a trait dissection-integration modelling principle; (2) improving the reliability of predicted molecular-trait-crop-environment system dynamics with experimental validation; and (3) innovative model application in synergy with cross-scale experimentation to evaluate G×M×E and predict yield outcomes of genetic intervention (or lack of it) for strategising further molecular and breeding efforts. The possible future roles of cross-scale plant/crop modelling in maximising crop improvement are discussed.

Increased bundle-sheath leakiness of CO2 during photosynthetic induction shows a lack of coordination between the C4 and C3 cycles

Use of a complete dynamic model of NADP-malic enzyme C₄ photosynthesis indicated that, during transitions from dark or shade to high light, induction of the C₄ pathway was more rapid than that of C₃ , resulting in a predicted transient increase in bundle-sheath CO₂ leakiness (ϕ). Previously, ϕ has been measured at steady state; here we developed a new method, coupling a tunable diode laser absorption spectroscope with a gas-exchange system to track ϕ in sorghum and maize through the nonsteady-state condition of photosynthetic induction. In both species, ϕ showed a transient increase to > 0.35 before declining to a steady state of 0.2 by 1500 s after illumination. Average ϕ was 60% higher than at steady state over the first 600 s of induction and 30% higher over the first 1500 s. The transient increase in ϕ, which was consistent with model prediction, indicated that capacity to assimilate CO₂ into the C₃ cycle in the bundle sheath failed to keep pace with the rate of dicarboxylate delivery by the C₄ cycle. Because nonsteady-state light conditions are the norm in field canopies, the results suggest that ϕ in these major crops in the field is significantly higher and energy conversion efficiency lower than previous measured values under steady-state conditions.

Photosynthesis in sun and shade: the surprising importance of far-red photons

The current definition of photosynthetically active radiation includes only photons from 400 up to 700 nm, despite evidence of the synergistic interaction between far-red photons and shorter-wavelength photons. The synergy between far-red and shorter-wavelength photons has not been studied in sunlight under natural conditions. We used a filter to remove photons above 700 nm to quantify the effects on photosynthesis in diverse species under full sun, medium light intensity and vegetation shade. Far-red photons (701 to 750 nm) in sunlight are used efficiently for photosynthesis. This is especially important for leaves in vegetation shade, where far-red photons can be > 50% of the total incident photons between 400 and 750 nm. Far-red photons accounted for 24-25% of leaf gross photosynthesis (P_gross ) in a C₃ and a C₄ species when sunlight was filtered through a leaf, and 10-14% of leaf P_gross in a tree and an understory species in deep shade. Accounting for the photosynthetic activity of far-red photons is critical for accurate measurement and modeling of photosynthesis at single leaf, canopy and ecosystem scales. This, in turn, is crucial in understanding crop productivity, the global carbon cycle and climate change impacts on agriculture and ecosystems.

A model-guided holistic review of exploiting natural variation of photosynthesis traits in crop improvement

Breeding for improved leaf photosynthesis is considered as a viable approach to increase crop yield. Whether it should be improved in combination with other traits has not been assessed critically. Based on the quantitative crop model GECROS that interconnects various traits to crop productivity, we review natural variation in relevant traits, from biochemical aspects of leaf photosynthesis to morpho-physiological crop characteristics. While large phenotypic variations (sometimes >2-fold) for leaf photosynthesis and its underlying biochemical parameters were reported, few quantitative trait loci (QTL) were identified, accounting for a small percentage of phenotypic variation. More QTL were reported for sink size (that feeds back on photosynthesis) or morpho-physiological traits (that affect canopy productivity and duration), together explaining a much greater percentage of their phenotypic variation. Traits for both photosynthetic rate and sustaining it during grain filling were strongly related to nitrogen-related traits. Much of the molecular basis of known photosynthesis QTL thus resides in genes controlling photosynthesis indirectly. Simulation using GECROS demonstrated the overwhelming importance of electron transport parameters, compared with the maximum Rubisco activity that largely determines the commonly studied light-saturated photosynthetic rate. Exploiting photosynthetic natural variation might significantly improve crop yield if nitrogen uptake, sink capacity, and other morpho-physiological traits are co-selected synergistically.