Prediction of Photosynthetic, Biophysical, and Biochemical Traits in Wheat Canopies to Reduce the Phenotyping Bottleneck

Abstract

To achieve food security, it is necessary to increase crop radiation use efficiency (RUE) and yield through the enhancement of canopy photosynthesis to increase the availability of assimilates for the grain, but its study in the field is constrained by low throughput and the lack of integrative measurements at canopy level. In this study, partial least squares regression (PLSR) was used with high-throughput phenotyping (HTP) data in spring wheat to build predictive models of photosynthetic, biophysical, and biochemical traits for the top, middle, and bottom layers of wheat canopies. The combined layer model predictions performed better than individual layer predictions with a significance as follows for photosynthesis R2 = 0.48, RMSE = 5.24 μmol m–2 s–1 and stomatal conductance: R2 = 0.36, RMSE = 0.14 mol m–2 s–1. The predictions of these traits from PLSR models upscaled to canopy level compared to field observations were statistically significant at initiation of booting (R2 = 0.3, p < 0.05; R2 = 0.29, p < 0.05) and at 7 days after anthesis (R2 = 0.15, p < 0.05; R2 = 0.65, p < 0.001). Using HTP allowed us to increase phenotyping capacity 30-fold compared to conventional phenotyping methods. This approach can be adapted to screen breeding progeny and genetic resources for RUE and to improve our understanding of wheat physiology by adding different layers of the canopy to physiological modeling.

Climate change impacts on crop breeding: Targeting interacting biotic and abiotic stresses for wheat improvement

“…To address this, we need to make more efficient use of field and laboratory high‐throughput phenotyping (HTP) capabilities and combine conventional and HTP to develop statistical models that could be used to introduce complex trait enhancements in photosynthesis, gs , biomass accumulation, and radiation use efficiency (RUE) into breeding pipelines. It has been shown that gs can be predicted with 97% accuracy using machine learning models (Gibbs et al., 2021), and RUE and photosynthesis can be predicted with 69% (Robles‐Zazueta et al., 2021) and 48% accuracy (Robles‐Zazueta et al., 2022), respectively. These models need to be fine‐tuned to improve accuracy, especially for gas exchange by increasing the amount of ground truth data available to build the models.…”

“…These models need to be fine‐tuned to improve accuracy, especially for gas exchange by increasing the amount of ground truth data available to build the models. Nonetheless, the time spent collecting data in the field and processing samples in the lab can be reduced approximately by 27 times for agronomic traits and 40 times for photosynthetic traits (Robles‐Zazueta et al., 2021, 2022). HTP protocols applied in combination with interdisciplinary efforts such as the Agricultural Model Intercomparison and Improvement Project (AgMIP) (Rosenzweig et al., 2013) can aid in the development of low‐cost platforms to phenotype multiple traits at the same time in the field, and coupled with field informed controlled environment experiments, combined stresses can be studied at a mechanistic and genetic level.…”

3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis

“…Lastly, while flag leaf photosynthesis has been described as a key trait to improve cereal yields, recent research has suggested the importance of middle and bottom layers of a canopy to radiation use efficiency, nonphotochemical quenching, and crop yield in wheat [61], rice [62], and cotton [63]. Here, we emphasize that other leaves besides the flag leaf are indeed key players of canopy photosynthesis, which contribute ~40%/~35% of net/gross canopy photosynthesis at the heading stage and~40%/~20% of net/gross canopy photosynthesis at the milking stage.…”

Exploring the trade‐off between individual fitness and community performance of wheat crops using simulated canopy shade

“…With the onset of stem elongation, the competition for resources between plants of the same row intensifies and broadens to the neighbouring rows, thereby creating a dense crop canopy around anthesis. At this time point, most of the individual wheat plants are largely covered or shaded by neighbouring plants, generating a steep illumination gradient towards the ground and stimulating an intense competition for photosynthetically active radiation (PAR) (Casal, 2013; Evers et al, 2006; Robles‐Zazueta et al, 2022).…”