Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum

Zhi, Xiaoyu; Massey-Reed, Sean Reynolds; Wu, Alex; Potgieter, Andries; Borrell, Andrew; Hunt, Colleen H.; Jordan, David R.; Zhao, Yan; Chapman, Scott C.; Hammer, Graeme; George‐Jaeggli, Barbara

doi:10.34133/2022/9768502

Cited by 10 publications

(8 citation statements)

References 96 publications

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“…At the whole-plant level, leaf area index is commonly used as a critical variable when simulating photosynthesis-and/or transpiration-related crop productivity in cereals (Duncan et al 1967;Wu et al 2018;Chenu et al 2018;Hammer et al 2019). In combination with leaf angle, the size of the largest leaf is also a key component of canopy structure and influences light capture and canopy photosynthesis (Duncan 1971;Zhi et al 2022a;Birch et al 1998).…”

Section: Introductionmentioning

confidence: 99%

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

et al. 2022

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Key message Leaf width was correlated with plant-level transpiration efficiency and associated with 19 QTL in sorghum, suggesting it could be a surrogate for transpiration efficiency in large breeding program. Abstract Enhancing plant transpiration efficiency (TE) by reducing transpiration without compromising photosynthesis and yield is a desirable selection target in crop improvement programs. While narrow individual leaf width has been correlated with greater intrinsic water use efficiency in C4 species, the extent to which this translates to greater plant TE has not been investigated. The aims of this study were to evaluate the correlation of leaf width with TE at the whole-plant scale and investigate the genetic control of leaf width in sorghum. Two lysimetry experiments using 16 genotypes varying for stomatal conductance and three field trials using a large sorghum diversity panel (n = 701 lines) were conducted. Negative associations of leaf width with plant TE were found in the lysimetry experiments, suggesting narrow leaves may result in reduced plant transpiration without trade-offs in biomass accumulation. A wide range in width of the largest leaf was found in the sorghum diversity panel with consistent ranking among sorghum races, suggesting that environmental adaptation may have a role in modifying leaf width. Nineteen QTL were identified by genome-wide association studies on leaf width adjusted for flowering time. The QTL identified showed high levels of correspondence with those in maize and rice, suggesting similarities in the genetic control of leaf width across cereals. Three a priori candidate genes for leaf width, previously found to regulate dorsoventrality, were identified based on a 1-cM threshold. This study provides useful physiological and genetic insights for potential manipulation of leaf width to improve plant adaptation to diverse environments.

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Section: Introductionmentioning

confidence: 99%

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

et al. 2022

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“…We propose that RUE can be targeted by measuring the photosynthetic low‐light performance, simplifying the laborious RUE phenotyping significantly and opens up new possibilities of using high‐throughput phenotyping methodologies (e.g. Zhi et al ., 2022) to screen for improved crop RUE. The knowledge gained from this modelling‐experimentation work provides testable hypothesis for further research, connecting with advances in the molecular (e.g.…”

Section: Discussionmentioning

confidence: 99%

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

Wu,

Truong,

McCormick

et al. 2024

New Phytologist

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Summary 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 tastable hypotheses for further physiological analysis and bioengineering applications.

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“…A key benefit of remote sensing is its ability to screen a number of plots relatively quickly, therefore enabling data collection at higher temporal frequencies. Combined with intensive observation campaigns where physiological data are collected, remotely sensed PLSR models may be used to extrapolate beyond campaign dates and subset genotypes [ 60 ]. In this study, ground-based remote sensing was collected at the weekly timescale.…”

Section: Discussionmentioning

confidence: 99%

Hyperspectral Remote Sensing for Phenotyping the Physiological Drought Response of Common and Tepary Bean

et al. 2023

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Proximal remote sensing offers a powerful tool for high-throughput phenotyping of plants for assessing stress response. Bean plants, an important legume for human consumption, are often grown in regions with limited rainfall and irrigation and are therefore bred to further enhance drought tolerance. We assessed physiological (stomatal conductance and predawn and midday leaf water potential) and ground- and tower-based hyperspectral remote sensing (400 to 2,400 nm and 400 to 900 nm, respectively) measurements to evaluate drought response in 12 common bean and 4 tepary bean genotypes across 3 field campaigns (1 predrought and 2 post-drought). Hyperspectral data in partial least squares regression models predicted these physiological traits ( R 2 = 0.20 to 0.55; root mean square percent error 16% to 31%). Furthermore, ground-based partial least squares regression models successfully ranked genotypic drought responses similar to the physiologically based ranks. This study demonstrates applications of high-resolution hyperspectral remote sensing for predicting plant traits and phenotyping drought response across genotypes for vegetation monitoring and breeding population screening.

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Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum

Cited by 10 publications

References 96 publications

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

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

Hyperspectral Remote Sensing for Phenotyping the Physiological Drought Response of Common and Tepary Bean

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