Abstract
High-throughput measurement of plant photosynthesis ability presents a challenge for the breeding process aimed to improve crop yield. As a novel technique, hyperspectral lidar (HSL) has the potential to characterize the spatial distribution of plant photosynthesis traits under less confounding factors. In this paper, HSL reflectance spectra of maize leaves were utilized for estimating the maximal velocity of Rubisco carboxylation (Vcmax) and maximum rate of electron transport at a specific light intensity (J) based on both reflectance-based and trait-based methods, and the results were compared with the commercial Analytical Spectral Devices (ASD) system. A linear combination of the Lambertian model and the Beckmann law was conducted to eliminate the angle effect of the maize point cloud. The results showed that the reflectance-based method (R2 ≥ 0.42, RMSE ≤ 28.1 for J and ≤4.32 for Vcmax) performed better than the trait-based method (R2 ≥ 0.31, RMSE ≤ 33.7 for J and ≤5.17 for Vcmax), where the estimating accuracy of ASD was higher than that of HSL. The Lambertian–Beckmann model performed well (R2 ranging from 0.74 to 0.92) for correcting the incident angle at different wavelength bands, so the spatial distribution of photosynthesis traits of two maize plants was visually displayed. This study provides the basis for the further application of HSL in high-throughput measurements of plant photosynthesis.
Abstract from the paper’s OpenAlex record; open copy licensed cc-by. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 5
Claim · model-written summary
The reflectance-based method estimated J more accurately than the trait-based method.
Zea maysOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The results showed that the reflectance-based method (R2 ≥ 0.42, RMSE ≤ 28.1 for J and ≤4.32 for Vcmax) performed better than the trait-based method (R2 ≥ 0.31, RMSE ≤ 33.7 for J and ≤5.17 for Vcmax), where the estimating accuracy of ASD was higher than that of HSL.”
t0“Maize Photosynthesis Traits”
Claim · model-written summary
The reflectance-based method estimated Vcmax more accurately than the trait-based method.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The results showed that the reflectance-based method (R2 ≥ 0.42, RMSE ≤ 28.1 for J and ≤4.32 for Vcmax) performed better than the trait-based method (R2 ≥ 0.31, RMSE ≤ 33.7 for J and ≤5.17 for Vcmax), where the estimating accuracy of ASD was higher than that of HSL.”
t0“Maize Photosynthesis Traits”
Claim · model-written summary
ASD estimation accuracy exceeded HSL accuracy.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the estimating accuracy of ASD was higher than that of HSL.”
t0“Maize Photosynthesis Traits”
Claim · model-written summary
The Lambertian–Beckmann model corrected incident angle across wavelength bands with R2 of 0.74 to 0.92.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The Lambertian–Beckmann model performed well (R2 ranging from 0.74 to 0.92) for correcting the incident angle at different wavelength bands, so the spatial distribution of photosynthesis traits of two maize plants was visually displayed.”
Claim · model-written summary
Spatial distributions of photosynthesis traits were displayed for two maize plants.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the spatial distribution of photosynthesis traits of two maize plants was visually displayed.”