Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity

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 fact...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Kaiyi Bi, Zheng Niu, Shunfu Xiao, Jie Bai, Gang Sun, Ji Wang, Zeying Han, Shuai Gao
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	hyperspectral light detection and ranging (lidar) biochemical parameters photosynthesis traits high-throughput Science Q
Acceso en línea:	https://doaj.org/article/3c4605bc2fe64b54bd25f17a34b792ef
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3c4605bc2fe64b54bd25f17a34b792ef
record_format	dspace
spelling	oai:doaj.org-article:3c4605bc2fe64b54bd25f17a34b792ef2021-11-11T18:49:53ZEstimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity10.3390/rs132142032072-4292https://doaj.org/article/3c4605bc2fe64b54bd25f17a34b792ef2021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4203https://doaj.org/toc/2072-4292High-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 (V<sub>cmax</sub>) 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 (R<sup>2</sup> ≥ 0.42, RMSE ≤ 28.1 for J and ≤4.32 for V<sub>cmax</sub>) performed better than the trait-based method (R<sup>2</sup> ≥ 0.31, RMSE ≤ 33.7 for J and ≤5.17 for V<sub>cmax</sub>), where the estimating accuracy of ASD was higher than that of HSL. The Lambertian–Beckmann model performed well (R<sup>2</sup> 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.Kaiyi BiZheng NiuShunfu XiaoJie BaiGang SunJi WangZeying HanShuai GaoMDPI AGarticlehyperspectrallight detection and ranging (lidar)biochemical parametersphotosynthesis traitshigh-throughputScienceQENRemote Sensing, Vol 13, Iss 4203, p 4203 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	hyperspectral light detection and ranging (lidar) biochemical parameters photosynthesis traits high-throughput Science Q
spellingShingle	hyperspectral light detection and ranging (lidar) biochemical parameters photosynthesis traits high-throughput Science Q Kaiyi Bi Zheng Niu Shunfu Xiao Jie Bai Gang Sun Ji Wang Zeying Han Shuai Gao Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity
description	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 (V<sub>cmax</sub>) 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 (R<sup>2</sup> ≥ 0.42, RMSE ≤ 28.1 for J and ≤4.32 for V<sub>cmax</sub>) performed better than the trait-based method (R<sup>2</sup> ≥ 0.31, RMSE ≤ 33.7 for J and ≤5.17 for V<sub>cmax</sub>), where the estimating accuracy of ASD was higher than that of HSL. The Lambertian–Beckmann model performed well (R<sup>2</sup> 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.
format	article
author	Kaiyi Bi Zheng Niu Shunfu Xiao Jie Bai Gang Sun Ji Wang Zeying Han Shuai Gao
author_facet	Kaiyi Bi Zheng Niu Shunfu Xiao Jie Bai Gang Sun Ji Wang Zeying Han Shuai Gao
author_sort	Kaiyi Bi
title	Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity
title_short	Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity
title_full	Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity
title_fullStr	Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity
title_full_unstemmed	Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity
title_sort	estimation of maize photosynthesis traits using hyperspectral lidar backscattered intensity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3c4605bc2fe64b54bd25f17a34b792ef
work_keys_str_mv	AT kaiyibi estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT zhengniu estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT shunfuxiao estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT jiebai estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT gangsun estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT jiwang estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT zeyinghan estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity AT shuaigao estimationofmaizephotosynthesistraitsusinghyperspectrallidarbackscatteredintensity
_version_	1718431696480632832

Estimation of Maize Photosynthesis Traits Using Hyperspectral Lidar Backscattered Intensity

Ejemplares similares