Limits...
Hyperspectral imaging techniques for rapid identification of Arabidopsis mutants with altered leaf pigment status.

Matsuda O, Tanaka A, Fujita T, Iba K - Plant Cell Physiol. (2012)

Bottom Line: The 'non-targeted' mode highlights differences in reflectance spectra of leaf samples relative to reference spectra from the wild-type leaves.Analysis of these and other mutants revealed that the RI-based targeted pigment estimation was robust at least against changes in trichome density, but was confounded by genetic defects in chloroplast photorelocation movement.Notwithstanding such a limitation, the techniques presented here provide rapid and high-sensitive means to identify genetic mechanisms that coordinate leaf pigment status with developmental stages and/or environmental stress conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Faculty of Sciences, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581 Japan. matsuda.osamu.084@m.kyushu-u.ac.jp

ABSTRACT
The spectral reflectance signature of living organisms provides information that closely reflects their physiological status. Because of its high potential for the estimation of geomorphic biological parameters, particularly of gross photosynthesis of plants, two-dimensional spectroscopy, via the use of hyperspectral instruments, has been widely used in remote sensing applications. In genetics research, in contrast, the reflectance phenotype has rarely been the subject of quantitative analysis; its potential for illuminating the pathway leading from the gene to phenotype remains largely unexplored. In this study, we employed hyperspectral imaging techniques to identify Arabidopsis mutants with altered leaf pigment status. The techniques are comprised of two modes; the first is referred to as the 'targeted mode' and the second as the 'non-targeted mode'. The 'targeted' mode is aimed at visualizing individual concentrations and compositional parameters of leaf pigments based on reflectance indices (RIs) developed for Chls a and b, carotenoids and anthocyanins. The 'non-targeted' mode highlights differences in reflectance spectra of leaf samples relative to reference spectra from the wild-type leaves. Through the latter approach, three mutant lines with weak irregular reflectance phenotypes, that are hardly identifiable by simple observation, were isolated. Analysis of these and other mutants revealed that the RI-based targeted pigment estimation was robust at least against changes in trichome density, but was confounded by genetic defects in chloroplast photorelocation movement. Notwithstanding such a limitation, the techniques presented here provide rapid and high-sensitive means to identify genetic mechanisms that coordinate leaf pigment status with developmental stages and/or environmental stress conditions.

Show MeSH

Related in: MedlinePlus

Applicability of reflectance-based pigment estimation in mutants with altered leaf surface structure and irregular reflectance (iref) phenotypes. Each plot shows the relationship between observed (horizontal axis, abbreviated as obs.) and expected (vertical axis, abbreviated as exp.) concentrations of pigment indicated at the top in mutant line gl1 (A–D), iref1 (E–H), iref3 (I–L) or iref4-D (M–P). Squares in orange indicate the data obtained from plants grown under Anth-inducing conditions, while those in blue are from plants kept in non-inducing conditions. The background data points in light gray are from the calibration data set and provide a measure of the possible deviation range in the estimation using Equations 3 (Chl a), 5 (Chl b), 7 (Anth) and 11 (Car). Details of each calibration subdata set (#1–5) are summarized in Table 1. The statistical details are summarized in Table 2.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3367163&req=5

pcs043-F9: Applicability of reflectance-based pigment estimation in mutants with altered leaf surface structure and irregular reflectance (iref) phenotypes. Each plot shows the relationship between observed (horizontal axis, abbreviated as obs.) and expected (vertical axis, abbreviated as exp.) concentrations of pigment indicated at the top in mutant line gl1 (A–D), iref1 (E–H), iref3 (I–L) or iref4-D (M–P). Squares in orange indicate the data obtained from plants grown under Anth-inducing conditions, while those in blue are from plants kept in non-inducing conditions. The background data points in light gray are from the calibration data set and provide a measure of the possible deviation range in the estimation using Equations 3 (Chl a), 5 (Chl b), 7 (Anth) and 11 (Car). Details of each calibration subdata set (#1–5) are summarized in Table 1. The statistical details are summarized in Table 2.

Mentions: In a previous report, it was warned that changes in leaf surface structure such as trichome density can mislead reflectance-based assessment of leaf chemistry and physiology, including the values of RIs conventionally used to approximate leaf pigment compositions (Levizou et al. 2005). To test if this is true of the ‘targeted system’ developed in this study, the predictive performance of the equations for the estimation of individual pigment concentrations (Equations 3, 5, 7 and 11) was evaluated in a trichome-less gl1 mutant. As shown by scatter plots in Fig. 9A–D, the correlation between the observed and expected concentrations of each pigment under routine growth conditions, i.e. the conditions used to obtain subdata sets #1 and 2 (Table 1), was comparable in the gl1 plants and the wild-type plants. This, in combination with the related statistical parameters (Table 2), corroborates the robustness of our ‘targeted’ system for leaf pigment estimation at least against the decrease in trichome density.Fig. 9


Hyperspectral imaging techniques for rapid identification of Arabidopsis mutants with altered leaf pigment status.

Matsuda O, Tanaka A, Fujita T, Iba K - Plant Cell Physiol. (2012)

Applicability of reflectance-based pigment estimation in mutants with altered leaf surface structure and irregular reflectance (iref) phenotypes. Each plot shows the relationship between observed (horizontal axis, abbreviated as obs.) and expected (vertical axis, abbreviated as exp.) concentrations of pigment indicated at the top in mutant line gl1 (A–D), iref1 (E–H), iref3 (I–L) or iref4-D (M–P). Squares in orange indicate the data obtained from plants grown under Anth-inducing conditions, while those in blue are from plants kept in non-inducing conditions. The background data points in light gray are from the calibration data set and provide a measure of the possible deviation range in the estimation using Equations 3 (Chl a), 5 (Chl b), 7 (Anth) and 11 (Car). Details of each calibration subdata set (#1–5) are summarized in Table 1. The statistical details are summarized in Table 2.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3367163&req=5

pcs043-F9: Applicability of reflectance-based pigment estimation in mutants with altered leaf surface structure and irregular reflectance (iref) phenotypes. Each plot shows the relationship between observed (horizontal axis, abbreviated as obs.) and expected (vertical axis, abbreviated as exp.) concentrations of pigment indicated at the top in mutant line gl1 (A–D), iref1 (E–H), iref3 (I–L) or iref4-D (M–P). Squares in orange indicate the data obtained from plants grown under Anth-inducing conditions, while those in blue are from plants kept in non-inducing conditions. The background data points in light gray are from the calibration data set and provide a measure of the possible deviation range in the estimation using Equations 3 (Chl a), 5 (Chl b), 7 (Anth) and 11 (Car). Details of each calibration subdata set (#1–5) are summarized in Table 1. The statistical details are summarized in Table 2.
Mentions: In a previous report, it was warned that changes in leaf surface structure such as trichome density can mislead reflectance-based assessment of leaf chemistry and physiology, including the values of RIs conventionally used to approximate leaf pigment compositions (Levizou et al. 2005). To test if this is true of the ‘targeted system’ developed in this study, the predictive performance of the equations for the estimation of individual pigment concentrations (Equations 3, 5, 7 and 11) was evaluated in a trichome-less gl1 mutant. As shown by scatter plots in Fig. 9A–D, the correlation between the observed and expected concentrations of each pigment under routine growth conditions, i.e. the conditions used to obtain subdata sets #1 and 2 (Table 1), was comparable in the gl1 plants and the wild-type plants. This, in combination with the related statistical parameters (Table 2), corroborates the robustness of our ‘targeted’ system for leaf pigment estimation at least against the decrease in trichome density.Fig. 9

Bottom Line: The 'non-targeted' mode highlights differences in reflectance spectra of leaf samples relative to reference spectra from the wild-type leaves.Analysis of these and other mutants revealed that the RI-based targeted pigment estimation was robust at least against changes in trichome density, but was confounded by genetic defects in chloroplast photorelocation movement.Notwithstanding such a limitation, the techniques presented here provide rapid and high-sensitive means to identify genetic mechanisms that coordinate leaf pigment status with developmental stages and/or environmental stress conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Faculty of Sciences, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581 Japan. matsuda.osamu.084@m.kyushu-u.ac.jp

ABSTRACT
The spectral reflectance signature of living organisms provides information that closely reflects their physiological status. Because of its high potential for the estimation of geomorphic biological parameters, particularly of gross photosynthesis of plants, two-dimensional spectroscopy, via the use of hyperspectral instruments, has been widely used in remote sensing applications. In genetics research, in contrast, the reflectance phenotype has rarely been the subject of quantitative analysis; its potential for illuminating the pathway leading from the gene to phenotype remains largely unexplored. In this study, we employed hyperspectral imaging techniques to identify Arabidopsis mutants with altered leaf pigment status. The techniques are comprised of two modes; the first is referred to as the 'targeted mode' and the second as the 'non-targeted mode'. The 'targeted' mode is aimed at visualizing individual concentrations and compositional parameters of leaf pigments based on reflectance indices (RIs) developed for Chls a and b, carotenoids and anthocyanins. The 'non-targeted' mode highlights differences in reflectance spectra of leaf samples relative to reference spectra from the wild-type leaves. Through the latter approach, three mutant lines with weak irregular reflectance phenotypes, that are hardly identifiable by simple observation, were isolated. Analysis of these and other mutants revealed that the RI-based targeted pigment estimation was robust at least against changes in trichome density, but was confounded by genetic defects in chloroplast photorelocation movement. Notwithstanding such a limitation, the techniques presented here provide rapid and high-sensitive means to identify genetic mechanisms that coordinate leaf pigment status with developmental stages and/or environmental stress conditions.

Show MeSH
Related in: MedlinePlus