Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability
Hyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a cr...
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MDPI AG
2020-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/20/3462 |
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| author | Wiktor R. Żelazny Jan Lukáš |
| author_facet | Wiktor R. Żelazny Jan Lukáš |
| author_sort | Wiktor R. Żelazny |
| collection | DOAJ |
| description | Hyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a crop subjected to various HSI studies, with the exception of drought. The aim of the present study was to determine the spectral responses of two cultivars, ‘Cadeli’ and ‘Viking’, representing distinctive water management strategies, to three types of watering regimes. Hyperspectral data cubes were acquired at the leaf level using a 2D frame camera. The influence of the experimental factors on the extent of leaf discolorations, vegetation index values, and principal component scores was investigated using Bayesian linear models. Clear treatment effects were obtained primarily for the vegetation indexes with respect to the watering regimes. The mean values of RGI, MTCI, RNDVI, and GI responded to the difference between the well-watered and water-deprived plants. The RGI index excelled among them in terms of effect strengths, which amounted to <inline-formula><math display="inline"><semantics><mrow><mo>−</mo><mn>0.96</mn><mspace width="0.222222em"></mspace><mo>[</mo><mo>−</mo><mn>2.21</mn><mo>,</mo><mn>0.21</mn><mo>]</mo></mrow></semantics></math></inline-formula> and <inline-formula><math display="inline"><semantics><mrow><mo>−</mo><mn>0.71</mn><mspace width="0.222222em"></mspace><mo>[</mo><mo>−</mo><mn>1.97</mn><mo>,</mo><mn>0.49</mn><mo>]</mo></mrow></semantics></math></inline-formula> units for each cultivar. A consistent increase in the multiple index standard deviations, especially RGI, PSRI, TCARI, and TCARI/OSAVI, was associated with worsening of the hydric regime. These increases were captured not only for the dry treatment but also for the plants subjected to regeneration after a drought episode, particularly by PSRI (a multiplicative effect of <inline-formula><math display="inline"><semantics><mrow><mn>0.33</mn><mspace width="0.222222em"></mspace><mo>[</mo><mn>0.16</mn><mo>,</mo><mn>0.68</mn><mo>]</mo></mrow></semantics></math></inline-formula> for ‘Cadeli’). This result suggests a higher sensitivity of the vegetation index variability measures relative to the means in the context of the oilseed rape drought stress diagnosis and justifies the application of HSI to capture these effects. RGI is an index deserving additional scrutiny in future studies, as both its mean and standard deviation were affected by the watering regimes. |
| first_indexed | 2024-03-10T15:26:48Z |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-10T15:26:48Z |
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| spelling | doaj.art-aad1302fcdfb4da88da7bc60a5f638ee2023-11-20T18:00:36ZengMDPI AGRemote Sensing2072-42922020-10-011220346210.3390/rs12203462Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra VariabilityWiktor R. Żelazny0Jan Lukáš1Crop Research Institute Prague-Ruzyně, Division of Crop Management Systems, Drnovská 507/73, CZ161 06 Praha 6 Ruzyně, Czech RepublicCrop Research Institute Prague-Ruzyně, Division of Crop Protection and Plant Health, Drnovská 507/73, CZ161 06 Praha 6 Ruzyně, Czech RepublicHyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a crop subjected to various HSI studies, with the exception of drought. The aim of the present study was to determine the spectral responses of two cultivars, ‘Cadeli’ and ‘Viking’, representing distinctive water management strategies, to three types of watering regimes. Hyperspectral data cubes were acquired at the leaf level using a 2D frame camera. The influence of the experimental factors on the extent of leaf discolorations, vegetation index values, and principal component scores was investigated using Bayesian linear models. Clear treatment effects were obtained primarily for the vegetation indexes with respect to the watering regimes. The mean values of RGI, MTCI, RNDVI, and GI responded to the difference between the well-watered and water-deprived plants. The RGI index excelled among them in terms of effect strengths, which amounted to <inline-formula><math display="inline"><semantics><mrow><mo>−</mo><mn>0.96</mn><mspace width="0.222222em"></mspace><mo>[</mo><mo>−</mo><mn>2.21</mn><mo>,</mo><mn>0.21</mn><mo>]</mo></mrow></semantics></math></inline-formula> and <inline-formula><math display="inline"><semantics><mrow><mo>−</mo><mn>0.71</mn><mspace width="0.222222em"></mspace><mo>[</mo><mo>−</mo><mn>1.97</mn><mo>,</mo><mn>0.49</mn><mo>]</mo></mrow></semantics></math></inline-formula> units for each cultivar. A consistent increase in the multiple index standard deviations, especially RGI, PSRI, TCARI, and TCARI/OSAVI, was associated with worsening of the hydric regime. These increases were captured not only for the dry treatment but also for the plants subjected to regeneration after a drought episode, particularly by PSRI (a multiplicative effect of <inline-formula><math display="inline"><semantics><mrow><mn>0.33</mn><mspace width="0.222222em"></mspace><mo>[</mo><mn>0.16</mn><mo>,</mo><mn>0.68</mn><mo>]</mo></mrow></semantics></math></inline-formula> for ‘Cadeli’). This result suggests a higher sensitivity of the vegetation index variability measures relative to the means in the context of the oilseed rape drought stress diagnosis and justifies the application of HSI to capture these effects. RGI is an index deserving additional scrutiny in future studies, as both its mean and standard deviation were affected by the watering regimes.https://www.mdpi.com/2072-4292/12/20/3462imaging spectroscopyRikolairradiance<i>Brassica napus</i> L.pot experimentsreproducibility |
| spellingShingle | Wiktor R. Żelazny Jan Lukáš Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability Remote Sensing imaging spectroscopy Rikola irradiance <i>Brassica napus</i> L. pot experiments reproducibility |
| title | Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability |
| title_full | Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability |
| title_fullStr | Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability |
| title_full_unstemmed | Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability |
| title_short | Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability |
| title_sort | drought stress detection in juvenile oilseed rape using hyperspectral imaging with a focus on spectra variability |
| topic | imaging spectroscopy Rikola irradiance <i>Brassica napus</i> L. pot experiments reproducibility |
| url | https://www.mdpi.com/2072-4292/12/20/3462 |
| work_keys_str_mv | AT wiktorrzelazny droughtstressdetectioninjuvenileoilseedrapeusinghyperspectralimagingwithafocusonspectravariability AT janlukas droughtstressdetectioninjuvenileoilseedrapeusinghyperspectralimagingwithafocusonspectravariability |