Comparing high-cost and lower-cost remote sensing tools for detecting pre-symptomatic downy mildew (Pseudoperonospora cubensis) infections in cucumbers

•Pre-symptomatic detection of infected plants using a small subset of spectral bands.•Detection of infection by spectral bands in the visible range and red edge region.•Decreased epidermal flavonol content as pre-symptomatic biomarker for infection.•DUALEX optical leaf sensor as affordable tool for...

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Veröffentlicht in:Computers and electronics in agriculture 2024-03, Vol.218, p.108736, Article 108736
Hauptverfasser: Vatter, Thomas, Barceló, Maria, Gjakoni, Patricia, Segarra, Guillem, Isabel Trillas, Mª, Aranjuelo, Iker, Kefauver, Shawn C., Araus, José L.
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container_issue
container_start_page 108736
container_title Computers and electronics in agriculture
container_volume 218
creator Vatter, Thomas
Barceló, Maria
Gjakoni, Patricia
Segarra, Guillem
Isabel Trillas, Mª
Aranjuelo, Iker
Kefauver, Shawn C.
Araus, José L.
description •Pre-symptomatic detection of infected plants using a small subset of spectral bands.•Detection of infection by spectral bands in the visible range and red edge region.•Decreased epidermal flavonol content as pre-symptomatic biomarker for infection.•DUALEX optical leaf sensor as affordable tool for pre-symptomatic disease detection. Downy mildew of cucumber caused by the oomycete Pseudoperonospora cubensis (P. cubensis) is currently the most destructive disease of this crop, causing high yield losses. Visual evaluation by experts is the most established method for the detection of P. cubensis infection, but depends on visual disease symptoms. Detection of fungal infection before visual symptoms appear is highly desirable, allowing to deploy disease control measures before extensive crop damage occurs. The capacity of remote sensing approaches, such as hyperspectral imaging or high-resolution spectrometry, have proved to be powerful tools for detecting plant fungal diseases at pre-symptomatic stages over the last years. However, these approaches are expensive and processing the massive amount of multidimensional data, in case of spectroscopy and hyperspectral imaging, remains complex. Affordable, easy to handle, devices enabling the identification of P. cubensis infected cucumber plants at the pre-symptomatic stage in-situ may represent a high-value alternative for farmers. This study compared the performance of a high-cost high-resolution spectroradiometer (FieldSpec4) and a lower-cost leaf-clip sensor (DUALEX) for the early detection of P. cubensis infection in cucumber. Screening of cucumber plants, grown in a growth chamber, 24 h and 48 h post inoculation, allowed to identify a subset of spectral bands and leaf pigments for differentiating between infected and healthy cucumber plants at the pre-symptomatic stage. In the case of the FieldSpec 4, models based on spectral bands at 402, 576, 690, 708, and 723 nm differentiated between cucumber plants infected with P. cubensis and healthy plants with a F1 value of 0.67. The use of the lower-cost leaf-clip DUALEX sensor differentiated between infected and healthy cucumber plants with a F1 value of 0.60. Furthermore, the epidermal flavonol content obtained with the + leaf-clip DUALEX sensor was shown to be decreased in cucumber plants infected with P. cubensis compared to those of healthy plants, highlighting its role as biomarker for detecting P. cubensis infection at the pre-symptomatic stage. Results of thi
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Downy mildew of cucumber caused by the oomycete Pseudoperonospora cubensis (P. cubensis) is currently the most destructive disease of this crop, causing high yield losses. Visual evaluation by experts is the most established method for the detection of P. cubensis infection, but depends on visual disease symptoms. Detection of fungal infection before visual symptoms appear is highly desirable, allowing to deploy disease control measures before extensive crop damage occurs. The capacity of remote sensing approaches, such as hyperspectral imaging or high-resolution spectrometry, have proved to be powerful tools for detecting plant fungal diseases at pre-symptomatic stages over the last years. However, these approaches are expensive and processing the massive amount of multidimensional data, in case of spectroscopy and hyperspectral imaging, remains complex. Affordable, easy to handle, devices enabling the identification of P. cubensis infected cucumber plants at the pre-symptomatic stage in-situ may represent a high-value alternative for farmers. This study compared the performance of a high-cost high-resolution spectroradiometer (FieldSpec4) and a lower-cost leaf-clip sensor (DUALEX) for the early detection of P. cubensis infection in cucumber. Screening of cucumber plants, grown in a growth chamber, 24 h and 48 h post inoculation, allowed to identify a subset of spectral bands and leaf pigments for differentiating between infected and healthy cucumber plants at the pre-symptomatic stage. In the case of the FieldSpec 4, models based on spectral bands at 402, 576, 690, 708, and 723 nm differentiated between cucumber plants infected with P. cubensis and healthy plants with a F1 value of 0.67. The use of the lower-cost leaf-clip DUALEX sensor differentiated between infected and healthy cucumber plants with a F1 value of 0.60. Furthermore, the epidermal flavonol content obtained with the + leaf-clip DUALEX sensor was shown to be decreased in cucumber plants infected with P. cubensis compared to those of healthy plants, highlighting its role as biomarker for detecting P. cubensis infection at the pre-symptomatic stage. 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Downy mildew of cucumber caused by the oomycete Pseudoperonospora cubensis (P. cubensis) is currently the most destructive disease of this crop, causing high yield losses. Visual evaluation by experts is the most established method for the detection of P. cubensis infection, but depends on visual disease symptoms. Detection of fungal infection before visual symptoms appear is highly desirable, allowing to deploy disease control measures before extensive crop damage occurs. The capacity of remote sensing approaches, such as hyperspectral imaging or high-resolution spectrometry, have proved to be powerful tools for detecting plant fungal diseases at pre-symptomatic stages over the last years. However, these approaches are expensive and processing the massive amount of multidimensional data, in case of spectroscopy and hyperspectral imaging, remains complex. Affordable, easy to handle, devices enabling the identification of P. cubensis infected cucumber plants at the pre-symptomatic stage in-situ may represent a high-value alternative for farmers. This study compared the performance of a high-cost high-resolution spectroradiometer (FieldSpec4) and a lower-cost leaf-clip sensor (DUALEX) for the early detection of P. cubensis infection in cucumber. Screening of cucumber plants, grown in a growth chamber, 24 h and 48 h post inoculation, allowed to identify a subset of spectral bands and leaf pigments for differentiating between infected and healthy cucumber plants at the pre-symptomatic stage. In the case of the FieldSpec 4, models based on spectral bands at 402, 576, 690, 708, and 723 nm differentiated between cucumber plants infected with P. cubensis and healthy plants with a F1 value of 0.67. The use of the lower-cost leaf-clip DUALEX sensor differentiated between infected and healthy cucumber plants with a F1 value of 0.60. Furthermore, the epidermal flavonol content obtained with the + leaf-clip DUALEX sensor was shown to be decreased in cucumber plants infected with P. cubensis compared to those of healthy plants, highlighting its role as biomarker for detecting P. cubensis infection at the pre-symptomatic stage. 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Downy mildew of cucumber caused by the oomycete Pseudoperonospora cubensis (P. cubensis) is currently the most destructive disease of this crop, causing high yield losses. Visual evaluation by experts is the most established method for the detection of P. cubensis infection, but depends on visual disease symptoms. Detection of fungal infection before visual symptoms appear is highly desirable, allowing to deploy disease control measures before extensive crop damage occurs. The capacity of remote sensing approaches, such as hyperspectral imaging or high-resolution spectrometry, have proved to be powerful tools for detecting plant fungal diseases at pre-symptomatic stages over the last years. However, these approaches are expensive and processing the massive amount of multidimensional data, in case of spectroscopy and hyperspectral imaging, remains complex. Affordable, easy to handle, devices enabling the identification of P. cubensis infected cucumber plants at the pre-symptomatic stage in-situ may represent a high-value alternative for farmers. This study compared the performance of a high-cost high-resolution spectroradiometer (FieldSpec4) and a lower-cost leaf-clip sensor (DUALEX) for the early detection of P. cubensis infection in cucumber. Screening of cucumber plants, grown in a growth chamber, 24 h and 48 h post inoculation, allowed to identify a subset of spectral bands and leaf pigments for differentiating between infected and healthy cucumber plants at the pre-symptomatic stage. In the case of the FieldSpec 4, models based on spectral bands at 402, 576, 690, 708, and 723 nm differentiated between cucumber plants infected with P. cubensis and healthy plants with a F1 value of 0.67. The use of the lower-cost leaf-clip DUALEX sensor differentiated between infected and healthy cucumber plants with a F1 value of 0.60. Furthermore, the epidermal flavonol content obtained with the + leaf-clip DUALEX sensor was shown to be decreased in cucumber plants infected with P. cubensis compared to those of healthy plants, highlighting its role as biomarker for detecting P. cubensis infection at the pre-symptomatic stage. Results of this study will help to develop affordable remote sensing tools suitable for detecting P. cubensis infection at the pre-symptomatic stage in-situ.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.compag.2024.108736</doi><oa>free_for_read</oa></addata></record>
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ispartof Computers and electronics in agriculture, 2024-03, Vol.218, p.108736, Article 108736
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source Elsevier ScienceDirect Journals
subjects agriculture
biomarkers
crop damage
Cucumber
cucumbers
disease control
Downy mildew
electronics
Epidermal flavonol
flavonols
fungi
growth chambers
leaves
Optical leaf sensor
Pre-symptomatic disease detection
Pseudoperonospora cubensis
Spectrometry
spectroradiometers
spectroscopy
title Comparing high-cost and lower-cost remote sensing tools for detecting pre-symptomatic downy mildew (Pseudoperonospora cubensis) infections in cucumbers
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