Laser-based remote detection of leaf wetness
Pesticide-free agricultural strategies need new tools for disease prevention. Better than early detection of disease, detection of conditions favorable to their appearance can be a progress. In the case of fungal diseases, the presence of water on the plant surface is necessary. In order to detect r...
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Veröffentlicht in: | Journal of applied physics 2023-09, Vol.134 (11) |
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creator | Gaetani, R. Feugier, F. G. Masenelli, B. |
description | Pesticide-free agricultural strategies need new tools for disease prevention. Better than early detection of disease, detection of conditions favorable to their appearance can be a progress. In the case of fungal diseases, the presence of water on the plant surface is necessary. In order to detect remotely this presence early and at the scale of a crop field, we propose a low-cost solution based on laser reflection. Here, experimental results in a controlled environment are presented on both hydrophobic and hydrophilic leaves (rapeseed Brassica Napus and grapevine Vitis Vinifera, respectively). We first assess the water detection on a leaf surface by recreating the dew formation process. We next evaluate the influence of the scanning measurement and leaf inclination on the detection to get closer to in-field conditions. Results show that this method is very sensitive on both types of leaves. Water detection is possible from a low surface coverage with a high temporal precision at 1 m. In the hydrophobic case, water on a leaf surface leads to an increase of the detected signal up to three times compared to a dry leaf. The corresponding minimum surface coverage detectable at 1 m is evaluated at 1.6% thanks to 2D ray-tracing numerical simulations. In the hydrophilic case, on the contrary, water on a leaf surface leads to a decrease of the detected signal by almost half. For both types, the dew detection delay is contained under 5 min and can be improved. Finally, the presented results pave the way to a field application. |
doi_str_mv | 10.1063/5.0158260 |
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G. ; Masenelli, B.</creator><creatorcontrib>Gaetani, R. ; Feugier, F. G. ; Masenelli, B.</creatorcontrib><description>Pesticide-free agricultural strategies need new tools for disease prevention. Better than early detection of disease, detection of conditions favorable to their appearance can be a progress. In the case of fungal diseases, the presence of water on the plant surface is necessary. In order to detect remotely this presence early and at the scale of a crop field, we propose a low-cost solution based on laser reflection. Here, experimental results in a controlled environment are presented on both hydrophobic and hydrophilic leaves (rapeseed Brassica Napus and grapevine Vitis Vinifera, respectively). We first assess the water detection on a leaf surface by recreating the dew formation process. We next evaluate the influence of the scanning measurement and leaf inclination on the detection to get closer to in-field conditions. Results show that this method is very sensitive on both types of leaves. Water detection is possible from a low surface coverage with a high temporal precision at 1 m. In the hydrophobic case, water on a leaf surface leads to an increase of the detected signal up to three times compared to a dry leaf. The corresponding minimum surface coverage detectable at 1 m is evaluated at 1.6% thanks to 2D ray-tracing numerical simulations. In the hydrophilic case, on the contrary, water on a leaf surface leads to a decrease of the detected signal by almost half. For both types, the dew detection delay is contained under 5 min and can be improved. 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G.</creatorcontrib><creatorcontrib>Masenelli, B.</creatorcontrib><title>Laser-based remote detection of leaf wetness</title><title>Journal of applied physics</title><description>Pesticide-free agricultural strategies need new tools for disease prevention. Better than early detection of disease, detection of conditions favorable to their appearance can be a progress. In the case of fungal diseases, the presence of water on the plant surface is necessary. In order to detect remotely this presence early and at the scale of a crop field, we propose a low-cost solution based on laser reflection. Here, experimental results in a controlled environment are presented on both hydrophobic and hydrophilic leaves (rapeseed Brassica Napus and grapevine Vitis Vinifera, respectively). We first assess the water detection on a leaf surface by recreating the dew formation process. We next evaluate the influence of the scanning measurement and leaf inclination on the detection to get closer to in-field conditions. Results show that this method is very sensitive on both types of leaves. Water detection is possible from a low surface coverage with a high temporal precision at 1 m. In the hydrophobic case, water on a leaf surface leads to an increase of the detected signal up to three times compared to a dry leaf. The corresponding minimum surface coverage detectable at 1 m is evaluated at 1.6% thanks to 2D ray-tracing numerical simulations. In the hydrophilic case, on the contrary, water on a leaf surface leads to a decrease of the detected signal by almost half. For both types, the dew detection delay is contained under 5 min and can be improved. Finally, the presented results pave the way to a field application.</description><subject>Agricultural sciences</subject><subject>Agrochemicals</subject><subject>Brassica</subject><subject>Dew</subject><subject>Engineering Sciences</subject><subject>Environmental Engineering</subject><subject>Environmental Sciences</subject><subject>Evaluation</subject><subject>Fungal diseases</subject><subject>Hydrophilicity</subject><subject>Hydrophobicity</subject><subject>Laser applications</subject><subject>Life Sciences</subject><subject>Rapeseed</subject><subject>Ray tracing</subject><subject>Sciences and technics of agriculture</subject><subject>Signal and Image processing</subject><issn>0021-8979</issn><issn>1089-7550</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpFkE9LAzEUxIMoWKsHv8GCJ8Gt72U3_46lWCsseNFzyGZfsKVtarJV_PZuadHLDAzDj2EYu0WYIMjqUUwAheYSztgIQZtSCQHnbATAsdRGmUt2lfMKAFFXZsQeGpcple2gXZFoE3sqOurJ98u4LWIo1uRC8U39lnK-ZhfBrTPdnHzM3udPb7NF2bw-v8ymTem5ln1Z16blaHRwGkTwijC0wkkpjaZOkiddCd3WnLgzoUVhNA8eleQIyhPKaszuj9wPt7a7tNy49GOjW9rFtLGHDGoOppb4hUP37tjdpfi5p9zbVdyn7TDPDmMEAleK_xN9ijknCn9YBHs4zgp7Oq76BRIGXIs</recordid><startdate>20230921</startdate><enddate>20230921</enddate><creator>Gaetani, R.</creator><creator>Feugier, F. 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G.</creatorcontrib><creatorcontrib>Masenelli, B.</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Journal of applied physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gaetani, R.</au><au>Feugier, F. G.</au><au>Masenelli, B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Laser-based remote detection of leaf wetness</atitle><jtitle>Journal of applied physics</jtitle><date>2023-09-21</date><risdate>2023</risdate><volume>134</volume><issue>11</issue><issn>0021-8979</issn><eissn>1089-7550</eissn><abstract>Pesticide-free agricultural strategies need new tools for disease prevention. Better than early detection of disease, detection of conditions favorable to their appearance can be a progress. In the case of fungal diseases, the presence of water on the plant surface is necessary. In order to detect remotely this presence early and at the scale of a crop field, we propose a low-cost solution based on laser reflection. Here, experimental results in a controlled environment are presented on both hydrophobic and hydrophilic leaves (rapeseed Brassica Napus and grapevine Vitis Vinifera, respectively). We first assess the water detection on a leaf surface by recreating the dew formation process. We next evaluate the influence of the scanning measurement and leaf inclination on the detection to get closer to in-field conditions. Results show that this method is very sensitive on both types of leaves. Water detection is possible from a low surface coverage with a high temporal precision at 1 m. In the hydrophobic case, water on a leaf surface leads to an increase of the detected signal up to three times compared to a dry leaf. The corresponding minimum surface coverage detectable at 1 m is evaluated at 1.6% thanks to 2D ray-tracing numerical simulations. In the hydrophilic case, on the contrary, water on a leaf surface leads to a decrease of the detected signal by almost half. For both types, the dew detection delay is contained under 5 min and can be improved. Finally, the presented results pave the way to a field application.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0158260</doi><orcidid>https://orcid.org/0000-0002-0654-3757</orcidid><orcidid>https://orcid.org/0009-0003-9523-2372</orcidid><orcidid>https://orcid.org/0000-0002-0254-5376</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural sciences Agrochemicals Brassica Dew Engineering Sciences Environmental Engineering Environmental Sciences Evaluation Fungal diseases Hydrophilicity Hydrophobicity Laser applications Life Sciences Rapeseed Ray tracing Sciences and technics of agriculture Signal and Image processing |
title | Laser-based remote detection of leaf wetness |
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