Technological Progress Toward Peanut Disease Management: A Review
Peanut (<i>Arachis hypogea</i> L.) crops in the southeastern U.S. suffer significant yield losses from diseases like leaf spot, southern blight, and stem rot. Traditionally, growers use conventional boom sprayers, which often leads to overuse and wastage of agrochemicals. However, advanc...
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MDPI AG
2025-02-01
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| author | Muhammad Asif Aleena Rayamajhi Md Sultan Mahmud |
| author_facet | Muhammad Asif Aleena Rayamajhi Md Sultan Mahmud |
| author_sort | Muhammad Asif |
| collection | DOAJ |
| description | Peanut (<i>Arachis hypogea</i> L.) crops in the southeastern U.S. suffer significant yield losses from diseases like leaf spot, southern blight, and stem rot. Traditionally, growers use conventional boom sprayers, which often leads to overuse and wastage of agrochemicals. However, advances in computer technologies have enabled the development of precision or variable-rate sprayers, both ground-based and drone-based, that apply agrochemicals more accurately. Historically, crop disease scouting has been labor-intensive and costly. Recent innovations in computer vision, artificial intelligence (AI), and remote sensing have transformed disease identification and scouting, making the process more efficient and economical. Over the past decade, numerous studies have focused on developing technologies for peanut disease scouting and sprayer technology. The current research trend shows significant advancements in precision spraying technologies, facilitating smart spraying capabilities. These advancements include the use of various platforms, such as ground-based and unmanned aerial vehicle (UAV)-based systems, equipped with sensors like RGB (red–blue–green), multispectral, thermal, hyperspectral, light detection and ranging (LiDAR), and other innovative detection technologies, as highlighted in this review. However, despite the availability of some commercial precision sprayers, their effectiveness is limited in managing certain peanut diseases, such as white mold, because the disease affects the roots, and the chemicals often remain in the canopy, failing to reach the soil where treatment is needed. The review concludes that further advances are necessary to develop more precise sprayers that can meet the needs of large-scale farmers and significantly enhance production outcomes. Overall, this review paper aims to provide a review of smart spraying techniques, estimating the required agrochemicals and applying them precisely in peanut fields. |
| format | Article |
| id | doaj-art-dbfd0eb3b37e42b1b44ef52388fb6e77 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-02-01 |
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| spelling | doaj-art-dbfd0eb3b37e42b1b44ef52388fb6e772025-08-20T03:12:04ZengMDPI AGSensors1424-82202025-02-01254125510.3390/s25041255Technological Progress Toward Peanut Disease Management: A ReviewMuhammad Asif0Aleena Rayamajhi1Md Sultan Mahmud2Department of Plant Pathology, University of Georgia, Athens, GA 30602, USASchool of Environmental, Civil, Agricultural, and Mechanical Engineering, College of Engineering, University of Georgia, Athens, GA 30602, USADepartment of Plant Pathology, University of Georgia, Athens, GA 30602, USAPeanut (<i>Arachis hypogea</i> L.) crops in the southeastern U.S. suffer significant yield losses from diseases like leaf spot, southern blight, and stem rot. Traditionally, growers use conventional boom sprayers, which often leads to overuse and wastage of agrochemicals. However, advances in computer technologies have enabled the development of precision or variable-rate sprayers, both ground-based and drone-based, that apply agrochemicals more accurately. Historically, crop disease scouting has been labor-intensive and costly. Recent innovations in computer vision, artificial intelligence (AI), and remote sensing have transformed disease identification and scouting, making the process more efficient and economical. Over the past decade, numerous studies have focused on developing technologies for peanut disease scouting and sprayer technology. The current research trend shows significant advancements in precision spraying technologies, facilitating smart spraying capabilities. These advancements include the use of various platforms, such as ground-based and unmanned aerial vehicle (UAV)-based systems, equipped with sensors like RGB (red–blue–green), multispectral, thermal, hyperspectral, light detection and ranging (LiDAR), and other innovative detection technologies, as highlighted in this review. However, despite the availability of some commercial precision sprayers, their effectiveness is limited in managing certain peanut diseases, such as white mold, because the disease affects the roots, and the chemicals often remain in the canopy, failing to reach the soil where treatment is needed. The review concludes that further advances are necessary to develop more precise sprayers that can meet the needs of large-scale farmers and significantly enhance production outcomes. Overall, this review paper aims to provide a review of smart spraying techniques, estimating the required agrochemicals and applying them precisely in peanut fields.https://www.mdpi.com/1424-8220/25/4/1255artificial intelligencecomputer visiondisease scoutingdrone technologyremote sensingprecision sprayers |
| spellingShingle | Muhammad Asif Aleena Rayamajhi Md Sultan Mahmud Technological Progress Toward Peanut Disease Management: A Review Sensors artificial intelligence computer vision disease scouting drone technology remote sensing precision sprayers |
| title | Technological Progress Toward Peanut Disease Management: A Review |
| title_full | Technological Progress Toward Peanut Disease Management: A Review |
| title_fullStr | Technological Progress Toward Peanut Disease Management: A Review |
| title_full_unstemmed | Technological Progress Toward Peanut Disease Management: A Review |
| title_short | Technological Progress Toward Peanut Disease Management: A Review |
| title_sort | technological progress toward peanut disease management a review |
| topic | artificial intelligence computer vision disease scouting drone technology remote sensing precision sprayers |
| url | https://www.mdpi.com/1424-8220/25/4/1255 |
| work_keys_str_mv | AT muhammadasif technologicalprogresstowardpeanutdiseasemanagementareview AT aleenarayamajhi technologicalprogresstowardpeanutdiseasemanagementareview AT mdsultanmahmud technologicalprogresstowardpeanutdiseasemanagementareview |