Challenges in Plant Disease Detection and Recent Advancements
In modern agriculture, addressing challenges such as population growth, climate change, and the emergence of new plant diseases is crucial. Diagnosing plant pathogens is increasingly difficult, posing new obstacles for diagnostic tools. Plant diseases caused by fungi, bacteria, viruses, nematodes, a...
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2024
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| description | In modern agriculture, addressing challenges such as population growth, climate change, and the emergence of new plant diseases is crucial. Diagnosing plant pathogens is increasingly difficult, posing new obstacles for diagnostic tools. Plant diseases caused by fungi, bacteria, viruses, nematodes, and mollicutes are causing major agricultural issues globally, hindering plant growth and spreading rapidly. Efficient, affordable, and user-friendly technologies are needed to accurately detect specific pathogens to overcome the limitations of traditional diagnostic methods. Accurate evaluation techniques are crucial for effectively managing diseases and minimizing yield loss. Cutting-edge technologies like machine learning (ML) and deep learning (DL), with the use of CNNs and DBNs, are employed to detect plant diseases and abnormalities in their early stages. These techniques have proven effective in identifying and studying the effects of severe abiotic environmental factors like drought. The progress of DL technology has significantly enhanced the identification and management of pests in crops and plants. Chlorophyll fluorescence (ChlF) has been extensively utilized for the early detection of crop diseases because of its remarkable sensitivity in indicating alterations in crop photosynthetic physiology. Nanotechnology and nanodiagnostics have made significant advancements and are currently one of the most intriguing fields of science, with the potential to greatly benefit sustainable agriculture through their small size, large surface area, enhanced reactivity, rapid disease detection, precise treatments, and improved nutrient absorption for plants. Trichoderma enhances crop production using sustainable methods and adeptly manages plant illnesses across various settings. Trichoderma acts as a biological control agent through multiple mechanisms, including competing for nutrients, mycoparasitism, producing antibiotic and hydrolytic enzymes, and inducing plant resistance. Enhancing plant growth helps increase their ability to withstand environmental stress, enhances the absorption of nutrients from the soil, and reduces the susceptibility to plant diseases. |
| format | Online |
| id | doab-20.500.12854ir-146488 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | IntechOpen |
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| spelling | doab-20.500.12854ir-1464882024-10-25T10:45:12Z Challenges in Plant Disease Detection and Recent Advancements Bahadur, Amar Botany and plant sciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences In modern agriculture, addressing challenges such as population growth, climate change, and the emergence of new plant diseases is crucial. Diagnosing plant pathogens is increasingly difficult, posing new obstacles for diagnostic tools. Plant diseases caused by fungi, bacteria, viruses, nematodes, and mollicutes are causing major agricultural issues globally, hindering plant growth and spreading rapidly. Efficient, affordable, and user-friendly technologies are needed to accurately detect specific pathogens to overcome the limitations of traditional diagnostic methods. Accurate evaluation techniques are crucial for effectively managing diseases and minimizing yield loss. Cutting-edge technologies like machine learning (ML) and deep learning (DL), with the use of CNNs and DBNs, are employed to detect plant diseases and abnormalities in their early stages. These techniques have proven effective in identifying and studying the effects of severe abiotic environmental factors like drought. The progress of DL technology has significantly enhanced the identification and management of pests in crops and plants. Chlorophyll fluorescence (ChlF) has been extensively utilized for the early detection of crop diseases because of its remarkable sensitivity in indicating alterations in crop photosynthetic physiology. Nanotechnology and nanodiagnostics have made significant advancements and are currently one of the most intriguing fields of science, with the potential to greatly benefit sustainable agriculture through their small size, large surface area, enhanced reactivity, rapid disease detection, precise treatments, and improved nutrient absorption for plants. Trichoderma enhances crop production using sustainable methods and adeptly manages plant illnesses across various settings. Trichoderma acts as a biological control agent through multiple mechanisms, including competing for nutrients, mycoparasitism, producing antibiotic and hydrolytic enzymes, and inducing plant resistance. Enhancing plant growth helps increase their ability to withstand environmental stress, enhances the absorption of nutrients from the soil, and reduces the susceptibility to plant diseases. 2024-10-25T10:45:06Z 2024-10-25T10:45:06Z 2024 book ONIX_20241025_9780854661428_31 9780854661428 9780854661435 9780854661442 https://directory.doabooks.org/handle/20.500.12854/146488 eng image/jpeg n/a https://www.intechopen.com/books/1002675 https://intech-files.s3.amazonaws.com/a043Y00000yJC79QAG/0014579_Authors_Book%20%282024-07-25%2009%3A19%3A12%29.pdf IntechOpen IntechOpen 10.5772/intechopen.1000441 10.5772/intechopen.1000441 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9780854661428 9780854661435 9780854661442 IntechOpen 186 open access |
| spellingShingle | Botany and plant sciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences Challenges in Plant Disease Detection and Recent Advancements |
| title | Challenges in Plant Disease Detection and Recent Advancements |
| title_full | Challenges in Plant Disease Detection and Recent Advancements |
| title_fullStr | Challenges in Plant Disease Detection and Recent Advancements |
| title_full_unstemmed | Challenges in Plant Disease Detection and Recent Advancements |
| title_short | Challenges in Plant Disease Detection and Recent Advancements |
| title_sort | challenges in plant disease detection and recent advancements |
| topic | Botany and plant sciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences |
| topic_facet | Botany and plant sciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences |
| url | ONIX_20241025_9780854661428_31 |