Early detection of bacterial wilt in bananas caused by Ralstonia solanacearum using reflectance spectroscopy

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Publicado en:Journal of Plant Diseases and Protection (DPG) vol. 131, no. 2 (Apr 2024), p. 523
Autor principal: Marín-Ortiz, Juan Carlos
Otros Autores: Botero-Fernández, Verónica, Zapata-Henao, Sebastián, Hoyos-Carvajal, Lilliana María
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Nature Publishing Group
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022 |a 1861-3829 
022 |a 1861-3837 
022 |a 0340-8159 
024 7 |a 10.1007/s41348-023-00830-9  |2 doi 
035 |a 3267316233 
045 2 |b d20240401  |b d20240430 
100 1 |a Marín-Ortiz, Juan Carlos  |u Universidad Nacional de Colombia, Facultad de Ciencias Agrarias, Medellín, Colombia (GRID:grid.10689.36) (ISNI:0000 0004 9129 0751) 
245 1 |a Early detection of bacterial wilt in bananas caused by <i>Ralstonia solanacearum</i> using reflectance spectroscopy 
260 |b Nature Publishing Group  |c Apr 2024 
513 |a Journal Article 
520 3 |a Bacterial wilt is one of the most important vascular diseases that generate high worldwide losses. The main strategy to control it involves early detection of infected plants that mitigate its spread in the field. This research characterized the spectral response of healthy plants, infected with Ralstonia solanacearum E.F. Smith race 2 and subjected to water stress, in two banana cultivars by spectroscopy reflectance. The spectral data were used to detect vascular wilt during the incubation period of the disease in Gros Michel and Cavendish banana cultivars. The reflectance data were collected from the leaves using a portable spectrometer. Both varieties of healthy plants showed a typical low reflectance in the visible range, with a peak of green of around 12% in Williams and 5% in Gros Michel. In the measured infrared range, the two varieties presented values between 60 and 70% in the latest days post-infection measurements, decreasing to ~ 50% after 12&#xa0;dpi. The results obtained indicate that plants infected with R. solanacearum have no initial increase in reflectance in the visible (Vis) range, whereas decrease rapidly after 6&#xa0;dpi in the 700–1000&#xa0;nm range. This methodology identifies three wavelengths (710, 770, and 965&#xa0;nm) that allow differentiation between ill and healthy plants after 6&#xa0;days post-inoculation, with a percentage of correct classification that ranges from 96 to 100%. The spectral response characterization in healthy plants and those subjected to various types of stress is a fundamental input for the development of early disease detection systems based on spectroscopy techniques. 
651 4 |a Asia 
651 4 |a United States--US 
651 4 |a Colombia 
653 |a Infections 
653 |a Reflectance 
653 |a Pathogens 
653 |a Flowers & plants 
653 |a Water stress 
653 |a Inoculation 
653 |a Leaves 
653 |a Plant bacterial diseases 
653 |a Crop diseases 
653 |a Cultivars 
653 |a Disease detection 
653 |a Bananas 
653 |a Spectroscopy 
653 |a Plant diseases 
653 |a Spectral sensitivity 
653 |a Wilt 
653 |a Wavelengths 
653 |a Ralstonia solanacearum 
653 |a Environmental 
700 1 |a Botero-Fernández, Verónica  |u Universidad Nacional de Colombia, Facultad de Minas, Medellín, Colombia (GRID:grid.10689.36) (ISNI:0000 0004 9129 0751) 
700 1 |a Zapata-Henao, Sebastián  |u Centro de Investigación del Banano (Cenibanano), Carepa, Colombia (GRID:grid.10689.36) 
700 1 |a Hoyos-Carvajal, Lilliana María  |u Universidad Nacional de Colombia, Facultad de Ciencias Agrarias, Medellín, Colombia (GRID:grid.10689.36) (ISNI:0000 0004 9129 0751) 
773 0 |t Journal of Plant Diseases and Protection (DPG)  |g vol. 131, no. 2 (Apr 2024), p. 523 
786 0 |d ProQuest  |t Agriculture Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3267316233/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3267316233/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3267316233/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch