The photosynthetic pigments are mainly responsible for absorbing the light intended to promote photosynthesis on the chloroplast of the leaves. Different studies have related the spectral response in the leaves of plants with the biotic stress generated by pathogens. In general, maximum differences in reflectance have been found in the range of 380–750 nm between plants subjected to biotic stress and healthy plants. In this study, it was possible to characterize and relate the spectral variance in leaves of S. lycopersicum infected with F. oxysporum with this physiological variation and pathogen concentration in tomato plants during the asymptomatic period of vascular wilt. Photosynthetic parameters derived from gaseous exchange analysis in the tomato leaves correlated related with four bands in the visible range (Vis). Additionally, five specific bands also present a high correlation with the increase in the concentration of F. oxysporum conidia measured at the root: 448–523 nm, 624–696 nm, 740–960 nm, 973–976 nm, and 992–995 nm. These wavelengths allowed a 100% correct classification of the plants inoculated with F. oxysporum from the plants subjected to hydric stress and the control plants in the asymptomatic period of the disease. The spectral response to biotic and abiotic stress in the measured Vis/NIR range can be explained by the general tendency to change the concentration of chlorophyll and carotene in tomato leaves. These studies also highlight the importance of the implementation of robust multivariate analysis over the multiple univariate analysis used in the applied biological sciences and specifically in the agricultural sciences. These results demonstrate that specific wavelength responses are due to physiological changes in plants subjected to stress, and can be used in indexes and algorithms applied to the early detection of diseases in plants on different pathosystems.
Ecoepidemiological scenarios for Chagas disease transmission are complex, so vector control measures to decrease human–vector contact and prevent infection transmission are difficult to implement in all geographic contexts. This study assessed the geographic abundance patterns of two vector species of Chagas disease: Triatoma maculata (Erichson, 1848) and Rhodnius pallescens (Barber, 1932) in Latin America. We modeled their potential distribution using the maximum entropy algorithm implemented in Maxent and calculated distances to their niche centroid by fitting a minimum-volume ellipsoid. In addition, to determine which method would accurately explain geographic abundance patterns, we compared the correlation between population abundance and the distance to the ecological niche centroid (DNC) and between population abundance and Maxent environmental suitability. The potential distribution estimated for T . maculata showed that environmental suitability covers a large area, from Panama to Northern Brazil. R . pallescens showed a more restricted potential distribution, with environmental suitability covering mostly the coastal zone of Costa Rica and some areas in Nicaragua, Honduras, Belize and the Yucatán Peninsula in Mexico, northern Colombia, Acre, and Rondônia states in Brazil, as well as a small region of the western Brazilian Amazon. We found a negative slope in the relationship between population abundance and the DNC in both species. R . pallecens has a more extensive potential latitudinal range than previously reported, and the distribution model for T . maculata corroborates previous studies. In addition, population abundance increases according to the niche centroid proximity, indicating that population abundance is limited by the set of scenopoetic variables at coarser scales (non-interactive variables) used to determine the ecological niche. These findings might be used by public health agencies in Latin America to implement actions and support programs for disease prevention and vector control, identifying areas in which to expand entomological surveillance and maintain chemical control, in order to decrease human–vector contact.
Las plantas asintomáticas son reservorios de patógenos, ya que pueden permanecer infectadas la mayor parte de su ciclo de desarrollo, convirtiéndose en fuente de contaminación para el resto del cultivo. El objetivo de este estudio fue evaluar un método de detección y discriminación de dos cepas de Fusarium oxysporum en tomate usando espectroscopia. La enfermedad en las plantas de tomate inoculadas con la cepa aislada de gulupa (F05) fue mayor a la observada en la cepa aislada de tomate (F07), presentando valores de 60,0% (11 días) y 81,8% (22 días); la cepa F07 presentó incidencias de 30,0 y 64,3% en ambas mediciones. La planta infectada con la cepa F05 fue mejor discriminada en el periodo de incubación de la enfermedad en ambos periodos de tiempo en los Análisis de Componentes Principales (PCA) y Análisis Discriminantes Lineales (LDA) realizados con los controles en comparación con la cepa F07. Estos resultados sugieren que la espectroscopia de reflectancia VIS es un método sensible y confiable que puede ser adecuado para el diagnóstico temprano de enfermedades en plantas.
Spectroscopy has become one of the most used non-invasive methods to detect plant diseases before symptoms are visible. In this study it was possible to characterize the spectral variation in leaves of Solanum lycopersicum L. infected with Fusarium oxysporum during the incubation period. It was also possible to identify the relevant specific wavelengths in the range of 380-1000 nm that can be used as spectral signatures for the detection and discrimination of vascular wilt in S. lycopersicum. It was observed that inoculated tomato plants increased their reflectance in the visible range (Vis) and decreased slowly in the near infrared range (NIR) measured during incubation, showing marked differences with plants subjected to water stress in the Vis/NIR. Additionally, three ranges were found in the spectrum related to infection by F. oxysporum (510-520 nm, 650-670 nm, 700-750 nm). Linear discriminant models on spectral reflectance data were able to differentiate between tomato varieties inoculated with F. oxysporum from healthy ones with accuracies higher than 70% 9 days after inoculation. The results showed the potential of reflectance spectroscopy to discriminate plants inoculated with F. oxysporum from healthy ones as well as those subjected to water stress in the incubation period of the disease.
Fusarium wilt is the greatest threat to Musaceae production worldwide; remote sensing techniques based on reflectance spectroscopy are proposed for its detection. The spectral response of leaves of healthy plants and plants infected with Fusarium oxysporum f. sp. cubense Race1 (Foc R1) from two banana cultivars during the incubation period of the disease were characterized. Spectra of 400-1000 nm were measured in healthy and Foc R1-infected plants on Gros Michel (GM: susceptible) and Williams (W: resistant) bananas with an Ocean Optics HR2000+ portable spectrometer. Similar general patterns were obtained in the spectra for both cultivars for the Vis, around 25% in the green region, but, as the foliar development progressed, reflectance decreased throughout the entire spectral range, close to 12.5% (green region of Vis range) on leaf 4 of both. Four wavelengths were discriminant for the healthy plants in the cultivars. Additionally, reflectance increased in the infected plants in the incubation period throughout the range, decreasing rapidly once the first visible symptoms appeared. The results suggested that an increase in reflectance at discriminating wavelengths can be used to diagnose diseased plants in the asymptomatic period, and a rapid decrease in this suggests the onset of the symptomatic phase.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.