Person: Rodrigues, F.
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Rodrigues
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F.
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Rodrigues, F.
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0000-0001-7273-22175 results
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- Multispectral and thermal infrared data, visual scores for severity of common rust symptoms, and genotypic single nucleotide polymorphism data of three F2-derived biparental doubled-haploid maize populations(Elsevier, 2024) Loladze, A.; Rodrigues, F.; Petroli, C.; Muñoz-Zavala, C.; Naranjo, S.; San Vicente Garcia, F.M.; Gerard, B.; Montesinos-Lopez, O.A.; Crossa, J.; Martini, J.W.R.
Publication - Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize(Elsevier, 2024) Loladze, A.; Rodrigues, F.; Petroli, C.; Muñoz-Zavala, C.; Naranjo, S.; San Vicente Garcia, F.M.; Gerard, B.; Montesinos-Lopez, O.A.; Crossa, J.; Martini, J.W.R.
Publication - Radiative transfer model inversion using high-resolution hyperspectral airborne imagery – Retrieving maize LAI to access biomass and grain yield(Elsevier, 2022) Ahmed Kayad; Rodrigues, F.; Naranjo, S.; Sozzi, M.; Pirotti, F.; Marinello, F.; Schulthess, U.; Defourny, P.; Gerard, B.; Weiss, M.
Publication - Application of remote sensing for phenotyping tar spot complex resistance in maize(Frontiers, 2019) Loladze, A.; Rodrigues, F.; Toledo, F.H.; San Vicente Garcia, F.M.; Gerard, B.; Prasanna, B.M.Tar spot complex (TSC), caused by at least two fungal pathogens, Phyllachora maydis and Monographella maydis, is one of the major foliar diseases of maize in Central and South America. P. maydis was also detected in the United States of America in 2015 and since then the pathogen has spread in the maize growing regions of the country. Although remote sensing (RS) techniques are increasingly being used for plant phenotyping, they have not been applied to phenotyping TSC resistance in maize. In this study, several multispectral vegetation indices (VIs) and thermal imaging of maize plots under disease pressure and disease-free conditions were tested using an unmanned aerial vehicle (UAV) over two crop seasons. A strong relationship between grain yield, a vegetative index (MCARI2), and canopy temperature was observed under disease pressure. A strong relationship was also observed between the area under the disease progress curve of TSC and three vegetative indices (RDVI, MCARI1, and MCARI2). In addition, we demonstrated that TSC could cause up to 58% yield loss in the most susceptible maize hybrids. Our results suggest that the RS techniques tested in this study could be used for high throughput phenotyping of TSC resistance and potentially for other foliar diseases of maize. This may help reduce the cost and time required for the development of improved maize germplasm. Challenges and opportunities in the use of RS technologies for disease resistance phenotyping are discussed.
Publication - Use of remote sensing technology in the assessment of resistance of maize to tar spot complex (TSC)(CIMMYT, 2017) Rodrigues, F.; Defourny, P.; Gerard, B.; San Vicente Garcia, F.M.; Loladze, A.
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