3 research outputs found

    Identification of new sources of resistance to RHBV- rice hoja blanca virus

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    With the aim to find new sources of resistance to rice hoja blanca (white leaf) disease, transmitted by the insect Tagosodes orizicolus, 660 genotypes were evaluated under greenhouse and field conditions. Seven resistant genotypes were identified, and genomic studies were performed to demonstrate that the resistance in these sources is genetically different from that of Fedearroz 2000, which is currently the variety with the most resistance to hoja blanca. These new resistance sources constitute a resource that can be used to sustainably extend hoja blanca disease management throughout all of the rice-growing regions of tropical America. This is the first report of hoja blanca resistance in indica rice and different from that of Fedearroz 2000

    High-throughput biomass estimation in rice crops using UAV multispectral imagery

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    This paper presents a high-throughput method for Above Ground Estimation of Biomass (AGBE) in rice using multispectral near-infrared (NIR) imagery captured at different scales of the crop. By developing an integrated aerial crop monitoring solution using an Unmanned Aerial Vehicle (UAV), our approach calculates 7 vegetation indices that are combined in the form of multivariable regressions depending on the stage of rice growth: vegetative, reproductive or ripening. We model the relationship of these vegetation indices to estimate the biomass of a certain crop area. The methods are calibrated by using a minimum sampling area of 1 linear meter of the crop. Comprehensive experimental tests have been carried out over two different rice varieties under upland and lowland rice production systems. Results show that the proposed approach is able to estimate the biomass of large areas of the crop with an average correlation of 0.76 compared with the traditional manual destructive method. To our knowledge, this is the first work that uses a small sampling area of 1 linear meter to calibrate and validate NIR image-based estimations of biomass in rice crops
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