Repositorio Nacional

Very high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties’ response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS–NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.

Very High Resolution Imagery Disease Detection Methods Early Growth Stages CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA UNMANNED AERIAL VEHICLES STEM RUST PHENOTYPING HIGH-THROUGHPUT PHENOTYPING WHEAT

Potential impact of scaling adaptation strategies for drought stress: a case of drought-tolerant maize varieties in Tanzania

Girma Gezmu Gebre Dil Bahadur Rahut Jeetendra Aryal (2023, [Artículo])

Drought-Tolerant Maize Varieties Scalability CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DROUGHT TOLERANCE MAIZE VARIETIES ECONOMIC IMPACT

Phenotypic assessment of genetic gain from selection for improved drought tolerance in semi-tropical maize populations

Terence Molnar Somak Dutta Thanda Dhliwayo Samuel Trachsel Michael Lee (2023, [Artículo])

Drought Tolerant Population Topcross Water Deficit CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DROUGHT TOLERANCE WATER MAIZE CLIMATE CHANGE GENETIC GAIN

Genome-wide association analysis of tan spot disease resistance in durum wheat accessions from Tunisia

marwa laribi Sarrah Ben M'barek Carolina Sansaloni Susanne Dreisigacker (2023, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISEASE RESISTANCE HARD WHEAT GENETIC DIVERSITY GENOME-WIDE ASSOCIATION STUDIES LANDRACES POPULATION STRUCTURE

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

EGS planning, production, maintenance of inbred lines and Quality Assurance/Quality Control (QA/QC)

Fidelis Owino Berhanu Tadesse Ertiro (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA INBRED LINES SEED QUALITY QUALITY CONTROL GENETIC MARKERS

Integration of novel SSR and gene-based SNP marker loci in the chickpea genetic map and establishment of new anchor points with Medicago truncatula genome

Spurthi Nayak Polavarapu Kavi Kishor Rajeev Varshney (2010, [Artículo])

Simple Sequence Repeats Mapping Population Translational Studies CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ANCHORS CHICKPEAS CICER ARIETINUM GENETIC MAPS GENETIC MARKERS MEDICAGO MEDICAGO TRUNCATULA MICROSATELLITES SINGLE NUCLEOTIDE POLYMORPHISM GENES