Evaluation of Kenya stem rust observation nursery wheat genotypes for yield and yield components under artificial rust conditions

Mandeep Randhawa (2021, [Artículo])

Grain Yield Yield Stability Genotype x Season Interaction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT HERITABILITY YIELDS RUSTS GENOTYPES

Wheat seed demand assessment assisted by genotyping in Ethiopia

Moti Jaleta Kindie Tesfaye Olaf Erenstein (2023, [Artículo])

This study examines the extent to which wheat varieties supplied by the formal seed system align with the varieties demanded and used by farmers in Ethiopia. The framework of stated and revealed preferences drawn from the consumer preference theory is used to analyze farmer demand for different wheat varieties. We used official data from the formal seed sector and representative survey data from wheat farm households in Ethiopia. The survey data allow to contrast the farmer reported varietal use with genotyping by sequencing (also known as DNA fingerprinting). Farmers' reliance on informal seed sources and own saved seed, among others, contributes to the misidentification of the varieties they grow. Consequently, farmers are likely to misinform the formal seed demand assessment leading to either an over- or underestimation of actual seed demand for specific wheat varieties. Genotyping by sequencing, as opposed to farmer reports, established the persistence of old varieties. This also implies vulnerability of wheat production to disease dynamics depending on the longevity of disease resistance by the variety in use. Apart from narrowing the gap between the actual and stated demand and ensuring timely replacement of wheat varieties, genotyping-assisted estimates can save seed carry-over cost. Genotyping by sequencing is increasingly used as the new benchmark and gold standard for identifying and tracking the adoption of crop varieties. The technique has potential to enhance the performance of the seed sector through effective planning that can optimize resource commitments and accelerate the rate of varietal replacement.

Seed Demand Varietal Replacement CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPING-BY-SEQUENCING SEEDS WHEAT

Genetic improvement of global wheat, including progress for enhancing insect resistance

Leonardo Abdiel Crespo Herrera (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC IMPROVEMENT WHEAT BREEDING CLIMATE CHANGE DISEASE RESISTANCE YIELDS

2022 Advanced wheat improvement course: Global wheat rust surveillance

&

monitoring

David Hodson (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT RUSTS DISEASE SURVEILLANCE NEW TECHNOLOGY REMOTE SENSING

Global rust monitoring

David Hodson (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT RUSTS DISEASE SURVEILLANCE REMOTE SENSING NEW TECHNOLOGY

Important wheat diseases in E. Africa and strategies to enhance durable resistance

sridhar bhavani (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE WHEAT BLASTS (OF PLANTS) ADULT PLANT RESISTANCE

Breeding for durable rust resistance

sridhar bhavani (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING RUSTS DISEASE RESISTANCE WHEAT

E. African spring wheat breeding pipeline and Network (CIMMYT-KALRO)

sridhar bhavani (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PLANT BREEDING RESEARCH NETWORKS

First detection of virulence in Puccinia striiformis f. Sp. tritici to wheat resistance genes Yr10 and Yr24 (=Yr26) in Mexico

JULIO HUERTA_ESPINO Ravi Singh (2017, [Artículo])

Near Isogenic Lines Virulence Spectrum Yellow Rust CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA VIRULENCE PUCCINIA STRIIFORMIS WHEAT RESISTANCE GENES

The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia

Gerald Blasch David Hodson Francelino Rodrigues (2023, [Artículo])

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