Variation of the ferulic acid concentration and kernel weight in CIMMYT bread wheat germplasm and selection of lines for functional food production

Wenfei Tian Maria Itria Ibba Govindan Velu Shuanghe Cao Zhonghu He (2024, [Artículo])

CIMMYT Germplasm CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GERMPLASM FERULIC ACID FUNCTIONAL FOODS PHYTOCHEMICALS YIELD POTENTIAL WHEAT FOOD PRODUCTION

A 'wiring diagram' for sink strength traits impacting wheat yield potential

Gustavo Slafer John Foulkes Matthew Paul Reynolds Erik Murchie A Elizabete Carmo-Silva Simon Griffiths (2023, [Artículo])

Grain Number Grain Weight Yield Physiology CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING GRAIN HARVEST INDEX SOURCE SINK RELATIONS YIELD COMPONENTS WHEAT

MLN disease diagnostics, surveillance, MLN disease-free seed production, and MLN disease management

Suresh L.M. (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISEASES DISEASE MANAGEMENT SEED PRODUCTION MAIZE NECROSIS YIELD LOSSES ECONOMIC IMPACT SURVEILLANCE SYSTEMS TRAINING

Identification and validation of stable quantitative trait loci for yield component traits in wheat

Yong Zhang Zhonghu He xianchun xia Yan Zhang Shuanghe Cao (2023, [Artículo])

Grain Number Per Spike KASP Markers QTL Mapping Thousand Grain Weight CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA QUANTITATIVE TRAIT LOCI MAPPING TRITICUM AESTIVUM GRAIN YIELD COMPONENTS MARKER-ASSISTED SELECTION

Using microsatellite data to estimate the persistence of field-level yield gaps and their drivers in smallholder systems

Balwinder-Singh Meha Jain (2023, [Artículo])

One way to meet growing food demand is to increase yields in regions that have large yield gaps, including smallholder systems. To do this, it is important to quantify yield gaps, their persistence, and their drivers at large spatio-temporal scales. Here we use microsatellite data to map field-level yields from 2014 to 2018 in Bihar, India and use these data to assess the magnitude, persistence, and drivers of yield gaps at the landscape scale. We find that overall yield gaps are large (33% of mean yields), but only 17% of yields are persistent across time. We find that sowing date, plot area, and weather are the factors that most explain variation in yield gaps across our study region, with earlier sowing associated with significantly higher yield values. Simulations suggest that if all farmers were able to adopt ideal management strategies, including earlier sowing and more irrigation use, yield gaps could be closed by up to 42%. These results highlight the ability of micro-satellite data to understand yield gaps and their drivers, and can be used to help identify ways to increase production in smallholder systems across the globe.

Yield Drivers Yield Mapping CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MICROSATELLITES YIELD GAP SMALLHOLDERS FOOD PRODUCTION YIELD INCREASES

Genotype×Environment interaction and stability analysis using GGE biplot for grain yield of bread wheat (Triticum aestivum) genotypes under low moisture stress areas of Ethiopia

Ayele Badebo Huluka Bekele Abeyo (2023, [Artículo])

Moisture Stress Grain Yield CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPE ENVIRONMENT INTERACTION DROUGHT STRESS STABILITY TRITICUM AESTIVUM LATTICE DESIGN

High Throughput-Phenotyping at CIMMYT: Experiences and needs

Francisco Pinto (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING PROGRAMMES GENETIC GAIN CROSS-BREEDING TECHNOLOGY YIELD POTENTIAL FIELD EXPERIMENTATION

Genetic effects of Rht-B1b and Rht-D1b dwarfing alleles on plant height and agronomic traits of bread wheat (Triticum aestivum L.) breeding lines

Zine El Abidine Fellahi Abderrahmane Hannachi Susanne Dreisigacker deepmala sehgal Hamenna Bouzerzour (2023, [Artículo])

Pleiotropic Effects Reduced Height Genes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT HEIGHT TRITICUM AESTIVUM YIELD COMPONENTS ALLELES BREEDING LINES

Catching-up with genetic progress: Simulation of potential production for modern wheat cultivars in the Netherlands

João Vasco Silva Frits K. Van Evert Pytrik Reidsma (2023, [Artículo])

Context: Wheat crop growth models from all over the world have been calibrated on the Groot and Verberne (1991) data set, collected between 1982 and 1984 in the Netherlands, in at least 28 published studies to date including various recent ones. However, the recent use of this data set for calibration of potential yield is questionable as actual Dutch winter wheat yields increased by 3.1 Mg ha-1 over the period 1984 – 2015. A new comprehensive set of winter wheat experiments, suitable for crop model calibration, was conducted in Wageningen during the growing seasons of 2013–2014 and of 2014–2015. Objective: The present study aimed to quantify the change of winter wheat variety traits between 1984 and 2015 and to examine which of the identified traits explained the increase in wheat yield most. Methods: PCSE-LINTUL3 was calibrated on the Groot and Verberne data (1991) set. Next, it was evaluated on the 2013–2015 data set. The model was further recalibrated on the 2013–2015 data set. Parameter values of both calibrations were compared. Sensitivity analysis was used to assess to what extent climate change, elevated CO2, changes in sowing dates, and changes in cultivar traits could explain yield increases. Results: The estimated reference light use efficiency and the temperature sum from anthesis to maturity were higher in 2013–2015 than in 1982–1984. PCSE-LINTUL3, calibrated on the 1982–1984 data set, underestimated the yield potential of 2013–2015. Sensitivity analyses showed that about half of the simulated winter wheat yield increase between 1984 and 2015 in the Netherlands was explained by elevated CO2 and climate change. The remaining part was explained by the increased temperature sum from anthesis to maturity and, to a smaller extent, by changes in the reference light use efficiency. Changes in sowing dates, biomass partitioning fractions, thermal requirements for anthesis, and biomass reallocation did not explain the yield increase. Conclusion: Recalibration of PCSE-LINTUL3 was necessary to reproduce the high wheat yields currently obtained in the Netherlands. About half of the reported winter wheat yield increase was attributed to climate change and elevated CO2. The remaining part of the increase was attributed to changes in the temperature sum from anthesis to maturity and, to a lesser extent, the reference light use efficiency. Significance: This study systematically addressed to what extent changes in various cultivar traits, climate change, and elevated CO2 can explain the winter wheat yield increase observed in the Netherlands between 1984 and 2015.

Light Use Efficiency Potential Yield CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP MODELLING LIGHT PHENOLOGY MAXIMUM SUSTAINABLE YIELD TRITICUM AESTIVUM WINTER WHEAT

Mapping QTL for phenological and grain-related traits in a mapping population derived from high-zinc-biofortified wheat

Gopalareddy Krishnappa Govindan Velu (2023, [Artículo])

DArT-Seq Gene Mapping Yield Component Traits CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT QUANTITATIVE TRAIT LOCI CANDIDATE GENES QUANTITATIVE TRAIT LOCI MAPPING YIELD COMPONENTS BIOFORTIFICATION