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Fungal pathogens associated with crown and root rot in wheat-growing areas of Northern Kyrgyzstan
Göksel ÖZER SENOL YILDIZ MUSTAFA IMREN Abdelfattah DABABAT (2023, [Artículo])
Wheat Diseases Crown and Root Rot CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TRITICUM WHEAT DISEASES ROOT ROTS PATHOGENICITY
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
Alison Bentley Charles Chen Nunzio D'Agostino (2022, [Artículo])
Allele Mining High-Throughput Phenotyping Genomic Estimated Breeding Value CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP IMPROVEMENT DNA CHROMOSOME MAPPING GENETIC LINKAGE GENOMES GENOTYPING GERMINATION HEAT STRESS QUALITY CONTROL SINGLE NUCLEOTIDE POLYMORPHISM TRITICUM AESTIVUM GENETIC DIVERSITY (AS RESOURCE) HIGH-THROUGHPUT SEQUENCING
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
Muhammad Massub Tehseen Fatma Aykut Tonk Ahmed Amri Carolina Sansaloni Ezgi Kurtulus Muhammad Salman Mubarik Kumarse Nazari (2022, [Artículo])
Wheat Landraces Genetic Diversity SNP Markers Analysis of Molecular Variance AMOVA CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING DISCRIMINANT ANALYSIS GENETIC VARIATION GENETIC DISTANCE GENETIC IMPROVEMENT GENETIC MARKERS HEXAPLOIDY LANDRACES POPULATION STRUCTURE SINGLE NUCLEOTIDE POLYMORPHISM TRITICUM AESTIVUM WHEAT
XUECAI ZHANG Yong Zhang (2022, [Artículo])
Fusarium Head Blight Resistance Fusarium verticillioides QTL Mapping Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FUSARIUM QUANTITATIVE TRAIT LOCI MAPPING TRITICUM AESTIVUM
CAIXIA LAN Ravi Singh (2023, [Artículo])
QTL mapping Kernel-Related Traits Putative Candidate Gene KASP Markers CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA KERNELS QUANTITATIVE TRAIT LOCI MAPPING TRITICUM AESTIVUM SINGLE NUCLEOTIDE POLYMORPHISM
Lesley Boyd sridhar bhavani Cristobal Uauy Annemarie Fejer Justesen Mogens Hovmoller (2022, [Artículo])
Cereals and Grains Pathogen Diversity Puccinia f. sp. tritici Stripe Rust Yellow Rust CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREALS FIELD CROPS FUNGI PATHOGENICITY RUSTS TRITICUM AESTIVUM
Introgresión del gen de resistencia a la roya del tallo Sr 47 en la variedad de trigo cirno C2008
JULIO HUERTA_ESPINO Susanne Dreisigacker (2023, [Artículo])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AEGILOPS SPELTOIDES PUCCINIA GRAMINIS TRITICUM TURGIDUM STEM RUST
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