Autor: Karim Ammar

Phenotypic and genotypic data from the CIMMYT Durum Wheat Breeding Program

Karim Ammar Carlos Guzman Susanne Dreisigacker JULIO HUERTA_ESPINO (2018)

Phenotypic data collected in on-station field trials and genotypic data for breeding materials from the CIMMYT Durum Wheat breeding program are included in this study.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Phenotypic and genotypic data from the CIMMYT Durum Wheat Breeding Program

Karim Ammar Carlos Guzman Susanne Dreisigacker JULIO HUERTA_ESPINO (2018)

Phenotypic data collected in on-station field trials and genotypic data for breeding materials from the CIMMYT Durum Wheat breeding program are included in this study.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Multi-trait multi-environment genomic prediction of durum wheat

Osval Antonio Montesinos-Lopez ROBERTO TUBEROSA MARCO MACCAFERRI GIUSEPPE SCIARA Karim Ammar Jose Crossa (2019)

In this paper we cover multi-trait prediction of grain yield (GY), days to heading (DH) and plant height (PH) of 270 durum wheat lines that were evaluated in 43 environments (location-year combinations) in Bologna, Italy. The results of the multi-trait deep learning method also were compared with univariate predictions of the genomic best linear unbiased predictor (GBLUP) method and the univariate counterpart of the multi-trait deep learning method. All models were implemented with and without the genotype×environment interaction term. We found that the best predictions were observed without the genotype×environment interaction term in the univariate and multivariate deep learning methods, but under the GBLUP method, the best predictions were observed taking into account the interaction term. We also found that in general the best predictions were observed under the GBLUP model but the predictions of the multi-trait deep learning model were very similar to those of the GBLUP model.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication data for: Increased ranking change in wheat breeding under climate change

Wei Xiong Matthew Paul Reynolds Jose Crossa Urs Schulthess Kai Sonder Carlo Montes Nicoletta Addimando Ravi Singh Karim Ammar Bruno Gerard Thomas Payne (2022)

A standard quantitative genetic model was used to examine how genotype-environment interactions have changed over the past decades from four spring wheat trial data sets. The variability of cross interactions for yield from one year to another is explained in more than 70% by climatic factors.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA