Kenya Rural Household Panel Survey - Household and maize data 2010 & 2013

Kevin Oluoch Hugo De Groote Zachary Gitonga (2022, [Dataset])

Data from two CIMMYT and KALRO household surveys representative of six maize production areas or agroecological zones in Kenya. The surveys were conducted in 2010 and 2013 collected data on farmer demographics, adoption of improved technologies and practices, marketing, access to agricultural information, and farmer adaptation to climate change.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Results from rapid-cycle recurrent genomic selection in spring bread wheat

Susanne Dreisigacker Leonardo Abdiel Crespo Herrera Alison Bentley Jose Crossa (2022, [Dataset])

Empirical studies of early generation genomic selection strategies for parental selection or population improvement are still lacking in wheat and other major crops. We show the potential of rapid-cycle recurrent GS to increase genetic gain for grain yield in wheat. We show a consistent realized genetic gain for grain yield after three cycles of recombination of bi-parental F1’s, when summarized across two years of phenotyping.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

GBS genotypic data for a JAAS spring wheat panel

Xinyao He Pawan Singh (2022, [Dataset])

GBS genotypic data for a panel of 265 spring wheat lines from JAAS-China, CIMMYT and other countries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: A comparison between three machine learning methods for multivariate genomic prediction using the Sparse Kernels Methods (SKM) library

Osval Antonio Montesinos-Lopez Pedro César Santana Mancilla Jose Crossa (2022, [Dataset])

Genomic selection (GS) provides a new way for plant breeders select the best genotype. It draws upon historical phenotypic and genotypic information for training a statistical machine learning model which is used for predicting phenotypic (or breeding) values of new lines for which only genotypic information is available. Many statistical machine learning methods have been proposed for this task, but multi-trait (MT) genomic prediction models are preferred because they take advantage of correlated traits to improve the prediction accuracy. This study contains six datasets that were used to compare the prediction performance of three MT methods: the MT genomic best linear unbiased predictor (GBLUP), the MT partial least square (PLS) and the multi-trait Random Forest (RF). The data come from groundnuts, rice, and wheat. The accompanying article describes the results of the analysis.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Full list of wheat genotypes evaluated for wheat blast resistance

Pawan Singh Xinyao He (2023, [Dataset])

The list includes wheat genotypes that have been evaluated for wheat blast resistance with data available publicly (database links are provided). The list is to be updated regularly

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Projecting Wheat demand in China and India for 2030 and 2050: Implications for Food Security

Khondoker Mottaleb (2023, [Dataset])

Implications for Food Security

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

20th High Temperature Wheat Yield Trial

Ravi Singh Carolina Saint Pierre (2022, [Dataset])

CIMMYT annually distributes improved germplasm developed by its researchers and partners in international nurseries trials and experiments. The High Temperature Wheat Yield Trial (HTWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to Mega-environment 1 (ME1) which represents high temperature areas.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

2022 CIMMYT Maize Latin America Product Announcement for Product Profile LA-PP2B / Anuncio de Productos de Maíz de CIMMYT en Latinoamérica por el Perfíl de Productos LA-PP2B

Thanda Dhliwayo Felix San Vicente Garcia Alberto Antonio Chassaigne Ricciulli natalia palacios rojas XUECAI ZHANG Michael Olsen Aparna Das Prasanna Boddupalli (2022, [Dataset])

New and improved maize hybrids, developed by the CIMMYT Global Maize Program, are available for uptake by public and private sector partners, especially those interested in marketing or disseminating hybrid maize seed across Latin America and similar agro-ecological zones. Following a rigorous trialing and a stage-gate advancement process culminating in the 2020 Stage 5 trials, CIMMYT advanced a total of one new elite maize hybrid in Latin America in 2022 for product profile LA-PP2B. Phenotypic data collected in Stage 4 and Stage 5 trials for the selected hybrid as well as information about the trial sites are provided in this dataset. These trials were conducted through a network of partners, including NARS and private seed companies, in Mexico under various management and environmental conditions. Nuevos y mejorados híbridos desarrollados por el Programa Global de Maíz del CIMMYT se ponen a disposición de instituciones del sector público y privado, especialmente para aquellas instituciones colaboradoras interesadas en la comercialización y diseminación de semilla de maíz en Latinoamérica o en zonas agroecológicas similares. Después de un riguroso proceso de evaluación de germoplasma en distintas etapas que culminó en ensayos de evaluación de híbridos en etapa cinco, el CIMMYT avanzó un nuevo híbrido élite en Latinoamérica en 2022 por el perfíl de producto LA-PP2B. Datos fenotípicos recopilados en los ensayos en etapa cuatro y cinco, además de información sobre los sitios están incluidos en este conjunto de datos. Estos ensayos fueron conducidos bajo diferentes condiciones de manejo y ambientes a través de redes colaborativas con instituciones de investigación pública y empresas semilleras de Latinoamérica.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

29th High Rainfall Wheat Yield Trial

Ravi Singh Thomas Payne (2022, [Dataset])

CIMMYT annually distributes improved germplasm developed by its researchers and partners in international nurseries trials and experiments. The High Rainfall Wheat Yield Trial (HRWYT) contains very top-yielding advance lines of spring bread wheat (Triticum aestivum) germplasm adapted to high rainfall, Wheat Mega-environment 2 (ME2HR).

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Phenotypic data of HIBAP I panel under yield potential and heat stress conditions

Gemma Molero Benedict Coombes Ryan Joynson Francisco Pinto Francisco Javier Pinera-Chavez Carolina Rivera-Amado Anthony Hall Matthew Paul Reynolds (2022, [Dataset])

Phenotypic data of HIBAP I panel evaluated under yield potential and heat stress conditions during Obregon wheat seasons 2015-16 and 2016-17. Combined data across years per environment. The HIBAP I panel is comprised of 149 high biomass spring wheat lines of a variety of elite and exotic backgrounds. It was demonstrated how strategic integration of exotic material significantly increases yield under heat stress compared to elite lines, with no significant yield penalty under favourable conditions. Through genome wide association analysis three marker trait associations were revealed. The yield increase was associated with lower canopy temperature. An Aegilops tauschii introgression was identified as the most significant of these associations. Publicly available sequencing data used in this study is available at the European Nucleotide Archive (ENA). More information about the location of sequencing data can be found in the section 'Data availability' of the referenced manuscript at https://doi.org/10.1101/2022.02.09.479695.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA