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

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

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

9th Wheat Yield Collaboration Yield Trial

Matthew Paul Reynolds Carolina Saint Pierre (2022, [Dataset])

The WYCYT international nurseries are the result of research conducted to raise the yield potential of spring wheat through the strategic crossing of physiological traits related to source and sink potential in wheat. These trials have been phenotyped in the major wheat-growing mega environments through the International Wheat Improvement Network (IWIN) and the Cereal System Initiative for South Asia (CSISA) network, which included a total of 136 environments (site-year combinations) in major spring wheat-growing countries such as Bangladesh, China, Egypt, India, Iran, Mexico, Nepal, and Pakistan.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Bayesian linear regression near infrared spectroscopy (NIR) to predict provitamin A carotenoids content in maize breeding programs

Jose Crossa Thanda Dhliwayo THOKOZILE NDHLELA natalia palacios rojas (2021, [Dataset])

Vitamin A deficiency (VAD) is a public health problem worldwide. For countries with a high per capita consumption of maize, breeding varieties with higher provitamin A carotenoid content than normal yellow maize — biofortification — can be a viable strategy to reduce VAD. Selection for provitamin A carotenoid content uses molecular markers and phenotypic data generated using expensive and laborious wet lab analyses. Near-infrared spectroscopy (NIRS) could be a fast and cheap method to measure carotenoids. This dataset contains carotenoid and NIRS data from 1857 tropical maize samples used as a training set to predict provitamin A carotenoid content of an independent set of 650 tropical maize samples using Bayesian linear regression models. The datasets contain information about specific carotenoids measured and the NIRS values measured at different wavelengths. The results of the analysis are described in the accompanying article.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

22nd Karnal Bunt Screening Nursery

Ravi Singh Thomas Payne (2022, [Dataset])

The Karnal Bunt Screening Nursery is a single replicate nursery that contains diverse spring bread wheat (Triticum aestivum) germplasm adapted to ME1 (Optimally irrigated, low rainfall environment) with total 50-100 entries and white/red grain color.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Daily wheat canopy temperature and meteorological data for IWIN locations

Carlo Montes Urs Schulthess Azam lashkari (2021, [Dataset])

Dataset of daily canopy temperature and meteorological data from the ECMWF’s AgERA5 product for the period 1979 though 2020, and for 785 points belonging to the International Wheat Improvement Network (IWIN). Wheat canopy temperature was estimated from a linear model using maximum air temperature, vapor pressure deficit, and solar radiation as inputs. The model was calibrated using multiple measurements of wheat canopy temperature.

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