48th International Bread Wheat Screening Nursery MAS data

Susanne Dreisigacker (2017, [Dataset])

The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The distribution of these nurseries is deliberately biased toward the major spring wheat regions of the world where the diseases of wheat are of high incidence. It is distributed to 180 locations and contains 300-450 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

6th Harvest Plus Yield Trial

Govindan Velu Thomas Payne (2020, [Dataset])

The Harvest Plus Yield Trial (HPYT) contains spring bread wheat (Triticum aestivum) germplasm adapted to ME1 (Optimally Irrigated, low rainfall environment) and ME5 (Warmer area environment) environments. It has total 50 entries with 2 replications, white grain color and distributed to more than 70 locations.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

45th International Durum Screening Nursery

Karim Ammar Thomas Payne (2017, [Dataset])

International Durum Screening Nursery (IDSN) distributes diverse CIMMYT-bred spring durum wheat germplasm adapted to irrigated and variable moisture stressed environments. Disease resistance and high industrial pasta quality are essential traits possessed in this germplasm. It is distributed to 100 locations, and contains 150 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Global map of wheat mega-environments

Kai Sonder (2016, [Dataset])

Global map of wheat mega-environments. The map show twelve different mega-environments around the world.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Genome-based prediction of multiple wheat quality traits in multiple years

Maria Itria Ibba Jose Crossa Osval Antonio Montesinos-Lopez Philomin Juliana Carlos Guzman Susanne Dreisigacker Jesse Poland (2020, [Dataset])

The use of genomic prediction could greatly help to increase the efficiency of selecting for wheat quality traits by reducing the cost and time required for this analysis. This study contains data used to evaluate the prediction performances of 13 wheat quality traits under two multi-trait models [Bayesian multi-trait multi-environment (BMTME) and multi-trait ridge regression (MTR)]. Separate files are provided for each year of data. An additional supplemental data file provides R code for running the analyses as well as a table describing the Average Pearson´s correlation (APC) and mean arctangent absolute percentage error (MAAPE) for the testing sets for each dataset and trait.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

26th Semi-Arid Wheat Screening Nursery

Ravi Singh Thomas Payne (2019, [Dataset])

The Semi-Arid Wheat Screening Nursery (SAWSN) is a single replicate trial that contains diverse spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall, drought prone, semi-arid environments typically receiving less than 500 mm of water available during the cropping cycle. CIMMYT's breeding approach attempts to combine high yield potential with drought resistance for ME4. The combination of water-use efficiency and water responsive traits plus yield potential is important in drought environments where rainfall is frequently erratic across years. When rains are significantly above average in certain years, the crop must respond appropriately (water responsive) with higher yields, while expressing resistance to the wider suite of diseases that appear under more favorable conditions. Constrains including leaf, stem and yellow rusts, and Septoria spp., Fusarium spp., Pyrenophora tritici-repentis tan spot, nematodes and root rots must be considered. It is distributed to 120 locations, and contains 150-250 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

38th International Bread Wheat Screening Nursery

Ravi Singh Thomas Payne (2019, [Dataset])

The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The distribution of these nurseries is deliberately biased toward the major spring wheat regions of the world where the diseases of wheat are of high incidence. It is distributed to 180 locations and contains 300-450 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

37th International Bread Wheat Screening Nursery

Thomas Payne Ravi Singh (2019, [Dataset])

The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The distribution of these nurseries is deliberately biased toward the major spring wheat regions of the world where the diseases of wheat are of high incidence. It is distributed to 180 locations and contains 300-450 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

5th Wheat Yield Collaboration Yield Trial

Matthew Paul Reynolds Thomas Payne (2020, [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

Aerial High-Throughput Phenotyping Enabling Indirect Selection for Grain Yield at the Early-generation Seed-limited Stages in Breeding Program - data for publication

Suchismita Mondal Jose Crossa Ravi Singh Jesse Poland (2020, [Dataset])

The files contain pedigree information on lines used in the study, trait data for grain yield, spectral traits and other agronomic data and genotypic data

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA