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1114 research outputs found
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Wheat consumption dynamics in selected countries in Asia and Africa: Implications for wheat supply by 2030 and 2050
No full textFAOSTAT dat
Replication Data for: Elucidating the genetics of grain yield and stress-resilience in bread wheat using a large-scale genome-wide association mapping study with 55,568 lines
No full textA large-scale genome-wide association study was carried out to dissect the genetic architecture of wheat grain yield potential and stress-resilience. Based on the findings,
grain yield-associated marker profiles were generated for a large panel of 73,142 wheat lines and the grain-yield favorable allele frequencies were also determined. The marker profile data are presented in this dataset
Genotypic data for the South Asian panel with 184 lines
No full textGenotypic data for the South Asian panel with 184 lines intended for multiple diseases resistance analysi
Replication Data for: Bayesian multi-trait kernel methods for multi-environment genome based prediction
No full textIn breeding, multi-trait data can be used with different models for genomic prediction analyses. The data files associated with this dataset were used to explore Bayesian multi-trait kernel methods for genomic prediction and to compare the performance of the different analyses
Replication Data for: Measurements for multi-trait genomic-enabled prediction accuracy in multi-year breeding trials
No full textSeveral different genome-based prediction models are available for the analysis of multi-trait data in genomic selection. The supplemental files included in this dataset
provide six extensive multi-trait wheat datasets (quality and grain yield) that enable the comparison of performance of genomic-enabled-prediction when calculating the prediction accuracy using different methods. The related article describes the results of the analysis and reports that trait grain yield prediction performance is better under a multi-trait model as compared with the single-trait model
Response to early generation genomic selection for yield in wheat
No full textGenotyping-by-Sequencing data of a training set consisting of 1340 CIMMYT elite lines and a validation set including 1925 F2 individual derived from 38 crosses and 21 parents from the training set
53rd International Bread Wheat Screening Nursery
No full textThe 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
Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
No full textThe database contains data about on-farm trials with transplanted rice were conducted during monsoon (‘Aman’) season in 2016 and 2017 and winter (‘Boro’) season in 2016 to 2017 in agroecological zones (AEZs) 11 and 12 of south-west Bangladesh with ten treatments - seven herbicide-based IWM options, one mechanical weed control-based option, and two checks – farmers’ current weed control practice and weed-free, to assess effects on weed control, grain yield, labor use, and profitability
Replication Data for: Bayesian linear regression near infrared spectroscopy (NIR) to predict provitamin A carotenoids content in maize breeding programs
No full textVitamin 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
Replication Data for: Genome-based genotype × environment prediction enhances potato (Solanum tuberosum L.) improvement using pseudo-diploid and polysomic tetraploid modeling
No full textPotato breeding efficiency can be improved by increasing the reliability of selection and identifying promising germplasm for crossing. The data provided in these datasets were used to compare the prediction accuracy of genomic-estimated breeding values for several potato (Solanum tuberosum L.) breeding clones and released cultivars evaluated in three locations in northern and southern Sweden. The analysis included several traits such as tuber starch percentage and total tuber weight. Results of the analyses are reported in an accompanying journal article