Replication Data for: Multi-trait Bayesian decision for parental selection

Jose Crossa Fernando Henrique Toledo Paulino Pérez-Rodríguez (2020, [Dataset])

The files included in this study contains the data used with three promising multivariate loss functions: Kullback-Leibler (KL); the Energy Score; and the Multivariate Asymmetric Loss (MALF); to select the best performing parents for the next breeding cycle in two extensive real wheat data sets.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

1st Stress Adapted Trait Yield Nurseries

Matthew Paul Reynolds Thomas Payne (2020, [Dataset])

Within the framework of SATYN, two types of nurseries are produced: SATYN series with odd numbers are lines for drought-stressed areas, and SATYN series with even numbers are lines for heat stress conditions. These nurseries 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

39th 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 Durum Yield Nursery

Karim Ammar Thomas Payne (2020, [Dataset])

International Durum Yield Nurseries are replicated yield trials designed to measure the yield potential and adaptation of superior CIMMYT-bred spring durum wheat germplasm that have been developed from tests conducted under irrigation and induced stressed cropping conditions in northwest Mexico. These materials have been subjected to numerous diseases (leaf, stem and yellow rust; Septoria tritici blotch) and varied growing environments. It is distributed to 70 locations, and contains 50 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

36th International Durum Screening Nursery

Karim Ammar Thomas Payne (2020, [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

29th High Rainfall Wheat Screening Nursery

Ravi Singh Thomas Payne (2019, [Dataset])

CIMMYT annually distributes improved germplasm developed by its researchers and partners in international nurseries trials and experiments. The High Rainfall Wheat Screening Nursery (HRWSN) contains spring bread wheat (Triticum aestivum) germplasm adapted to high rainfall areas (Mega-environment 2).

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, [Dataset])

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.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

23rd High Rainfall Wheat Screening Nursery

Ravi Singh Thomas Payne (2019, [Dataset])

CIMMYT annually distributes improved germplasm developed by its researchers and partners in international nurseries trials and experiments. The High Rainfall Wheat Screening Nursery (HRWSN) contains spring bread wheat (Triticum aestivum) germplasm adapted to high rainfall areas (Mega-environment 2).

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Assessing the Adoption Dynamics of Zero-tillage (ZT) Wheat and the Growth Dynamics of Related Custom Hire Services in Bihar. Survey 2: ZT Service Provision as a Business Opportunity

Alwin Keil Archisman Mitra (2018, [Dataset])

While there existed some empirical evidence of the incidence of zero-tillage (ZT) adoption in wheat – rice farming systems in Punjab, in 2013 no such assessment existed for Bihar, one of the major focal points of CSISA activities in the second phase. In Bihar, a relatively extensive network of ZT service providers exists, and the technology is probably relatively widely known, making a study which is based on a random sample of ZT service providers, ZT adopters, and non-adopters of the technology feasible. This kind of ground-truthing of the potential of ZT service provision as a business model and the adoption and impacts of the technology at the farm household level is urgently needed in view of a credible quantitative assessment of the impact of CSISA with respect to one of its major supported technologies. The results can help to more effectively target the promotion of ZT and the provision of ZT services and related training activities. The study consists of two interlinked panel household surveys, one focusing on ZT adoption and its welfare impacts at the farm household level (Survey 1) and the other focusing on ZT service provision as a business opportunity (Survey 2). For both surveys, data were collected in two rounds, the initial survey being conducted in 2013 with a follow-up survey in 2016. The objectives of this study are: (1) to assess service providers’ resource endowment and risk preferences; (2) based on (1), and pooling data with Survey 1, identify influencing factors of engaging in ZT service provision, including influencing factors of the scale of service provision.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Osval Antonio Montesinos-Lopez Francisco Javier Martin Vallejo Jose Crossa Philomin Juliana Ravi Singh (2018, [Dataset])

The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA