Replication Data for: Divergence with gene flow is driven by local adaptation to temperature and soil phosphorus concentration in teosinte subspecies (Zea mays parviglumis and Zea mays mexicana)

Jonas Aguirre Brandon Gaut Juan P. Jaramillo_Correa Maud Tenaillon Felipe García Oliva Sarah Hearne Luis Eguiarte (2019, [Dataset])

Dartseq data were used to analyze the demographic history of teosintes, and also identify SNPs under selection to bioclimatic and soil variables (pH, phosphorus and nitrogen concentration in the soil).

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Prediction of multiple-trait and multiple-environment genomic data using recommender systems

Osval Antonio Montesinos-Lopez Jose Crossa Ravi Singh Suchismita Mondal Philomin Juliana (2017, [Dataset])

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, while researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although statistical models are usually mathematically elegant, they are also computatio nally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: a) item-based collaborative filtering (IBCF; method M1) and b) the matrix factorization algorithm (method M2) in the context of multiple traits and multiple environments. The IBCF and matrix factorization methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique (method M1) was slightly better in terms of prediction accuracy than the two conventional methods and the matrix factorization method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment-trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

TAMASA Ethiopia. Performance trial dataset for validating maize nutrient management recommendations, 2016 season.

MESFIN KEBEDE DESTA Tolera Abera Goshu (2017, [Dataset])

Performance trials (N=52) in two zones (West Shewa and Jimma) in Ethiopia. Trials comprise four nutrient management treatments, namely control with zero fertilizer ; and three fertilizer recommendations to achieve the same target yield based on regional fertilizer recommendation, a Nutrient Expert (IPNI software) based recommendation and a soil-test NE based recommendation. Trials were conducted on-farm with four plots per farm. Observations include biomass and grain yields, as well as pre-sowing pH, nitrogen and phosphorus levels. Some N & K data are missing.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

47th 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

Genomics and Genebank Workshop on the use of genotypic data to rationalize genebank collections: diversity gaps and duplicates

Thomas Payne Sarah Hearne Michael Abberton Peter Wenzl (2017, [Dataset])

Genotyping and re-sequencing are among a suite of tools used to enable rapid and cost-effective tool to study genetic diversity. This workshop will explore its use in the genetic curation of accessi ons within and between collection(s). With such information across global collections, it becomes possible identify the truly unique accessions across all of our gene banks, identify possible gaps in the global collection and enable more targeted access to genetic diversity. The workshop will discuss presentations from each participant on use cases. Lessons learned from initiatives such as CIMMYT’s Seeds for Discovery for maize and wheat, and CIP’s investigations on sweet potato and at IITA and CIAT for cassava will be considered.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Zero-Tillage adoption and its welfare impacts at the farm household level

Alwin Keil (2016, [Dataset])

The purpose of the study was (1) to assess the performance of ZT wheat as compared to conventional-tillage wheat in farmers' fields in six CSISA target districts in Bihar; (2) to assess farmers’ resource endowment, risk exposure, risk preferences, and risk management practices; (3) based on (2), to identify influencing factors of farmers' awareness and adoption of ZT in wheat, including social network effects.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

FAO-SIAC Estimating CA adoption in Sinaloa, Mexico (calibration sites)

Kai Sonder Guillaume Chomé (2017, [Dataset])

Use of remote sensing based radar images for zero tillage detection in Sinaloa, Mexico.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Pathways to sustainable intensification in Eastern and Southern Africa - Mozambique 2013

Paswel Marenya Menale Kassie Fulgence Mishili Gideon Obare (2016, [Dataset])

The Adoption Pathways project was part of a portfolio of projects that has contributed to the broader theme of sustainable intensification research led by the International Maize and Wheat Improvement Center (CIMMYT) and made possible by the contribution of several teams from national and international research groups brought together by funding from the Australian Centre for International Agricultural Research (ACIAR). The project was undertaken in the five Eastern and Southern African countries of Ethiopia, Kenya, Malawi, Mozambique and Tanzania. 1. Gender disaggregated three wave panel data set (2010/11, 2013), building on a legacy dataset collected under a related ACIAR funded project (SIMLESA) is now being developed covering close to 3500 households in each data wave across the five project countries. The 2015/16 data will be available in due course. 2. Several empirical evaluations of the gender gaps in technology adoption, food security and market access have been completed and published. 3. These results have been shared in various policy forums including but not limited to annual project meetings. In order to achieve its full impact in the coming years; we propose that new projects and initiatives based on the work of the Adoption Pathways project be established. These should focus on capacity building for the analysis of panel datasets, continued work on studying intrahousehold input allocation and sharing of agricultural output and scaling up the findings from this project to influence next generation of sustainable agriculture policies.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Pathways to sustainable intensification in Eastern and Southern Africa - Malawi 2010

Paswel Marenya Menale Kassie (2016, [Dataset])

Using purposive sampling, the central and Southern regions were selected. The Central region transcends from high to low altitude while the Southern region is predominantly a low altitude area. Maize is extensively grown in both regions with groundnuts and haricot beans being the dominant legume crops. The southern region however has pigeon pea as the most dominant legume. Purposive sampling in consideration of maize production potential and the agro-ecological conditions was then used in combination with stratified sampling to arrive at 6 districts; 5 in the Central region (Lilongwe, Kasungu, Mchinji, Salima and Ntcheu) and; Balaka in the Southern region. Three districts in the Central region (Lilongwe, Kasungu and Mchinji) fall under high potential area while the remaining two (Salima and Ntcheu) and Balaka in the southern region fall under a low potential area. Multi-stage random sampling combined with probability to proportional size sampling methods were then used to get 66 Extension Planning Areas (EPA’s), 91 Sections and 234 villages. The same procedure was again used to get 895 households from the 235 villages. Please refer to baseline reports include with the data. Please refer to baseline reports include with the data.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

29th Semi-Arid Wheat Screening Nursery

Ravi Singh Thomas Payne (2017, [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