International Durum Yield Nurseries are replicated yield trials designed to measure the yiel d 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.
The 2016 Agronomy Panel Survey (APS) for Tanzania is the first wave of a yearly farm household panel dataset collected under the BMGF-funded project Taking Maize Agronomy to Scale in Africa (TAMASA), in collaboration with the Sustainable Intensification Innovation Lab (SIIL). The APS is a detailed farm household survey with agronomic, yield and soils components for a focal field. This is a yearly panel survey, i.e. data are collected on the same households and fields every year for the duration of the project. The purpose of the data collection is severalfold: 1. To better document spatio-temporal variability in agronomic management and yield outcomes 2. To facilitate research on a. drivers of yield outcomes (i.e. role of alternative agronomic practices), and b. the determinants of farmer decision-making (i.e. in adopting particular agronomic practices) that contribute to observed yield outcomes 3. To test the hypothesis that farm-level socioeconomic data adds value to our understanding of yield outcomes (and, thus, our ability to predict such outcomes in the future, using geospatially explicit approaches) 4. To serve as a baseline for the evaluation of site-specific nutrient management tools, using randomized control experimental approaches, combined with econometric analysis of panel survey data
Bread wheat breeding lines from yield and elite yield trials are analyzed annually for grain quality traits at the Wheat Chemistry and Quality Laboratory of CIMMYT. The analysis done are the following: grain morphology (test weight and thousand kernel weight), grain hardness and protein content, flour yield, flour protein content, SDS-sedimentation test, mixograph, alveograph and bread-making. Based on this data breeding lines combining good agronomic performance and desirable processing and end-use quality are selected and move forward in the breeding process.
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.
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.
Replicated crop-cuts and related agronomy data for maize from 142 farmers' fields in Southern, Eastern and Northern Zones in 2014/2015 season. The soils data from these fields can be found here.
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.
Conservation agriculture has been tested and out scaled for over 60 years in rural areas of Mexico, however the rate of adoption and dis adoption, as well as the current area under CA is unknown. Estimates range between 50,000 ha and over 800,000 ha depending on the source. Studies and surveys in several states where CA was propagated in the past show an unclear picture. Tillage and crop residue detection based on remote sensing data has been successfully tested since the mid-1980s and seems a valid technology to essay larger areas or countries with minimal cost based on freely available satellite image sources. A promising approach utilizing radar imagery from Sentinel 1A developed in Belgium for tillage recognition was chosen for the current study. Radar imagery having the advantage of not being affected by clouds or haze. In parallel work being done in the Indo Gangetic Plains as a collaboration between the Université catholique de Louvain and CIMMYT images for areas in the states of Sonora and Sinaloa in Northern Mexico as well as Guanajuato in Central Mexico were acquired from ESA and analyzed. Initial results for Sinaloa show an average accuracy of 94% for predicting tillage type. Current limitations of widespread utilization of the technology include the need for availability of spatial data delineating field boundaries in order to clearly identify cropped and non cropped areas as well as the association of crop management data such as irrigation timings and crop types. Some of this is expected to improve in the near future with big data and crowd sourcing applications for field boundary detection. The results from the associated study in India indicate however that there is good potential to utilize this also in areas with smaller field sizes and utilizing Sentinel 2 data for segmentation of landscapes to substitute detailed field boundary data.
