CIMMYT Research Data & Software Repository Network
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Data for: Hermetic bags minimize postharvest loss during at least four successive cycles of storage in Mexican highlands
No full textCIMMYT implemented a study at its station in Texcoco to compare the effectiveness of 5 different storage technologies in minimizing grain loss during four consecutive storage cycles. In each storage cycle, the conventional practice of farmers in the area, polypropylene bag, was compared to four hermetic plastic bags from three different brands ((1) GrainPro® Hermetic Bag Premium TM Zipper (HBZ), (2) GrainPro® Hermetic Bag Premium TM Twist & Tie (HBT), (3) Ecotact 80 Multilayered Hermetic Storage Bag (HEC), (4) ZeroFly® Hermetic Storage Bag (ZFLY)) and silage plastic bag (an alternative low-cost plastic bag used as hermetic technology). The same experiment was repeated during four cycles to evaluate how each technology maintains its performance in minimizing storage loss. After the first storage cycle, the number of holes in each bag due to insect activities was counted. The data collected during each storage cycle included (1) characteristics of the storage cycle, including the crop and variety evaluated; (2) storage technologies evaluated; (3) grain damage, percentage of insect-damaged grain and weight loss; (4) the number of holes per bag
Replication Data for: Mexico's maize seed production and sales, 2011-2019
No full textThis dataset contains variety-level seed production and sales data of 297 public and private maize seed producers in Mexico during the period 2011-2019. The dataset was compiled using four different sources. The first is the MasAgro seed marketing survey, administered from 2013 to 2019 to MasAgro affiliated seed companies to monitor their seed sales and the uptake of new MasAgro hybrids. The number of companies that responded to the seed marketing survey each year was: 2013 (n=29), 2014 (n=24), 2015 (n=39), 2016 (n=42), 2017 (n=42), 2018 (n=52), 2019 (n=61). The second is the CIMMYT germplasm impact survey, a cross-sectional survey applied to thirty-nine MasAgro seed companies in 2015, to collect information of their 2014 seed sales, seed origin, variety type, variety colour, and first year of introduction to the market. The third is the MasAgro product portfolio survey, responded by thirty-one MasAgro seed firms in 2020 to cover existing information gaps, specially the 2011-2012 seed sales, company size (seed sales and number of employees) and each product’s first year of introduction to the market. All surveys were handled via e-mail by the MasAgro maize direction in the CIMMYT Global Maize Program. However, to protect the confidentiality of seed companies, all personal and commercial information on private companies collected through email surveys was made confidential. These data were complemented with official maize seed production statistics provided by the National Seed Inspection and Certification Agency (SNICS). The final dataset contains detailed seed production and sales figures of the entire maize seed industry in Mexico for the period 2011-2019
Round II: Gender-disaggregated household survey data on rural women empowerment and technological change in wheat, Madhya Pradesh
No full textThis dataset was generated as part of a research project that aimed to identify relevant gender considerations associated with wheat varietal development and the modifications required in wheat seed value chains in order to ensure inclusive diffusion of varieties and faster varietal turnover. Understanding the role that women play in agricultural production decisions is now widely considered as a pre-requisite to attain food security and alleviate poverty. There have been studies conducted on gender-sensitive breeding on a number of crops, however there are no evidence with respect to wheat in India. The role of gender-sensitive seed and information networks, which could facilitate the spread of varietal technologies ensuring social inclusiveness, is also rarely examined. The lack of control of women over the benefits from participation in value chains and gender discrimination in access to complementary inputs such as credit could be the reasons for not carrying out such analysis. However, when technology interventions do not capture gender-specific preferences for traits of varieties and dissemination networks, intra-household disparities in workloads and incomes persist or even worsen over time. This could also result in a lower rate of adoption by farm households. The study was conducted in the wheat growing tracts of Madhya Pradesh, with the the following research outputs expected.
1. Gender-specific farmer preferences for (a) wheat varietal traits and (b) attributes of seed and information networks are elicited.
2. Solutions to meet heterogeneous demand through inclusive delivery of improved wheat varieties among men and women farmers are identified and the associated transaction costs are estimated.
The empirical part of this study was conducted in three districts of Madhya Pradesh, India – Jabalpur, Mandla and Damoh – where one round of farm household survey and focus group discussions had been already completed one year ago.
In 2018, a first-round of farm household survey was conducted among 400 households in Madhya Pradesh (Dataset Persistent ID: hdl:11529/10548897). We interviewed both male and female heads (i.e., a total of 800 interviews). Questions were asked on women’s role in decision making and their involvement in farm-household activities. In addition to farm household surveys, 60 sex-specific focus group discussions were conducted with male and female farmers. The results revealed that the varietal turnover rate in wheat is significantly low in this region, with most farmers cultivating age-old varieties such as Lok 1.
The same farm households were interviewed in 2018, to form the current dataset. The aim was to better understand their preferences for wheat varietal traits (e.g., early maturing; suitability for chapatti making, drought tolerance etc.). Choice experiments and contingent valuation approaches will be used to elicit farmer preference for varietal attributes. The elicited preferences will be explained using data from the 2018 survey
Analysis of Household-Level Survey Data: Farm Characteristics and Resource Allocation in Three Regions of Bangladesh (2023)
No full textDataset processed from a household-level survey to describe the main farm characteristics, production, and resource allocation in two municipalities across three regions of Bangladesh: North (Dinajpur, Nilphamari, Rangpur), West (Nawabganj, Rajshahi), and South (Barguna, Barisal, Patuakhali). Data was collected between December 2022 and June 2023
Analysis of Household-Level Survey Data: Farm Characteristics and Resource Allocation in Nepal (2023)
No full textDataset processed from a household-level survey to describe the main farm characteristics, production, and resource allocation in two municipalities across three regions of the country: Surkhet (Gurbhakot) and Khotang (Tuwachung) districts. Data was collected between March and June 2023
Clim2Agri version 1.0
No full textClim2Agri is a set of data processing tools (Clim2Agri) that allow the agricultural research and development community to simply and efficiently access data from open access platforms to be used in applications such as modeling or analysis of observations was generated. Clim2Agri is a Python-based application allowing the extraction and subsetting of agriculturally-relevant climate and land surface data from multiple gridded products (e.g., atmospheric reanalysis, satellite-derived products), from multiple formats (e.g., netCDF4, HDF), and their transformation into formats that are required by the agriculture research and crop modeling community (e.g., csv, txt)
Replication Data for: Risk aversion, impatience, and adoption of conservation agriculture practices among smallholders in Zambia
No full textMore than 60% of Zambia's population lives in rural areas and relies on rain-fed agriculture, with smallholder farmers playing a key role in food production. However, their dependence on the climate makes them vulnerable. It is essential to sustainably increase food production to feed a growing population and address climate change. Sustainable Intensification Practices (SIPs) are a solution that increases productivity without harming the environment. Examples of SIPs include Conservation Agriculture (CA), agroforestry, and the use of improved fertilizers. Although SIPs have benefits such as improving soil fertility and increasing productivity, their adoption is low due to obstacles like competition for crop residues, credit and labor constraints, and technical limitations. Additionally, farmers' risk and time preferences influence the adoption of these practices.
To better understand these factors, data were collected from two household surveys conducted in nine districts of Zambia, located in the Eastern (Chipata, Lundazi and Sinda), Northern (Kasama, Mbala and Senga Hill), and Southern provinces (Choma, Mazabuka and Monze), where CIMMYT promotes various SIPs. The surveys were carried out in specific communities using the mother and baby trial approach of the SIFAZ project. Households of farmers hosting mother and baby trials, as well as other farmers in each camp, were randomly sampled. In total, 678 households were surveyed in 2021 and 646 in 2022, achieving a balanced panel of 1292 observations. Adoption refers to the use of CA practices on non-demonstration and non-trial plots that are not supported by external projects. Ethical approval was obtained for both surveys.
This study in Zambia uses this data to analyze how risk and time preferences affect the adoption of CA-based practices, concluding that risk aversion and impatience reduce the likelihood of adoption
CIMMYT-Asia Maize Regional On-Station (Stage 4) and On-Farm (Stage 5) Trials: Results of the 2022-2023 Seasons and Product Announcement
No full textNew and improved maize hybrids, developed by the CIMMYT Global Maize Program, are available for uptake by public and private sector partners, especially those interested in marketing or disseminating hybrid maize seed across tropical regions of South Asia and similar agro-ecologies in other regions.. Following a rigorous trialing and a stage-gate advancement process culminating in the 2023 Stage 5 trials, CIMMYT advanced a total of six new elite maize hybrids in Asia in 2024 across the SADHT, SAWLDT, and SADT product profiles. Phenotypic data collected in Stage 4 and Stage 5 trials for the selected hybrids as well as information about the trial sites are provided in this dataset. These trials were conducted through a network of partners, including NARES and private seed companies, in Asia, under various management and environmental conditions
Soil properties predicted from mid-infrared spectral (MIRS) analysis of soil samples collected in 2022 before establishing on-farm trials on yield response to lime rates in Rwanda
No full textSelected soil properties were predicted from 104 topsoil samples subjected to spectral analysis (MIRS).
A subset of samples were also subjected to wet chemistry analysis, and results were used to calibrate a machine-learning algorithm developed by the International Centre for Research in Agroforestry (ICRAF) in Kenya. Coordinates were truncated to protect farmer's privacy.
Unless specified, all properties were predicted. When calculated from other predicted properties, the variable name contained the string: "Estimated".
A link is provided to match terms used in the "terminag" GitHub (https://github.com/reagro/terminag/)</p
Replication Data for: Efficient Arabinoxylan Assay for Wheat: Exploring Variability and Molecular Marker Associations in Wholemeal and Refined Flour
No full textThis dataset is derived from a study focused on developing an efficient method for arabinoxylan quantification, called PentoQuant. It includes phenotypic and molecular characterization data from 606 bread wheat samples developed through the spring bread wheat breeding program. The dataset comprises total and water-extractable arabinoxylan content values measured using the PentoQuant protocol. Furthermore, it incorporates results obtained from analyzing the same 606 lines with four molecular markers associated with two major QTLs for arabinoxylan content variation in wheat, located on chromosomes 1B and 6B