This dataset includes experimental data collected from a long-term field experiment conducted over 20 years (1999-2019) in a semiarid region of central Mexico. The study focused on evaluating the effects of various soil management practices—including the use of permanent beds, crop residue management, and tied ridges—on the yield and profitability of maize (Zea mays L.) and wheat (Triticum aestivum L.) under rainfed conditions. The dataset includes: Grain yield data for maize and wheat, Biomass production measurements, Information on soil management practices applied during the experiment.
We investigated the effect of conservation agriculture based cropping systems in the yield and profitability of maize in a semiarid region of central Mexico, under rainfed conditions. The database contains yield data, production cost and profitability for maize (Zea mays L.), bean (Phaseolus vulgaris L.), triticale (× Triticosecale Wittmack) and oats (Avena sativa) in two field experiments and 17 farmer's fields.
El estudio examina el impacto del cambio climático en el cultivo de maíz en México para el período de los años 2050. Se identifica una tendencia generalizada hacia una disminución en los rendimientos debido al aumento de temperaturas y la reducción de precipitaciones, lo que podría amenazar la seguridad alimentaria y económica del país. Se utilizó un modelo de cultivos integrado en una suite de modelos para simular el crecimiento del maíz bajo diferentes condiciones climáticas y se aplicaron dos modelos globales de cambio climático para estimar los impactos en los rendimientos. Los resultados indican que la mayoría de los estados mexicanos sufrirán pérdidas en los rendimientos de maíz, con las mayores pérdidas pronosticadas bajo un escenario más seco. Se concluye que es crucial iniciar la planificación y actividades de adaptación para contrarrestar los efectos negativos del cambio climático en el cultivo de maíz en México, aprovechando las áreas con mejores condiciones y desarrollando prácticas agrícolas adecuadas. Se recomienda la integración de más modelos climáticos y tecnologías de adaptación en futuras investigaciones para una comprensión más completa de los efectos del cambio climático en la agricultura mexicana.
The data were collected for the publication: "Does leaving crop residues in the field lead to greater frost damage in wheat and barley under conservation agriculture?" The dataset contains data from three experiments conducted to evaluate if leaving more residue in the field is associated with higher levels of frost damage. Farmers in the Bajio had indicated that leaving more crop residue in the field when sowing barley in permanent raised beds is associated with higher frost damage, which is an occasional problem in the region. To evaluate whether this is really the case frost damage was evaluated in a 1) a 2 year on farm experiment in San Juan del Rio, Queretaro, Mexico where barley was sown with different levels of residue retention, 2) An experiment with different types of tillage and levels of residue on the Sanjaya Rajaram station in Metepec, Mexico state, Mexico, where due to the high elevation frost damage was guaranteed to occur and 3) An comparison of yield in side by side comparison of conservation agriculture and conventional agriculture grown during the winter season across Mexico to assess whether conservation agriculture is associated with lower yields which could be indicative of a real problem.
New version of maize mega environments based upon new wordlclim 2.1 data. Based on Bellon et al. 2005 https://doi.org/10.1016/j.foodpol.2005.09.003 Supersedes previous version
In 2019, we conducted a survey through face-to-face interviews with farmers in the El Bajío region of Guanajuato using the GeoODK mobile phone app, an open-source tool. A database (2014–2019) of presumably active farmers in the innovation hub containing their corresponding municipalities was used to select the respondents in two stages. First, respondents that were connected to the hub were randomly selected from the mentioned database. In some cases, we learned that the farmer passed away or could not be reached after several attempts. Then, another farmer who connected to the innovation hub in the same municipality was surveyed. Two municipalities were removed from the sampling frame due to security issues resulting from increased drug-cartel activity in the region. The second stage of the sampling comprised farmers not connected to the innovation hub, in the same municipalities, approached at meeting points (while they were waiting in a queue) or before events in the region (e.g., association, presentation of agricultural products, etc.). Around one out of two non-connected farmers who were approached agreed to take the survey. Therefore, a similar number of non-connected farmers were approached and interviewed in the same municipalities. A total of 394 responses were obtained (205 from MasAgro-connected farmers and 189 from non-connected farmers), with no missing values. We obtained prior informed verbal consent from all respondents, and no personal data were gathered. Farmers were surveyed using standardized questions based on literature with sections covering general information and demographic characteristics, their history of use of mobile phones to access agronomic data and recommendations, and questions of the model used. Each construct was based on three to five items, as recommended. A total of 30 measurement items adapted from prior studies were carefully rephrased in the context of an agriculture-related mobile-phone app, with response selections on a seven-point Likert scale ranging from “Totally disagree” (1) to "Totally agree" (7). To investigate incentives for the farmers to use an agricultural advisory app in which they share their data, a Discrete Choice Experiment (DCE) was designed, presenting respondents with a choice between two or more alternatives described by pre-established attributes. that simulate different configurations which the AgroTutor app could take when launched. Six attributes were identified (data input requirements, data-usage cost, access to trainings, access to shared data, replacing extension service visits). An efficient design with 24 alternatives was chosen and arranged into 12 choice sets with a comparison of 2 alternatives. These were then assigned into two blocks of six choice, respondents randomly allocated to the two blocks.
The study shows the database made from interviews conducted in Texcoco, Mexico during April, May and June 2019. The objective of the study was to understand consumer preferences and consumption and purchasing habits for white and blue maize tortillas.
The file contains the coordinates of 399 soil samples collected in 2016, 2022, 2023, and 2025 from farmers' fields in the state of Zacatecas, Mexico, along with the corresponding soil analysis data. The soil samples were analyzed by Fertilab (www.fertilab.com.mx). Coordinates are provided to two decimal places. If full-precision GPS coordinates are required for research purposes, please contact CIMMYT.
The file contains the coordinates of 57 soil samples collected in 2019 from farmers' fields in the state of Yucatan, Mexico, along with the corresponding soil analysis data. The soil samples were analyzed by Fertilab (www.fertilab.com.mx). Coordinates are provided to two decimal places. If full-precision GPS coordinates are required for research purposes, please contact CIMMYT.
