TY - JOUR
T1 - Multiyear Maize Management Dataset collected in Chiapas, Mexico
AU - Trevisan, Rodrigo G.
AU - Martin, Nicolas F.
AU - Fonteyne, Simon
AU - Verhulst, Nele
AU - Dorado Betancourt, Hugo A.
AU - Jimenez, Daniel
AU - Gardeazabal, Andrea
N1 - Funding Information:
Data collection was part of the projects ``Cultivos para México - MasAgro'' and ``Strengthening market access for smallholder maize and legume farmers in Oaxaca, Chiapas, and Campeche'', supported by the Mexican Government through SADER and by the Walmart Foundation. This work was also carried out with the financial support of the CGIAR Research Programs MAIZE, CCAFS (under the project Towards a Digital Climate Smart Agriculture transformation in Latin America), and the CGIAR Platform for Big Data in Agriculture (under the community of practice Data-Driven Agronomy). The CGIAR programs are carried out with support from CGIAR Trust Fund Donors and through bilateral funding agreements. We thank the hub team (Jorge Garcia, Benancio Jimenez, Ana Laura Medina and Rodolfo Vilchis) and the network of collaborators for their invaluable help with data collection. Manuscript preparation was supported by the ACES Office of International programs at the University of Illinois.
Publisher Copyright:
© 2022
PY - 2022/2
Y1 - 2022/2
N2 - For several decades, maize (Zea mays L.) management decisions in smallholder farming in tropical regions have been a puzzle. To best balance alternative management practices' environmental and economic outcomes, an extensive dataset was gathered through CIMMYT's knowledge hub in Chiapas, a state in southern Mexico. In a knowledge hub, farmers, with the support of farm advisors, compare conventional and improved agronomic practices side-by-side and install demonstration fields where they implement improved practices. In all these fields data on on-farm operations and results is collected. The dataset was assembled using field variables (yield, cultivars, fertilization and tillage practice), as well as environment variables from soil mapping (slope, elevation, soil texture, pH and organic matter concentration) and gridded weather datasets (precipitation, temperature, radiation and evapotranspiration). The dataset contains observations from 4585 fields and comprises a period of 7 years between 2012 and 2018. This dataset will facilitate analytical approaches to represent spatial and temporal variability of alternative crop management decisions based on observational data and explain model-generated predictions for maize in Chiapas, Mexico. In addition, this data can serve as an example for similar efforts in Big Data in Agriculture.
AB - For several decades, maize (Zea mays L.) management decisions in smallholder farming in tropical regions have been a puzzle. To best balance alternative management practices' environmental and economic outcomes, an extensive dataset was gathered through CIMMYT's knowledge hub in Chiapas, a state in southern Mexico. In a knowledge hub, farmers, with the support of farm advisors, compare conventional and improved agronomic practices side-by-side and install demonstration fields where they implement improved practices. In all these fields data on on-farm operations and results is collected. The dataset was assembled using field variables (yield, cultivars, fertilization and tillage practice), as well as environment variables from soil mapping (slope, elevation, soil texture, pH and organic matter concentration) and gridded weather datasets (precipitation, temperature, radiation and evapotranspiration). The dataset contains observations from 4585 fields and comprises a period of 7 years between 2012 and 2018. This dataset will facilitate analytical approaches to represent spatial and temporal variability of alternative crop management decisions based on observational data and explain model-generated predictions for maize in Chiapas, Mexico. In addition, this data can serve as an example for similar efforts in Big Data in Agriculture.
KW - Explanatory machine learning
KW - Smallholders
KW - Sustainable intensification
KW - Tropical agriculture
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U2 - 10.1016/j.dib.2022.107837
DO - 10.1016/j.dib.2022.107837
M3 - Article
C2 - 35242900
AN - SCOPUS:85123123018
SN - 2352-3409
VL - 40
JO - Data in Brief
JF - Data in Brief
M1 - 107837
ER -