Multiyear Maize management dataset collected in Chiapas, Mexico

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cg.authorship.typesCGIAR and developing country instituteen
cg.contributor.affiliationUniversity of Illinoisen
cg.contributor.affiliationInternational Maize and Wheat Improvement Centeren
cg.contributor.affiliationInternational Center for Tropical Agricultureen
cg.contributor.affiliationUniversidad ICESIen
cg.coverage.countryMexico
cg.coverage.iso3166-alpha2MX
cg.coverage.regionAmericas
cg.coverage.regionCentral America
cg.coverage.regionLatin America and the Caribbean
cg.creator.identifierDaniel Jiménez: 0000-0003-4218-4306
cg.creator.identifierNele Verhulst: 0000-0001-5032-4386
cg.identifier.doihttps://doi.org/10.1016/j.dib.2022.107837en
cg.isijournalISI Journalen
cg.issn2352-3409en
cg.issue107837en
cg.journalData in Briefen
cg.reviewStatusPeer Reviewen
cg.subject.actionAreaResilient Agrifood Systems
cg.subject.alliancebiovciatAGRICULTUREen
cg.subject.alliancebiovciatSMALLHOLDER FARMERSen
cg.subject.alliancebiovciatSUSTAINABILITYen
cg.subject.impactAreaNutrition, health and food security
cg.volume40en
dc.contributor.authorTrevisan, Rodrigo G.en
dc.contributor.authorMartin, Nicolas F.en
dc.contributor.authorFonteyne, Simonen
dc.contributor.authorVerhulst, Neleen
dc.contributor.authorDorado Betancourt, Hugo Andresen
dc.contributor.authorJiménez, Danielen
dc.contributor.authorGardeazábal Monsalve, Andreaen
dc.date.accessioned2022-12-12T16:13:29Zen
dc.date.available2022-12-12T16:13:29Zen
dc.identifier.urihttps://hdl.handle.net/10568/125880
dc.titleMultiyear Maize management dataset collected in Chiapas, Mexicoen
dcterms.abstractFor 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.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationTrevisan, R.G.; Martin, N.F.; Fonteyne, S.; Verhulst, N.; Dorado Betancourt, H.A.; Jimenez, D.; Gardeazabal, A. (2022) Multiyear Maize management dataset collected in Chiapas, Mexico. Data in Brief 40: 107837. 7 p. ISSN: 2352-3409en
dcterms.extent7 p.en
dcterms.issued2022-02
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherElsevieren
dcterms.subjectsmallholdersen
dcterms.subjecttropical agricultureen
dcterms.subjectsustainable intensificationen
dcterms.subjectmachine learningen
dcterms.subjectcrop managementen
dcterms.subjectaprendizaje automáticoen
dcterms.subjectintensificación sostenibleen
dcterms.subjectpequeños agricultoresen
dcterms.subjectdata papersen
dcterms.typeJournal Article

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