Mapping field-scale yield gaps for maize: An example from Bangladesh

dc.creatorSchulthess, U.
dc.creatorTimsina, J.
dc.creatorHerrera, J.M.
dc.creatorMcDonald, A.
dc.date2013-06-30T05:24:50Z
dc.date2013-06-30T05:24:50Z
dc.date2013
dc.date.accessioned2023-07-17T19:57:17Z
dc.date.available2023-07-17T19:57:17Z
dc.identifier0378-4290
dc.identifierhttp://hdl.handle.net/10883/3199
dc.identifier10.1016/j.fcr.2012.11.004
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7509076
dc.descriptionAccurate estimation of the size and spatial distribution of the yield gap has many practical applications, including relevance to precision agriculture and technology targeting. The objectives of this study were to illustrate a methodology to create a yield gap map and to discuss its potential uses to provide optimal crop management recommendations to the farmers. We used the HybridMaize crop simulation model to estimate potential yield for maize grown in the winter season in northwestern Bangladesh. This is a high yielding environment, where farmers achieve yields as high as 12 Mg/ha. The model predicted a mean potential yield of 12.87 Mg/ha. We used a RapidEye satellite image acquired around tasseling to identify the maize fields, calculate ground cover and its regression to actual yield from farmers? fields. Next, the regression was applied to all the maize pixels in the image to calculate actual yield. In the last step, we created a yield gap map based on the difference between potential and actual yield. Yield gap maps will enable agronomists to identify production constraints on farmers? fields with large yield gaps. Alternatively, by learning from the farmers with the highest actual yields and analyzing their data, it will be possible to generate region or field specific, optimized crop management recommendations.
dc.description151-156
dc.formatPDF
dc.languageEnglish
dc.publisherElsevier
dc.publisherhttp://www.sciencedirect.com/science/article/pii/S0378429012003735
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
dc.rightsOpen Access
dc.source143
dc.sourceField Crops Research
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectYield Gap Analysis
dc.subjectGround Cover
dc.subjectYIELD GAP
dc.subjectREMOTE SENSING
dc.subjectCOVER PLANTS
dc.subjectON-FARM RESEARCH
dc.subjectMAIZE
dc.titleMapping field-scale yield gaps for maize: An example from Bangladesh
dc.typeArticle
dc.coverageBangladesh


Este ítem pertenece a la siguiente institución