Combining field surveys, remote sensing, and regression trees to understand yield variations in an irrigated wheat landscape

David B. Lobell, J. Ivan Ortiz-Monasterio, Gregory P. Asner, Rosamond L. Naylor, Walter P. Falcon

Research output: Contribution to journalReview article

106 Citations (Scopus)

Abstract

Improved understanding of the factors that limit crop yields in farmers' fields will play an important role in increasing regional food production while minimizing environmental impacts. However, causes of spatial variability in crop yields are poorly known in many regions because of limited data availability and analysis methods. In this study, we assessed sources of between-field wheat (Triticum aestivum L.) yield variability for two growing seasons in the Yaqui Valley, Mexico. Field surveys conducted in 2001 and 2003 provided data on management practices for 68 and 80 wheat fields throughout the Valley, respectively, while yields on these fields were estimated using concurrent Landsat satellite imagery. Management-yield relationships were analyzed with t tests, linear regression, and regression trees, all of which revealed significant but year-dependent impacts of management on yields. In 2001, an unusually cool year that favored high yields, N fertilizer was the most important source of between-field variability. In 2003, a warmer year with reduced irrigation water allocations, the timing of the first postplanting irrigation was found to be the most important control. Management explained at least 50% of spatial yield variability in both years. Regression tree models, which were able to capture important nonlinearities and interactions, were more appropriate for analyzing yield controls than traditional linear models. The results of this study indicate that adjustments in management can significantly improve wheat production in the Yaqui Valley but that the relevant controls change from year to year.

Original languageEnglish (US)
Pages (from-to)241-249
Number of pages9
JournalAgronomy Journal
Volume97
Issue number1
StatePublished - Jan 1 2005
Externally publishedYes

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remote sensing
wheat
valleys
crop yield
water allocation
traditional foods
Landsat
food production
irrigation water
environmental impact
nitrogen fertilizers
Triticum aestivum
linear models
Mexico
growing season
irrigation
farmers

ASJC Scopus subject areas

  • Agronomy and Crop Science

Cite this

Combining field surveys, remote sensing, and regression trees to understand yield variations in an irrigated wheat landscape. / Lobell, David B.; Ortiz-Monasterio, J. Ivan; Asner, Gregory P.; Naylor, Rosamond L.; Falcon, Walter P.

In: Agronomy Journal, Vol. 97, No. 1, 01.01.2005, p. 241-249.

Research output: Contribution to journalReview article

Lobell, David B. ; Ortiz-Monasterio, J. Ivan ; Asner, Gregory P. ; Naylor, Rosamond L. ; Falcon, Walter P. / Combining field surveys, remote sensing, and regression trees to understand yield variations in an irrigated wheat landscape. In: Agronomy Journal. 2005 ; Vol. 97, No. 1. pp. 241-249.
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