Contribution of persistent factors to yield gaps in high-yield irrigated maize

Bhupinder S. Farmaha, David B. Lobell, Katherine E. Boone, Kenneth G. Cassman, Haishun S. Yang, Patricio Grassini

Research output: Contribution to journalArticlepeer-review

Abstract

Crop yield gap (Yg) can be disaggregated into two components: (i) one that is consistent across years and is, therefore, attributable to persistent factors that limit yields, and (ii) a second that varies from year to year due to inconsistent constraints on yields. Quantifying relative contributions of persistent and non-persistent factors to overall Yg, and identifying their underpinning causes, can help identify sound interventions to narrow current Yg and estimate magnitude of likely impact. The objective of this study was to apply this analytical framework to quantify the contribution of persistent factors to current Yg in high-yield irrigated maize systems in western US Corn Belt and identify some of the underpinning explanatory factors. We used a database containing producer yields collected during 10 years (2004-2013) from ca. 3000 irrigated fields in three regions of the state of Nebraska (USA). Yield potential was estimated for each region-year using a crop simulation model and actual weather and management data. Yg was calculated for each field-year as the difference between simulated yield potential and field yield. Two independent sources of field yield data were used: (i) producer-reported yields, and (ii) estimated yields using a combined satellite-crop model approach that does not rely on actual yield data. In each year (hereafter called 'ranking years'), fields were grouped into 'small' and 'large' Yg categories. For a given category, Yg persistence was calculated by comparing mean Yg estimated for ranking years against mean Yg calculated, for the same group of fields, for the rest of the years. Explanatory factors for persistent Yg were assessed. Yg persistence ranged between ca. 30% and 50% across regions, with higher persistence in regions with heterogeneous soils. Estimates of Yg size and persistence based on producer-reported yields and satellite-model approach were in reasonable agreement, though the latter approach consistently underestimated Yg size and persistence. Small Yg category exhibited a higher frequency of fields with favorable soils and soybean-maize rotation and greater N fertilizer and irrigation inputs relative to the large Yg category. Remarkably, despite higher applied inputs, efficiencies in the use of N fertilizer, irrigation, and solar radiation were much higher in fields exhibiting small Yg. The framework implemented in this study can be applied to any cropping system for which a reasonable number of field-year yield and management data are available.

Original languageEnglish (US)
Pages (from-to)124-132
Number of pages9
JournalField Crops Research
Volume186
DOIs
StatePublished - Feb 1 2016

Keywords

  • Crop simulation model
  • Irrigated maize
  • Producer data
  • Remote sensing
  • Yield gap

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Soil Science

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