Analysis of the inter-annual variation of peanut yield in Georgia using a dynamic crop simulation model

Axel Garcia Y Garcia, Gerrit Hoogenboom, Larry C. Guerra, Joel O. Paz, Clyde W. Fraisse

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

It is common practice to use crop simulation models and long-term weather data to study the impact of climate variability on yield. Simulated yields mainly reflect the weather variability but not the adoption of new technologies; both sources of variation are reflected in long-term observed yields. Therefore, long-term observed yields, if available, cannot be readily used for evaluation of crop models. The objectives of this study were to analyze the impact of climate variability on long-term historical peanut yield in Georgia obtained with a dynamic crop simulation model and to assess the applicability of using long-term average county yield determined from statistical estimates for evaluation of the simulated yield. Observed yields obtained from state variety trials as well as yield estimates from the USDA-NASS for three counties in the Georgia peanut belt from 1934 to 2003 were used for evaluating simulated yield series. Simulated yields based on the CSM-CROPGRO-Peanut model were categorized into three technological periods (TP). A weighted average based on the acreage of the soil type, the peanut type, and the irrigated land in each county was calculated to obtain a unique simulated yield. Then yields and weather data of the 70-year period were grouped with respect to El Niño Southern Oscillation phases and TPs. Pearson's coefficient of correlation, the least significant difference (LSD), and the t-test were used to evaluate the results. When compared with observed yields, NASS estimates failed to estimate the weather variability at the beginning of the period, but simulated yields clearly reflected that variability during the 70-year period. NASS yield estimates seemed to be useful for evaluating simulated yields from the mid-1970s. The results showed that crop models can be useful in understanding the inter-annual variation of yield due to climate variability if appropriate adjustments are made to account for changes and improvements in agrotechnology.

Original languageEnglish (US)
Pages (from-to)2005-2015
Number of pages11
JournalTransactions of the ASABE
Volume49
Issue number6
StatePublished - Nov 1 2006

Keywords

  • CSM-CROPGRO-Peanut
  • Climate variability
  • DSSAT
  • ENSO phases

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