TY - GEN
T1 - Rotation and the temporal stability of landscape defined management zones
T2 - 7th European Conference on Precision Agriculture, ECPA 2009
AU - Pena-Yewtukhiw, E. M.
AU - Grove, J. H.
PY - 2009
Y1 - 2009
N2 - Yield and landscape position are used to delineate management zones, but this approach is confounded by yield's weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options also influence yield stability, and among these, crop rotation is important. Our objective was to describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotations, monoculture corn (C-C) and corn alternating yearly (W/S-C) with winter wheat (Triticum aestivum L.)/double-crop soybean (Glycine max L. Merr.), taken in four landscape (shoulder, upper backslope, lower backslope, footslope) management zones, were obtained from a 21-year rotation study established near Lexington, Kentucky. Yields were evaluated for spatial and temporal stability by ANOVA, Spearman rank correlation, and time series analysis, using Box-Jenkins methodology. The 21-year average yields were lower for C-C (8.3±2.6 Mg/ha) than for W/S-C (9.6±2.7 Mg/ha). A plot of yield versus time for individual landscape zones exhibited slightly positive linear trend (0.13 Mg/ha/yr) for both rotations. The rank correlations among landscape positions, for each rotation, were generally high (above 0.80), and rotation choice determined which positions were most, and least, similar. After removing linear yield trend, Box-Jenkins time series analysis found that C-C yield exhibited greater temporal lag (less yield stability) than W/S-C yield, though this trend was not equally true across the four zones. The lag predicting C-C yield was greatest (5 years) in the upper backslope, while upper backslope and footslope W/S-C yields exhibited maximal autocorrelation at lags of one to three years in length. These 21-year time series models indicate that similar management zones would require a minimum of three prior years of yield data in order to forecast their yield response behavior.
AB - Yield and landscape position are used to delineate management zones, but this approach is confounded by yield's weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options also influence yield stability, and among these, crop rotation is important. Our objective was to describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotations, monoculture corn (C-C) and corn alternating yearly (W/S-C) with winter wheat (Triticum aestivum L.)/double-crop soybean (Glycine max L. Merr.), taken in four landscape (shoulder, upper backslope, lower backslope, footslope) management zones, were obtained from a 21-year rotation study established near Lexington, Kentucky. Yields were evaluated for spatial and temporal stability by ANOVA, Spearman rank correlation, and time series analysis, using Box-Jenkins methodology. The 21-year average yields were lower for C-C (8.3±2.6 Mg/ha) than for W/S-C (9.6±2.7 Mg/ha). A plot of yield versus time for individual landscape zones exhibited slightly positive linear trend (0.13 Mg/ha/yr) for both rotations. The rank correlations among landscape positions, for each rotation, were generally high (above 0.80), and rotation choice determined which positions were most, and least, similar. After removing linear yield trend, Box-Jenkins time series analysis found that C-C yield exhibited greater temporal lag (less yield stability) than W/S-C yield, though this trend was not equally true across the four zones. The lag predicting C-C yield was greatest (5 years) in the upper backslope, while upper backslope and footslope W/S-C yields exhibited maximal autocorrelation at lags of one to three years in length. These 21-year time series models indicate that similar management zones would require a minimum of three prior years of yield data in order to forecast their yield response behavior.
KW - ARMA models
KW - Corn rotations
KW - Spearman rank correlation
KW - Yield stability
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M3 - Conference contribution
AN - SCOPUS:84893429514
SN - 9789086861132
T3 - Precision Agriculture 2009 - Papers Presented at the 7th European Conference on Precision Agriculture, ECPA 2009
SP - 567
EP - 574
BT - Precision Agriculture 2009 - Papers Presented at the 7th European Conference on Precision Agriculture, ECPA 2009
Y2 - 6 July 2009 through 8 July 2009
ER -