Quantification and comparison of wheat yield variation across space and time

Abstract

Research about spatio-temporal variation of crop yield does not abound. From a precision agriculture (PA) perspective and particularly considering site-specific crop management (SSCM), this is an aberration. There is a serious need to further question how temporal variation of crop yield impacts ones ability to manage spatial variation. The aim of this study is to consider and develop new and existing approaches to this question. Spatio-temporal analysis was undertaken for two wheat fields in South Australia with 3 and 4 years of wheat yield data. Temporal analysis included the calculation of semi-variance across each field between pairs of years for the creation of maps and the calculation of rank correlations between pairs of years. These analyses supported previous notions that the magnitude of temporal variation is large compared with spatial variation. However, some consistence of spatial patterns between years was also observed for each of the fields indicating that considering magnitudes of variation alone is not an exhaustive analysis. A long-term (100 years) temporal analysis using variograms was undertaken for a single point simulated using the Agricultural Production Simulator Model (APSIM). The long-term analysis overcame the fact that 3 or 4 years of yield data are an extremely small sample size for the time dimension. This analysis provided some useful insight into temporal variation such as a large nugget variance accounting for 75% of the temporal variation and the cyclical nature of temporal yield variation. A novel use of pseudo cross semi-variograms was applied to a spatio-temporal analysis of yield variation for the two fields. This analysis provides a preliminary insight into identifying space–time variance equivalents. With greater depth of temporal crop yield data this is a promising perspective from which to identify optimal spatial management strategies.