A discussion on the significance associated with Pearson’s correlation in precision agriculture studies
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Pearson’s correlation is a commonly used descriptive statistic in many published precision agriculture studies, not only in the Precision Agriculture Journal, but also in other journals that publish in this domain. Very few of these articles take into consideration auto-correlation in data when performing correlation analysis, despite a statistical solution being available. A brief discussion on the need to consider auto-correlation and the effective sample size when using Pearson’s correlation in precision agriculture research is presented. The discussion is supported by an example using spatial data on vine size and canopy vigour in a juice-grape vineyard. The example data demonstrated that the p-value of the correlation between vine size and canopy vigour increased when auto-correlation was accounted for, potentially to a non-significant level depending on the desired α-level. The example data also demonstrated that the method by which data are processed (interpolated) to achieve co-located data will also affect the amount of auto-correlation and the effective sample size. The results showed that for the same variables, with different approaches to data co-location, a lower r-value may have a lower p-value and potentially hold more statistical significance.
KeywordsAuto-correlation Pruning weight NDVI
The authors would like to acknowledge the diligence and efforts of the technical staff at CLEREL during the collection of the NDVI and pruning weight data.
- Jordan, T. D., Pool, R. M., Zabadal, T. J., & Tompkins, J. P. (1981). Cultural practices for commercial vineyards; miscellaneous bulletin 111. Geneva: New York State College of Agriculture and Life Sciences.Google Scholar
- Minasny, B., McBratney, A. B., & Whelan, B. M. (2005). VESPER version 1.62. Precision Agriculture Laboratory, Faculty of Agriculture and Environment, University of Sydney, NSW 2006. http://sydney.edu.au/agriculture/pal/software/vesper.shtml. Accessed 16 April 2013.
- Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. In S. C. Freden, E. P. Mercanti & M. A. Becker (Eds.), Third Earth Resource Technology Satellite (ERTS) Symposium (Vol. 1, pp. 309–317). Washington, DC: NASA. Special Publication SP-351.Google Scholar
- Whelan, B. M., McBratney, A. B., & Minasny, B. (2001). Vesper - Spatial prediction software for precision agriculture. In G. Grenier & S. Blackmore (Eds.), ECPA 2001—Proceedings of the 3rd European Conference on Precision Agriculture (pp. 139–144). Montpellier: agro-Montpellier. FR.Google Scholar