Abstract
Quality of measurements is an important factor affecting the reliability of analyses in environmental sciences. In this paper we combine foliar measurement data from Finland and results of multiple measurement quality tests from different sources in order to study the effect of measurement quality on the reliability of foliar nutrient analysis. In particular, we study the use of weighted linear regression models in detecting trends in foliar time series data and show that the development of measurement quality has a clear effect on the significance of results. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Sulkava, M., Rautio, P., & Hollmén, J. (2005). Combining measurement quality into monitoring trends in foliar nutrient concentrations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3697 LNCS, pp. 761–767). https://doi.org/10.1007/11550907_121
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