Summary
Soil microbial properties are increasingly recognised as a crucial metric of both soil condition and soil carbon dynamics. However, these properties remain underutilised due to challenges in quantifying these properties at scale. This study assesses the potential for Near (NIR) and Mid (MIR) Infrared spectroscopy, as well as Granger Ramanathan Averaging (GRA) models that integrate predictions from both spectra simultaneously, to provide reliable estimations of microbial properties when incorporating a range of soil samples collected across Australia. Given that these properties are not spectrally active, the accuracy of their predictions relies on correlations with physicochemical properties such as organic matter, clay minerals and soil moisture. Using soil samples from across Australia,
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