Seven California soils were studied to determine if near infrared (700 to 2500 nm) reflectance spectroscopy could
be used to determine soil moisture content. Near infrared absorbance data in the 1400– to 2400–nm region correlated well
(r 2 = 0.97, SEP = 1.3%, Bias = 0.2%) with soil moisture content when a partial least squares calibration model was used
to estimate the moisture content of soil samples of the same soil type and particle size as those in the calibration data set.
However, when the model was used to estimate the moisture content of a soil sample with a particle size which differed from
those included in the calibration set, the performance was degraded due to large slope and bias errors (Bias = 4.0%, SEP =
2.2%). However, the high coefficient of determination (r 2 = 0.98) suggested that predictions for soil samples which differ from
those included in the calibration set could be improved if the slope and intercept were corrected for a given site. An example
validation of this type was shown where the SEP and bias were reduced from SEP = 2.1% and Bias = 6.0% to SEP = 1.0%
and Bias = 0.9% after slope and bias correction.