Prediction of soil organic matter under different soil moisture conditions using Vis-NIR spectroscopy
Reflection spectra of 86 soil samples collected from Fengqiu County were obtained in the laboratory under nine moisture conditions,and the prediction models for each moisture conditions were built using Partial least-squares regression.Models under the soil moisture content 0 ～ 50 g · kg-1,200 ～ 250 g · kg-1 and 400 ～ 450 g · kg-1 were then applied to the other validation sets with different moisture conditions to explore the effect of different soil moisture on the prediction accuracy.The results show that the prediction models for each moisture condition perform well with acceptable prediction accuracy when applied it to the validation set under the same moisture conditions with the calibration set.However,the accuracy decreased dramatically with the increase of difference in soil moisture conditions between the built data set and prediction data set.Spectroscopy could be directly used to predict soil organic matter on moist samples with the similar soil moisture condition.Moist samples should be classified by soil moisture content,and then predict soil organic matter with separate prediction models under the same soil moisture condition.
国家科技期刊平台
NSTL
万方数据
维普
