Optimal sample selection for measurement of soil organic carbon using on-line vis-NIR spectroscopy
作者: Said NawarAbdul M. Mouazen
作者单位: 1Department of Environment, Ghent University, Coupure Links 653, 9000 Gent, Belgium
刊名: Computers and Electronics in Agriculture, 2018, Vol.151 , pp.469-477
来源数据库: Elsevier Journal
DOI: 10.1016/j.compag.2018.06.042
关键词: Vis-NIR spectroscopySoil organic carbonSpikingPartial least squares regressionSample selection
英文摘要: Abstract(#br)The selection of samples for modelling of visible and near infrared (vis-NIR) spectra for prediction of soil organic carbon (OC) is a crucial step for improving model prediction performance. This paper aims at comparing three soil sample selection methods coupled with spiking technique for improving on-line prediction performance of OC. Sample selection methods included random selection (RS), Kennard-Stone (KS) algorithm and similarity analysis (SA). Soil vis-NIR spectra was measured with an on-line fibre-type vis-NIR spectrophotometer (tec5 Technology for Spectroscopy, Germany), with a spectral range of 305–2200 nm. A multiple field sample set (268 samples) was merged with samples (148 samples) collected from one target field, and the resulted sample set was subjected to the...
全文获取路径: Elsevier  (合作)
影响因子:1.766 (2012)

  • carbon 
  • spectroscopy 分光学
  • organic 有机的
  • selection 选择
  • measurement 测量
  • least 最少的
  • regression 海退
  • sample 样品