VisNIR integrated multi-sensing penetrometer for in situ high-resolution vertical soil sensing

Nuwan K. Wijewardane, Sarah Hetrick, Jason Ackerson, Cristine L.S. Morgan, Yufeng Ge

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

An in situ penetrometer system that can measure profile soil properties rapidly, cost-effectively, and at high vertical resolution would benefit the soil science and agriculture communities. A visible and near infrared (VisNIR) integrated multi-sensing penetrometer system was developed to automatically measure in situ soil VisNIR reflectance spectra, penetration resistance, and insertion depth along a soil profile. The system was tested in 11 agricultural fields in Nebraska, Illinois, Iowa, and South Dakota of the U.S. An independent soil VisNIR spectral library was used to build calibration models for soil property prediction. External Parameter Orthogonalization (EPO) was used to correct for the field intactness of in situ VisNIR spectra. The results showed that EPO was effective in correcting for the spectral disparity between in situ and dry-ground VisNIR spectra. The EPO correction showed an improvement of prediction accuracy of soil total carbon (R2 and RMSE improved from 0.29 and 3.06 % to 0.5 and 0.79 %, respectively) and total nitrogen (R2 and RMSE improved from 0.51 and 0.36 % to 0.62 and 0.06 %, respectively). The system also predicted soil bulk density with an RMSE of 0.12 g cm−3 and R2 of 0.80. It is concluded that the VisNIR multi-sensing penetrometer, along with the use of external soil spectral libraries and the spectral correction algorithm EPO, can lead to a rapid, robust and cost-effective system for in situ high resolution vertical soil sensing.

Original languageEnglish (US)
Article number104604
JournalSoil and Tillage Research
Volume199
DOIs
StatePublished - May 2020

Keywords

  • Bulk density
  • External parameter orthogonalization
  • Machine learning
  • Partial least squares regression
  • Soil profile
  • Spectral library
  • Support vector regression
  • Total carbon
  • Total nitrogen

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Soil Science
  • Earth-Surface Processes

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