Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties

Thumbnail Image
Date
2001-03-01
Authors
Chang, Cheng-Wen
Laird, David
Mausbach, Maurice
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Person
Hurburgh, Charles
Professor
Research Projects
Organizational Units
Organizational Unit
Agricultural and Biosystems Engineering

Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.

History
In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.

Dates of Existence
1905–present

Historical Names

  • Department of Agricultural Engineering (1907–1990)

Related Units

Journal Issue
Is Version Of
Versions
Series
Abstract

A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of near-infrared reflectance spectroscopy (NIRS) to predict diverse soil properties. Near-infrared reflectance spectra, obtained from a Perstrop NIR Systems 6500 scanning monochromator (Foss NIRSystems, Silver Spring, MD), and 33 chemical, physical, and biochemical properties were studied for 802 soil samples collected from four Major Land Resource Areas (MLRAs). Calibrations were based on principal component regression (PCR) using the first derivatives of optical density [log(1/R)] for the 1300- to 2500-nm spectral range. Total C, total N, moisture, cation-exchange capacity (CEC), 1.5 MPa water, basal respiration rate, sand, silt, and Mehlich III extractable Ca were successfully predicted by NIRS (r 2 > 0.80). Some Mehlich III extractable metals (Fe, K, Mg, Mn) and exchangeable cations (Ca, Mg, and K), sum of exchangeable bases, exchangeable acidity, clay, potentially mineralizable N, total respiration rate, biomass C, and pH were also estimated by NIRS but with less accuracy (r 2 = 0.80∼0.50). The predicted results for aggregation (wt% > 2, 1, 0.5, 0.25 mm, and macroaggregation) were not reliable (r 2 = 0.46∼0.60). Mehlich III extractable Cu, P, and Zn, and exchangeable Na could not be predicted using the NIRS–PCR technique (r 2 < 0.50). The results indicate that NIRS can be used as a rapid analytical technique to simultaneously estimate several soil properties with acceptable accuracy in a very short time.

Comments

This article is from Soil Science Society of America Journal 65 (2001): 480–490, doi:10.2136/sssaj2001.652480x.

Description
Keywords
Citation
DOI
Keywords
Copyright
Collections