Evaluating low-cost portable near infrared sensors for rapid analysis of soils from South Eastern Australia

• Published in: Geoderma Regional Vol. 20; p. e00240
• Main Authors: Tang, Yijia, Jones, Edward, Minasny, Budiman
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2020
• Subjects: Accuracy; calcium; carbon; clay; cost effectiveness; Cubist; data collection; exchangeable calcium; exchangeable magnesium; least squares; Lixisols; Low-cost sensors; Luvisols; magnesium; Near infrared spectroscopy; New South Wales; Partial Least Squares Regression; Portable sensors; prediction; Proximal sensing; rapid methods; reflectance; sand; soil pH; soil sampling; soil texture; Solonetz; spectrometers; wavelengths; New South Wales; Near infrared spectroscopy; Low-cost sensors; Accuracy; Luvisols; Portable sensors; Cubist; Proximal sensing; Lixisols; Solonetz; Partial Least Squares Regression
• DOI: 10.1016/j.geodrs.2019.e00240
• ISSN: 2352-0094

Near infrared spectroscopy has been proposed as a rapid and cost-effective method for soil analysis. Full-range visible near infrared (Vis-NIR) spectrometers working in the 350–2500 nm wavelength are commonly used for research purposes, but now miniaturized spectrometers with limited NIR ranges have become available. This study aims to compare the accuracy of near infrared reflectance (NIR) instruments with different sizes and wavelength ranges on the prediction of soil properties. Soil samples were taken from southern New South Wales and northern Victoria, comprised of Chromosols, Dermosols, Kandosols, and Sodosols. In total, the dataset consists of 392 soil samples from the top 1 m. The study compared two research-grade Vis-NIR spectrometers (350–2500 nm) and two miniaturized NIR spectrometers with limited wavelengths (NeoSpectra operating at 1250–2500 nm and NIRVascan operating at 900–1700 nm). Cubist regression tree and Partial Least Squares Regression (PLSR) were used to build calibration models. The results showed that both modelling procedures are reliable for estimating soil properties. Cubist models gave greater validation r2 values for ten soil properties investigated for all four instruments. Based on the Cubist model, promising results were found in predictions of clay, sand, total carbon, CEC, pH, exchangeable Mg and Ca (r2: 0.43–0.81). The results are also comparable to published studies for all instruments. As expected, the research-grade spectrometers provided the best prediction accuracies (r2: 0.56–0.81). Results from NeoSpectra provided a comparable accuracy with the Vis-NIR spectrometers in prediction of soil pH, CEC and exchangeable Ca and Mg (r2 > 0.63–0.78). NeoSpectra produced a slightly less accurate prediction of total carbon, sand, and clay. While NIRVascan showed the lowest accuracy, it still can be used in prediction of soil texture and total carbon with reasonable accuracy (r2 clay: 0.73; sand: 0.63; total carbon: 0.73). This study demonstrates the potential of miniaturized spectrometers with reduced wavelength ranges as cheaper instruments in soil analysis. •Miniaturized NIR spectrometers with limited spectral range were evaluated for soil analysis.•Good prediction accuracy was obtained for clay, sand, total carbon, CEC, pH, exchangeable Mg and Ca.•Spectrometer 1250–2500 nm provided comparable accuracy compared to Vis-NIR spectrometers.•Low cost spectrometers are potentially useful for soil analysis.