Mid-infrared spectroscopy for accurate measurement of an extensive set of soil properties for assessing soil functions

Ng, Wartini; Minasny, Budiman; Jeon, Sang Ho; McBratney, Alex B.

doi:10.1016/j.soisec.2022.100043

Cited by 44 publications

(27 citation statements)

References 72 publications

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“…Apart from the difference in costs of the used instruments and the level of portability, there was no obvious benefit of vis-NIR system over mid-IR, or vice versa. The stated error estimates reported in this study and in earlier studies ( Table 1 ) [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 39 , 40 ] are higher than those corresponding to traditional analysis, where the laboratory method has a detection limit of 20 g kg −1 for sand and clay (dry basis), and generally, is reproducible to within ±80 g kg −1 , Ref. [ 49 ].…”

Section: Resultssupporting

confidence: 64%

“…This suggests its wide usage in agricultural and environmental soil sensing applications. However, this is still being debated [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

“…These portable instruments are built using semiconductor technologies and they are relatively inexpensive, robust, and simpler to use when compared to laboratory-based bench-top instruments. They are suitable for deployment in the field for proximal sensing [ 1 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Numerous studies support their use for the simultaneous assessment of primary and secondary soil properties on the go [ 34 , 35 , 36 ].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Two Portable Hyperspectral-Sensor-Based Instruments to Predict Key Soil Properties in Canadian Soils

Dhawale

Adamchuk

Prasher

et al. 2022

Sensors

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In contrast with classic bench-top hyperspectral (multispectral)-sensor-based instruments (spectrophotometers), the portable ones are rugged, relatively inexpensive, and simple to use; therefore, they are suitable for field implementation to more closely examine various soil properties on the spot. The purpose of this study was to evaluate two portable spectrophotometers to predict key soil properties such as texture and soil organic carbon (SOC) in 282 soil samples collected from proportional fields in four Canadian provinces. Of the two instruments, one was the first of its kind (prototype) and was a mid-infrared (mid-IR) spectrophotometer operating between ~5500 and ~11,000 nm. The other instrument was a readily available dual-type spectrophotometer having a spectral range in both visible (vis) and near-infrared (NIR) regions with wavelengths ranging between ~400 and ~2220 nm. A large number of soil samples (n = 282) were used to represent a wide variety of soil textures, from clay loam to sandy soils, with a considerable range of SOC. These samples were subjected to routine laboratory soil analysis before both spectrophotometers were used to collect diffuse reflectance spectroscopy (DRS) measurements. After data collection, the mid-IR and vis-NIR spectra were randomly divided into calibration (70%) and validation (30%) sets. Partial least squares regression (PLSR) was used with leave one out cross-validation techniques to derive the spectral calibrations to predict SOC, sand, and clay content. The performances of the calibration models were reevaluated on the validation set. It was found that sand content can be predicted more accurately using the portable mid-IR spectrophotometer and clay content is better predicted using the readily available dual-type vis-NIR spectrophotometer. The coefficients of determination (R2) and root mean squared error (RMSE) were determined to be most favorable for clay (0.82 and 78 g kg−1) and sand (0.82 and 103 g kg−1), respectively. The ability to predict SOC content precisely was not particularly good for the dataset of soils used in this study with an R2 and RMSE of 0.54 and 4.1 g kg−1. The tested method demonstrated that both portable mid-IR and vis-NIR spectrophotometers were comparable in predicting soil texture on a large soil dataset collected from agricultural fields in four Canadian provinces.

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Section: Resultssupporting

confidence: 64%

“…This suggests its wide usage in agricultural and environmental soil sensing applications. However, this is still being debated [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Two Portable Hyperspectral-Sensor-Based Instruments to Predict Key Soil Properties in Canadian Soils

Dhawale

Adamchuk

Prasher

et al. 2022

Sensors

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“…Many researchers have demonstrated the efficiency of soil spectroscopy and robust predictive capabilities for multiple soil properties [28], summarized in [7]. In addition, the MIR spectral range has been proven to provide superior prediction compared to vis-NIR-SWIR spectra [29][30][31]. The SSLs, thus, are important research initiatives [10] but the data are only available through scientific journal publications.…”

Section: Introduction and Contextualizationmentioning

confidence: 99%

The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication

et al. 2022

Self Cite

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Although many Soil Spectral Libraries (SSLs) have been created globally, these libraries still have not been operationalized for end-users. To address this limitation, this study created an online Brazilian Soil Spectral Service (BraSpecS). The system was based on the Brazilian Soil Spectral Library (BSSL) with samples collected in the Visible–Near–Short-wave infrared (vis–NIR–SWIR) and Mid-infrared (MIR) ranges. The interactive platform allows users to find spectra, act as custodians of the data, and estimate several soil properties and classification. The system was tested by 500 Brazilian and 65 international users. Users accessed the platform (besbbr.com.br), uploaded their spectra, and received soil organic carbon (SOC) and clay content prediction results via email. The BraSpecS prediction provided good results for Brazilian data, but performed variably for other countries. Prediction for countries outside of Brazil using local spectra (External Country Soil Spectral Libraries, ExCSSL) mostly showed greater performance than BraSpecS. Clay R2 ranged from 0.5 (BraSpecS) to 0.8 (ExCSSL) in vis–NIR–SWIR, but BraSpecS MIR models were more accurate in most situations. The development of external models based on the fusion of local samples with BSSL formed the Global Soil Spectral Library (GSSL). The GSSL models improved soil properties prediction for different countries. Nevertheless, the proposed system needs to be continually updated with new spectra so they can be applied broadly. Accordingly, the online system is dynamic, users can contribute their data and the models will adapt to local information. Our community-driven web platform allows users to predict soil attributes without learning soil spectral modeling, which will invite end-users to utilize this powerful technique.

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“…This measure shows how well the variance of the predicted spectral values coincides with the values measured in the laboratory. R 2 is calculated according to the following formula (Ng et al 2022):…”

Section: Accuracy Assessmentmentioning

confidence: 99%

Assessment of Soil Characteristics Using a Three-Band Agricultural Digital Camera

Glinko

Kaźmierowski

Piekarczyk

et al. 2022

Quaestiones Geographicae

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Remote sensing techniques based on soil spectral characteristics are the key to future land management; however, they still require field measurement and an agrochemical laboratory for the calibration of the soil property model. Visible and near-infrared diffuse reflectance spectroscopy has proven to be a rapid and effective method. This study aimed to assess the suitability of multispectral data acquired with the agricultural digital camera in determining soil properties. This 3.2-Mpx camera captures images in three spectral bands – green, red and near-infrared. First, the reference data were collected, which consist of 151 samples that were later examined in the laboratory to specify the granulometric composition and to quantify some chemical elements. Second, additional soil properties such as cation exchange capacity, organic carbon and soil pH were measured. Finally, the agricultural digital camera photograph was taken for every soil sample. Reflectance values in three available spectra bands were used to calculate the spectra indices. The relationships between the collected data were calculated using the independent validation regression model such as Cubist and cross-validation model like partial least square in R Studio. Additionally, different types of data normalisation multiplicative scatter correction, standard normal variate, min–max normalisation, conversion into absorbance] were used. The results proved that the agricultural digital camera is suitable for soil property assessment of sand and silt, pH, K, Cu, Pb, Mn, F, cation exchange capacity and organic carbon content. Coefficient of determination varied from 0.563 (for K) to 0.986 (for soil organic carbon). Higher values were obtained with the Cubist regression model than with partial least squares.

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Mid-infrared spectroscopy for accurate measurement of an extensive set of soil properties for assessing soil functions

Cited by 44 publications

References 72 publications

Evaluation of Two Portable Hyperspectral-Sensor-Based Instruments to Predict Key Soil Properties in Canadian Soils

Evaluation of Two Portable Hyperspectral-Sensor-Based Instruments to Predict Key Soil Properties in Canadian Soils

The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication

Assessment of Soil Characteristics Using a Three-Band Agricultural Digital Camera

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