Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe
This research compared the accuracy of laboratory reference measurements of soil C and N fractions with soil reflectance spectra acquired using a portable field spectroradiometer with an illuminating contact probe. Soil samples were taken from eight, 1.6 ha watersheds, located in El Reno, Oklahoma o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-10-01
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| Series: | Soil Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-8789/3/4/71 |
| _version_ | 1818541590960930816 |
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| author | Ann-Marie Fortuna Patrick J. Starks Amanda M. Nelson Jean L. Steiner |
| author_facet | Ann-Marie Fortuna Patrick J. Starks Amanda M. Nelson Jean L. Steiner |
| author_sort | Ann-Marie Fortuna |
| collection | DOAJ |
| description | This research compared the accuracy of laboratory reference measurements of soil C and N fractions with soil reflectance spectra acquired using a portable field spectroradiometer with an illuminating contact probe. Soil samples were taken from eight, 1.6 ha watersheds, located in El Reno, Oklahoma on native warm season grasslands and agronomic managements with landform complexes serving as replicates within and among treatments. Soil samples were taken from 0−30-cm. Measurements included total soil organic carbon (TSOC), total soil nitrogen (TSN), residual C of acid hydrolysis (RCAH), and particulate organic matter C (POMC) and N (POMN). Soil reflectance in the 350 to 2500 nm region was correlated with individual laboratory measurements. Each reference dataset was divided into model development data (70%) and model validation data (30%). Calibrated models were applied to validation datasets. Statistical analysis revealed that prediction efficiencies of soil reflectance models were highly quantitative. Coefficients of determination (<i>R</i><sup>2</sup>) were near 1 (≥0.90) and ratios of predicted values to the measured standard deviation (RPD) were >2, indicative of good predictive models. The field spectroradiometer enabled us to parameterize soil spatial variability and soil reflectance measurements, reducing the resources required to acquire edaphic measurements. |
| first_indexed | 2024-12-11T22:11:17Z |
| format | Article |
| id | doaj.art-a26229861c044a0680ea73045e0d23b5 |
| institution | Directory Open Access Journal |
| issn | 2571-8789 |
| language | English |
| last_indexed | 2024-12-11T22:11:17Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Soil Systems |
| spelling | doaj.art-a26229861c044a0680ea73045e0d23b52022-12-22T00:48:47ZengMDPI AGSoil Systems2571-87892019-10-01347110.3390/soilsystems3040071soilsystems3040071Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact ProbeAnn-Marie Fortuna0Patrick J. Starks1Amanda M. Nelson2Jean L. Steiner3Grazingland Research Laboratory, USDA-ARS, El Reno, OK 73036, USAGrazingland Research Laboratory, USDA-ARS, El Reno, OK 73036, USAGrazingland Research Laboratory, USDA-ARS, El Reno, OK 73036, USAGrazingland Research Laboratory, USDA-ARS, El Reno, OK 73036, USAThis research compared the accuracy of laboratory reference measurements of soil C and N fractions with soil reflectance spectra acquired using a portable field spectroradiometer with an illuminating contact probe. Soil samples were taken from eight, 1.6 ha watersheds, located in El Reno, Oklahoma on native warm season grasslands and agronomic managements with landform complexes serving as replicates within and among treatments. Soil samples were taken from 0−30-cm. Measurements included total soil organic carbon (TSOC), total soil nitrogen (TSN), residual C of acid hydrolysis (RCAH), and particulate organic matter C (POMC) and N (POMN). Soil reflectance in the 350 to 2500 nm region was correlated with individual laboratory measurements. Each reference dataset was divided into model development data (70%) and model validation data (30%). Calibrated models were applied to validation datasets. Statistical analysis revealed that prediction efficiencies of soil reflectance models were highly quantitative. Coefficients of determination (<i>R</i><sup>2</sup>) were near 1 (≥0.90) and ratios of predicted values to the measured standard deviation (RPD) were >2, indicative of good predictive models. The field spectroradiometer enabled us to parameterize soil spatial variability and soil reflectance measurements, reducing the resources required to acquire edaphic measurements.https://www.mdpi.com/2571-8789/3/4/71spectroradiometerparticulate organic matter fractionsoil organic matter fractionsmineral associated organic fractions |
| spellingShingle | Ann-Marie Fortuna Patrick J. Starks Amanda M. Nelson Jean L. Steiner Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe Soil Systems spectroradiometer particulate organic matter fraction soil organic matter fractions mineral associated organic fractions |
| title | Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe |
| title_full | Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe |
| title_fullStr | Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe |
| title_full_unstemmed | Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe |
| title_short | Prediction of Soil Carbon Fractions Using a Field Spectroradiometer Equipped with an Illuminating Contact Probe |
| title_sort | prediction of soil carbon fractions using a field spectroradiometer equipped with an illuminating contact probe |
| topic | spectroradiometer particulate organic matter fraction soil organic matter fractions mineral associated organic fractions |
| url | https://www.mdpi.com/2571-8789/3/4/71 |
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