Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques
Agricultural practices affect arbuscular mycorrhizal fungal (AMF) hyphae growth and glomalin production, which is a recalcitrant carbon (C) source in soil. Since the spatial distribution of glomalin is an interesting issue for agronomists in terms of carbon sequestration, digital maps are a cost-fre...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/12/7/1653 |
| _version_ | 1797407839908528128 |
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| author | Arezou Siami Nasser Aliasgharzad Leili Aghebati Maleki Nosratollah Najafi Farzin Shahbazi Asim Biswas |
| author_facet | Arezou Siami Nasser Aliasgharzad Leili Aghebati Maleki Nosratollah Najafi Farzin Shahbazi Asim Biswas |
| author_sort | Arezou Siami |
| collection | DOAJ |
| description | Agricultural practices affect arbuscular mycorrhizal fungal (AMF) hyphae growth and glomalin production, which is a recalcitrant carbon (C) source in soil. Since the spatial distribution of glomalin is an interesting issue for agronomists in terms of carbon sequestration, digital maps are a cost-free and useful approach. For this study, a set of 120 soil samples was collected from an experimental area of 310 km<sup>2</sup> from the Sarab region of Iran. Soil total glomalin (TG) and easily extractable glomalin (EEG) were determined via ELISA using the monoclonal antibody 32B11. Soil organic carbon (OC) was also measured. The ratios of TG/OC and EEG/OC as the glomalin–C quotes of OC were calculated. A total of 17 terrain-related attributes were also derived from the digital elevation model (DEM) and used as static environmental covariates in digital soil mapping (DSM) using three predictive models, including multiple linear regression (MLR), random forests (RF), and Cubist (CU). The major findings were as follows: (a) DSM facilitated the interpretation of recalcitrant C source variation; (b) RF outperformed MLR and CU as models in predicting and mapping the spatial distribution of glomalin using available covariates; (c) the best accuracy in predictions was for EEG, followed by EEG/OC, TG, and TG/OC. |
| first_indexed | 2024-03-09T03:48:29Z |
| format | Article |
| id | doaj.art-773723cc0b0441ef8fe8026db475e13a |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-09T03:48:29Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-773723cc0b0441ef8fe8026db475e13a2023-12-03T14:31:05ZengMDPI AGAgronomy2073-43952022-07-01127165310.3390/agronomy12071653Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining TechniquesArezou Siami0Nasser Aliasgharzad1Leili Aghebati Maleki2Nosratollah Najafi3Farzin Shahbazi4Asim Biswas5Soil Science Department, Faculty of Agriculture, University of Tabriz, Tabriz 5166616471, IranSoil Science Department, Faculty of Agriculture, University of Tabriz, Tabriz 5166616471, IranImmunology Research Center, Tabriz University of Medical Sciences, Tabriz 5165665931, IranSoil Science Department, Faculty of Agriculture, University of Tabriz, Tabriz 5166616471, IranSoil Science Department, Faculty of Agriculture, University of Tabriz, Tabriz 5166616471, IranSchool of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaAgricultural practices affect arbuscular mycorrhizal fungal (AMF) hyphae growth and glomalin production, which is a recalcitrant carbon (C) source in soil. Since the spatial distribution of glomalin is an interesting issue for agronomists in terms of carbon sequestration, digital maps are a cost-free and useful approach. For this study, a set of 120 soil samples was collected from an experimental area of 310 km<sup>2</sup> from the Sarab region of Iran. Soil total glomalin (TG) and easily extractable glomalin (EEG) were determined via ELISA using the monoclonal antibody 32B11. Soil organic carbon (OC) was also measured. The ratios of TG/OC and EEG/OC as the glomalin–C quotes of OC were calculated. A total of 17 terrain-related attributes were also derived from the digital elevation model (DEM) and used as static environmental covariates in digital soil mapping (DSM) using three predictive models, including multiple linear regression (MLR), random forests (RF), and Cubist (CU). The major findings were as follows: (a) DSM facilitated the interpretation of recalcitrant C source variation; (b) RF outperformed MLR and CU as models in predicting and mapping the spatial distribution of glomalin using available covariates; (c) the best accuracy in predictions was for EEG, followed by EEG/OC, TG, and TG/OC.https://www.mdpi.com/2073-4395/12/7/1653digital soil mappingenvironmental covariatesglomalinmodelingorganic carbonrandom forest |
| spellingShingle | Arezou Siami Nasser Aliasgharzad Leili Aghebati Maleki Nosratollah Najafi Farzin Shahbazi Asim Biswas Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques Agronomy digital soil mapping environmental covariates glomalin modeling organic carbon random forest |
| title | Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques |
| title_full | Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques |
| title_fullStr | Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques |
| title_full_unstemmed | Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques |
| title_short | Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques |
| title_sort | recalcitrant c source mapping utilizing solely terrain related attributes and data mining techniques |
| topic | digital soil mapping environmental covariates glomalin modeling organic carbon random forest |
| url | https://www.mdpi.com/2073-4395/12/7/1653 |
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