지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
이용수
초록· 키워드
오류제보하기
Random forest models (RFM) are useful in predicting the soil carbon (C) contents because RFM predicts soil C with high accuracy under complicated environmental conditions. However, there are very few studies on prediction of soil C using RFM in Korea. Moreover, there is no case study using RFM to predict soil C content of reclaimed tideland (RTL) soils, which have high C sequestration capacity. Therefore, in this study, the applicability of RFM was evaluated using published soil properties data, including soil C and soil variables, for RTL soils located in southwestern coastal areas of Korea. In the present study, RFM was built using the data of 16 variables (e.g., sand, silt, and clay contents, pH, electrical conductivity of saturated soil paste (EC<SUB>e</SUB>), and nutrient concentrations) obtained from five RTLs with similar climate, topography, and vegetation. The 80% of the total data were trained to build the model, and searched optimal hyper parameters were used to improve accuracy. The determination coefficient (R²) of the model was 0.67, and the difference between measured and predicted soil C content was 25.9% on average. However, when the measured values were out of the range of the data trained for building the model or the measured values were close to the minimum or maximum value, the difference between the predicted and measured values became larger (73.9%). The contribution of the independent variables to the prediction of soil C using the model was the greatest (14.9%) for soil NH₄⁺ concentrations. Meanwhile, the contribution of EC<SUB>e</SUB>, which was highly correlated with soil C content, was not detected, suggesting that the importance of the number and range of training data used to build model. Our study shows the possible application of RFM to predict soil C contents of RTL soils in Korea, and further highlights that a large amount of data should be accumulated for high accuracy prediction of soil C using RFM.
목차
ABSTRACT
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
참고문헌 (32)
참고문헌 신청
Ahn, B.K., D.Y. Ko, H.J. Choi, and H.G. Chon. 2020. Distribution of water-soluble nutrients and physico-chemical properties of upland and orchard field soils in Jeonbuk province. Korea J. Soil Sci. Fert. 53:375-381.
Breiman, L. 2001. Random forests. Mach. Learn. 45:5-32.
Calle, J.L.P., M. Ferreiro-Gonzalez, A. Ruiz-Rodriguez, G.F. Barbero, J.A. Alvarez, M. Palma, and J. Ayuso. 2021. A methodology based on FT-IR data combined with random forest model to generate spectralprints for the characterization of high-quality vinegars. Foods 10:1141.
Chaplot, V., M. Bernoux, C. Walter, P. Curmi, and U. Herpin. 2001. Soil carbon storage prediction in temperate hydromorphic soils using a morphologic index and digital elevation model. Soil Sci. 166:48-60.
Florinsky, I.V., R.G. Eilers, G. Manning, and L. Fuller. 2002. Prediction of soil properties by digital terrain modelling. Environ. Modell. Software 17:295-311.
Breiman, L. 2001. Random forests. Mach. Learn. 45:5-32.
Calle, J.L.P., M. Ferreiro-Gonzalez, A. Ruiz-Rodriguez, G.F. Barbero, J.A. Alvarez, M. Palma, and J. Ayuso. 2021. A methodology based on FT-IR data combined with random forest model to generate spectralprints for the characterization of high-quality vinegars. Foods 10:1141.
Chaplot, V., M. Bernoux, C. Walter, P. Curmi, and U. Herpin. 2001. Soil carbon storage prediction in temperate hydromorphic soils using a morphologic index and digital elevation model. Soil Sci. 166:48-60.
Florinsky, I.V., R.G. Eilers, G. Manning, and L. Fuller. 2002. Prediction of soil properties by digital terrain modelling. Environ. Modell. Software 17:295-311.
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Introduction on Soil Information Production Using Various Soil Database
한국토양비료학회 학술발표회 초록집
2023 .10
-
Spatial Soil Database for Sustainable Soil Management in Korea
한국토양비료학회 학술발표회 초록집
2018 .10
-
Impact of Soil Chemical Properties on Soil Carbon Fraction in Agricultural Soils
한국토양비료학회 학술발표회 초록집
2024 .10
-
Feasibility of Adapting Soil Quality Assessment Model for Estimation of Rice Productivity in Paddy Field
한국토양비료학회지
2022 .02
-
토양 특성 분석을 기반으로 한 농경지에서의 토양질 평가
한국토양비료학회 학술발표회 초록집
2022 .10
-
우리나라 토양에 적합한 토양 발달 지수 개발
한국토양비료학회 학술발표회 초록집
2024 .10
-
Quantitative classification of ‘excessively drained’ and ‘somewhat excessively drained’ of Korean soils using soil properties
한국토양비료학회지
2025 .02
-
Evaluating Feasibility of Soil Quality Assessment According to Soil Carbon Contents
한국토양비료학회지
2017 .02
-
Effects of soil chemical properties on inorganic and organic carbon contents in organic, calcareous, and reclaimed-tidal soils
한국토양비료학회지
2025 .02
-
Comparing Soil Chemical and Biological Properties in Varied Land Use
한국토양비료학회지
2021 .02
-
Characteristics of Distribution and Decomposition of Organic Matter in Soils Cultivated with Various Fruits and Vegetables in Plastic Film House Fields
한국토양비료학회지
2021 .11
-
Estimation of Soil Organic Matter Content Using Soil Organic Color Chart and Soil Color Meter SPAD 503
한국토양비료학회지
2022 .02
-
Analysis of Catena on Representative Soils derived from Granite and Granite Gneiss
한국토양비료학회지
2015 .08
-
Characteristics of Anthropogenic Soil Formed from Paddy near the River
한국토양비료학회지
2016 .10
-
Research Trends Using Soil Sensors for Precise Nutrient and Water Management in Soil for Smart Farm
한국토양비료학회지
2021 .08
-
Monitoring physical and chemical properties of soil in Chungcheongbuk-do
Korean Journal of Agricultural Science
2022 .12
-
The Global Soil Partnership : Tackling Soil Health through Sustainable Soil Management
한국토양비료학회 학술발표회 초록집
2018 .10
-
Effects of Equilibrium Time on Electrical Conductivity Measurements Using Soil-Water Extracts and Soil Saturated Paste
한국토양비료학회지
2021 .05
-
Quality Assessment of the Soils Used for Urban Agriculture in Seoul and its Vicinity
한국토양비료학회지
2016 .10
-
Australian Soil Classification
한국토양비료학회지
2016 .02
이 논문의 저자 정보
최근 본 자료
댓글(0)
0