The stability of calibration model in measuring and mapping soil organic matter in a dry climatic area

• Published in: IOP conference series. Earth and environmental science Vol. 824; no. 1; pp. 12052 - 12057
• Main Authors: Kusumo, B H, Idris, M H, Sukartono, Mulyati, Susilowati, L E, Bakti, L A A, Baharudin, Purwanto, Y A, Bustan
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2021
• Subjects: Calibration; Carbon dioxide; Carbon sequestration; Climate change; Climate change mitigation; Environmental monitoring; Fertilizers; Global warming; Greenhouse effect; Greenhouse gases; Grid method; Infrared spectroscopy; Mapping; Near infrared radiation; Organic fertilizers; Organic matter; Organic soils; Reliability; Sequestering; Soil fertility; Soil mapping; Soil organic matter; Soil stability
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/824/1/012052

Abstract The increase of atmospheric CO 2 concentration from soil organic matter (SOM) decomposition may contribute to the global warming and climate change. So, sequestering this greenhouse gas into SOM may be used to mitigate climate change. However, tedious procedures in measuring and mapping SOM need to be replaced with a method which works based on the reliability of calibration model developed. This research aimed to test the reliability of the calibration model that was built from a separate soil sample group to be used to measure and map SOM on other validation soil sample group, in the mostly dry climatic area of Kayangan Sub-district, North Lombok Indonesia. For this purpose, 300 soil samples were collected from the area using grid method, which were then dried, ground, sieved, analysed for SOM content using the Walkley and Black method, and scanned using Near Infrared Spectroscopy. The model built using calibration sample group was able to reliably measure and map the SOM content of the spectral data collected from the validation sample set. This is shown by the coefficient of determination (R 2 V = 0.79), root mean square error (RMSE V = 0.246%) and the ratio prediction to deviation (RPD V = 2.09). SOM maps generated from both laboratory and near infrared method can show very low, low and medium SOM content. These maps can be further used as a reference for applying organic fertilizers, avoiding excessive use of fertilizers, and monitoring soil carbon sequestration in mitigating climate change.