Soil Organic Carbon Fractions and Stocks as Affected by Organic Fertilizers in Rice Paddy Soil

Self Cite

This study investigated the effect of different livestock manure composts application on yield, soil chemical properties and carbon sequestration in maize cultivation. The experiment consisted of six different fertilizations; no fertilization (control), chemical fertilizer (NPK), pig manure (PM), NPK + residue of maize (NPKR), NPK + pig manure compost + residue of maize (NPKPR) and NPK + cow manure compost + residue of maize (NPKCR). The yield of maize under NPKPR (5,064.0 kg 10a -1 ) and NPKCR (4,183.7 kg 10a -1 ) were higher than that of NPK (3,775.6 kg 10a -1 ). In soil chemical properties, pH, EC and Avail. P 2 O 5 were increased when livestock compost applied in soil. The content of soil organic carbon (SOC) was higher in order: NPKPR (3.37 g kg -1 ) > NPKCR (3.27 g kg -1 ) > NPKR (3.12 g kg -1 ) > PR (2.88 g kg -1 ) > NPK (2.79 g kg -1 ) > NF (2.48 g kg -1 ). The highest SOC stock was observed in NPKCR (14.67 kg C ha -1 ) due to the high SOC and low bulk density. In conclusion, application of livestock manure composts with inorganic fertilizer increase maize yield, SOC stock. Therefore, it is recommendable for suitable soil management strategy to improve soil fertility and increase crop yield in upland soil. Further study might be required to evaluate long-term compost application effect on soil chemical properties and crop yield.

Section: Resultsunclassified

Effect of Livestock Manure Composts Application on Yield, Soil Chemical Properties and Carbon Sequestration of Maize Cropping for Five Years

Lee

Park

Shim

et al. 2021

Self Cite

“…최근 국내에서는 논 토양에 볏짚을 투입했을 때 탄소 저장 확인을 위한 연구 (Hwang et al, 2019;Byeon et al, 2022)와 온실가스 배출량 감소를 위한 유기물 관리 측면 (Lee et al, 2020;Gwon et al, 2022)…”

Section: Introductionunclassified

Effects of Rice Straw Return on Soil Labile Organic Carbon and β-Glucosidase Activity in Paddy Soil

Choi,

Kim,

Jeong

et al. 2023

Rice straw is a source of organic matter (OM) that improves soil fertility. After rice straw is returned to the soil, increased microbial enzyme activity decomposes organic residues, affecting soil carbon. To evaluate the effects of continuous rice straw return on soil labile organic carbon (LOC) fraction and β-glucosidase (BG) activity in paddy soil, an experiment was conducted with four treatments; Chemical fertilizer treatment (NPK), Chemical fertilizer + rice straw treatment (NPKR), Green manure treatment (GM) and Green manure + rice straw treatment (GMR). Hot water extractable carbon (HWEC) content, permanganate oxidizable carbon (POXC) content, and BG activity were analyzed. HWEC content was 42% higher than in NPKR than in NPK. It was 8% higher in GMR than in GM, but there was no significant difference. In addition, POXC content was 17% higher in NPKR than in NPK. It was 11% higher than in GMR than in GM, but there was no significant difference. BG activity was 36% higher in NPKR than NPK, and 55% higher in GMR than GM. As a result, in paddy soil that are low in OM due to the predominant use of chemical fertilizers, rice straw return is likely to increase OM supply and LOC content in the soil and contribute to carbon cycling.

“…따라서, 우리나라에서도 농업환경변동조사 사업 등을 통해 논 (Hwang et al, 2019), 밭 (Ahn et al, 2020;, 과수원 (Ahn et al, 2020;Kim et al, 2021) 등 농경지 유형별 토양 탄소 함량을 조사하고 있다. 토양 탄소 함량은 기본적으로 기후, 식생, 지형 등 토양 생성 요인에 영향을 받지만 (Wiesmeier et al, 2019), 농경지에서는 투입 되는 유기물의 종류와 양 (Karhu et al, 2012), 그리고 토양 유기물의 물리화학적 안정화와 관련된 토양 특성 (토성, pH, 점토 함량 등) (Wiesmeier et al, 2019;Park et al, 2022)에 의해서도 영향을 받는다.…”

Section: Introductionunclassified

Prediction of Soil Organic Carbon Contents of Rice Paddies in South-Western Coastal Area of Korea Using Random Forest Models

Park¹,

Choi²

2022

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 e ), 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 (R 2 ) 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 NH 4 + concentrations. Meanwhile, the contribution of EC e , 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.