• Article

    Difference in Soil Biogeochemical Properties of Agricultural Highland by Topographical Characteristic and Soil Management
    Jung-Hwan Yoon, Kye-Hoon Kim, and Jae E. Yang
    In agricultural highland, soil properties change over time due to soil management methods, soil erosion, and cultivation. The objective of this study … + READ MORE
    In agricultural highland, soil properties change over time due to soil management methods, soil erosion, and cultivation. The objective of this study was to investigate the differences in soil properties according to land management in agricultural highland. As a result of the soil analysis, Anbandegi, Maebongsan, Yeongwol, and Jeongseon, located near the top of the mountain, had low bulk densities, and organic matter, CEC, exchangeable cation, water stable aggregation rate, and dehydrogenase activity, were relatively higher than those of Daegwallyeong and Punch bowl. In the Daegwallyeong and Punch bowl, saprolite soil was periodically piled to replace eroded top-soil, and as a result, soil characteristics differed significantly from those located near the top of the mountain. In the principal component analysis result, organic matter showed the largest eigenvalue in PC1, and pH was selected as PC2. The distribution of soil clusters by sampling point was PC1, and Daegwallyeong and Punch bowl were classified differently from highland areas near the top of the mountain, and coastal basins and Daegwallyeong were classified by PC2. In conclusion, highland soil showed different soil properties for each region, which was the result of differences according to the soil management methods. And considering the relationship between soil characteristics, it was confirmed that organic matter was the most important factor in the soil management methods. Coefficients of each variable for PC1 and PC2 through the PCA of agricultural highland soils. - COLLAPSE
    28 February 2022
  • Article

    Assessment of Soil Enzyme Activities in TPH-Contaminated Soil after Soil Washing and Landfarming Application
    Jin Wook Kim, Young Kyu Hong, Hyuck Soo Kim, Eun Jee Oh, Yong-Ha Park, and Sung Chul Kim
    Soil washing and landfarming processes are mainly used to remediate total petroleum hydrocarbon (TPH) contaminated soil, but the effect of these remediation … + READ MORE
    Soil washing and landfarming processes are mainly used to remediate total petroleum hydrocarbon (TPH) contaminated soil, but the effect of these remediation processes on soil enzyme activity is not well known. Soil enzymes catalyze biochemical reactions in the soil and play a very important role in the circulation of nutrients. In addition, soil enzyme activity is widely used as a biological indicator of soil quality. Four groups (non-contaminated soil, TPH contaminated soil, after soil washing, and landfarming soil) were collected to assess chemical properties and soil enzyme activity. As a result, TPH decreased the arylsulfatase and urease activity, and the soil remediation process can recover soil enzyme activities. Arylsulfatase activity slightly increased after the soil washing and landfarming process. However, urease activity increased significantly after landfarming. In contrast, beta-glucosidase activity did not change after the soil remediation processes. In conclusion, it suggests that the measurement of soil enzyme activity in TPH-contaminated and remediated soils can enable a comprehensive evaluation of soil quality. Arylsulfatase (A), beta-glucosidase (B), urease (C) activities in four soil groups collected in April and July 2021 (CS, TPH contaminated soil; SW, soil washing; LF, landfarming). - COLLAPSE
    28 February 2022
  • Article

    Feasibility of Adapting Soil Quality Assessment Model for Estimation of Rice Productivity in Paddy Field
    Youngkyu Hong, Jinwook Kim, Hyucksoo Kim, Junghwan Yoon, Sangphil Lee, Jae E. Yang, Sangho Jeon, and Sungchul Kim
    Soil security has been awarded in national wide because of food security. In order to evaluate soil security, soil quality needs to … + READ MORE
    Soil security has been awarded in national wide because of food security. In order to evaluate soil security, soil quality needs to be assessed utilizing various soil properties. The main purpose of this research was to develop a protocol for soil quality assessment in paddy field and to evaluate correlation between soil quality and rice production in paddy field. Principle component analysis (PCA) was used to select minimum data set (MDS) and soil pH, cation exchange capacity (CEC), soil organic matter (SOM), and available phosphorus (Av. P2O5) was chosen as MDS. Based on database of soil properties, optimized soil quality model was determined. Average soil quality index in paddy field at the period of 1999 - 2015 was 0.35 - 0.50 and soil pH and SOM were high in soil quality index while CEC and Av. P2O5 were low. Correlation analysis showed a high correlation between soil quality index and rice production indicating that developed soil quality assessment tool in this study is suitable for predicting crop productivity. Overall, soil security can be obtained by conserving soil quality and soil properties in agricultural field. Correlation analysis between soil quality index and rice production in paddy field. - COLLAPSE
    28 February 2022
  • Article

    Varying Nitrogen Fertigation for Cucumbers Grown in Greenhouses with Soil of Optimal or High Nutrient Status
    Yang-Min Kim, Chan-Wook Lee, Yo-Sung Song, and Ye-Jin Lee
    The standard growth-stage-based fertigation schedule has provided the weekly supply amount of fertilizer considering the expecting yield with no regard of soil … + READ MORE
    The standard growth-stage-based fertigation schedule has provided the weekly supply amount of fertilizer considering the expecting yield with no regard of soil nutrient status. The study aimed to examine if fertigation with nitrogen applied at a standard rate results in the best cucumber yield in two greenhouses with different soil nutrient levels, i.e. optimal and high. We investigated the nitrogen (N) uptake pattern of cucumbers with the different nitrogen supply levels which included half the standard rate (N0.5), the standard rate (N1) and double the standard rate (N2). In year 2020, the N1 amendment resulted in highest yield in the soil with optimal nutrient level, however, lower N0.5 resulted in higher yield in the high-nutrient soil. In year 2021, there was no statistical difference in the yield by different nitrogen supply levels in both soils with optimal and high nutrient level. Soil NO3-N remained low in the low nutrient soil regardless of the amount of N supplied, but soil NO3-N was high in the high nutrient soil supplied with N2. The Partial Factor Productivity of Nitrogen (PFPN) was highest in the N0.5 and it decreased as N supply increased in the optimal and high nutrient soil. In conclusion, a precise fertigation schedule is needed to be set with the consideration of the soil nutrient status. Soil NO3-N concentrations (mg kg-1) during the growth of spring cucumber decreased below the optimal level (100) in the low soil nutrient greenhouse, however soil NO3-N concentrations fluctuated at the higher values than 70 in the high soil nutrient greenhouse. - COLLAPSE
    28 February 2022
  • Article

    Nutrients Runoff and Rice Growth by Soil Texture and Transplanting Time during Early Maturing Rice Cultivating
    Tae-Gu Lee, Myung-Sook Kim, Sang-Ho Jeon, Ha-il Jung, and Jung-Hun Ok
    The early maturing rice is a species that can be cultivated at various times, such as early, normal season, and late cultivation, … + READ MORE
    The early maturing rice is a species that can be cultivated at various times, such as early, normal season, and late cultivation, depending on the purpose. There are many studies on the characteristics of rice according to the transplanting time for these early maturing rice, but studies on the runoff of nutrients are insignificant. The surface runoff of NH4+-N was the highest among the treatment at 1.337 g m-2 (2020 year) in the Clay Loam (CL) & late cultivation, and the smallest treatment was the Sandy Loam (SL) & normal season cultivation (0.005 g m-2, 2019 year). The highest NO3--N surface runoff was 0.137 g m-2 (2020 year) in the CL & late cultivation. In the case of phosphate, there were more nutrients runoff from late cultivation with large outflows than normal season cultivation. The underground runoff of NH4+-N was the highest among the treatment at 0.147 g m-2 (2020 year) in the SL & late cultivation, and the smallest treatment was the CL & normal season cultivation (0.007 g m-2, 2019 year). The highest NO3--N underground runoff was 2.113 g m-2 (2019 year) in the SL & normal season cultivation. In order to compare rice growth, the dry weight of leaves, shoots, and ears after rice harvest was compared. ear was a little larger in the normal season cultivation than in the late cultivation in 2019 (p < 0.05), but there was no difference in ear according to soil texture and the transplanting time in 2020. There may be differences in nutrient outflow and rice growth depending on the soil texture and transplanting time when cultivating early maturing rice, and the results of this study can be used as basic data on nutrient outflow in paddy when cultivating early maturing rice. The amount of nutrients losses due to underground runoff during cultivation. Year Transplanting time Soil texture Water runoff (mm) Nutrient runoff (g m-2) NH4+-N NO3--N PO43- 2019 Normal CL 91.5 0.007 0.094 0.003 SL 365.4 0.027 2.113 0.005 Late CL 56.7 0.011 0.035 0.003 SL 431.2 0.034 1.301 0.025 2020 Normal CL 329.7 0.012 0.106 0.002 SL 337.1 0.080 0.558 0.016 Late CL 27.5 0.019 0.020 0.001 SL 356.3 0.147 0.218 0.012 CL, clay loam; SL, sandy loam. - COLLAPSE
    28 February 2022
  • Article

    Estimation of Soil Organic Matter Content Using Soil Organic Color Chart and Soil Color Meter SPAD 503
    Byung-Keun Hyun, Yejin Lee, Cheol-Hyun Ryu, and Yuri Cho
    Soil organic matter (SOM) is one of the most representative indicators of soil fertility. In order to quickly estimate the SOM content … + READ MORE
    Soil organic matter (SOM) is one of the most representative indicators of soil fertility. In order to quickly estimate the SOM content through soil color in the field, a soil color chart (AG-1941-Color Chart, University of Illinois Extension, USA) and soil color meter (SPAD 503) were used. The results are summarized as follows. A total of 173 soil samples were analyzed, of which 78 were paddy soil and 95 upland soil (including plastic film house soil). The soil color mater was more useful than the soil color chart in estimating the SOM content. The coefficient of determination of the regression equation for estimating soil organic matter content using the soil color chart was 0.5857*** for upland soil, 0.5460*** for all soil, and 0.3499*** for paddy soil. In the case of upland soils, estimating the SOM content using regression model of upland soil had higher estimating power than using regression equation of all soils. The coefficient of determination of the regression equation for estimating soil organic matter content using a soil color meter was higher in the model divided (R2 = 0.9537***) in to paddy and upland soil than in all soil model (R2 = 0.7738***). When the highest value of SOM content used for model validation was excluded, the coefficient of determination of the existing model was reduced, but the trend was the same. When using the soil color meter, the all soil model decreased from 0.9029 to 0.5723, and from 0.9095 to 0.6879 when dividing the paddy and upland soils. Also, when using the soil color chart, the all soil model was reduced from 0.5246 to 0.2111, and when dividing the paddy and upland soil from 0.5987 to 0.1863. Soil organic matter content estimation model using SPAD 503. - COLLAPSE
    28 February 2022
  • Article

    Prediction of Soil Organic Carbon Contents of Rice Paddies in South-Western Coastal Area of Korea Using Random Forest Models
    Hyun-Jin Park and Woo-Jung Choi
    Random forest models (RFM) are useful in predicting the soil carbon (C) contents because RFM predicts soil C with high accuracy under … + READ MORE
    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 (ECe), 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 ECe, 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. Random forest models can predict soil carbon content with high accuracy under complicated environmental conditions by randomly learning multiple decision trees. - COLLAPSE
    28 February 2022
  • Short Communication

    A Study on the Nutrition Components for Compost Fertilizers in 2020 to 2021
    Jae-Hong Shim, Seong-Heon Kim, Yun-Hae Lee, Soon-Ik Kwon, and Seong Jin Park
    This study was conducted to confirm the necessity of a fertilizer labeling with the nutrition components. The contents of total nitrogen (T-N), … + READ MORE
    This study was conducted to confirm the necessity of a fertilizer labeling with the nutrition components. The contents of total nitrogen (T-N), phosphorus (T-P2O5), and potassium (T-K2O) are important factors to determine the application rate of the organic fertilizers to arable lands. The mean values of total nitrogen, phosphorus, and potassium recorded in compost fertilizer in 2020 and 2021 were 1.91%, 2.40%, and 2.33%, respectively. Comparatively, the mean values of T-N, T-P2O5, and T-K2O increased by 0.23%p, 090%p, and 0.91%, respectively, relative to the respective mean concentrations in 2016. The nutrient contents were observed to the within the range of 1.5 to 2.0% distributed in 306 samples (39.6%), 206 samples (26.6%), and 191 samples (24.7%), for T-N, P2O5, K2O, respectively. There was no significant change in fertilizer nutrient composition (T-N, T-P2O5, T-K2O) and chemical properties (pH, EC, water content, organic matter, NO3-N, NH4-N) during storage period. Mean contents of total nitrogen (T-N), phosphorus (T-P2O5), and potassium (T-K2O) in compost fertilizers in 2020 and 2021 (n = 773). - COLLAPSE
    28 February 2022
  • Short Communication

    Effects of Protaetia brevitarsis Larvae Manure Application on Lettuce Growth and Soil Chemical Properties
    Kyong-Hee Joung, Jong-Won Kim, Seul-Bi Lee, Da-Hyun Jang, Byung-Man Yoo, Sung-Mun Bea, Young-Ho Chang, Young Han Lee, and Dong-Cheol Seo
    Agricultural land application of Protaetia brevitarsis larvae manure (PM) is a common process that improves soil fertility and increases crop production. The … + READ MORE
    Agricultural land application of Protaetia brevitarsis larvae manure (PM) is a common process that improves soil fertility and increases crop production. The objective of this study was to evaluate the effects of PM on the growth of lettuce and soil chemical properties. Lettuce was planted in silt loam soil amended with three rates of PM 0 (CF), 540 (CFP1), and 1,080 (CFP2) kg 10a-1 with chemical fertilizer (20.0 kg 10a-1 N, 5.9 kg 10a-1 P2O5, and 12.8 kg 10a-1 K2O) and animal mixed compost 540 kg 10a-1 with chemical fertilizer (CFC). Increasing rates of PM caused a significant increase in soil organic matter content and yield of lettuce compared to CF (P < 0.05). Our findings suggest that Protaetia brevitarsis larvae manure can be used as an organic fertilizer to raise crops. Effect of Protaetia brevitarsis larvae manure application on lettuce growth. Treatments Leaf length (cm) Leaf width (cm) Leaf number (no. plant-1) Fresh weight (g plant-1) Yield (kg 10a-1) CF 24.1 b 16.8 b 23.0 b 239 c 3,898 c CFC 24.3 ab 16.9 b 23.6 a 261 b 4,250 b CFP1 24.7 a 16.9 b 23.6 a 262 b 4,255 b CFP2 24.3 ab 18.2 a 23.5 a 287 a 4,676 a CF, chemical fertilizer; CFC, chemical fertilizer + animal mixed compost 540 kg 10a-1; CFP1, chemical fertilizer + Protaetia brevitarsis larvae manure 540 kg 10a-1; CFP2, chemical fertilizer + Protaetia brevitarsis larvae manure 1,080 kg 10a-1. Means followed by different letters within the same row are significantly different at significance level α = 0.05 according to Duncan’s multiple range test. - COLLAPSE
    28 February 2022
  • Short Communication

    Determination of Dissolved Organic Carbon Concentrations Using UV-Visible Absorbance for Water Samples in a Rural Watershed, the Republic of Korea
    Young-Jae Jeong, Su-Jin Lee, Nuri Baek, Hyun-Jin Park, and Woo-Jung Choi
    Dissolved organic carbon (DOC) in water discharged from agricultural land is one of the indicators of water pollution. As aromatic compounds, which … + READ MORE
    Dissolved organic carbon (DOC) in water discharged from agricultural land is one of the indicators of water pollution. As aromatic compounds, which is the main component of DOC, absorb light in the UV-visible region, the intensity of UV-visible absorbance is correlated with DOC concentrations in water. In this study, a regression equation between DOC concentration of reference samples (n = 12, extracts of manure composts) and UV-visible absorbance was established. The applicability of the established equation was tested using water samples (n = 44) collected from a rural watershed in Jeonnam, South Korea. The peak absorbance of DOC in the compost extracts was detected at 275 nm, and was positively correlated (R2 = 0.99, P < 0.001) with DOC concentrations. Although the DOC concentrations of water samples determined using the equation were lower than those measured by TOC analysis by about 15%, the estimated DOC concentrations were strongly (R2 = 0.96, RMSE = 0.97, P < 0.001) correlated with measured DOC concentrations. Our study suggests that the DOC concentrations of watershed can be estimated by measuring the UV-visible absorbance method. The peak of UV-visible absorbance of dissolved organic carbon (DOC) in the compost extracts with different DOC concentrations was detected at 275 nm among the range of 200 - 500 nm. - COLLAPSE
    28 February 2022