• 한국환경농학회:학술대회논문집
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• 2011.07a
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• pp.177-187
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• 2011

This study was conducted to determine some physical and chemical properties of the soil and their relationship to spectroscopic-based (visible range) analytical methods while evaluating soil organic matter fractions and soil quality in degraded and non-degraded soils in a wide range of environments. Soil samples were collected from the different landscape positions of cultivated and noncultivated soils, and the latter from the same landscape positions but with different vegetation, at Songco, Lantapan, Bukidnon. The physical and chemical properties of the soils were determined at the SPAL, CMU, Musuan, Bukidnon while the metagenomic properties were determined at the Laboratory of the University of Missourri, Missourri, USA. Bulk density and air dry soil strength values of the soils from the cultivated areas were generally higher than those of the uncultivated areas. Also, soils at the summit generally had lower bulk density and soil strength values than the other landscape positions. Moreover, soils planted to camote (Ipomoea batatas) had higher bulk density and soil strength values compared to soils grown to pepper under the trees. Exchangeable calcium (Ca), magnesium (Mg), and potassium (K) and cation exchange capacity (CEC) of the soils were generally higher in uncultivated areas than those of the cultivated areas. A similar trend was observed for the potassium permanganate ($KMnO_4$)-oxidizable organic C contents determined by spectroscopic method and the total C contents determined by the Walkley-Black method. The $KMnO_4$-oxidizable organic C contents determined by spectroscopic method and the total C contents determined by the Walkley-Black method were closely related ($r=0.631^{**}$). Hence, the former method shows promise in assessing soil quality as it is a rapid test, relatively low cost and can be distributed as a field kit either with a portable spectrometer or with a color chart.

• Near Infrared Analysis
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• v.1 no.1
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• pp.37-41
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• 2000

The purpose of this research was to develop a the reflection technique with near infrared (NIR) radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1100 to 2500nm with an InfraAlyzer 500 (Bran & Luebbe Co.). Over 400 soil sample from fields of different crops and land-use over Youngnam and Honam regions were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter (OM) and total nitrogen (T-N) of the soils. Multiple linear regression (MLR) was used to evaluate the correlation of NIR spectroscopy method. Reflection pattern of NIR spectra for finely sized sample (<0.5mm) and coarsely sized soil(<2mm) did not show much difference. The results showed that NIR spectroscopy and coarsely sized soil (<2mm) did not show much difference. The results showed that NIR spectroscopy could be used as a routine soil testing method in estimating OM, moisture, T-N in soil samples simultaneously.

• Near Infrared Analysis
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• v.1 no.2
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• pp.35-39
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• 2000

The purpose of this research was to find out suitable soil sample preparation and sample holding tools for NIR reflection radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1,100 to 2,500nm with an InfraAlyzer 500(Bran+Luebbe Co.). Coarse(2.0mm) and fine(0.5mm) soil sample and various sample holding tools were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter and total nitrogen of the soils. Multiple linear regression was used to obtain the best correlation of NIR spectroscopy method. Correlation of NIR spectroscopy method. Correlation of NIR spectra for finely and coarsely sized soil did not show much difference. The standard errors of prediction(SE) using different types of sample holding tools for organic matter, total nitrogen and soil moisture were better than 0.765, 0.041 and 0.63% respectively. From the results it can be concluded that NIR spectroscopy with flow type cell could be used as a fast routine testing method in quantitative determination of organic matter, total nitrogen and soil moisture.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.236-245
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• 2000

The feasibility of precision farming for small sized fields was studied by determining fertilizing amount of nitrogenous and calcareous to a cite specific region. A detailed soil survey at three experimental fields of 672㎡, 300㎡ and 140㎡ revealed a considerable spatial variation of the pH and organic matter(OM) levels. Soil organic matter was measured using Walkley-Black method and soil pH was measured with a pH sensor. Soil sample was obtained by Grid Node Sampling Method. The soil sampling depth was 10 - 20 cm from the soil surface. To display soil nutrient variation, a soil map was made using Geographic Information System (GIS) software. In soil mapping, soil data between nodes was interpolated using Inverse Distance Weighting (IDW) method. The variation was about 1 - 1.8 in pH value and 1.4 -7 % in OM content. Fertilizing Amount of nitrogenous and calcareous was determined by the fertilizing equation which was proposed by National Institute of Agricultural Science and Technology.(NIAST). The variation of fertilizing amount was about 3 - 11 kg/10a in nitrogenous and 70 - 140 kg/10a in calcareous. The results showed a feasibility of precision fertilizing for small size fields.

• Journal of Biosystems Engineering
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• v.25 no.3
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• pp.241-250
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• 2000

The feasibility of precision fertilizing for small size fields was studied by determining fertilizing amount of nitrogenous and calcareous to a cite specific region. A detailed soil survey at three experimental fields of $672m^2$, $300m^2$ and $140m^2$ revealed a considerable spatial variation of the pH and organic matter(OM) levels. Soil organic matter was measured using Walkley-Black method and soil pH was measured with a pH sensor. Soil sample was obtained by Grid Node Sampling Method. The soil sampling depth was 10∼20 cm from the soil surface. To display soil nutrient variation, a soil map was made using Geographic Information System (GIS) software. In soil mapping, soil data between nodes was interpolated using Inverse Distance Weighting (IDW) method. The variation was about 1∼1.8 in pH value and 1.4∼7% in OM content. Fertilizing Amount of nitrogenous and calcareous was determined by th fertilizing equation which was proposed by National Institute of Agricultural Science and Technology(NIAST). The variation of fertilizing amount was about 3∼11 kg/10a in nitrogenous and 70∼140 kg/10a in calcareous. The results showed a feasibility of precision fertilizing for small size fields.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.4
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• pp.497-502
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• 2012

This study investigates the prediction of soil OM on Korean soils using the Visible-Near Infrared (Vis-NIR) spectroscopy. The ASD Field Spec Pro was used to acquire the reflectance of soil samples to visible to near-infrared radiation (350 to 2500 nm). A total of 503 soil samples from 61 Korean soil series were scanned using the instrument and OM was measured using the Walkley and Black method. For data analysis, the spectra were resampled from 500-2450 nm with 4 nm spacing and converted to the $1^{st}$ derivative of absorbance (log (1/R)). Partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil OM. Regression rules model estimates the target value by building conditional rules, and each rule contains a linear expression predicting OM from selected absorbance values. The regression rules model was shown to give a better prediction compared to PLSR. Although the prediction for Andisols had a larger error, soil order was not found to be useful in stratifying the prediction model. The stratification used by Cubist was mainly based on absorbance at wavelengths of 850 and 2320 nm, which corresponds to the organic absorption bands. These results showed that there could be more information on soil properties useful to classify or group OM data from Korean soils. In conclusion, this study shows it is possible to develop good prediction model of OM from Korean soils and provide data to reexamine the existing prediction models for more accurate prediction.