Kyou Seung Lee

Wavelength Identification for Reflectance Estimation of Surface and Subsurface Soil Properties

Optical diffuse reflectance sensing is a potential approach for rapid and reliable on-site estimation of soil properties. In this study, reflectance sensing in visible (VIS) and near-infrared (NIR) wavelengths was combined with partial least squares (PLS) regression to estimate surface and subsurface soil properties, and wavelength bands important for estimating soil properties were identified. Soil cores (120 cm deep) from ten fields in five states in the US cornbelt were segmented by horizon and analyzed in laboratory for texture (sand, silt, and clay fractions), cation exchange capacity (CEC), Ca, Mg, K, pH, total and organic C, and total N. Using air-dried, sieved soil samples, reflectance data were obtained from 350 to 2500 nm with a laboratory spectrometer. Over all soil horizons, cross-validated predictions of organic C were good (R2=0.87, RPD (the ratio of standard deviation to standard error of prediction) =2.78), while predictions of clay fraction, CEC, and pH were also acceptable (0.63< R2<0.79, RPD about 2). Calibrations restricted to the surface horizon were somewhat better, with R2 values from 0.81 to 0.85 and RPD values from 2.08 to 2.73 for clay fraction, Ca, CEC, and organic C. Important wavelengths were 440-600 nm and 1780-2460 nm for clay; 470-600, 965, and 1750-2330 nm for CEC; and 450-465, 965, 1409, and 1775-2200 nm for organic C. These results will be useful in the design and application of in-situ close range sensors for soil physical and chemical properties.

Determination of Tillage Depth Based on Physical Properties of Soil for Rice Production in Korea

Compaction is becoming a great concern in crop production and the environment. Recently, three has been a need of field management based on site-specific conditions to improve sustainability of agriculture and reduce environmental damage. In the study, soil management or tillage depth was recommended nondestructively based on cone index profiles for typical Korean rice paddy fields. Field variables related to tillage, soil strength, rice growth, and other soil physical properties showed considerable spatial and vertical variations as well as significant (α<0.1) correlations among them. Cone index profiles observed also varied by field sites, and maximum cone index and depth to the maximum cone index showed significant (α<0.1) correlation with tilled depth as well as rice growth and other field variables. When soil management was recommended based on CI measurements, 13.4, 16.8, and 95.3% of the total surveyed areas, and 10.6, 18.9, and 51.6% of the total soil volume were chosen for management depth of 10, 20, 40 cm, respectively, indicating that soils of many field sites would not restrict rice growth. It was concluded that the concept of site-specific soil management based on soil conditions could save labor, time, machine use, and energy.

Development of a Real-Time Measurement System for Horizontal Soil Strength

Purpose: Accurate monitoring of soil strength is a key technology applicable to various precision agricultural practices. Soil strength has been traditionally measured using a cone penetrometer, which is time-consuming and expensive, making it difficult to obtain the spatial data required for precision agriculture. To improve the current, inefficient method of measuring soil strength, our objective was to develop and evaluate an in-situ system that could measure horizontal soil strength in real-time, while moving across a soil bin. Methods: Multiple cone-shape penetrometers were horizontally assembled at the front of a vertical plow blade at intervals of 5 cm. Each penetrometer was directly connected to a load cell, which measured loads of 0-2.54 kN. In order to process the digital signals from every individual transducer concurrently, a microcontroller was embedded into the measurement system. Wireless data communication was used between a data storage device and this real-time horizontal soil strength (RHSS) measurement system travelling at 0.5 m/s through an indoor experimental soil bin. The horizontal soil strength index (HSSI) measured by the developed system was compared with the cone index (CI) measured by a traditional cone penetrometer. Results: The coefficient of determination between the CI and the HSSI at depths of 5 cm and 10 cm (

Improvement of Shade Structures for Ginseng Cultivation

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Evaluation methods to verify the improvements in measuring soil physical properties by new fusion device using geostatistical analysis

Purpose: Using agricultural machinery was not easy in the conventional shading structure, specified as a standard facility by standard cultivation methods for ginseng. Thus, this study desi gned the new types of facility allowing machine access by modifying the conventional type. Methods: Two types of facility (i.e. wide roof type and long & short roof type) were designed and installed in an experimental site to evaluate its growing environments and applicability of riding-type cultivator. Results: From the results of incoming light measurement, all three types (i.e. two new types and a conventional type) of shading structures blocked the incoming light after 9:00 am. The temperature distribution inside the new types was similar with the one in the conventional type, so the growth of ginseng was in good condition in all three types of facility. The riding-type cultivator was operated well with the low speed first gear of 0.13 m/s in the new types. However, a long & short typed roof needs to be raised 18 cm height in order to use the cultivator. Conclusions: With the results of this study, the new types of roof can be used in the ginseng farm in that they satisfied the growing environments for ginseng and the needs for agricultural mechanization.

Development of Autonomous Sprayer Considering Tracking Performance on Geometrical Complexity of Ground in Greenhouse

Abstract. In our previous study, a new device for measuring soil cone index (CI) was developed in order to replace the conventional devices. Although basic experiments at various field conditions had proved that the device was suitable to replace the conventional device, the improvements in measuring soil CI by new device were not sufficiently evaluated. One of the most major difficulty could be the absence of promising datasets to be referenced due to both spatial variations and the limitation of spatial frequency of measurement. In this study, evaluation methods based on geostatistical analysis were investigated and compared to verify the improvements and effectiveness by new device. Basically,spatial interpolation method using various algorithms and nugget estimation from semi-variogram method were investigated. Additionally, phase correlation method was investigated to compare relative consistency between spatial variations from different measuring depths. As a result, estimated nugget was some or less than 5% and phase correlation index was some or higher than 3% in every case with comparison analysis between the conventional and new device. The improvement and effectiveness in the developed measuring device could be proved by results from both of methods. Based on the results, the proposed methodology could be useful to evaluate the performance of a similar kind of measuring device that has to process spatial variations, e.g., soil water content and chemical properties in field.

SAMPLING AND CALIBRATION REQUIREMENTS FOR SOIL PROPERTY ESTIMATION USING NIR SPECTROSCOPY

Purpose: Some of the most representative approaches are to apply next generation technologies to save energy consumption, fully automated control system to appropriately maintain environmental conditions, and autonomous assistance system to reduce labor load and ensure operator’s safety. Nevertheless, improvement of upcoming method for soil cultured greenhouse has not been sufficiently achieved. Geometrical complexity of ground in protected crop cultivation might be one of the most dominant factors in design of autonomous vehicle. While there is a practical solution fairly enough to promise an accurate travelling, such as autonomous sprayer guided by rail or induction coil, for various reasons including the limitation of producer’s budget, the previously developed sprayer has not been widely distributed to market. Methods: In this study, we developed an autonomous sprayer considering travelling perfo rmance on geometrical complexity of ground in soil cultured greenhouse. To maintain a stable travelling and to acquire a real time feedback, common wire with 80 mm thick and body frame and sprayer boom. To evaluate performance of the prototype, tracking performance, climbing performance and spraying boom’s uniform leveling performance were individually evaluated by corresponding experimental tests. Results: The autonomous guidance system was proved to be sufficiently suitable for accurate linear traveling with RMS as lower than approximately 10 cm from designated path. Also the prototype could climb 10° of ground’s slope angle with 40 kg of water weight. Uniform leveling of spraying boom was succe ssfully performed within 0.5° of sprayer boom’s slope. Conclusions: Considering more complex pathways and coarse ground conditions, evaluations and improvements of the prototype should be performed for promising reliability to commercialization.

Sampling and Calibration Requirements for Soil Property Estimation Using Reflectance Spectroscopy

Soil physical and chemical properties are important in crop production since they control the availability of plant water and nutrients. Optical diffuse reflectance sensing is a potential approach for rapid and reliable on-site estimation of soil properties. One issue with this sensing approach is whether additional calibration is necessary when the sensor is applied under conditions (e.g., soil types or ambient conditions) different from those used to generate an initial calibration, and if so how many sample points are required in this additional calibration. In this study, these issues were addressed using data from 10 fields from 5 states in the north-central USA, selected to represent ranges in climate, soil, and landscape characteristics. Results showed that data from soil regions and horizons with variations spanning those expected in sensor use should be included in the initial calibration of a sensor. Otherwise, modification of the initial sensor calibration with a minimum of 8 to 12 sample points for each new soil region and horizon would be needed. These results will provide useful guidelines for calibration and field application of an optical diffuse reflectance sensor to estimate soil properties.

Development of Threshing Machine for Shatter-Resistant Sesame

Optical diffuse reflectance sensing is a potential approach for rapid and reliable on-site estimation of soil properties. One issue with this sensing approach is whether additional calibration is necessary when the sensor is applied under conditions (e.g., soil types or ambient conditions) different from those used to generate an initial calibration, and if so, how many sample points are required in this additional calibration. In this study, these issues were addressed using data from 10 fields from 5 states in the north-central USA. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination (R2) and RPD, the ratio of standard deviation to RMSEP. When sample data from a field in question were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.16 to 1.78 for profile data and 0.02 to 1.58 for surface soil data, compared with results from calibration models not including data from the test field (calibration without field-specific information). Including some samples from the test field (hybrid calibration) generally increased RPD by 0.7 to 1.5 with 6 to 15 sample points, with little further improvement given additional points. Using test field points as a bias adjustment (two-stage calibration) increased RPD by 0.1 to 0.2 with 2 to 3 sample points for profile data, and by 0.3 to 0.7 with 5 to 7 sample points for surface data. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.