Soil physical property estimation from soil strength and apparent electrical conductivity sensor data

Cho, Yongjin,Sudduth, Kenneth A.,Chung, Sun-Ok Elsevier 2016 Biosystems engineering Vol.152 No.-

<P>Proximal soil sensing is an attractive approach for quantifying soil properties, but many currently available sensors do not respond to a single soil property. For example, soil strength and apparent electrical conductivity (EC<SUB>a</SUB>) sensor measurements are significantly affected by soil texture, bulk density (BD), and water content (WC). The objective of this study was to explore the potential for estimating soil texture, BD, and WC using combinations of sensor-based soil strength and EC<SUB>a</SUB> data obtained from sites with varying soil physical properties. Data collected from three research sites in Missouri included on-the-go horizontal soil strength at five depths up to 0.5 m on a 0.1-m interval, cone index measurements at the same depths, EC<SUB>a</SUB> measured by a Veris 3100, and depth-dependent, laboratory-determined soil properties. An EC<SUB>a</SUB> model inversion approach was used to generate layer EC values corresponding to the depth increments of the other variables. Fits of models using EC to estimate WC were variable (R<SUP>2</SUP> = 0.31–0.79). Best fitting BD estimation models (R<SUP>2</SUP> = 0.11–0.55) generally included EC, but soil strength was included in fewer than half of the models. BD model fits were improved considerably by adding lab-measured WC to the model (R<SUP>2</SUP> = 0.30–0.86), suggesting the need for a WC sensor. Soil clay texture fraction models based on EC and WC fit well (R<SUP>2</SUP> = 0.80–0.93). This study showed the potential of combining data from multiple mobile proximal sensors to estimate important soil physical properties.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Soil physical properties were estimated from soil sensor measurements. </LI> <LI> Properties examined were water content (WC), bulk density, and clay fraction. </LI> <LI> Best WC estimates used both soil strength and apparent electrical conductivity (EC<SUB>a</SUB>). </LI> <LI> Best bulk density estimates included lab-measured water content in the model. </LI> <LI> Clay texture fraction was well-estimated at most measurement depths by EC<SUB>a</SUB>. </LI> </UL> </P>

(Original Articles) [Environment] Contrasting grain crop and grassland management effects on soil quality properties for a north-central Missouri claypan soil landscape

JUNG, Won Kyo,KITCHEN, Newell R.,SUDDUTH, Kenneth A.,KREMER, Robert J. Society of the Science of Soil and Manure, Japan 2008 Soil science and plant nutrition Vol.54 No.6

Crop management has the potential to either enhance or degrade soil quality, which in turn impacts on crop production and the environment. Few studies have investigated how crop management affects soil quality over different landscape positions. The objective of the present study was to investigate how 12 years of annual cropping system (ACS) and conservation reserve program (CRP) practices impacted soil quality indicators at summit, backslope and footslope landscape positions of a claypan soil in north-central Missouri. Claypan soils are particularly poorly drained because of a restrictive high-clay subsoil layer and are vulnerable to high water erosion. Three replicates of four management systems were established in 1991 in a randomized complete block design, with landscape position as a split-block treatment. The management systems were investigated: (1) annual cropping system 1 (ACS1) was a mulch tillage (typically ≥ 30% of soil covered with residue after tillage operations) corn (Zea mays L.)?soybean (Glycine max (L.) Merr.) rotation system, (2) annual cropping system 2 (ACS2) was a no-till corn?soybean rotation system, (3) annual cropping system 3 (ACS3) was a no-till corn?soybean?wheat (Triticum aestivum L.) rotation system, with a cover crop following wheat, (4) CRP was a continuous cool-season grass and legume system. In 2002, soil cores (at depths of 0?7.5, 7.5?15 and 15?30 cm) were collected by landscape position and analyzed for physical, chemical and biological soil quality properties. No interactions were observed between landscape and crop management. Relative to management effects, soil organic carbon (SOC) significantly increased with 12 years of CRP management, but not with the other management systems. At the 0?7.5-cm soil depth in the CRP system, SOC increased over this period by 33% and soil total nitrogen storage increased by 34%. Soil aggregate stability was approximately 40% higher in the no-till management systems (ACS2 and ACS3) than in the tilled system (ACS1). Soil aggregation under CRP management was more than double that of the three grain-cropping systems. Soil bulk density at the shallow sampling depth was greater in ACS3 than in ACS1 and ACS2. In contrast to studies on other soil types, these results indicate only minor changes to claypan soil quality after 12 years of no-till management. The landscape had minor effects on the soil properties. Of note, SOC was significantly lower in the 7.5?15-cm soil depth at the footslope compared with the other landscape positions. We attribute this to wetter and more humid conditions at this position and extended periods of high microbial activity and SOC mineralization. We conclude that claypan soils degraded by historical cropping practices will benefit most from the adoption of CRP or CRP-like management.

Spatial Variability of Soil Properties using Nested Variograms at Multiple Scales

( Sun Ok Chung ),( Kenneth A Sudduth ),( Scott T Drummond ),( Newell R Kitchen ) 한국농업기계학회 2014 바이오시스템공학 Vol.39 No.4

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short- range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

Disposable Nitrate-Selective Optical Sensor Based on Fluorescent Dye

Kim, Gi-Young,Sudduth, Kenneth A.,Grant, Sheila A.,Kitchen, Newell R. Korean Society for Agricultural Machinery 2012 바이오시스템공학 Vol.37 No.3

Purpose: This study was performed to develop a simple, disposable thin-film optical nitrate sensor. Methods: The sensor was fabricated by applying a nitrate-selective polymer membrane on the surface of a thin polyester film. The membrane was composed of polyvinylchloride (PVC), plasticizer, fluorescent dye, and nitrate-selective ionophore. Fluorescence intensity of the sensor increased on contact with a nitrate solution. The fluorescence response of the optical nitrate sensor was measured with a commercial fluorospectrometer. Results: The optical sensor exhibited linear response over four concentration decades. Conclusions: Nitrate ion concentrations in plant nutrient solutions can be determined by direct optical measurements without any conditioning before measurements.

Research Articles : Information Processing and Interdisciplinary Technology ; Disposable Nitrate-Selective Optical Sensor Based on Fluorescent Dye

( Gi Young Kim ),( Kenneth A. Sudduth ),( Sheila A. Grant ),( Newell R. Kitchen ) 한국농업기계학회 2012 바이오시스템공학 Vol.37 No.3

Purpose: This study was performed to develop a simple, disposable thin-film optical nitrate sensor. Methods: The sensor was fabricated by applying a nitrate-selective polymer membrane on the surface of a thin polyester film. The membrane was composed of polyvinylchloride (PVC), plasticizer, fluorescent dye, and nitrate-selective ionophore. Fluorescence intensity of the sensor increased on contact with a nitrate solution. The fluorescence response of the optical nitrate sensor was measured with a commercial fluorospectrometer. Results: The optical sensor exhibited linear response over four concentration decades. Conclusions: Nitrate ion concentrations in plant nutrient solutions can be determined by direct optical measurements without any conditioning before measurements.

Spatial Variability of Soil Properties using Nested Variograms at Multiple Scales

Chung, Sun-Ok,Sudduth, Kenneth A.,Drummond, Scott T.,Kitchen, Newell R. Korean Society for Agricultural Machinery 2014 바이오시스템공학 Vol.39 No.4

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

On-the-go Soil Strength Profile Sensor to Quantify Spatial and Vertical Variations in Soil Strength

Chung, Sun-Ok,Sudduth, Kenneth A. Korean Society for Agricultural Machinery 2005 Agricultural and Biosystems Engineering Vol.6 No.2

Because soil compaction is a concern in crop production and environmental pollution, quantification and management of spatial and vertical variability in soil compaction for soil strength) would be a useful aspect of site -specific field management. In this paper, a soil strength profile sensor (SSPS) that could take measurements continuously while traveling across the field was developed and the performance was evaluated through laboratory and field tests. The SSPS obtained data simultaneously at 5 evenly spaced depths up to 50 em using an array of load cells, each of which was interfaced with a soil-cutting tip. Means of soil strength measurements collected in adjacent, parallel transects were not significantly different, confirming the repeatability of soil strength sensing with the SSPS. Maps created with sensor data showed spatial and vertical variability in soil strength. Depth to the restrictive layer was different for different field locations, and only 5 to 16% of the tested field areas were highly compacted.

Analysis of Spatial Variability in a Korean Paddy Field Using Median Polish Detrending

Chung, Sun-Ok,Jung, In-Kyu,Sung, Je-Hoon,Sudduth, Kenneth A.,Drummond, Scott T. Korean Society for Agricultural Machinery 2008 바이오시스템공학 Vol.33 No.5

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

논문 : 정보처리 및 복합기술 ; 광반사를 이용한 한국 논 토양 특성 추정

정선옥 ( S. O Chung ),정기열 ( K. Y. Jung ),( Kenneth A. Sudduth ) 한국농업기계학회 2011 바이오시스템공학 Vol.36 No.1

An optical sensing approach based on diffuse reflectance has shown potential for rapid and reliable on-site estimation of soil properties. Important sensing ranges and the resulting regression models useful for soil property estimation have been reported. In this study, a similar approach was applied to investigate the potential of reflectance sensing in estimating soil properties for Korean paddy fields. Soil cores up to a 65-cm depth were collected from 42 paddy fields representing 14 distinct soil series that account for 74% of the total Korean paddy field area. These were analyzed in the laboratory for several important physical and chemical properties. Using air-dried, sieved soil samples, reflectance data were obtained from 350 to 2500 nm on a 3 nm sampling interval with a laboratory spectrometer. Calibrations were developed using partial least squares (PLS) regression, and wavelength bands important for estimating the measured soil properties were identified. PLS regression provided good estimations of Mg (R2=0.80), Ca (R2=0.77), and total C (R2=0.92); fair estimations of pH, EC, P2O5, K, Na, sand, silt, and clay (R2 = 0.59 to 0.72); and poor estimation of total N. Many wavelengths selected for estimation of the soil properties were identical or similar for multiple soil properties. More important wavelengths were selected in the visible-short NIR range (350-1000 nm) and the long NIR range (1800-2500 nm) than in the intermediate NIR range (1000-1800 nm). These results will be useful for design and application of in-situ close range sensors for paddy field soil properties.

Research Articles : Characterization of Cone Index and Tillage Draft Data to Define Design Parameters for an On-the-go Soil Strength Profile Sensor

( Sun Ok Chung ),( Kenneth A. Sudduth ) 한국농업기계학회 2004 Agricultural and Biosystems Engineering Vol.5 No.1