Analysis of the influence of soil temperature and soil surface conditions on soil moisture estimation using the Theta Probe

Soil moisture is an important component of numerous systems, influencing crop development, and runoff and infiltration partitioning, among other things. However, due to its spatial and temporal variability, it is difficult to estimate soil moisture consistently using conventional techniques such as gravimetric sampling, which is point-based and time-consuming. Therefore, to overcome this drawback in soil moisture estimation and mapping, and to facilitate its measurement spatially and temporarily, remote sensing in microwave, visible, near infrared and short wave infrared is being explored and is proving to be a promising technique. But to develop models using spectral data there is a need to validate these models using ground truth data collected using gravimetric measurements and various dielectric and capacitance probes. Theta probe is one such dielectric probe, which is widely used by the remote sensing community. Not only does soil surface conditions change the response of reflectance data in various spectral ranges but has been observed to influence the measurements from Theta probe. As a part of this study an attempt has been made to understand the influence of soil temperature, roughness and crusting on Theta probe measurements by analyzing moisture content as a function of time. A nonlinear relationship was observed between the actual moisture content and Theta probe soil moisture content. A t-test conducted on the estimate of temperature concluded that the effect of temperature on Theta probe measurements was insignificant, but there is a possibility that soil surface conditions involving soil roughness and crusting could be a reason for observed nonlinearity between actual and Theta probe measurements. Therefore, future work is suggested to test the feasibility of using Theta probe under different soil surface conditions

Aeration system design for cone-bottom round bins

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311.Biosystems and Agricultural Engineerin

Quality Estimation of Canola Using Machine Vision and Vis-nir Spectroscopy

Canola is mainly graded either by visual inspection or by smelling. These methods are subjective in nature and are bound to cause errors while deciding the grade of canola. To test canola for amount of erucic acid present the sample needs to be sent to a laboratory for testing through wet chemical analysis. This is a time consuming process. An electronic method that can quantify amount of dockage, presence of distinctly green and heat treated seeds, distinguish samples on the basis of erucic acid, its free fatty acid content and PV, would not only be less time consuming but also would be a more reliable method to grade canola samples. Findings and Conclusions: 1. Canola samples cannot be classified on the basis of total dockage present using L and RGB data obtained from flat-bed scanner. Inclusion of morphological and textural features would improve the classification accuracy. 2. Machine vision can be considered as a potential method to grade canola on the basis of good, distinctly green and heat damagedBiosystems and Agricultural Engineerin

Aeration systems for flat-bottom round bins

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311.Biosystems and Agricultural Engineerin

Analysis of the influence of soil temperature and soil surface conditions on soil moisture estimation using the Theta Probe

Soil moisture is an important component of numerous systems, influencing crop development, and runoff and infiltration partitioning, among other things. However, due to its spatial and temporal variability, it is difficult to estimate soil moisture consistently using conventional techniques such as gravimetric sampling, which is point-based and time-consuming. Therefore, to overcome this drawback in soil moisture estimation and mapping, and to facilitate its measurement spatially and temporarily, remote sensing in microwave, visible, near infrared and short wave infrared is being explored and is proving to be a promising technique. But to develop models using spectral data there is a need to validate these models using ground truth data collected using gravimetric measurements and various dielectric and capacitance probes. Theta probe is one such dielectric probe, which is widely used by the remote sensing community. Not only does soil surface conditions change the response of reflectance data in various spectral ranges but has been observed to influence the measurements from Theta probe. As a part of this study an attempt has been made to understand the influence of soil temperature, roughness and crusting on Theta probe measurements by analyzing moisture content as a function of time. A nonlinear relationship was observed between the actual moisture content and Theta probe soil moisture content. A t-test conducted on the estimate of temperature concluded that the effect of temperature on Theta probe measurements was insignificant, but there is a possibility that soil surface conditions involving soil roughness and crusting could be a reason for observed nonlinearity between actual and Theta probe measurements. Therefore, future work is suggested to test the feasibility of using Theta probe under different soil surface conditions.</p

Analysis of the Influence of Soil Roughness, Surface Crust and Soil Moisture on Spectral Reflectance

Soil moisture is an important component of numerous systems, influencing crop development, and runoff and infiltration partitioning, among other things. However, due to its spatial and temporal variability, it is difficult to estimate soil moisture consistently using conventional techniques such as gravimetric sampling, which is point-based and time-consuming. Therefore, to overcome this drawback in soil moisture estimation and mapping, and to facilitate its measurement spatially and temporarily, remote sensing is a promising technique. Measurement of soil surface reflectance in the visible and near infrared (VIS/NIR) may be used for this purpose. However, soil reflectance within this spectral range is affected by numerous factors, including soil surface roughness and the presence of soil crust. Thus, in order to determine the utility of VIS/NIR remote sensing for surface soil moisture estimation, roughness and crusting must be considered. In this study, we quantify the effects of these three components (moisture, roughness, and degree of crusting) on soil surface reflectance within the spectral range of 450 nm to 1000 nm in order to determine the extent to which moisture can be estimated under different soil surface conditions.</p