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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #357767

Title: A smartphone-based application for estimating soil color

Author
item Salley, Shawn
item Maynard, Jonathan
item Herrick, Jeffrey - Jeff

Submitted to: International Soil Science Society Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 9/19/2018
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Color is one of soils most distinguishing characteristic. Soil color is primarily used to classify, interpret, and differentiate soils due to the strong relationship between color and important soil properties, including organic matter, mineralogy, moisture content, drainage class, and fertility. Routine estimation of soil color is regularly accomplished by subjective perception between a soil sample and chips of standard colors, of which the Munsell Soil Color Chart is the most familiar to soil scientists. With the rise of global smartphone ubiquity, there has been an increasing demand for smartphone-based applications to estimate soil properties, including color. While most proposed smartphone-based apps use the phone’s camera under controlled illumination conditions or the use of proximal sensors, recent work has suggested that soil color estimates can reliably be determined under natural, variable outdoor conditions. This is achieved by calibrating directly to an in-frame color standard placed next to a soil sample. Our study tested multiple color standards across a full array of hues ranging from low-to-high values and chromas. We demonstrate that a simple yellow sticky note, whose “true” color was determined by a color spectrophotometer, can estimate color within a similar accuracy and tolerance as a calibrated grey-scaled card. We propose that this color estimation is within the precision and tolerance reported by trained soil scientists. Our presentation will describe the details of the SoilColor module and its implementation into the Land Potential Knowledge System (LandPKS) smartphone app, as well as discuss its utility for the citizen soil scientist.