Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Low-Cost Microcontroller-Based Device to Measure Kaolin Clay Concentrations for ISO Sprayer Cleanout TestsPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: Applied Engineering in Agriculture. 38(1): 135-143. (doi: 10.13031/aea.14764) @2022Authors: Hongyoung Jeon, Heping Zhu Keywords: Kaolin Clay , ISO Standard, Photodiode, Spectrophotometer, Spraying equipment. Highlights Simple low-cost microcontroller-based device was developed to measure ASP® 602 concentrations of residue samples from ISO 22368 tests. Sensitivity analysis showed the device was able to detect ASP® 602 concentrations as low as 22.5 ppm depending on sample variations. Various prediction models were built from the output of the device and validated to understand their accuracy and measurement variations. Logarithmic prediction model showed approximation errors from 3.9% to 19.7% with CV of 7.7% to 19.8% for the ASP® 602 concentration range from 0 to 250 ppm. Abstract.A simple microcontroller-based device with operating software was developed for analyzing samples from ISO 22368 sprayer cleanout tests. The device could measure ASP® 602 concentrations of residue samples from the sprayer cleanout tests with measurement variations, a coefficient of variations (CV), less than 4%. Sensitivity analysis of the device carried out to understand the measurement limits, and the results showed that the limit of quantification of the device was 22.5 ppm with sample variations which was sufficient for assaying residue samples from ISO 22368 tests. The measurement variations of the device were also affected by homogeneity of the samples. Several prediction models were developed with the device outputs, and prediction accuracy (approximation error) and measurement variations (CV) of the models were validated with additional ASP® 602 samples. The prediction results from the models had a wide range of approximation errors and the results showed approximation errors from 2.6% to 26.2% with CV from 3.0% to 33.4% with the models for a prediction ranges from 0 to above 500 ppm, while considering the results above limit of quantification. The models for a prediction range from 0 to 250 ppm showed the error from 3.9% to 19.7% with CV from 7.5% to 27.5%, under the same consideration. The logarithmic prediction model with the prediction range from 0 to 250 ppm showed most acceptable performance in terms of approximation error and CV that were less than 20%, when considering the results within limit of quantification. (Download PDF) (Export to EndNotes)
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