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Preliminary evaluation of a turbidity sensor-based system to monitor concentration of simulated pesticide mixture for in-line injection systems

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2021 ASABE Annual International Virtual Meeting  2101162.(doi:10.13031/aim.202101162)
Authors:   Zhihong Zhang, Heping Zhu, Zhiming Wei, Ramón Salcedo
Keywords:   concentration accuracy, in-line injection system, mixture uniformity, pesticide, turbidity sensor.

Abstract. The real-time monitoring of spray mixture concentrations for in-line injection systems is critical to ensure high accuracy of precision pesticide applications. The goal of this study was to evaluate the potential of using an in-line turbidity sensor-based system to monitor concentrations of spray mixtures. To achieve this goal, firstly, regression mode was developed to correlate output voltages of the turbidity sensor to concentrations (0%, 6%, 12%, 18%, 24%, and 30%) of simulated pesticides (commercial skimmed milk); secondly, the accuracy and precision of the measurement system at different nominal concentrations (from 2% to 30% with interval of 2%) were evaluated by using relative errors and standard deviations, respectively; thirdly, the effects of flowrate (204.3, 323.3 and 436.0 mL min-1.) on measurement errors were assessed. The results showed that increasing concentrations of simulated pesticide caused a monotonic decrease in the sensor output voltage. A third-order polynomial regression model was found with a great coefficient of determination to adequately fit the experimental readings. With the lower concentration ranges, this system characterized with better precision and accuracy as compared with higher ones. Within nominal concentrations from 2% to 22%, the measurement errors did not exceed 1.37% (Mean=0.66%), and the standard deviation was below 0.2% (Mean=0.12%); however, within nominal concentrations from 22% to 30%, the measurement error was above 2.23% (Mean=3.36%), and standard deviation was higher than 0.22% (Mean=0.23%). Errors of the measured concentrations firstly increased with flowrate; however, as flowrate further increased, the measured concentration decreased instead. Deviations of mean measured concentrations caused by the flowrate were below 0.15%, which could be neglectable for the measurement task of injection systems. Therefore, turbidity sensor-based system was a feasible method for measurements of simulated pesticide mixture concentrations for in-line injection systems.

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