Improve Competitiveness of Specialty Crop Production through a New Product Quality Verification Method

Agricultural sorting and grading is most commonly preformed primarily through the use of human resources. Farm workers sort crops by hand through visual inspection. This process is expensive and highly subjective. In addition the labor force is susceptible to human error which can impact the quality of the resulting data. The outcome of this project will be to increase efficiencies in the grading and sorting process through the use of visual automation. With our current algorithm, cameras and computers are used to sort crops, which increases the overall accuracy of the agricultural grading and sorting processe, contributing to increases in efficiency as well as profitability. Our current installations of this technology have decreased their labor costs by as much as 47%. Phase one of this project will have the outcome of improving our current process by allowing two seperate functions, grading and sorting, to be preformed on the same machine. We will do this by increasing the availabe functions of the algorithm, including but not limited to color, and increasing the accuracy and efficiency of the algorithm.