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Development and parameter optimization of automatic separation and identification equipment for grain tracing systems based on grain tracers with QR codes
- Liang, Kun, Chen, Xiaohe, He, Ruiyin, Li, Jiawei, Okinda, Cedric, Han, Dongsheng, Shen, Mingxia
- Computers and electronics in agriculture 2019 v.162 pp. 709-718
- computer software, equipment, experimental design, models, response surface methodology, screening, traceability, tracer techniques, vibration, wheat
- It is difficult to trace grains to their original harvest because doing so requires unique and accurate grain labels, which are mixed when handled in massive quantities and derived from different origins. Food-grade grain tracers have been developed as an identification technology for tracing from original harvest to final destination. To implement online production operation for food-grade grain tracers by QR code scanning and information recording, automatic separation and identification equipment was designed in three parts: vibration screen separation, transmission and recognition assembly and host computer software for traceability. Improvements in the recognition rate, wear rate and screening rate of the equipment in the grain tracing system was achieved based on a Box–Behnken design (BBD) using response surface methodology (RSM). Four factors that affect the working parameters (i.e., vibration frequency, screen angle, tracer density and conveyor speed) were selected, and their value ranges were confirmed. The following optimal working parameters were obtained: a vibration frequency of 40.13 Hz, a screen angle of 5.00°, a tracer density of 5 tracers per 1.5 kg wheat and a conveyor speed of 0.15 m/s. Test results show that the automatic separation and identification equipment is practical for grain tracing systems. The experimental values of the recognition rate and screening rate under optimized conditions were similar to the predicted values, which confirmed the validity of the models. The advantage of this equipment is that it represents an online approach for separating and identifying tracers that would not require production interruptions or manual recognition. Therefore, this automatic separation and identification equipment holds a certain significance for the design and development of grain tracing systems, possibly providing a basis for the implementation and further research of other food traceability systems.