• Smart Media Journal
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• v.11 no.4
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• pp.46-55
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• 2022

It is very important to first detect and remove defective fruits with scratches or bruised areas in the automatic fruit quality screening system. This paper proposes a method of detecting defective areas in fruits using the latest artificial intelligence technology, the Yolo V4 deep learning model in order to overcome the limitations of the method of detecting fruit's defective areas using the existing image processing techniques. In this study, a total of 2,400 defective fruits, including 1,000 defective apples and 1,400 defective fruits with scratch or decayed areas, were learned using the Yolo V4 deep learning model and experiments were conducted to detect defective areas. As a result of the performance test, the precision of apples is 0.80, recall is 0.76, IoU is 69.92% and mAP is 65.27%. The precision of pears is 0.86, recall is 0.81, IoU is 70.54% and mAP is 68.75%. The method proposed in this study can dramatically improve the performance of the existing automatic fruit quality screening system by accurately selecting fruits with defective areas in real time rather than using the existing image processing techniques.

• Journal of Food Hygiene and Safety
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• v.33 no.6
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• pp.453-459
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• 2018

This study was performed to investigate the contamination levels of heavy metals (such as lead, cadmium, arsenic and mercury) and aflatoxin (such as $B_1$, $B_2$, $G_1$ and $G_2$) in commercial herbs for food and medicine. The concentrations of the heavy metals were measured by the ICP-MS and a mercury analyzer. The aflatoxins were analyzed by a HPLC-florescence coupled with photochemical derivatization. The detection ranges of the lead, cadmium, arsenic and mercury were found to be 0.006~4.088 mg/kg, 0.002~2.150 mg/kg, ND~0.610 mg/kg and ND~0.0139 mg/kg respectively. Among the total samples, the 3 samples (2.6%) were not suitable for the specification of cadmium by the MFDS (Ministry of Food and Drug Safety). The 13 samples of the total 117 samples were aflatoxin positive (11.1%). The amount of aflatoxin $G_1$ was $0.7834{\mu}g/kg$ in the Puerariae Radix and aflatoxin $G_2$ were $0.3517{\mu}g/kg$, $0.4881{\mu}g/kg$ in two samples of the Glycyrrhizae Radix et Rhizoma, respectively. The aflatoxins $B_2$ and $G_1$ were simultaneously detected in the 10 Angelicae Gigantis Radix. The detection ranges of aflatoxins $B_2$ and $G_1$ were $0.2324{\sim}1.0358{\mu}g/kg$ and $0.7552{\sim}1.6545{\mu}g/kg$ respectively in Angelicae Gigantis Radix. The results of the current study suggest that continuous monitoring is needed for the proactive management of commercial herbs for food and medicine safety.