Kurniawan Hary, Arief Muhammad Akbar Andi, Lohumi Santosh, Kim Moon S, Baek Insuck, Cho Byoung-Kwan
Department of Smart Agriculture Systems, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, South Korea.
Department of Agricultural Engineering, Faculty of Food Technology and Agroindustry, University of Mataram, West Nusa Tenggara, 83126, Indonesia.
Curr Res Food Sci. 2024 Jul 4;9:100802. doi: 10.1016/j.crfs.2024.100802. eCollection 2024.
Fresh-cut vegetables are a food product susceptible to contamination by foreign materials (FMs). To detect a range of potential FMs in fresh-cut vegetables, a dual imaging technique (fluorescence and color imaging) with a simple and effective image processing algorithm in a user-friendly software interface was developed for a real-time inspection system. The inspection system consisted of feeding and sensing units, including two cameras positioned in parallel, illuminations (white LED and UV light), and a conveyor unit. A camera equipped with a long-pass filter was used to collect fluorescence images. Another camera collected color images of fresh-cut vegetables and FMs. The feeding unit fed FMs mixed with fresh-cut vegetables onto a conveyor belt. Two cameras synchronized programmatically in the software interface simultaneously collected fluorescence and color image samples based on the region of interest as they moved through the conveyor belt. Using simple image processing algorithms, FMs could be detected and depicted in two different image windows. The results demonstrated that the dual imaging technique can effectively detect potential FMs in two types of fresh-cut vegetables (cabbage and green onion), as indicated by the combined fluorescence and color imaging accuracy. The test results showed that the real-time inspection system could detect FMs measuring 0.5 mm in fresh-cut vegetables. The results showed that the combined detection accuracy of FMs in the cabbage (95.77%) sample was superior to that of green onion samples (87.89%). Therefore, the inspection system was more effective at detecting FMs in cabbage samples than in green onion samples.
鲜切蔬菜是一种容易受到外来物质(FMs)污染的食品。为了检测鲜切蔬菜中一系列潜在的外来物质,开发了一种双成像技术(荧光和彩色成像),该技术在用户友好的软件界面中采用了简单有效的图像处理算法,用于实时检测系统。检测系统由进料和传感单元组成,包括两个平行放置的摄像头、照明设备(白色发光二极管和紫外线灯)以及一个输送单元。配备长波通滤光片的摄像头用于采集荧光图像。另一个摄像头采集鲜切蔬菜和外来物质的彩色图像。进料单元将与鲜切蔬菜混合的外来物质输送到传送带上。两个摄像头在软件界面中通过编程同步,在它们通过传送带移动时,基于感兴趣区域同时采集荧光和彩色图像样本。使用简单的图像处理算法,可以在两个不同的图像窗口中检测并描绘出外来物质。结果表明,双成像技术可以有效地检测两种鲜切蔬菜(卷心菜和大葱)中的潜在外来物质,荧光和彩色成像的综合准确率表明了这一点。测试结果表明,实时检测系统能够检测出鲜切蔬菜中尺寸为0.5毫米的外来物质。结果表明,卷心菜样本中外来物质的综合检测准确率(95.77%)高于大葱样本(87.89%)。因此,该检测系统在检测卷心菜样本中的外来物质方面比大葱样本更有效。