Detection of cuticle defects on cherry tomatoes using hyperspectral fluorescence imagery
Detection of cuticle defects on cherry tomatoes using hyperspectral fluorescence imagery
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DOI：
10.1016/j.postharvbio.2012.09.002
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发表时间：
2013-02-01
影响因子：
7
通讯作者：
Kim, Young-Sik
中科院分区：
文献类型：
--
作者：
Cho, Byoung-Kwan;Kim, Moon S.;Kim, Young-Sik
樱桃番茄是鲜切市场上消费的主要蔬菜之一。然而，依赖于简单的尺寸或颜色分类技术的质量评估过程不足以满足消费者对高质量和安全的日益增长的需求。在各种质量评估中，检测樱桃番茄中的开裂缺陷是一个关键过程，因为这种类型的损伤可能隐藏致病微生物，可能对消费者健康产生有害影响。在这项研究中，多光谱荧光成像技术已被提出作为一种诊断工具，无损检测有缺陷的樱桃番茄。开裂角质层区域的荧光强度在蓝绿色光谱区域显著高于完好表面，表明多光谱荧光成像技术是检测樱桃番茄开裂缺陷的有效分类工具。采用简单方差分析和主成分分析确定了最佳荧光波段。结果表明，与基于ANOVA分析结果的一对选定波段线性组合的多光谱荧光图像能够以>99%的准确度检测有缺陷的樱桃番茄。在这项研究中的检测算法，预计将被用来开发现场和实时多光谱系统的樱桃番茄采后加工厂的质量评价。(C)2012爱思唯尔有限公司版权所有。
Cherry tomatoes are one of the major vegetables consumed in the fresh-cut market. However, the quality evaluation process, which is dependent on simple size- or color-sorting techniques, is inadequate to meet increased consumer demands for high quality and safety. Among various quality evaluations, detection of cracking defects in cherry tomatoes is a critical process since this type of damage can harbor pathogenic microbes that may have detrimental consequences on consumer health. In this study, a multi-spectral fluorescence imaging technique has been presented as a diagnostic tool for non-destructive detection of defective cherry tomatoes. Fluorescence intensity in the area of cracked cuticle was significantly higher in the blue-green spectral region than that of the sound surfaces, suggesting the multi-spectral fluorescence imaging technique as an effective classification tool for detecting cracking defects on cherry tomatoes. Simple ANOVA classification analysis and principal component analysis were employed to investigate optimal fluorescence wavebands. The results illustrate that a multi-spectral fluorescence image in linear combination with a pair of selected wavebands based on the results of ANOVA analysis was able to detect defective cherry tomatoes with >99% accuracy. The detection algorithm investigated in this study is expected to be used to develop on-site and real-time multi-spectral systems for quality evaluation of cherry tomatoes in postharvest processing plants. (C) 2012 Elsevier B.V. All rights reserved.