Foodborne pathogens cause serious health issues and have a strong impact on the economy of the country. In this context, quality testing of royal delicious apple by detecting pathogen contamination using an electronic nose, which contains an array of six ready-made sensors, has been proposed. To estimate the types of pathogens in fresh, half and completely contaminated apple samples were considered for bacterial studies. This study revealed the presence of Staphylococcus, Salmonella and Shigella bacteria, which were in the order of zero, 10², 10³−10⁴ CFU/mL. Further, the recorded headspace GC–MS spectra of contaminated samples confirmed the presence of bacterial spoilage markers namely acetone, ethyl acetate, ethyl alcohol and acetaldehyde. Voltage swing of 0.2 and 0.5 V was observed for half and completely contaminated apple samples respectively with reference to the fresh sample. Voltage responses of the sensors fed to Principal component analysis and Ward's method of hierarchical cluster algorithms helped to assess the quality of apple samples. By correlating the results of tri-layers namely bacterial count, GCMS data and classification results, reference table was developed and embedded in the ATmega processor of the electronic nose for real-time quality estimation of apple samples.

食源性病原体会引起严重的健康问题，并对该国的经济产生重大影响。在这种情况下，已经提出了通过使用电子鼻检测病原体污染来对皇家美味苹果进行质量测试的方法，该电子鼻包含六个现成的传感器阵列。为了评估新鲜，半污染和完全污染的苹果样品中的病原体类型，将其用于细菌研究。这项研究揭示了存在葡萄球菌，沙门氏菌和志贺氏菌，这是在零阶，10 ²，10 ³ -10 ⁴ CFU / mL。此外，记录的受污染样品的顶空GC-MS光谱证实存在细菌腐败标记物，即丙酮，乙酸乙酯，乙醇和乙醛。参照新鲜样品，分别对一半和完全污染的苹果样品观察到0.2 V和0.5 V的电压摆幅。传感器的电压响应馈入主成分分析和Ward的层次聚类算法方法有助于评估苹果样品的质量。通过关联三层结果，即细菌计数，GCMS数据和分类结果，开发了参考表并将其嵌入电子鼻的ATmega处理器中，以实时评估苹果样品的质量。