Nanosensors Lab, SASTRA Deemed University, Thanjavur 613 401, Tamil Nadu, India; School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur 613 401, Tamil Nadu, India; Centre for Nanotechnology & Advanced Biomaterials, SASTRA Deemed University, Thanjavur 613 401, Tamil Nadu, India.
Electrodics & Electrocatalysis Division, Central Electrochemical Research Institute, Karaikudi 630 003, Tamil Nadu, India.
Food Res Int. 2018 Jul;109:44-51. doi: 10.1016/j.foodres.2018.04.009. Epub 2018 Apr 11.
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, 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, 10, 10-10 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.
食源性致病菌会导致严重的健康问题，并对国家经济产生重大影响。在此背景下，提出了使用包含 6 个预制传感器的电子鼻来检测病原体污染，从而对皇家美味苹果进行质量检测。为了估计病原体的类型，对新鲜、半污染和完全污染的苹果样本进行了细菌研究。该研究表明存在葡萄球菌、沙门氏菌和志贺氏菌，其数量分别为零、10、10-10 CFU/mL。此外，污染样本的记录的顶空 GC-MS 谱证实了细菌腐败标志物的存在，即丙酮、乙酸乙酯、乙醇和乙醛。与新鲜样本相比，半污染和完全污染的苹果样本的电压摆动分别为 0.2 和 0.5 V。将传感器的电压响应输入主成分分析和 Ward 层次聚类算法，有助于评估苹果样本的质量。通过对细菌计数、GCMS 数据和分类结果的三层结果进行关联，开发了参考表，并将其嵌入电子鼻的 ATmega 处理器中，用于实时估计苹果样本的质量。
