Evaluation of Smart Portable Device for Food Diagnostics: A Preliminary Study on Cape Hake Fillets (M-capensis and M-paradoxus)
Evaluation of Smart Portable Device for Food Diagnostics: A Preliminary Study on Cape Hake Fillets (M-capensis and M-paradoxus)
复制标题
DOI：
10.1155/2019/2904724
复制
发表时间：
2019-01-01
影响因子：
3
通讯作者：
Balzaretti, Claudia M.
中科院分区：
文献类型：
--
作者：
Castrica, Marta;Panseri, Sara;Balzaretti, Claudia M.
与传统方法相比，新的基于智能手机的食品诊断技术具有显著的优势，因为它们可以很容易地应用于农业食品供应链的各个步骤，包括家庭使用，也可以用于慈善目的的食品回收领域，旨在帮助减少食物浪费。其他优势包括成本低、设备最少和所需的非专业人员。该研究评估了传感器的两种仪器测量的性能：电子鼻（PEN 3; WinMuster Airsense Analytics）和智能便携式设备（FOODsniffer; ARS LAB US）。对鳕鱼片进行了初步研究。为了测试PEN 3和FOODsniffer的性能，总挥发性盐基氮（TVB-N）值被认为是参考。进行主成分分析（PCA）和皮尔逊相关性以比较PEN 3与TVB-N，并且对于FOOD嗅探器评估，进行单因素ANOVA。PEN 3、第一组分与TVB-N呈显著相关（r=0.92，P=0.01）。方差分析结果也证实了FOODsniffer、TVB-N（F=519.9，P=0.01）和PEN 3（F=143.17，P=0.01）之间的良好一致性。我们的仿真结果证实了这两种方法的良好性能。
The new smartphone-based food diagnostic technologies offer significant advantages over traditional methods as they can be easily applied in various steps of the agrifood supply chain including household use and also in the food recovery field for charitable purposes, aimed at helping to reduce food waste. Further advantages include the low cost, the minimal equipment, and nonspecialized personnel required. This study evaluated the performance of two instrumental measurements of the sensors: an electronic nose (PEN3; WinMuster Airsense Analytics) and a smart portable device (FOODsniffer; ARS LAB US). The preliminary study was conducted on cape hake fillets. In order to test the performance of PEN3 and FOODsniffer, total volatile basic nitrogen (TVB-N) values were considered as the reference. Principal component analysis (PCA) and Pearson's correlation were performed in order to compare PEN3 with TVB-N, and for the FOODsniffer evaluation, a one-way ANOVA was carried out. A significant correlation was shown between PEN3, first component, and TVB-N (r=0.92, P=0.01). The ANOVA results also confirmed a good agreement between FOODsniffer, TVB-N (F=519.9, P=0.01), and PEN3 (F=143.17, P=0.01). Our simulation results confirmed good performance in both methods.