Application of Electronic Nose with Multivariate Analysis and Sensor Selection for Botanical Origin Identification and Quality Determination of Honey

By Lingxia Huang, Hongru Liu, Bo Zhang, Di Wu. Food and Bioprocess Technology, 2015

79 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Insect Science

View Paper: https://www.semanticscholar.org/paper/38d9fd448fa36b9de9b84cd0f609d7de371a5e09

How researchers see this paper

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1. Zhilin Gan
2. Yuanying Ni
3. X. Wen
4. Yundong Jiang
5. Minghui Zhu
6. Jing Li
7. Yang Yang

Citations in the corpus

• Using sensor and spectral analysis to classify botanical origin and determine adulteration of raw honey (2016, methodology): “Traditionally, PCA, artificial neural network (ANN), linear discriminant analysis (LDA), discriminating factor analysis (DFA) were the best common models applied to EN and ET data for identification of honey botanical origin (Huang et al., 2014; Ampuero et al., 2004; Tiwari et al., 2013;”