研究目的
To identify the uniqueness and authenticity of Maltese extra virgin olive oil (EVOO) using multivariate three-way data analysis techniques on three-dimensional excitation emission matrix (3D-EEM) fluorescent data.
研究成果
The application of 3D-fluorescence spectroscopy in conjunction with three-way methods has proven to be a useful tool for analyzing and interpreting complex data, offering a cheap, fast, and reliable way for the discrimination of Maltese EVOOs from non-Maltese EVOOs. The study successfully identified four fluorescent components and demonstrated the potential of these methods for authenticity determination.
研究不足
The study is limited by the sample size and geographical coverage, focusing primarily on Maltese and neighboring Mediterranean EVOOs. The techniques used, while effective, may require further validation with a broader range of samples and conditions.
1：Experimental Design and Method Selection:
The study employed parallel factor analysis (PARAFAC) and discriminant multi-way partial least squares regression (DN-PLSR) on 3D-EEM fluorescent data.
2：Sample Selection and Data Sources:
A total of 65 extra virgin olive oil samples were collected from the Maltese islands over four harvest seasons from 2013–2016 and from other neighboring Mediterranean countries.
3：List of Experimental Equipment and Materials:
A Jasco FP-8300 fluorescence spectrophotometer was used for EEM spectra acquisition.
4：Experimental Procedures and Operational Workflow:
The oil samples were examined by means of right-angle geometry with specific settings for excitation and emission bandwidths, acquisition interval, and scan speed.
5：Data Analysis Methods:
PARAFAC and DN-PLSR modeling was performed using the 'N-way' MATLAB toolbox from Eigenvector, with specific constraints and validation methods applied.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
