标题
Olive Oil Classification and Fraud Detection Using E-Nose and Ultrasonic System
作者
关键词
-
出版物
Food Analytical Methods
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2021-05-14
DOI
10.1007/s12161-021-02035-y
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Flash Gas Chromatography in Tandem with Chemometrics: A Rapid Screening Tool for Quality Grades of Virgin Olive Oils
- (2020) Sara Barbieri et al. Foods
- Triangular Test of Amanita Mushrooms by Using Electronic Nose and Sensory Panel
- (2019) Portalo-Calero et al. Foods
- Development of Rapid Extra Virgin Olive Oil Quality Assessment Procedures Based on Spectroscopic Techniques
- (2019) Paola Baltazar et al. Agronomy-Basel
- Evaluation of extra-virgin olive oil adulteration using FTIR Spectroscopy combined with multivariate algorithms
- (2018) Y. Xu et al. Quality Assurance and Safety of Crops & Foods
- Comparison of different classification methods for analyzing fluorescence spectra to characterize type and freshness of olive oils
- (2018) A. Dankowska et al. EUROPEAN FOOD RESEARCH AND TECHNOLOGY
- Detection of olive oil adulteration by low-field NMR relaxometry and UV-Vis spectroscopy upon mixing olive oil with various edible oils
- (2017) S. Ok GRASAS Y ACEITES
- Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods
- (2017) Ana M. Jiménez-Carvelo et al. JOURNAL OF AOAC INTERNATIONAL
- Portable Electronic Nose Based on Electrochemical Sensors for Food Quality Assessment
- (2017) Wojciech Wojnowski et al. SENSORS
- Application of MOS based electronic nose for the prediction of banana quality properties
- (2016) Alireza Sanaeifar et al. MEASUREMENT
- Data fusion methodologies for food and beverage authentication and quality assessment – A review
- (2015) Eva Borràs et al. ANALYTICA CHIMICA ACTA
- Discrimination of Adulterated Sesame Oil Using Mid-infrared Spectroscopy and Chemometrics
- (2015) Xiande Zhao et al. Food Analytical Methods
- Extra-Virgin Olive Oil and Cheap Vegetable Oils: Distinction and Detection of Adulteration as Determined by GC and Chemometrics
- (2015) Hazem Jabeur et al. Food Analytical Methods
- Determination of volatile compounds by GC–IMS to assign the quality of virgin olive oil
- (2015) Rocío Garrido-Delgado et al. FOOD CHEMISTRY
- Detection of sunflower oil in extra virgin olive oil by fast differential scanning calorimetry
- (2015) I.A. van Wetten et al. THERMOCHIMICA ACTA
- Detection of Adulteration in Saffron Samples Using Electronic Nose
- (2014) Kobra Heidarbeigi et al. INTERNATIONAL JOURNAL OF FOOD PROPERTIES
- Ultrasonic technique for non-destructive quality evaluation of oranges
- (2014) D.S. Morrison et al. JOURNAL OF FOOD ENGINEERING
- Estimation of orange skin thickness based on visual texture coarseness
- (2013) Abdolabbas Jafari et al. BIOSYSTEMS ENGINEERING
- Electronic nose and tongue combination for improved classification of Moroccan virgin olive oil profiles
- (2013) Z. Haddi et al. FOOD RESEARCH INTERNATIONAL
- A Novel Method To Quantify the Adulteration of Extra Virgin Olive Oil with Low-Grade Olive Oils by UV−Vis
- (2010) José S. Torrecilla et al. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
- Properties of sesame oil by detailed 1H and 13C NMR assignments before and after ozonation and their correlation with iodine value, peroxide value, and viscosity measurements
- (2009) Alessandro Sega et al. CHEMISTRY AND PHYSICS OF LIPIDS
- High-power gradient diffusion NMR spectroscopy for the rapid assessment of extra-virgin olive oil adulteration
- (2009) Daniela Šmejkalová et al. FOOD CHEMISTRY
- DETECTION OF OLIVE OIL ADULTERATION WITH RAPESEED AND SUNFLOWER OILS USING MOS ELECTRONIC NOSE AND SMPE-MS
- (2009) SYLWIA MILDNER-SZKUDLARZ et al. JOURNAL OF FOOD QUALITY
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