scholarly journals Real time continuous oxygen concentration monitoring system during malaxation for the production of Virgin Olive Oil

2012 ◽  
Vol 63 (4) ◽  
pp. 475-483 ◽  
Author(s):  
M. Vallone ◽  
G. Aiello ◽  
P. Catania ◽  
M. Enea ◽  
G. La Scalia ◽  
...  
2017 ◽  
Vol 25 (4) ◽  
pp. 278-285 ◽  
Author(s):  
Estrella Funes ◽  
Yosra Allouche ◽  
Gabriel Beltrán ◽  
M Paz Aguliera ◽  
Antonio Jiménez

Nine neural models were created to predict the characteristics of the extra virgin olive oil developed as a quality objective and by-products. These models are designed with the help of data of process variables from physical sensors such as temperature, flows, current intensity, etc. and physicochemical ones like the near infrared spectrum of the olive mass. The results obtained for the extractability of the process (fatty content and moisture) were highly significant correlations (r2≥0.90) and with similar prediction errors (root mean of squared error of prediction) relative to other analysis techniques which measure the by-product directly. For prediction the models gave correlations above 0.94, with the exception of ultraviolet absorption coefficients (0.72–0.84), with small prediction errors and the quality indicator relative error range with values above the optimal 10. The set of developed artificial neural networks models constitute the basis of the global ‘simulator’ tool of the extra virgin olive oil process. This simulator can perform a predictive optimization of the process to pre-adjust the process variables according to the goals marked in productivity or quality, from an near infrared spectral database or by real-time scanning. This simulator could be integrated into a control system that performs the function of a ‘virtual plant’ that allows the said system to adjust in real time the appropriate variables to meet the objectives.


2008 ◽  
Vol 56 (12) ◽  
pp. 4681-4685 ◽  
Author(s):  
Araceli Sánchez-Ortiz ◽  
Carmen Romero ◽  
Ana G. Pérez ◽  
Carlos Sanz

2019 ◽  
Vol 11 (4) ◽  
pp. 472-482 ◽  
Author(s):  
Marinella Farré ◽  
Yolanda Picó ◽  
Damiá Barceló

A fast and reliable method to characterize the polyphenolic compound profiles in extra virgin olive oil (EVOO) has been developed using direct analysis in real time (DART) and linear ion-trap Orbitrap mass spectrometry (LTQ-Orbitrap-MS).


2019 ◽  
Vol 295 ◽  
pp. 94-100 ◽  
Author(s):  
Dimitrios Trypidis ◽  
Diego Luis García-González ◽  
Ana Lobo-Prieto ◽  
Nikolaos Nenadis ◽  
Maria Z. Tsimidou ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xueqi Li ◽  
Selina C. Wang

Extra virgin olive oil (EVOO), with high unsaturation degree (oleic acid, linoleic acid, and linolenic acid), is prone to oxidation during production and storage even with the presence of abundant antioxidants (e.g., phenolic compounds, alpha-tocopherol, and chlorophyll). The level of oxidation degradation is greatly affected by the EVOO chemical composition (free fatty acids, saturated and unsaturated fat ratio, total phenol content, etc.) and storage conditions (packaging material, oxygen, temperature, and light). With the increasing demand on qualitative acceptability and food safety of an EVOO product, consumers rely heavily on “shelf life” as a good indicator. Hence, it is critical for olive oil producers to provide accurate and practical information on shelf-life prediction. This review analyzes ten shelf-life prediction models that used various parameters and approaches for model establishment. Due to the complexity of chemical interactions between oil phase and environment under real-time storage and rapid accelerated testing conditions, further investigation is needed to scrutinize and minimize the discrepancies between real-time shelf life and predicted shelf life of EVOO products.


2021 ◽  
Author(s):  
Hicham Zaroual ◽  
El Mestafa El Hadrami ◽  
Romdhane Karoui

This study examines the feasibility of using front face fluorescence spectroscopy (FFFS) to authenticate 41 virgin olive oil (VOO) samples collected from 5 regions in Morocco during 2 consecutive crop seasons.


Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
M Dell'Agli ◽  
R Fagnani ◽  
G Galli ◽  
O Maschi ◽  
E de Fabiani ◽  
...  

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