scholarly journals Visible Near Infrared Spectroscopy as a Green Technology: An Environmental Impact Comparative Study on Olive Oil Analyses

2019 ◽  
Vol 11 (9) ◽  
pp. 2611 ◽  
Author(s):  
Andrea Casson ◽  
Roberto Beghi ◽  
Valentina Giovenzana ◽  
Ilaria Fiorindo ◽  
Alessio Tugnolo ◽  
...  
Keyword(s):  
Environmental Impact ◽  
Olive Oil ◽  
Near Infrared ◽  
Oil Quality ◽  
Nir Spectroscopy ◽  
Assessment Method ◽  
Quality Parameters ◽  
Green Technology ◽  
Optical Methods ◽  
The European Union

The olive oil industry is a significant productive sector in the European Union and the related production process is characterised by practices and techniques associated with several adverse effects on the environment. In the literature, many works on the environmental impact assessment of the olive oil chain have been carried out but the effects of the analytical analyses procedures were considered to be negligible. Currently, the reduction of solvents and of energy consumption in the laboratory has become a crucial aspect to be investigated. In this scenario, non-destructive optical methods based on visible/near-infrared (vis/NIR) spectroscopy represent a simple, rapid, and easy-to-use method to predict olive and olive oil quality parameters. Therefore, the aim of the work was to evaluate the environmental impact of the use of optical vis/NIR technologies for analytical assessment in comparison to chemical analyses on olive oil. The life cycle assessment method (LCA) was used. The functional unit defined for this study was the analysis and a “from cradle to grave” approach was applied. The vis/NIR technology results were distinctly better, by 36 times on average, than the chemical methods. Attention must be paid to the calibration phase of the vis/NIR instrumentation: In this case, the two methods must coexist for this initial procedure to obtain the required reference data for a reliable chemometric model. In conclusion, the vis/NIR spectroscopy gives very reliable results and can be considered a green technology, representing a choice among applications of low environmental impact analytical technologies.

scholarly journals Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 674
Author(s):  
Nawaf Abu-Khalaf
Keyword(s):  
Olive Oil ◽  
Electronic Nose ◽  
Chemical Sensor ◽  
Chemical Constituents ◽  
Oil Quality ◽  
Quality Parameters ◽  
Signal Acquisition ◽  
Good Precision ◽  
Olive Oil Quality ◽  
Quality Categories

An electronic nose (EN), which is a kind of chemical sensor, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.

scholarly journals Near Infrared Spectroscopy as a Green Technology for the Quality Prediction of Intact Olives

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1042
Author(s):  
Silvia Grassi ◽  
Olusola Samuel Jolayemi ◽  
Valentina Giovenzana ◽  
Alessio Tugnolo ◽  
Giacomo Squeo ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Olive Oil ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Green Technology ◽  
Soluble Solids ◽  
Integrating Sphere ◽  
Total Phenolic ◽  
Handheld Device ◽  
Quality Design

Poorly emphasized aspects for a sustainable olive oil system are chemical analysis replacement and quality design of the final product. In this context, near infrared spectroscopy (NIRS) can play a pivotal role. Thus, this study aims at comparing performances of different NIRS systems for the prediction of moisture, oil content, soluble solids, total phenolic content, and antioxidant activity of intact olive drupes. The results obtained by a Fourier transform (FT)-NIR spectrometer, equipped with both an integrating sphere and a fiber optic probe, and a Vis/NIR handheld device are discussed. Almost all the partial least squares regression models were encouraging in predicting the quality parameters (0.64 < R2pred < 0.84), with small and comparable biases (p > 0.05). The pair-wise comparison between the standard deviations demonstrated that the FT-NIR models were always similar except for moisture (p < 0.05), whereas a slightly lower performance of the Vis/NIR models was assessed. Summarizing, while on-line or in-line applications of the FT-NIR optical probe should be promoted in oil mills in order to quickly classify the drupes for a better quality design of the olive oil, the portable and cheaper Vis/NIR device could be useful for preliminary quality evaluation of olive drupes directly in the field.

scholarly journals Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Sylvio Barbon ◽  
Ana Paula Ayub da Costa Barbon ◽  
Rafael Gomes Mantovani ◽  
Douglas Fernandes Barbin
Keyword(s):  
Near Infrared ◽  
Prediction Models ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Chicken Meat ◽  
Poultry Meat ◽  
Spectral Information ◽  
Support Vector ◽  
Near Infrared Spectra ◽  
Meat Samples

Identification of chicken quality parameters is often inconsistent, time-consuming, and laborious. Near-infrared (NIR) spectroscopy has been used as a powerful tool for food quality assessment. However, the near-infrared (NIR) spectra comprise a large number of redundant information. Determining wavelengths relevance and selecting subsets for classification and prediction models are mandatory for the development of multispectral systems. A combination of both attribute and wavelength selection for NIR spectral information of chicken meat samples was investigated. Decision Trees and Decision Table predictors exploit these optimal wavelengths for classification tasks according to different quality grades of poultry meat. The proposed methodology was conducted with a support vector machine algorithm (SVM) to compare the precision of the proposed model. Experiments were performed on NIR spectral information (1050 wavelengths), colour (CIEL∗a∗b∗, chroma, and hue), water holding capacity (WHC), and pH of each sample analyzed. Results show that the best method was the REPTree based on 12 wavelengths, allowing for classification of poultry samples according to quality grades with 77.2% precision. The selected wavelengths could lead to potential simple multispectral acquisition devices.

scholarly journals A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety

2013 ◽  
Vol 2013 ◽  
pp. 1-36 ◽  
Author(s):  
Jarmo T. Alander ◽  
Vladimir Bochko ◽  
Birgitta Martinkauppi ◽  
Sirinnapa Saranwong ◽  
Timo Mantere
Keyword(s):  
Food Quality ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Optical Methods ◽  
General View ◽  
Analysis Method ◽  
Food Quality And Safety ◽  
Infrared Wavelengths ◽  
Work Done ◽  
Infrared Methods

This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.

scholarly journals Conventional and Ultra-fast Analysis Exposing the Harvest Date Impact on Lebanese Olive Oil: The Soury Variety

2021 ◽  
Vol 10 (1) ◽  
pp. 39
Author(s):  
Omar H. Dib ◽  
Christophe B. Y. Cordella ◽  
Rita Yaacoub ◽  
Hussein Dib ◽  
Nathalie Locquet ◽  
...  
Keyword(s):  
Olive Oil ◽  
Volatile Compounds ◽  
Oil Quality ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Quality Parameters ◽  
Harvest Date ◽  
Fast Analysis ◽  
Total Polyphenol ◽  
The Impact

The impact of harvest period on the quality parameters, polyphenols, fatty acids, sterols, and volatile compounds of Lebanese olive oil from the Soury variety was investigated in this study. Two groups of olive oil were compared, each with a specific harvest date. HD1 was harvested in October, whereas HD2 was picked in November. The analysis of both olive oil categories showed that HD2 witnessed a significant increase in all quality parameters except K270 and a decrease in total polyphenol content from 138 mg/mL to 44 mg/mL. Oleic and linoleic acids had an inverse relation, where the former decreased and the latter increased with the harvest date&rsquo;s advancement. Palmitic acid in both groups was higher than the standards set for extra virgin olive oil. The relative amount of &beta; -Sitosterol was mainly found to decrease, while those of stigmasterol, ∆5,24 -stigmastadienol, ∆7 -stigmastenol, and ∆7 -avenasterol increased with delaying harvest time. As for the volatile compounds, principle component analysis was used on the flash GC data to differentiate HD1 from HD2. Ethanol was found mostly characterizing HD2, whereas HD1 was influenced by 1-hexanol and (E,E)-2,4-decadienal. It can be concluded that the Soury variety should be harvested early, and a delay would result in the declassification of Lebanese olive oil quality from extra virgin to virgin olive oil.

scholarly journals Rapid NIR determination of alkyl esters in virgin olive oil

2017 ◽  
Vol 68 (2) ◽  
pp. 195 ◽  
Author(s):  
J. A. Cayuela
Keyword(s):  
Fatty Acid ◽  
Olive Oil ◽  
Predictive Models ◽  
Near Infrared ◽  
Methyl Esters ◽  
External Validation ◽  
Virgin Olive Oil ◽  
Ethyl Esters ◽  
The European Union ◽  
Alkyl Esters

The regulation of The European Union for olive oil and olive pomace established the limit of 35 mg·kg-1 for fatty acids ethyl ester contents in extra virgin olive oils, from grinding seasons after 2016. In this work, predictive models have been established for measuring fatty acid ethyl and methyl esters and to measure the total fatty acid alkyl esters based on near infrared spectroscopy (NIRS), and used successfully for this purpose. The correlation coefficients from the external validation exercises carried out with these predictive models ranged from 0.84 to 0.91. Different classification tests using the same models for the thresholds 35 mg·kg-1 for fatty acid ethyl esters and 75 mg·kg-1 for fatty acid alkyl esters provided success percentages from 75.0% to 95.2%.

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