Review: Recent Advances in the Use of Non-Destructive near Infrared Spectroscopy for Intact Olive Fruits

The objective of this review is to illustrate the state of the art in the use of non-destructive near infrared (NIR) spectroscopy for quality evaluation of intact fruit in the olive industry. First, the most recent studies regarding the application of non-destructive NIR spectroscopy methods for the assessment of external olive quality are reviewed. External defects including mechanical damage, bruising, ground origin and insect infestation, and the consequences of these defects for finished products are reported. Second, research regarding chemical parameters of olive fruits is reviewed; in particular, the use of portable instruments to measure quality parameters such as moisture, oil and phenolic content while the fruit is on the tree, with the goal of monitoring the trends in these parameters during olive development. Finally, research on intact olive authenticity, an important aspect for legal and economic reasons, is reviewed. As most studies cited indicate the feasibility of NIR spectroscopy for non-destructive evaluation of many quality parameters, this review stresses the urgent need for technology transfer to olive facilities to enhance product quality while reducing production costs.

[1]  Nathalie Dupuy,et al.  Chemometric analysis of combined NIR and MIR spectra to characterize French olives , 2010 .

[2]  S. Sayadi,et al.  Effect of olive fruit fly infestation on the quality of olive oil from Chemlali cultivar during ripening. , 2010, Food and Chemical Toxicology.

[3]  Lourdes Salguero-Chaparro,et al.  On-line versus off-line NIRS analysis of intact olives , 2014 .

[4]  Ana Garrido-Varo,et al.  Parent and harvest year effects on near-infrared reflectance spectroscopic analysis of olive (Olea europaea L.) fruit traits. , 2004, Journal of agricultural and food chemistry.

[5]  A. J. Gaitán-Jurado,et al.  Feasibility of using NIR spectroscopy to detect herbicide residues in intact olives , 2013 .

[6]  Sumio Kawano,et al.  Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes , 2013 .

[7]  M. Casale,et al.  Review: Near Infrared Spectroscopy for Analysing Olive Oils , 2014 .

[8]  M. De La Guardia,et al.  The Use of Near-Infrared Spectrometry in the Olive Oil Industry , 2010, Critical reviews in food science and nutrition.

[9]  José Antonio Cayuela,et al.  NIR prediction of fruit moisture, free acidity and oil content in intact olives. , 2009 .

[10]  P. Williams,et al.  Near-Infrared Technology in the Agricultural and Food Industries , 1987 .

[11]  Lorenzo León,et al.  Non-destructive assessment of olive fruit ripening by portable near infrared spectroscopy , 2011 .

[12]  Pilar Rallo,et al.  Feasibility of NIR spectroscopy for non-destructive characterization of table olive traits , 2011 .

[13]  Renfu Lu,et al.  Prediction of olive quality using FT-NIR spectroscopy in reflectance and transmittance modes , 2009 .

[14]  Vincent Baeten,et al.  On-line analysis of intact olive fruits by vis–NIR spectroscopy: Optimisation of the acquisition parameters , 2012 .

[15]  R. Haff,et al.  A multispectral sorting device for isolating single wheat kernels with high protein content , 2013, Journal of Food Measurement and Characterization.

[16]  E. Harel,et al.  Enzymic browning in green olives and its prevention , 1978 .

[17]  A. Garrido-Fernández,et al.  Browning reactions in olives: Mechanism and polyphenols involved , 2009 .

[18]  Danilo Monarca,et al.  Feasibility of NIR spectroscopy to detect olive fruit infested by Bactrocera oleae , 2015 .

[19]  R. G. Ackman Olive Oil: From the Tree to the Table, by A.K. Kiritsakis, Food and Nutrition Press, Inc., Trumbull, CT 06611, USA, Price: US$100.00, 348 pages, ISBN 0-917678-42-7 , 1999 .

[20]  José Antonio Cayuela,et al.  Prediction of quality of intact olives by near infrared spectroscopy. , 2010 .

[21]  Vincent Baeten,et al.  Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives. , 2013, Food chemistry.

[22]  Jean-Michel Roger,et al.  Calibration transfer of intact olive NIR spectra between a pre-dispersive instrument and a portable spectrometer , 2013 .

[23]  Margarita Ruiz-Altisent,et al.  Olive classification according to external damage using image analysis. , 2008 .

[24]  Danilo Monarca,et al.  Detection of Mold-Damaged Chestnuts by Near-Infrared Spectroscopy , 2014 .

[25]  R. Mailer Rapid evaluation of olive oil quality by NIR reflectance spectroscopy , 2004 .

[26]  D. Lewis Chemistry and Technology of Wool-Wax , 1957, Nature.

[27]  Francisco Jiménez-Jiménez,et al.  Non-destructive determination of impact bruising on table olives using Vis–NIR spectroscopy , 2012 .

[28]  Maurizio Servili,et al.  Volatile compounds in virgin olive oil: occurrence and their relationship with the quality. , 2004, Journal of chromatography. A.

[29]  V. Giovenzana,et al.  Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy , 2013 .

[30]  G. Blanco-Roldán,et al.  Isolation of table olive damage causes and bruise time evolution during fruit detachment with trunk shaker. , 2013 .

[31]  R. P. Haff,et al.  SPECTRAL BAND SELECTION FOR OPTICAL SORTING OF PISTACHIO NUT DEFECTS , 2006 .

[32]  Danilo Monarca,et al.  Feasibility of Vis/NIR spectroscopy for detection of flaws in hazelnut kernels , 2013 .

[33]  T. C. Pearson,et al.  Sorting of In-Shell Pistachio Nuts from Kernels Using Color Imaging , 2010 .

[34]  Ron P. Haff,et al.  Low Cost Real-Time Sorting of In-Shell Pistachio Nuts from Kernels , 2008 .

[35]  F. Mencarelli,et al.  Oil accumulation in intact olive fruits measured by near infrared spectroscopy-acousto-optically tunable filter. , 2013, Journal of the science of food and agriculture.

[36]  A. Peirs,et al.  Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .

[37]  Por L. León,et al.  Análisis de aceituna intacta mediante espectroscopía en el infrarrojo cercano (NIRS): una herramienta de utilidad en programas de mejora de olivo , 2003 .

[38]  Danilo Monarca,et al.  Nondestructive detection of insect infested chestnuts based on NIR spectroscopy , 2014 .

[39]  Monica Casale,et al.  A spectral transfer procedure for application of a single class-model to spectra recorded by different near-infrared spectrometers for authentication of olives in brine. , 2013, Analytica chimica acta.

[40]  Andrea Bellincontro,et al.  Feasible application of a portable NIR-AOTF tool for on-field prediction of phenolic compounds during the ripening of olives for oil production. , 2012, Journal of agricultural and food chemistry.

[41]  G. Morozzi,et al.  Health and sensory properties of virgin olive oil hydrophilic phenols: agronomic and technological aspects of production that affect their occurrence in the oil. , 2004, Journal of chromatography. A.

[42]  Monica Casale,et al.  Characterisation of table olive cultivar by NIR spectroscopy , 2010 .

[43]  U. Rosa,et al.  Table olive cultivar susceptibility to impact bruising , 2013 .

[44]  Vincent Baeten,et al.  Infrared machine vision system for the automatic detection of olive fruit quality. , 2013, Talanta.

[45]  José A. García-Mesa,et al.  Fourier‐Transform Near‐Infrared Spectroscopy as a Tool for Olive Fruit Classification and Quantitative Analysis , 2005 .