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In‐process monitoring in industrial olive mill by means of FT‐NIR
Author(s) -
Bendini Alessandra,
Cerretani Lorenzo,
Di Virgilio Fabio,
Belloni Paolo,
Lercker Giovanni,
Toschi Tullia Gallina
Publication year - 2007
Publication title -
european journal of lipid science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 94
eISSN - 1438-9312
pISSN - 1438-7697
DOI - 10.1002/ejlt.200700001
Subject(s) - partial least squares regression , olive oil , pulp and paper industry , environmental science , moisture , water content , mathematics , chemistry , food science , statistics , geology , engineering , organic chemistry , geotechnical engineering
A total of 287 olive lots and 161 olive oil samples were analyzed for fat content, moisture and free acidity, using a Fourier transform near‐infrared (FT‐NIR) instrument located in an industrial mill. Samples having a wide range of both reference values and olive lot sizes (from <0.5 to >4 t) were collected at three industrial mill plants, located in the same Italian region, which utilize different technological equipment for virgin olive oil production. Olive paste spectra were acquired in diffuse reflectance, while oil samples were measured in transmission. Calibration models for oil content and moisture of olives as well as free acidity of virgin olive oils were developed using partial least squares (PLS) regression, first derivative and straight line subtraction. Results of calibration and validation of the PLS models selected were good. The PLS results indicate good similarity between data obtained from FT‐NIR and reference laboratory methods, allowing a rapid and less expensive screening analysis. Unfortunately, the correlation between the oil yield values recorded for all olive lots at the industrial mills and the oil content predicted by FT‐NIR was not satisfactory ( R 2 = 0.605).