Nondestructive measurement of the internal quality of bayberry juice using Vis/NIR spectroscopy

Abstract A nondestructive optical method for determining the internal quality of bayberry juice was investigated. Two types of preprocessing were used before the data were analyzed with multivariate calibration methods of PLS. Spectral data set as the logarithms of the reflectance reciprocal (absorbance (log1/ R )) were analyzed to build a best model for predicting the SSC and acidity (pH) of bayberry juice. A model with a regression coefficient of 0.85, a standard error of prediction (SEP) of 0.40 g/100 ml and a bias of −0.14 for SSC and 0.92, 0.19 g/100 ml, −0.05 for acidity showed an excellent prediction performance. At the same time, the sensitive wavelengths corresponding to the SSC and acidity of bayberry juices or some element at a certain band were proposed on the basis of regression coefficients by PLS. The results show that using Vis/NIRS technique to fast and nondestructive detection the internal quality of bayberry juices was feasible.

[1]  E. V. Thomas,et al.  Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information , 1988 .

[2]  S. Kawano,et al.  Nondestructive Determination of Sugar Content in Satsuma Mandarin using Near Infrared (NIR) Transmittance , 1993 .

[3]  C. Barbas,et al.  Development and validation of a capillary electrophoresis method for direct measurement of isocitric, citric, tartaric and malic acids as adulteration markers in orange juice. , 2000, Journal of chromatography. A.

[4]  Athanasia M. Goula,et al.  Application of near-infrared reflectance spectroscopy in the determination of major components in taramosalata , 2004 .

[5]  Robert B Jordan,et al.  Comparing density and NIR methods for measurement of Kiwifruit dry matter and soluble solids content , 2002 .

[6]  S. Sivakesava,et al.  Detection of Adulteration in Apple Juice Using Mid Infrared Spectroscopy , 2001 .

[7]  R. Lu.  PREDICTING FIRMNESS AND SUGAR CONTENT OF SWEET CHERRIES USING NEAR–INFRARED DIFFUSE REFLECTANCE SPECTROSCOPY , 2001 .

[8]  D. Slaughter.  Nondestructive Determination of Internal Quality in Peaches and Nectarines , 1995 .

[9]  Bin Chen,et al.  Application of wavelet transforms to improve prediction precision of near infrared spectra , 2005 .

[10]  Rainer Künnemeyer,et al.  Internal Quality Assessment of Mandarin Fruit by vis/NIR Spectroscopy , 2003 .

[11]  D M Haaland,et al.  PARTIAL LEAST - SQUARES METHOD FOR SPECTRAL ANALYSIS , 1988 .

[12]  L. Curda,et al.  NIR spectroscopy: a useful tool for rapid monitoring of processed cheeses manufacture , 2004 .

[13]  B. Nicolai,et al.  NON-DESTRUCTIVE MEASUREMENT OF ACIDITY, SOLUBLE SOLIDS, AND FIRMNESS OF JONAGOLD APPLES USING NIR-SPECTROSCOPY , 1998 .

[14]  G. S. Birth,et al.  INSTRUMENT FOR NONDESTRUCTIVE MEASUREMENT OF SOLUBLE SOLIDS IN HONEYDEW MELONS , 1990 .

[15]  L. Rodriguez-Saona,et al.  Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy. , 2001, Carbohydrate research.

[16]  Bin Chen,et al.  Improvement of predicting precision of oil content in instant noodles by using wavelet transforms to treat near-infrared spectroscopy , 2002 .

[17]  S. Kawano,et al.  Determination of Sugar Content in Intact Peaches by Near Infrared Spectroscopy with Fiber Optics in Interactance Mode , 1992 .

[18]  K. Miyamoto,et al.  Classification of High Acid Fruits by Partial Least Squares Using the near Infrared Transmittance Spectra of Intact Satsuma Mandarins , 1998 .

[19]  M. Cronin,et al.  The Impact of variable selection on the modelling of oestrogenicity , 2005, SAR and QSAR in environmental research.

[20]  Yong He,et al.  A New Approach to Predict N, P, K and OM Content in a Loamy Mixed Soil by Using Near Infrared Reflectance Spectroscopy , 2005, ICIC.

[21]  A. D. Jager,et al.  Non-destructive determination of soluble solids in apple fruit by near infrared spectroscopy (NIRS) , 1998 .

[22]  Y. Ozaki,et al.  Short-wave near-infrared spectroscopy of biological fluids. 1. Quantitative analysis of fat, protein, and lactose in raw milk by partial least-squares regression and band assignment. , 2001, Analytical chemistry.