Predicting the anthocyanin content of wine grapes by NIR hyperspectral imaging.

The aim of this study was to demonstrate the capability of hyperspectral imaging in predicting anthocyanin content changes in wine grapes during ripening. One hundred twenty groups of Cabernet Sauvignon grapes were collected periodically after veraison. The hyperspectral images were recorded by a hyperspectral imaging system with a spectral range from 900 to 1700 nm. The anthocyanin content was measured by the pH differential method. A quantitative model was developed using partial least squares regression (PLSR) or support vector regression (SVR) for calculating the anthocyanin content. The best model was obtained using SVR, yielding a coefficient of validation (P-R(2)) of 0.9414 and a root mean square error of prediction (RMSEP) of 0.0046, higher than the PLSR model, which had a P-R(2) of 0.8407 and a RMSEP of 0.0129. Therefore, hyperspectral imaging can be a fast and non-destructive method for predicting the anthocyanin content of wine grapes during ripening.

[1]  Ning Wang,et al.  Studies on banana fruit quality and maturity stages using hyperspectral imaging , 2012 .

[2]  Junhong Liu,et al.  Single-Kernel Maize Analysis by Near-Infrared Hyperspectral Imaging , 2004 .

[3]  Linzhang Yang,et al.  Deriving leaf chlorophyll content of green-leafy vegetables from hyperspectral reflectance , 2009 .

[4]  Pere Gou,et al.  Feasibility of near-infrared spectroscopy to predict a(w) and moisture and NaCl contents of fermented pork sausages. , 2010, Meat science.

[5]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[6]  Benhong Wu,et al.  Anthocyanin composition and content in grape berry skin in Vitis germplasm , 2008 .

[7]  Yande Liu,et al.  Computer and Computing Technologies in Agriculture V , 2011, IFIP Advances in Information and Communication Technology.

[8]  Jean-Michel Roger,et al.  Comparison of multispectral indexes extracted from hyperspectral images for the assessment of fruit ripening , 2011 .

[9]  Y. Glories,et al.  MATURATION PHENOLIQUE DES RAISINS ROUGES. RELATION AVEC LA QUALITE DES VINS. COMPARAISON DES CEPAGES MERLOT ET TEMPRANILLO , 1998 .

[10]  J. Blasco,et al.  Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment , 2012, Food and Bioprocess Technology.

[11]  Luca Rolle,et al.  Phenolic ripeness assessment of grape skin by texture analysis , 2008 .

[12]  A. Versari,et al.  Relationship among sensory descriptors, consumer preference and color parameters of Italian Novello red wines , 2009 .

[13]  Hongbin Pu,et al.  Feasibility of using hyperspectral imaging to predict moisture content of porcine meat during salting process. , 2014, Food chemistry.

[14]  M. José,et al.  Evolution of anthocyanins during maturation of tempranillo grape variety (Vitis vinifera) using polynomial regression models , 1990 .

[15]  F. E. LaMastus,et al.  The analysis of hyperspectral data using Savitzky-Golay filtering-practical issues. 2 , 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

[16]  Antonietta Baiano,et al.  Application of hyperspectral imaging for prediction of physico-chemical and sensory characteristics of table grapes , 2012 .

[17]  J. López-Roca,et al.  The effects of enological practices in anthocyanins, phenolic compounds and wine colour and their dependence on grape characteristics , 2007 .

[18]  M. Villanueva,et al.  Effect of irrigation on changes in the anthocyanin composition of the skin of cv Tempranillo (Vitis vinifera L) grape berries during ripening , 2001 .

[19]  S. Wold,et al.  The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses , 1984 .

[20]  W. R. Windham,et al.  CALIBRATION OF A PUSHBROOM HYPERSPECTRAL IMAGING SYSTEM FOR AGRICULTURAL INSPECTION , 2003 .

[21]  The Determination of Red Grape Quality Parameters Using the LOCAL Algorithm , 2006 .

[22]  Paul Allen,et al.  Prediction of moisture, color and pH in cooked, pre-sliced turkey hams by NIR hyperspectral imaging system , 2013 .

[23]  F. Cabello,et al.  Anthocyanin fingerprint of clones of Tempranillo grapes and wines made with them , 2009 .

[24]  Andrew L. Waterhouse,et al.  Effect of Maturity and Vine Water Status on Grape Skin and Wine Flavonoids , 2002, American Journal of Enology and Viticulture.

[25]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[26]  Pedro Melo-Pinto,et al.  Determination of anthocyanin concentration in whole grape skins using hyperspectral imaging and adaptive boosting neural networks , 2011 .

[27]  Gamal ElMasry,et al.  Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging , 2011 .