José Miguel Hernández-Hierro

Determination of technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars during ripening by near infrared hyperspectral image: A preliminary approach

Hyperspectral images of intact grapes during ripening were recorded using a near infrared hyperspectral imaging system (900-1700 nm). Spectral data have been correlated with grape skin total phenolic concentration, sugar concentration, titratable acidity and pH by modified partial least squares regression (MPLS) using a number of spectral pre-treatments and different sets of calibration. The obtained results (RSQ and SEP, respectively) for the global model of red and white grape samples were: 0.89 and 1.23 mg g(-1) of grape skin for total phenolic concentration, 0.99 and 1.37 °Brix for sugar concentration, 0.98 and 3.88 g L(-1) for titratable acidity and for pH 0.94 and 0.12. Moreover, separate calibration models for red and white grape samples were also developed. The obtained results present a good potential for a fast and reasonably inexpensive screening of these parameters in intact grapes and therefore, for a fast control of technological and phenolic maturity.

Statistical correlation between flavanolic composition, colour and sensorial parameters in grape seed during ripening.

The aim of this work has been to determine the correlations between sensory analysis, colour and content of main flavanols present in seeds. For this, the flavanic composition of grape seeds with different degrees of maturity was analysed by HPLC-DAD-MS and the obtained results were correlated with CIELab colour parameters, perceived colour (C), hardness of the seed (HS), tannic intensity (TI) and astringency (A). Multiple linear regression analysis (MLR) with the variables showing significant correlations (p<0.05) was also performed. Grape seeds undergo important decreases in the content of catechins and procyanidin oligomers during ripening. Epicatechin-(4-8)-epicatechin-3-O-gallate (B2G) and (-)-epicatechin-3-O-gallate (ECG) are the flavanolic compounds whose contents decrease most. The changes in the phenolic composition accompany changes in TI, A and HS. The total content of flavanols in the seed is not the only factor affecting these attributes, since samples containing higher contents in flavanols can exhibit less astringency and tannic intensity than others with lower ones. The qualitative profile of the seeds is, therefore, also responsible for the sensations elicited in the mouth. A and HS parameters are more affected by the presence of galloylated dimeric procyanidins in the molecule than TI. CIELab colour parameters of seeds have high correlation coefficients with many flavanolic compounds. ECG was the compound most related to these parameters.

Colour and pigment composition of red wines obtained from co-maceration of Tempranillo and Graciano varieties.

The Vitis vinifera L. cv Graciano is often used as an integral component of Rioja wines because it is considered to contribute significantly to the quality of Tempranillo based wines. The aim of this work was to determine the effect of the incorporation of the Graciano variety on the colour and pigment composition of Tempranillo based wine and to evaluate the possible differences between blending Tempranillo with Graciano varietal wine (W wine) in contrast to a wine obtained by mixing these two grape varieties in the prefermentative maceration step (M wine). Results indicated that pigment extraction and retention in M wine was higher than in Tempranillo (T) wine. Colour differences (DeltaE(ab)(*)) between wines at the end of the study (after 12 months in bottles) were detectable by the human eye (DeltaE(ab)(*) > or = 3) in all cases except for T and W. These wines have indistinguishable colours even when using analytical methods (DeltaE(ab)(*) < or = 1). Regarding hue h(ab), T and W presented higher values (more orange-red) than Graciano (G) and M (more blue-red). PCA allowed the colour and composition analytical data to be reduced to a small number of principal components that could separate successfully between T and G wines and between the different steps of the winemaking process.

Relationship between skin cell wall composition and anthocyanin extractability of Vitis vinifera L. cv. Tempranillo at different grape ripeness degree

The relationship between cell wall composition and extractability of anthocyanins from red grape skins was assessed in Tempranillo grape samples harvested at three stages of ripening (pre-harvest, harvest and over-ripening) and three different contents of soluble solids (22, 24 and 26 °Brix) within each stage. Cell wall material was isolated and analysed in order to determine cellulose, lignin, non-cellulosic polysaccharides, protein, total polyphenols index and the degree of esterification of pectins. Results showed the influence of ripeness degree and contents of soluble solids on cell wall composition. Furthermore, principal components analysis was applied to the obtained data set in order to establish relationships between cell wall composition and extractability of anthocyanins. Total insoluble material exhibits the biggest opposition to anthocyanin extraction, while the highest amounts of cellulose, rhamnogalacturonans-II and polyphenols were positively correlated with anthocyanin extraction. Moreover, multiple linear regression was performed to assess the influence of the cell wall composition on the extraction of anthocyanin compounds. A model connecting cell wall composition and anthocyanin extractabilities was built, explaining 96.2% of the observed variability.

Feasibility Study on the Use of Near-Infrared Hyperspectral Imaging for the Screening of Anthocyanins in Intact Grapes during Ripening

The potential of near-infrared hyperspectral imaging to determine anthocyanins in intact grape has been evaluated. The hyperspectral images of intact grapes during ripening were recorded using a near-infrared hyperspectral imaging covering the spectral range between 900 and 1700 nm. Reference values of anthocyanins were obtained by HPLC-DAD. A number of spectral pretreatments and different mask development strategies were studied. Calibrations were performed by modified partial least-squares regression (MPLS) and present a good potential (RSQ of 0.86 and SEP values of 2.62 and 3.05 mg g(-1) of grape skin for nonacylated and total anthocyanins, respectively) for a fast and reasonably inexpensive screening of these compounds in intact grapes.

A novel method for evaluating flavanols in grape seeds by near infrared hyperspectral imaging.

Chemical composition of seeds changes during grape ripening and this affects the sensory properties of wine. In order to control the features of wines, the condition of seeds is becoming an important factor for deciding the moment of harvesting by winemakers. Sensory analysis is not easy to carry out and chemical analysis needs lengthy procedures, reagents, and it is destructive and time-consuming. In the present work, near infrared hyperspectral imaging has been used to determine flavanols in seeds of red (cv. Tempranillo) and white (cv. Zalema) grapes (Vitis vinifera L.). As reference measurements, the flavanol content was estimated using the p-dimethylaminocinnamaldehyde (DMACA) method. Not only total flavanol content was evaluated but also the quantity of flavanols that would be extracted into the wine during winemaking. A like-wine model solution was used for this purpose. Calibrations were performed by partial least squares regression and they provide coefficients of determination R(2)=0.73 for total flavanol content and R(2)=0.85 for predicting flavanols extracted with model solution. Values up to R(2)=0.88 were reached when cultivars were considered individually.

Feasibility study on the use of near infrared spectroscopy to determine flavanols in grape seeds

The potential of near infrared spectroscopy to determine the content of flavanols directly recording the infrared spectra of grape seeds has been evaluated. Moreover, the study shows the potential of this technique to obtain qualitative information related to the samples. In this case, the feasibility to discriminate between possible vineyards of origin has also been evaluated. Modified Partial Least Squares (MPLS) regression was used to develop the quantitative models in order to predict the content of flavanols. These models have been validated showing differences between 3.5% and 14.3% in the external validation. Moreover, Discriminant Partial Least Squares algorithm was used in the qualitative analysis to distinguish between two possible vineyards of origin and showed a high degree of accuracy. Prediction rates of samples correctly classified with a mean of 95% in internal validation and 97% in external validation were obtained. The procedure reported here seems to have an excellent potential for a fast and reasonably inexpensive analysis of these flavanols in grape seeds and could also be a tool to distinguish between possible vineyards of origin.

Influence of climatic conditions on the phenolic composition of Vitis vinifera L. cv. Graciano

The influence of different climatic conditions on the phenolic composition of grape skins and seeds of Vitis vinifera L. cv. Graciano - an autochthonous cultivar from Rioja and Navarra regions (Spain) - was evaluated during ripening in a separate way. Graciano grapes from two different vineyards with different climatic conditions and from two different vintages (2008 and 2009) were analysed. Clear differences between phenolic maturity pattern of grape skins and seeds were observed. In this context, it may be important to evaluate the phenolic maturity of seeds and skins in a separate way in order to decide the optimal harvest time. It was also noticeable that the effect of vintage (mainly due to changes in climatic conditions) may affect the changes in the phenolic composition of both grape skins and seeds. Although in a lesser extent, the effect of the vineyard was also observable, and it was especially relevant in vintages with irregular climatic conditions such as 2008 vintage. In a second strand, results obtained from the phenolic composition of grape seeds and skins at harvest, oenological parameters at harvest and climate conditions during vegetative stage were evaluated and relationships among the aforementioned variables were revealed.

Feasibility Study on the Use of Visible–Near-Infrared Spectroscopy for the Screening of Individual and Total Glucosinolate Contents in Broccoli

The potential of visible-near-infrared spectroscopy to determine selected individual and total glucosinolates in broccoli has been evaluated. Modified partial least-squares regression was used to develop quantitative models to predict glucosinolate contents. Both the whole spectrum and different spectral regions were separately evaluated to develop the quantitative models; in all cases the best results were obtained using the near-infrared zone between 2000 and 2498 nm. These models have been externally validated for the screening of glucoraphanin, glucobrassicin, 4-methoxyglucobrassicin, neoglucobrassicin, and total glucosinolates contents. In addition, discriminant partial least-squares was used to distinguish between two possible broccoli cultivars and showed a high degree of accuracy. In the case of the qualitative analysis, best results were obtained using the whole spectrum (i.e., 400-2498 nm) with a correct classification rate of 100% in external validation being obtained.

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting major components in bee pollen.

In the present work the potential of near infra-red spectroscopy technology (NIRS) together with the use of a remote reflectance fibre-optic probe for the analysis of fat, moisture, protein and chlorides contents of commercial cheeses elaborated with mixtures of cows, ewes and goats milk and with different curing times was examined. The probe was applied directly, with no previous sample treatment. The regression method employed was modified partial least squares (MPLS). The equations developed for the cheese samples afforded fat, moisture, protein, and chloride contents in the range 13-52%, 10-62%, 20-30%, and 0.7-2.9%, respectively. The multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEP (C)) obtained were respectively 0.97 and 0.995% for fat; 0.96% and 1.640% for moisture; 0.78% and 0.760% for protein, and 0.89% and 0.112% for chlorides.