Physicochemical, Spectroscopic and Chromatographic Analyses in Combination with Chemometrics for the Discrimination of Four Sweet Cherry Cultivars Grown in Northern Greece.

A total of 56 sweet cherry samples belonging to four cultivars (Ferrovia, Canada Giant, Lapins, and Germersdorfer) grown in northern Greece were characterized and differentiated according to botanical origin. For the above purpose, the following parameters were determined: conventional quality parameters (titratable acidity (TA), pH, total soluble solids (TSS), total phenolic content (TPC), mechanical properties and sensory evaluation, sugars by High Performance Liquid Chromatography (HPLC), volatile compounds by GC/MS, and minerals by ICP-OES. Statistical treatment of the data was carried out using Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA). The results showed that the combination of volatile compounds and conventional quality parameters provided a correct classification rate of 84.1%, the combination of minerals and conventional quality parameters 86.4%, and the combination of minerals, conventional quality parameters and sugars provided the highest correct classification rate of 88.6%. When the above four cherry cultivars were combined with previously studied Kordia, Regina, Skeena and Mpakirtzeika cultivars, collected from the same regions during the same seasons, the respective values for the differentiation of all eight cultivars were: 85.5% for the combination of conventional quality parameters, volatiles and minerals; and 91.3% for the combination of conventional quality parameters, volatiles, minerals, and sugars.

Characterization and Botanical Differentiation of Monofloral and Multifloral Honeys Produced in Cyprus, Greece, and Egypt Using Physicochemical Parameter Analysis and Mineral Content in Conjunction with Supervised Statistical Techniques.

Thirty-four honey samples donated by beekeepers and purchased from supermarkets were collected during harvesting years 2010-2014 from Cyprus, Greece, and Egypt. The aims of this study were to characterize honey samples and, if possible, to differentiate honeys according to the honey type on the basis of physicochemical parameter values, mineral content, and their combination using supervised statistical techniques (linear discriminant analysis (LDA)). Physicochemical parameters (colour, pH, free acidity, total dissolved solids, salinity, electrical conductivity, and moisture content) were determined according to official methods, while minerals (Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, Hg, Mg, Mn, Mo, Ni, P, Pb, Sb, Si, Ti, Tl, V, and Zn) using inductively coupled plasma optical emission spectrometry. The majority of honey samples analyzed met the quality criteria set by the European directive and national decision related to honey. Implementation of multivariate analysis of variance (MANOVA) and LDA on specific physicochemical parameters, minerals, or their combination provided a satisfactory classification of honeys according to floral type. The overall correct classification rate (based on the cross-validation method) was 79.4% using 7 minerals and 91.2% using 8 physicochemical parameters. When the 15 parameters were combined, the classification rate of Egyptian honeys was improved by 25%.

Characterization and differentiation of sheep's milk from Greek breeds based on physicochemical parameters, fatty acid composition and volatile profile.

BACKGROUND: There are only limited studies in the literature attempting to differentiate sheep's milk originating from different sheep breeds. In the present study the physicochemical parameters (pH, percent fat, percent protein, percent lactose and percent total solids), fatty acid composition and volatile profile of raw milk from four autochthonous Greek breeds (Karagouniko, Mpoutsiko, Artas and Chios) were determined. The objective of the present study was to characterize and differentiate the sheep breeds based on the above analytical parameters in combination with chemometrics. RESULTS: The overall correct classification rate was 79.7%%, 84.4% and 100% based on physicochemical parameters, fatty acid composition and volatile profile, respectively. Volatiles proved to be the most effective of parameters analyzed for the differentiation of sheep breed. Furthermore, the combination of physicochemical parameters and fatty acid composition gave a correct classification rate equal to 96.9%. CONCLUSION: Either volatile profile or the combination of physicochemical parameters and fatty acid composition may be easily determined and used for the differentiation of sheep's milk from four different Greek breeds, this being the novelty of the present work. This may be very important in terms of PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) products related to specific geographical origin and sensory characteristics. © 2018 Society of Chemical Industry.

Characterization and geographical discrimination of commercial Citrus spp. honeys produced in different Mediterranean countries based on minerals, volatile compounds and physicochemical parameters, using chemometrics.

The objective of the present study was: i) to characterize Mediterranean citrus honeys based on conventional physicochemical parameter values, volatile compounds, and mineral content ii) to investigate the potential of above parameters to differentiate citrus honeys according to geographical origin using chemometrics. Thus, 37 citrus honey samples were collected during harvesting periods 2013 and 2014 from Greece, Egypt, Morocco, and Spain. Conventional physicochemical and CIELAB colour parameters were determined using official methods of analysis and the Commission Internationale de l' Eclairage recommendations, respectively. Minerals were determined using ICP-OES and volatiles using SPME-GC/MS. Results showed that honey samples analyzed, met the standard quality criteria set by the EU and were successfully classified according to geographical origin. Correct classification rates were 97.3% using 8 physicochemical parameter values, 86.5% using 15 volatile compound data and 83.8% using 13 minerals.

Characterization of four popular sweet cherry cultivars grown in Greece by volatile compound and physicochemical data analysis and sensory evaluation.

Volatile compounds, physicochemical and sensory attributes of four sweet cherry cultivars (Canada giant, Ferrovia, Lapins and Skeena) grown in Northern Greece were determined. Eighteen volatile compounds were identified and semi-quantified in cherries using solid phase micro extraction in combination with gas chromatography/mass spectrometry (SPME-GC/MS). Carbonyl compounds were the most abundant in sweet cherry aroma, followed by alcohols, esters and hydrocarbons/terpenes. Cherry cultivars in order of increasing amounts of volatiles were: Lapins < Canada giant < Ferrovia < Skeena. Physicochemical parameters determined included: titratable acidity (TA), pH, total soluble solids (TSS), maturity index (MI) and total phenolic content (TPC). TA ranged between 0.21 and 0.28 g malic acid/100 g fresh weight (FW). The pH ranged between 3.81 and 3.96. TSS ranged between 13.00 and 16.00 °Brix. MI ranged between 51.8 and 75.0. TPC ranged between 95.14 and 170.35 mg gallic acid equivalents (GAE)/100 g FW. Sensory evaluation showed that cherry colour, in order of increasing intensity, was: Canada giant < Ferrovia < Lapins < Skeena. Respective order for cherry firmness was: Canada giant < Lapins ≤ Ferrovia < Skeena and for flavour: Lapins < Canada giant < Skeena ≤ Ferrovia. Correlation of volatiles to physicochemical and sensory attributes showed varying trends.

Botanical discrimination of Greek unifloral honeys with physico-chemical and chemometric analyses.

The aim of the present study was to investigate the possibility of characterisation and classification of Greek unifloral honeys (pine, thyme, fir and orange blossom) according to botanical origin using volatile compounds, conventional physico-chemical parameters and chemometric analyses (MANOVA and Linear Discriminant Analysis). For this purpose, 119 honey samples were collected during the harvesting period 2011 from 14 different regions in Greece known to produce unifloral honey of good quality. Physico-chemical analysis included the identification and semi quantification of fifty five volatile compounds performed by Headspace Solid Phase Microextraction coupled to gas chromatography/mass spectroscopy and the determination of conventional quality parameters such as pH, free, lactonic, total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L, a, b. Results showed that using 40 diverse variables (30 volatile compounds of different classes and 10 physico-chemical parameters) the honey samples were satisfactorily classified according to botanical origin using volatile compounds (84.0% correct prediction), physicochemical parameters (97.5% correct prediction), and the combination of both (95.8% correct prediction) indicating that multi element analysis comprises a powerful tool for honey discrimination purposes.

Characterisation and classification of Greek pine honeys according to their geographical origin based on volatiles, physicochemical parameters and chemometrics.

The aim of the present study was to characterise and classify Greek pine honeys according to geographical origin, based on the determination of volatile compounds and physicochemical parameters using MANOVA and Linear Discriminant Analysis. Thirty-nine pine honey samples were collected during the harvesting period 2011 from 4 different regions in Greece known to produce good quality pine honey. The analysis of volatile compounds was performed by Headspace Solid Phase Microextraction-Gas Chromatography/Mass Spectroscopy. Fifty-five volatile compounds were tentatively identified and semi quantified. Physicochemical parameter analysis included the determination of pH, free, lactonic and total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L(∗), a(∗), b(∗). Using 8 selected volatile compounds and 11 physicochemical parameters, the honey samples were satisfactorily classified according to geographical origin using volatile compounds (84.6% correct prediction), physicochemical parameters (79.5% correct prediction) and the combination of both (74.4% correct prediction).

Characterization and classification of Western Greek olive oils according to cultivar and geographical origin based on volatile compounds.

The aim of the present study was to characterize and classify olive oils from Western Greece according to cultivar and geographical origin, based on volatile compound composition, by means of Linear Discriminant Analysis. A total of 51 olive oil samples were collected during the harvesting period 2007-2008 from six regions of Western Greece and from six local cultivars. Forty-five of the samples were characterized as extra virgin olive oils. The analysis of volatile compounds was performed by Headspace Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Fifty-three (53) different volatile compounds were tentatively identified and semi-quantified. Using selected volatile compound composition data (selection was based on the application of ANOVA to total volatiles to determine those variables showing substantial differences among samples of different geographical origin/cultivar), the olive oil samples were satisfactorily classified according to geographical origin (87.2%) and cultivar (74%).