Evaluation of physico‐chemical properties,trace metal content and antioxidant activity of Indian honeys

In this study, effect of plant sources viz. Gossypium hirsutum, Coriander sativum, Murraya koenigii and Dalbergia sisso on twelve physico‐chemical properties, phenolic content, flavonoids content as well as on trace mineral (Fe, Cu, Ni, Mn, Cd and Pb) contents of honey were investigated and compared. All the physico‐chemical values were in the range of approved limits of European Commission Regulation and the source of honey had a significant (P < 0.05) effect on physico‐chemical properties, phenol content, flavonoid content and trace mineral content. The results of positive correlations between physico‐chemical properties (colour and antioxidant properties) and compositional components (phenols and flavonoids content) established that antioxidant properties were dependent on source of honey rather than on colour of honey. Pattern recognition methods such as principal component analysis and linear discriminate analysis were performed to classify honey on the basis of physico‐chemical properties, phenolic content, flavonoids content and trace metal content. The variables proline and lead exhibited higher discrimination power.     

Easy classification of traditional Minas cheeses using artificial neural networks and discriminant analysis

The classification of traditional Minas cheese (TMC) from different regions is important to ensure authenticity. Different chemometric approaches were used to discriminate TMCs from three different regions (Serro, Canastra and Araxá) of Minas Gerais, Brazil. The data obtained from the literature were used to develop an artificial neural network and to obtain linear discriminant functions, which were able to classify 100% of cheeses from different regions as a function of physico‐chemical composition. Both chemometric methods can be very useful tools to discriminate TMC from different regions based on physico‐chemical data which are obtained in a very quick and simple way.     

Evaluation of the effect of a maternal rearing system on the odour profile of meat from suckling lamb

The aim was to evaluate the effect of maternal rearing system on the chemical composition and odour profile of meat from suckling lamb. Twenty-four single male suckling lambs raised exclusively on maternal milk came from two rearing systems (extensive and intensive), and from Castellana and Churra breeds. The fatty acid composition of lamb meat from both breeds was affected by the rearing system, and Churra lamb reared under the extensive system had noticeable changes in odour attributes as detected by panellists and an electronic nose. Using partial least squares-discriminant analysis, the electronic nose was able to discriminate accurately between samples of Churra and Castellana meat according to their production system. However, it was not able to correctly classify meat samples from the extensive and intensive systems when both breeds were analysed together. The results suggest a significant effect of the rearing system and breed on suckling lamb meat quality traits.     

Rapid Differentiation of Listeria monocytogenes Epidemic Clones III and IV and Their Intact Compared with Heat‐Killed Populations Using Fourier Transform Infrared Spectroscopy and Chemometrics

The objectives of this study were to determine if Fourier transform infrared (FT‐IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat‐killed populations. FT‐IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1‐101 and R2‐499; ECIV: J1‐129 and J1‐220), and also from intact and heat‐killed cell populations of each EC strain using 250 scans at a resolution of 4 cm^?1 in the mid‐infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm^?1 separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat‐killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT‐IR spectral wavenumbers 1650 to 1390 cm^?1 were used to separate heat‐killed and intact populations of L. monocytogenes. The FT‐IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT‐IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism.     

Two by-products of the olive oil extraction industry as oleic acid supplement source for Iberian pigs: effect on the meat's chemical composition and induced lipoperoxidation

BACKGROUND: The objective of the present study was to evaluate the effect of two by‐products of the olive oil extraction industry—olive soapstocks and olive‐pomace oil—as added fat sources into feed concentrates, in two different rearing systems (free‐range complemented with concentrates and intensive rearing with concentrates) on the chemical composition and oxidative stability of Iberian pig meat. RESULTS: No differences in the chemical composition, colour and fatty acid composition of gluteobiceps m. were found due to added fat source. However, the feeding system had a significant effect on protein (P < 0.05), γ‐tocopherol (P < 0.05), colour (P < 0.01) and fatty acid composition of gluteobiceps m. Neither added fat source nor the feeding system had an effect on the malondialdehyde content. CONCLUSION: The addition of olive soapstock or olive‐pomace oil as fat sources into concentrates did not influence meat composition or fatty acid profile. However, there are differences in the fatty acid composition of meat from Iberian pigs as a result of the production system used. Copyright © 2012 Society of Chemical Industry     

Varietal Differentiation of Grape Juice Based on the Analysis of Near- and Mid-infrared Spectral Data

The aim of this study was to evaluate the usefulness of visible (VIS), near-infrared reflectance (NIR) and mid-infrared (MIR) spectroscopy combined with pattern recognition methods as tools to differentiate grape juice samples from commercial Australian Chardonnay (n = 121) and Riesling (n = 91) varieties. Principal component analysis (PCA), partial least squares discriminant analysis and linear discriminant analysis (LDA) were applied to classified grape juice samples according to variety based on both NIR and MIR spectra using full cross-validation (leave-one-out) as a validation method. Overall, LDA models correctly classify 86% and 80% of the grape juice samples according to variety using MIR and VIS-NIR, respectively. The results from this study demonstrated that spectral differences exist between the juice samples from different varietal origins and confirmed that the infrared (IR) spectrum contains information able to discriminate among samples. Furthermore, analysis and interpretation of the eigenvectors from the PCA models developed verified that the IR spectrum of the grape juice has enough information to allow the prediction of the variety. These results also suggested that IR spectroscopy coupled with pattern recognition methods holds the necessary information for a successful classification of juice samples of different varieties.     

Influence of cultivation parameters on the composition of volatile compounds and physico‐chemical characteristics of kiwi fruit

BACKGROUND: The effect of four cultivation parameters (post‐maturity harvest date, storage period at 0 °C and input of nitrogen or potassium fertilisers) on the physico‐chemical characteristics and composition of volatile compounds in kiwi fruit (Actinidia deliciosa) were evaluated. Five physico‐chemical parameters were selected, namely, pH, total acidity, dry matter, conductivity and refractive index. To our knowledge, no published data are available concerning the influence of nitrogen or potassium fertilisers on the volatile compounds and physico‐chemical parameters in kiwi fruit. RESULTS: Except for total acidity, these parameters were only weakly influenced by cultivation parameters. The concentrations of five main volatile compounds [hexanal, (E)‐hex‐2‐enal, hexan‐2‐ol, ethyl butyrate and hexanol] were also measured using gas chromatography and gas chromatography‐mass spectrometry. This work showed that the total content of volatile compounds decreased with post‐maturity harvest date and storage period of 3 months. In contrast, the input levels of nitrogen and potassium had little effect on the concentrations of volatile components CONCLUSION: This study demonstrates a high degree of difference in the physiochemical parameters and volatile composition of kiwi fruit, depending on the harvest date, the time of storage and the input of fertilisers. © 2012 Society of Chemical Industry     

Variety‐based discrimination of apple juices by an electronic nose and gas chromatography–mass spectrometry

The variety of raw material plays a crucial role in the quality and authenticity of fruit juices and juice products. To characterise and classify apple juices according to variety on the basis of their volatile compounds, electronic nose (EN) and gas chromatography–mass spectrometry (GC‐MS) were applied to detect the apple juices prepared by eight different varieties. The EN was used to analyse the mixture of volatile compounds as a whole and enabled rapid classification of juice samples when coupled with linear discriminant analysis (LDA). LDA showed a perfect discrimination of apple juices based on varieties. GC‐MS was utilised to illustrate the differences of volatile compounds among juice samples. Identification of volatile compositions and their contents provides useful access to differentiate juices from different varieties.     

Influence of sorghum grain type on wort physico‐chemical and sensory quality in a whole‐grain and commercial enzyme mashing process

To determine the most suitable types of sorghum for whole‐grain adjunct in lager beer brewing, 14 cultivars of five different types: white tan‐plant, white non‐tan‐plant, red non‐tannin, white tannin (type II) and red tannin (type III) were evaluated. The effects of grain type on wort physico‐chemical and sensory quality with raw grain and malt plus commercial enzyme mashing were assessed. Tannin content correlated significantly and negatively with wort extract and fermentable sugars (p < 0.001) and free amino nitrogen (FAN; p < 0.1). This is attributable to inactivation of the exogenous enzymes by the tannins during the mashing process. However, the type II tannin sorghums had wort quality attributes closer to the non‐tannin sorghum types, probably owing to their relatively low tannin content (≤1%). Malting gave a great improvement in wort extract, fermentable sugars and FAN, but substantially influenced wort sensory properties in terms of higher sourness, bitterness and astringency, as well as the expected more malty flavour. Worts from raw red non‐tannin sorghums were similar to those of white tan‐plant sorghums in both physico‐chemical and sensory quality. Thus, red non‐tannin sorghums, in view of their better agronomic quality, have considerable potential as a whole‐grain adjunct in lager beer brewing. Copyright © 2013 The Institute of Brewing & Distilling     

Discrimination of climacteric and non‐climacteric melon fruit at harvest or at the senescence stage by quality traits

BACKGROUND: This paper characterizes the quality traits at harvest and the changes associated with fruit senescence based on fruit physiological behaviour (climacteric or non‐climacteric) found in a collection of near‐isogenic lines (NILs) of melon (Cucumis melo L.). Data from both stages of postharvest development were analyzed by univariate and multivariate statistical analysis. RESULTS: The principal components and random forest analyses of the fruit quality traits allowed the best classification of the NILs by time (harvest, senescence), or by climacteric behaviour at harvest, but not at the senescent stage. The overall quality profile of the non‐climacteric senescent melons was, in general, very different from that of the climacteric ones, and was in accord with a longer storage life. Most of the taste quality traits (individual sugars or sucrose equivalents, titratable acidity and the citric, oxalacetic, glutamic and succinic acids) and the traits related to skin, flesh and juice colour parameters (chroma, hue angle) helped to distinguish the climacteric NILs from the non‐climacteric ones independently of the time considered. CONCLUSIONS: The time had a stronger effect on quality than the physiological behaviour. The discrimination by climacteric or non‐climacteric behaviour was usually better at harvest than at the senescent stage irrespective of the methodology used. Principal component analysis was the best multivariate method to discriminate by time and physiological behaviour followed by random forest and linear discriminant analysis. Copyright © 2009 Society of Chemical Industry     

Classification of geographical origins and prediction of δ13C and δ15N values of lamb meat by near infrared reflectance spectroscopy

Near infrared spectroscopy (NIRS) combined with chemometric analysis was investigated for its potential to classify the geographical origin and predict δ(13)C and δ(15)N values of lamb meat samples (n=99) from three pastoral regions and two agricultural regions of China. Principal component analysis (PCA), discriminant partial least squares analysis (D-PLS), linear discriminant analysis (LDA) and partial least squares regression (PLSR) were used for data analysis. D-PLS and LDA correctly classified 100% of the both pastoral and agricultural region samples, and gave a total correct classification of 88.9% and 75% to the five individual region samples, respectively. The best PLSR calibration models for predicting δ(13)C and δ(15)N of lamb meat were obtained with the determination coefficient (R(2)) 0.76 and 0.87, respectively. These results show that NIRS combined with chemometrics can be used as a rapid and effective method to discriminate the geographical origin and estimate the δ(13)C and δ(15)N of lamb meat.     

Detection of clenbuterol in beef meat,liver and kidney by mid‐infrared spectroscopy (FT‐Mid IR) and multivariate analysis

Mid‐infrared spectroscopy (FT‐Mid IR) coupled with multivariate analysis was used to predict clenbuterol in beef meat, liver and kidney. A SIMCA model was also developed to discriminate between pure (beef meat, liver and kidney) and spiked with clenbuterol samples (beef meat‐clenbuterol, liver‐clenbuterol and kidney‐clenbuterol). The best models to predict clenbuterol concentrations were obtained using the partial least squares algorithm (PLS) with a R² > 0.9 and SEC and standard error of prediction <0.296 and 0.324, respectively. The SIMCA model used to discriminate pure and spiked with clenbuterol samples showed 100% correct classification rate. Methods detection limit was 2 μg kg^?1. FT‐Mid IR coupled with chemometrics could be a simple and rapid screening tool for monitoring clenbuterol in beef meat, liver and kidney implicated in food poisoning. This method could be use for screening purposes.     

Physico‐chemical and sensory attributes in conjunction with multivariate analysis of two potato (Solanum tuberosum L.) cultivars after 90 days of storage: an exploratory authentication study

Two cultivars of potato (Spunta and Agria), were studied in terms of their physico‐chemical and sensory characteristics. These cultivars were cultivated in three geographical regions of Greece (Macedonia, North Greece; Thessaly, Central Greece; Peloponnese, South Greece) and were stored for 90 days after harvesting. The physico‐chemical characteristics of the tubers determined, were pH, total acidity, firmness, dry matter and content in Ν, in Κ, P, Cu, Mn, Zn and Fe. The sensory characteristics measured for raw tubers of potato after storage, were skin colour, skin brightness, internal colour, surface roughness, odour intensity, moistness, surface wrinkling and stains while the sensory characteristics measured for the boiled tubers of potato were odour intensity, moistness, special taste, sweet taste, aftertaste persistence, metal taste, pastiness, mastication, flavour intensity, elasticity and overall acceptability. The application of multivariate analysis (principal component analysis, cluster analysis and discriminant analysis), revealed a variety of relations between the various parameters and resulted in satisfactory grouping either per geographical region or per cultivar.     

An overview of the use of infrared spectroscopy and chemometrics in authenticity and traceability of cereals

Although both near infrared (NIR) spectroscopy and mid infrared (MIR) spectroscopy combined with multivariate data analysis (MVA) have been extensively used to measure chemical composition (e.g. protein, moisture, oil) in a wide number of grains few reports can be found on the use of this methods for varietal discrimination and traceability of cereals. In this overview applications of NIR spectroscopy and MIR spectroscopy combined with multivariate data methods such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA) to aid on the authentication and traceability of cereals are discussed.     

Multispectral image analysis approach to detect adulteration of beef and pork in raw meats

The aim of this study was to investigate the potential of multispectral imaging supported by multivariate data analysis for the detection of minced beef fraudulently substituted with pork and vice versa. Multispectral images in 18 different wavelengths of 220 meat samples in total from four independent experiments (55 samples per experiment) were acquired for this work. The appropriate amount of beef and pork-minced meat was mixed in order to achieve nine different proportions of adulteration and two categories of pure pork and beef. After an image processing step, data from the first three experiments were used for partial least squares-discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) so as to discriminate among all adulteration classes, as well as among adulterated, pure beef and pure pork samples. Results showed very good discrimination between pure and adulterated samples, for PLS-DA and LDA, yielding 98.48% overall correct classification. Additionally, 98.48% and 96.97% of the samples were classified within a ± 10% category of adulteration for LDA and PLS-DA respectively. Lastly, the models were further validated using the data of the fourth experiment for independent testing, where all pure and adulterated samples were classified correctly in the case of PLS-DA, while LDA was proved to be less accurate.     

Beef quality of young Angus × Nellore cattle supplemented with rumen-protected lipids during rearing and fatting periods

This work evaluated the beef quality parameters of 108 bulls randomly administered to three treatments during rearing in pastures and two treatments during fatting in feedlots, including mineral and rumen-protected lipids. Meat and fat color, cooking yield, shear force, sensorial traits and chemical and fatty acid compositions were evaluated. Generally, the beef quality parameters were not affected by the rumen protected lipids; however, supplementation with rumen-protected lipids during the rearing period yielded darker beef and brighter fat and increased beef tenderness in meat aged for 28 days compared to the meat from animals that received only mineral supplementation. In addition, the percent of meat polyunsaturated fatty acids was negatively affected by the inclusion of protected lipids, yielding 5.58 and 3.72% in animals fed with and without rumen-protected lipids, respectively, during the fatting period.     

Pig sire type and sex effects on carcass traits,meat quality and physicochemical and sensory characteristics of Serrano dry‐cured ham

This study demonstrates that improvements in animal line selection by breeding enterprises exert a strong effect on carcass traits, meat quality and sensory characteristics of Serrano dry‐cured ham. A total of 461 pigs from the offspring of a Duroc (DU) × Landrace (LD) sow mated with two DU boars and a DU × Large White (LW) boar from three breeding enterprises were evaluated. The two DU terminal sires were significantly different (P < 0.05) in carcass conformation, backfat thickness, ham and loin yields, raw ham traits, myoglobin concentration and total pigments formed during the curing process; in addition, the two lines provided different percentages of hams (54 vs 91%) with sufficient subcutaneous fat and weight to manufacture dry‐cured Serrano hams using a slow ripening process (11 months). The DU × LW sire had the best carcass and ham traits from an economic standpoint and obtained highest scores for sensory characteristics of Serrano ham evaluated by a trained panel test; furthermore, this line provided 84% of total hams suitable for manufacturing Serrano hams by a slow process. When the sex effect was analysed, carcass and ham traits of females were more favourable, but females presented a higher incidence of pale, soft and exudative (PSE) meat and a lower percentage of hams with sufficient subcutaneous fat and weight to produce Serrano hams using a slow ripening process (61% for females and 91% for castrates). On the other hand, castrates provided Serrano hams cured by a slow procedure with better organoleptic characteristics than females. Right and left hams were similar. Copyright © 2005 Society of Chemical Industry     

Sucrose‐free chocolate sweetened with Stevia rebaudiana extract and containing different bulking agents – effects on physicochemical and sensory properties

Sucrose‐free milk chocolates sweetened with Stevia and containing different types of commercial inulin or polydextrose as bulking agents, were examined in relation to their physico‐chemical, rheological and sensory properties. Compared with chocolate sweetened with sucrose, noticeable differences in lightness (L* values) were observed for sucrose‐free chocolates and attributed to changes in surface roughness. Chocolate containing inulin with a higher degree of polymerisation (DP) had higher melting points, greater plastic viscosity and an increased flow behaviour index. The Herschel‐Bulkley mathematical model most closely fitted to the rheological data. Chocolate containing the highest DP inulin was found to be very similar to control in tested sensory attributes (appearance, firmness, smoothness, mouth feel, flavour/taste and overall acceptance) when assessed by a consumer panel. These data indicate that it is possible to manufacture sucrose‐free chocolate using high DP inulin without adversely affecting its important physico‐chemical properties and sensory acceptance.     

Discrimination of yerba mate (<Emphasis Type="Italic">Ilex paraguayensis</Emphasis> St. Hil.) samples according to their geographical origin by means of near infrared spectroscopy and multivariate analysis

Near infrared reflectance (NIR) spectroscopy combined with multivariate data analysis was used to discriminate between the geographical origins of yerba mate (Ilex paraguayensis St. Hil.) samples. Samples were purchased from the local market and scanned in the NIR region (1100–2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to classify the samples based on their NIR spectra according to their geographical origin. Full cross validation was used as validation method when classification models were developed. The overall classification rates obtained were 76 and 100% using PLS-DA and LDA, respectively. The results demonstrated the usefulness of NIR spectra combined with multivariate data analysis as an objective and rapid method to classify yerba mate samples according to their geographical origin. Nevertheless, NIR spectroscopic might provide initial screening in the food chain and enable costly methods to be used more productively on suspect specimens.