The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea.

The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of 322 samples of pure black, red, and green teas and binary blends were analyzed. The results showed that pure red teas had the highest content of As and Pb, green teas were the only ones containing Hg, and black teas showed higher levels of Cu. NIRS allowed to predict the content of Al, Pb, As, Hg, and Cu with ratio performance deviation values > 3 for all of them. Additionally, it was possible to discriminate pure samples from their respective blends with an accuracy of 98.3% in calibration and 92.3% in validation. However, when the samples were discriminated according to the percentage of blending (>95%, 95-85%, 85-75%, or 75-50% of pure tea) 100% of the samples of 10 out of 12 groups were correctly classified in calibration, but only the groups with a level of pure tea of >95% showed 100% of the samples as being correctly classified as to validation.

Performance of benchtop and portable spectroscopy equipment for discriminating Iberian ham according to breed.

Iberian ham is a highly appreciated product and according to Spanish legislation different labels identify different products depending on the genetic purity. Consequently, "100% Iberian" ham from purebred Iberian animals is more expensive than "Iberian" ham from Iberian x Duroc crosses. The hypothesis of this study was that to avoid labelling fraud it is possible to distinguish the breed (Iberian or Iberian x Duroc) of acorn-fed pigs of Iberian ham without any prior preparation of the sample by using spectroscopy that is a rapid and reliable technology. Moreover, portable devices which can be used in situ could provide similar results to those of benchtop equipment. Therefore, the spectra of the 60 samples (24 samples of 100% Iberian ham and 36 samples of Iberian x Duroc crossbreed ham) were recorded only for the fat, only for the muscle, or for the whole slice with two benchtop near-infrared (NIR) spectrometers (Büchi NIRFlex N-500 and Foss NIRSystem 5000) and five portable spectrometers including four portable NIR devices (VIAVI MicroNIR 1700 ES, TellSpec Enterprise Sensor, Thermo Fischer Scientific microPHAZIR, and Consumer Physics SCiO Sensor), and one RAMAN device (BRAVO handheld). The results showed that, in general, the whole slice recording produced the best results for classification purposes. The SCiO device showed the highest percentages of correctly classified samples (97% in calibration and 92% in validation) followed by TellSpec (100% and 81%). The SCiO sensor also showed the highest percentages of success when the analyses were performed only on lean meat (97% in calibration and 83% in validation) followed by microPHAZIR (84% and 81%), while in the case of the fat tissue. Raman technology showed the best discrimination capacity (96% and 78%) followed by microPHAZIR (89% and 81%). Therefore, spectroscopy has proved to be a suitable technology for discriminating ham samples according to breed purity; portable devices have been shown to give even better results than benchtop spectrometers.

Prediction of Mineral Composition in Wheat Flours Fortified with Lentil Flour Using NIR Technology.

Lentil flour is an important source of minerals, including iron, so its use in food fortification programs is becoming increasingly important. In this study, the potential of near infrared technology to discriminate the presence of lentil flour in fortified wheat flours and the quantification of their mineral composition is evaluated. Three varieties of lentils (Castellana, Pardina and Guareña) were used to produce flours, and a total of 153 samples of wheat flours fortified with them have been analyzed. The results show that it is possible to discriminate fortified flours with 100% efficiency according to their lentil flour content and to discriminate them according to the variety of lentil flour used. Regarding their mineral composition, the models developed have shown that it is possible to predict the Ca, Mg, Fe, K and P content in fortified flours using near infrared spectroscopy. Moreover, these models can be applied to unknown samples with results comparable to ICP-MS determination of these minerals.

Effects of the Replacement of Pork Backfat with High Oleic Sunflower Oil on the Quality of the "Chorizo Zamorano" Dry Fermented Sausage.

The "Chorizo Zamorano" dry fermented sausage is a traditional Spanish product which is highly appreciated by consumers. This paper studies the reformulation of this product in order to improve its lipid composition and its fatty acid profile and to reduce its fat content. To achieve this, the fat used in the production of the product was partially replaced with high oleic sunflower oil in proportions of 12.5%, 20%, and 50% of the total fat content. Proximate analysis, fatty acid profiles, lipid oxidation, and sensory analysis were studied. The replacement of fat with oil showed a significant effect on the evolution of the parameters analyzed during ripening in all cases. The batches with sunflower oil presented higher levels of monounsaturated fatty acids (MUFA) and lower levels of saturated fatty acids (SFA) and a similar amount of polyunsaturated fatty acids (PUFA) to the control products. The replacement of up to 20% of oil showed no significant differences for most of the physicochemical and sensory parameters analyzed at the end of the ripening.

Pistacia Root and Leaf Extracts as Potential Bioherbicides.

The allelopathic effect of pistachios was analyzed by field and laboratory tests. The parameters analyzed in the field trials were the biomass, weed density, weed diversity, and specific richness of the weed community. The studies were carried out in the area under the canopy and in the area beyond the influence of the pistachio tree, and the results obtained were compared. In the laboratory, germination bioassays were carried out on seeds of 11 weed species in root water extract, rhizosphere soil, and leaf water extract. The germination percentage, radicle elongation, epicotyl elongation, and germination index were determined. The results obtained show that significantly less biomass was present in the area under the influence of the trees, and fewer different weed species were detected in that area. In addition, germination bioassays showed that the aqueous leaf extract was a potent inhibitor of germination. The total content of flavonoids and phenols according to the organs (roots or leaves) was also studied. Extracts obtained from leaves showed higher concentrations of total phenols and also of flavones and flavanols than roots. Gallic acid, catechin, myricetin, and quercetin were identified in extracts obtained from both leaves and roots, while naringenin and rutin were identified only in the leaf extract. The presence of phenolic compounds in which allelopathic activity has been previously described and the results obtained in the trials seem to indicate that there is an allelopathic effect of the leaf extract, which could be used for weed control, thus facilitating ecological and/or sustainable management.

NIR Spectroscopy for Discriminating and Predicting the Sensory Profile of Dry-Cured Beef "Cecina".

For Protected Geographical Indication (PGI)-labeled products, such as the dry-cured beef meat "cecina de León", a sensory analysis is compulsory. However, this is a complex and time-consuming process. This study explores the viability of using near infrared spectroscopy (NIRS) together with artificial neural networks (ANN) for predicting sensory attributes. Spectra of 50 samples of cecina were recorded and 451 reflectance data were obtained. A feedforward multilayer perceptron ANN with 451 neurons in the input layer, a number of neurons varying between 1 and 30 in the hidden layer, and a single neuron in the output layer were optimized for each sensory parameter. The regression coefficient R squared (RSQ > 0.8 except for odor intensity) and mean squared error of prediction (MSEP) values obtained when comparing predicted and reference values showed that it is possible to predict accurately 23 out of 24 sensory parameters. Although only 3 sensory parameters showed significant differences between PGI and non-PGI samples, the optimized ANN architecture applied to NIR spectra achieved the correct classification of the 100% of the samples while the residual mean squares method (RMS-X) allowed 100% of non-PGI samples to be distinguished.

Flavonoid and Antioxidant Capacity of Propolis Prediction Using Near Infrared Spectroscopy.

The use of propolis as a dietary supplement or as an ingredient in different food products is increasing, due to its antioxidant and bactericidal properties. These nutritional properties directly depend on its phenolic composition. For this reason, this study analysed the total contents of flavones and flavonols, flavanones and dihydroflavonols, and the antioxidant capacity by using the methods of ABTS and linoleic acid/ß-carotene in 99 samples of propolis from Spain and Chile. A rapid method was developed for quantifying these parameters in raw propolis using near infrared (NIR) spectroscopy with a remote reflectance fibre-optic probe applied directly to the ground-up sample. The models developed allow for the determination of the total flavones and flavonols (0-183 mg quercetin/g propolis and 0-72 mg rutin/g propolis), of the total flavanones and dihydroflavonols (9-109 mg pinocembrin/g propolis extract), and of its antioxidant capacity by the ABTS method based on the reduction of the 2.2-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) radical cation(0-3212.6 nmol Trolox/mg of propolis) and of linoleic acid/ß-carotene (22-86% inhibition). The NIR spectroscopy models were applied in external validation to different samples of the calibration group, which led to the conclusion that the methods developed provide significantly identical data to the initial chemical data of reference.

Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy.

The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption.

Effects of somatic cells on the protein profile of hard ovine cheese produced from different breeds.

Bulk tank ewe's milks with low (<500,000 ml(-1)), medium (1,000,000-1,500,000 ml(-1)) and high (>2,500,000 ml(-1)) somatic cell counts (SCC) from three breeds were used to manufacture hard ewes'-milk cheese. Physico-chemical analysis and capillary electrophoresis of fresh cheeses and cheeses that had been ripened for 1, 2, 3 and 6 months were carried out. The results showed that high SCC levels in milk affected the moisture content of only freshly made cheeses and the pH, fat content and fat acidity of ripened cheeses. Regarding proteolysis, the levels of all ß-CNs in freshly made cheeses were significantly lower as the SCC values increased and the Castellana breed was the most affected by SCC levels because a significant decrease in all α-CNs was also observed as SCC levels rose. Analysis of the casein profile by principal component analysis (PCA) revealed that there were no clear differences according the SCC up to the third month. However in the third and sixth months cheeses with low levels of SC were closely grouped and characterised by the highest levels of intact caseins. Regarding the effect of breed, the results point to a more intense proteolytic activity in the Assaf breed, whose more matured cheeses showed the highest content of casein proteolytic fragments.

Influence of somatic cell counts and breed on physico-chemical and sensory characteristics of hard ewes'-milk cheeses.

The aim of the present work was to perform a physico-chemical, descriptive quantitative and consumer-preference analysis of hard ewes'-milk cheeses that had been matured for one year and to determine the correlations between the variables studied. The cheeses were elaborated with milk from three breeds of sheep (Castellana, Churra and Assaf) with different somatic cell counts (lower than 500,000 cells ml-1; between 1,000,000 and 1,500,000 cells ml-1, and more than 2,500,000 cells ml-1). The results show that the cheeses elaborated with milk with high SCC had lower values of dry extract and fat and high values of pH and fat acidity and were described as pungent, granulose and less creamy. Regarding the effect of breed, the cheeses made with milk from the Churra breed had lower values for fat and those made with Assaf breed milk were significantly more rancid. The study of correlations showed that creaminess was positively correlated with the dry extract and total fat content and negatively correlated with ash and fat acidity, indeed grainy texture and pungency had the opposite sign in their correlation with these latter variables. The yellow colour was positively correlated with ash and negatively with protein. Finally, the consumer preferences reveals that the less accepted cheeses showed the higher values for rancidness and pungency and they were less likely to accept the cheeses made with Assaf breed milk.

Effect of somatic cell counts on ewes' milk protein profile and cheese-making properties in different sheep breeds reared in Spain.

Bulk tank ewe's milks from Assaf, Castellana and Churra breeds categorized within three different Somatic Cell Count (SCC) groups (LSCC: <500,000; MSCC: 1,000,000 to 1,500,000; and HSCC: 2,500,000 to 3,000,000 cells ml-1) were used to investigate changes in capillary electrophoresis protein profiles and cheese-making properties. The results do not reveal a significant effect of SCC on total casein contents, because the sum of beta-caseins decreased as SCC increased; no statistically significant differences were observed for the sum of alpha-caseins, and the values of kappa-casein were higher in the HSCC milk. However, the soluble proteins other than alpha-lactalbumin and beta-lactoglobulin increased with SCC. Regarding the effect of breed, the Assaf breed had the lowest contents of kappa-CN, alpha s1-I-CN, alpha s1-II-CN 1-CN, alpha s1-III-CN, beta1-CN and beta2-CN. The protein profile was significantly correlated with curd textural properties. alpha s1-I-CN was the most influential variant because it was positively correlated with a large number of textural parameters. Cheese yield was positively correlated with all casein variants except alpha s1-III-CN, showing that the milk from local breeds were more suitable for cheese-making due to their higher contents of all the casein variants. Regarding curd texture properties LSCC milk curds showed more cohesiveness, associated with its lower content of alpha s1-III-CN and Castellana milk curds showed the highest values for firmness owing to their higher content of alpha s1-I-CN.

Proteolysis and texture of hard ewes' milk cheese during ripening as affected by somatic cell counts.

Ewes' milk samples with low (<500,000 ml(-1)), medium (1,000,000-1,500,000 ml(-1)) and high (> 2,500,000 ml(-1)) somatic cell counts (SCC) were used to manufacture hard ewes' cheese using the Zamorano cheese manufacturing protocol. Cheeses that had been ripened for 1, 2 and 3 months were used to obtain isoelectric ovine casein that was analysed by capillary electrophoresis. The texture of the cheeses during ripening was determined instrumentally using the Warner-Bratzler maximum shear force and assessed for sensory qualities by consumers using hedonic tests. The study revealed that the pH value and the lactose content of the milk were affected by high SCC and that the coagulation properties were dependent on the somatic cell content. The protein and moisture contents of the cheeses were unaffected by SCC but a significant increase of pH with ripening time were observed in high-SCC cheeses. The results also pointed to a significant increase in proteolysis related to SCC levels, showing that intact casein, both alphas1 and beta-casein, decreased as the SCC of milk increased, and that the proteolytic fragments, mainly I-alphas1, increased with SCC levels. Significant differences in texture were found among the samples, the cheeses made with high levels of SCC being significantly less compact at each ripening time. The differences in texture were detected by the consumers, who reported defects in cheeses made with high levels of SCC. Indeed, high SCC cheeses were significantly less well accepted.

Evaluation of the effect of somatic cell counts on casein proteolysis in ovine milk cheese by means of capillary electrophoresis.

The primary proteolysis of ewe's cheeses made from milk with different somatic cell counts (5CC) included three groups of study: cheeses made with milk with less than 500,000 somatic cells (SC); with milk containing 1 x 10(6) to 1.5 x 10(6) SC, the normal range for ewe's milk; and with milk containing more than 3.106 SC. These were examined by capillary eledrophoresis. Intact caseins as alpha(s1)-CN (I, II, and III), alpha(s2)-CN, and beta-CN (beta, beta1, and beta2) were identified. Some peptides resulting from casein proteolysis as gamma-CN and l-alpha(s1)-CN were also identified. The study reveals that proteolysis increased with ripening time and the extent of casein degradation depended on the content in SC, showing that residual intact casein, both alpha(s1)-CN and beta-CN, decreased as the SCC of milk increased because of their higher proteolytic enzyme levels. The proteolysis pattern indicated that several enzymes were implicated in increased proteolysis in high SCC cheeses.

Experimental design applied for the simultaneous analysis of whey proteins and caseins of binary and ternary milk mixtures by capillary electrophoresis.

A capillary electrophoresis method for the simultaneous separation of caseins, whey proteins, and para-kappa-casein that appears during the manufacture of cheese was optimized using the response surface methodology. The parameters selected for this study were pH, voltage, and temperature. Under the optimized conditions (30 kV at 20 degrees C with 10 mM phosphate buffer at pH 3) casein proteins alpha(s)-casein; beta-casein, including genetic variants A1, A2, and B, kappa-CN, and para-kappa-CN; and whey proteins alpha-lactalbumin and beta-lactoglobulin (A and B variants) were separated. The method was applied successfully to skim milk, to casein precipitated at pH 4.6, and to a model sample containing rennet casein and milk. The milk used was of three types: cow, ewe, and goat. The present procedure can be easily applied to the separation of the major bovine, ovine, and caprine milk proteins in binary and ternary milk mixtures.