Determination of Carbohydrate Composition in Lentils Using Near-Infrared Spectroscopy.

Carbohydrates are the main components of lentils, accounting for more than 60% of their composition. Their content is influenced by genetic factors, with different contents depending on the variety. These compounds have not only been linked to interesting health benefits, but they also have a significant influence on the techno-functional properties of lentil-derived products. In this study, the use of near-infrared spectroscopy (NIRS) to predict the concentration of total carbohydrate, fibre, starch, total sugars, fructose, sucrose and raffinose was investigated. For this purpose, six different cultivars of macrosperm (n = 37) and microsperm (n = 43) lentils have been analysed, the samples were recorded whole and ground and the suitability of both recording methods were compared. Different spectral and mathematical pre-treatments were evaluated before developing the calibration models using the Modified Partial Least Squares regression method, with a cross-validation and an external validation. The predictive models developed show excellent coefficients of determination (RSQ > 0.9) for the total sugars and fructose, sucrose, and raffinose. The recording of ground samples allowed for obtaining better models for the calibration of starch content (R > 0.8), total sugars and sucrose (R > 0.93), and raffinose (R > 0.91). The results obtained confirm that there is sufficient information in the NIRS spectral region for the development of predictive models for the quantification of the carbohydrate content in lentils.

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics - a review.

Provenance is becoming increasingly important in meat supply chains as it lends products higher perceived quality. However, its precise definition and interpretation along with its associated characteristics factors have remained somewhat elusive. This review meticulously defines meat provenance while dissecting the essential factors and associated quality attributes that constitute its essence and are subsequently employed to establish pertinent markers for provenance. Meat provenance emerges as a multi-dimensional construct stemming from the adept management of a constellation of factors relating to geographical origin, farm production system, traceability, and authenticity. Through intricate interactions, these factors unveil innate originality that not only forges a distinct reputation but also imparts a unique typicity to the meat product. Gaining insights into a meat product's provenance becomes attainable by scrutinizing its pertinent composition and organoleptic quality traits. Trace elements and stable isotopes stand out as provenance markers, forging a direct connection to both geographical origin and dietary sources. While somewhat less direct in linkage, other markers such as plant biomarkers, fatty acid composition, pH levels, flavour and aromatic compounds along with organoleptic characteristics contribute to the overall understanding of provenance. Additionally, the identification of animal species and breeds serves as key markers, particularly in the context of protected geographical indications. The study findings are useful for the various stakeholders of how the information for meat provenance can be linked with intrinsic and extrinsic factors for meat quality and protecting the integrity of the supply chain with special reference to traceability and authenticity. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Nutritional, chemical, and antioxidant screening of selected varieties of lentils (Lens culinaris spp.) from organic and conventional agriculture.

BACKGROUND: Lentils are an ancient legume established worldwide for direct consumption and with great potential for application in food processing. In addition, it is a sustainable crop owing to its ability to scavenge nitrogen and carbon, and it improves the nutrient status of the soil. A diet rich in lentils has been linked to significant health benefits. However, the composition of lentils can be influenced by both the lentil variety and the growing conditions. The aim of this work was to evaluate the nutritional profiles and antioxidant potential, as well as the impact that the type of cultivation (conventional or organic) and the variety could have on these parameters, in different lentil varieties. RESULTS: Overall, carbohydrates are the major macronutrients in all varieties, with notable amounts of fibre (11.62-27.36%) and starch (41.98-50.27%). High amounts of protein and ash were also identified, particularly in the Beluga variety, with 21.9-23.3 and 1.38-1.82 g 100 g-1 fresh weight, respectively. Fructose and sucrose were detected (high-performance liquid chromatography (HPLC) with refraction index detection), along with oxalic, quinic, malic, and shikimic acids (ultra-fast liquid chromatography with photodiode array detection), and α- and γ-tocopherol isoforms (HPLC with fluorescence detection). Fatty acid methyl ester assessment showed the prevalence of polyunsaturated fatty acids (33.5-46.3%). Good antioxidant capacity (thiobarbituric acid reactive substances and oxidative haemolysis inhibition assay) was also noted. CONCLUSION: The results obtained showed that all the varieties analysed are an excellent source of fibre and have a good antioxidant capacity. Lentil variety has a greater influence on its nutritional composition than the type of cultivation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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.

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.

Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks.

Dry-cured ham is a high-quality product owing to its organoleptic characteristics. Sensory analysis is an essential part of assessing its quality. However, sensory assessment is a laborious process which implies the availability of a trained tasting panel. The aim of this study was the prediction of dry-ham sensory characteristics by means of an instrumental technique. To do so, an artificial neural network (ANN) model for the prediction of sensory parameters of dry-cured hams based on NIR spectral information was developed and optimized. The NIR spectra were obtained with a fiber-optic probe applied directly to the ham sample. In order to achieve this objective, the neural network was designed using 28 sensory parameters analyzed by a trained panel for sensory profile analysis as output data. A total of 91 samples of dry-cured ham matured for 24 months were analyzed. The hams corresponded to two different breeds (Iberian and Iberian x Duroc) and two different feeding systems (feeding outdoors with acorns or feeding with concentrates). The training algorithm and ANN architecture (the number of neurons in the hidden layer) used for the training were optimized. The parameters of ANN architecture analyzed have been shown to have an effect on the prediction capacity of the network. The Levenberg-Marquardt training algorithm has been shown to be the most suitable for the application of an ANN to sensory parameters.

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.

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.

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.

Effect of different physical pre-treatments on physicochemical and techno-functional properties, and on the antinutritional factors of lentils (Lens culinaris spp).

Lentils have a valuable physicochemical profile, which can be affected by the presence of antinutrients that may impair the benefits arising from their consumption. Different treatments can be used to reduce these undesirable compounds, although they can also affect the general composition and behaviour of the lentils. Thus, the effect of different processing methods on the physicochemical and techno-functional properties, as well as on the antinutritional factors of different lentil varieties was studied. Phytic acid was eliminated during germination, while tannins and trypsin inhibitors are mostly affected by cooking. Functional properties were also altered by processing, these being dependent on the concentration of different nutrients in lentils. All the studied treatments affected the physicochemical profile of lentils and their functional properties. Cooking and germination appear to be the most effective in reducing antinutritional factors and improving the physicochemical profile of the lentils, meeting the current nutritional demands of today's society.

The Characterization of Dry Fermented Sausages under the "Chorizo Zamorano" Quality Label: The Application of an Alternative Statistical Approach.

The characterization of quality brand meat products, such as "Chorizo Zamorano" dry fermented sausages, involves a wide range of data which makes it necessary to use alternative statistical methodologies. In this study, the feasibility of the Categorical Principal Components Analysis as a multivariate non-linear technique for the characterization of "Chorizo Zamorano" was assessed. The data analyzed were those of eight commercial brands covered by the quality mark over an eight-year period (2013-2020) and included parameters of the physicochemical composition and organoleptic properties of the product. The results showed that "Chorizo Zamorano" has an average moisture content (28.28%), high protein (38.38%) and fat (51.05%) contents, and a very low carbohydrate concentration (1.52%). Results showed that the fat and protein content and the sensory parameters related to external and internal odor appeared to be the studied variables with the greatest influence on the classification of the products according to their quality.

Nutritional, chemical and antioxidant evaluation of Armuña lentil (Lens culinaris spp): Influence of season and soil.

Lentils (Lens culinaris spp.) are a type of edible pulse consumed and produced worldwide; they are known for their valuable nutritional assets. The nutritional and chemical profiles of 34 Armuña lentil samples were assessed together with their antioxidant capacity. In addition, the influence of both the climatic conditions during the growing season and the soil type in which they grow (Luvisol and Cambisol) on nutritional and chemical profiles was also evaluated. Our results showed large amounts of valuable nutrients, such as carbohydrates, of which approximately 47.06 % and 29.11 % consist of fibers and starch respectively and significant amounts of proteins (20.47 to 25.56 g/100 g fw) and ashes. Sucrose stood out as the main free sugar in this variety, and oxalic and γ-tocopherol as the main organic acid and tocopherol isoform respectively. Fatty acid assessment showed the prevalence of PUFAs (45.3 to 63.7 %). A high antioxidant capacity (TBARS and OxHLIA) was also observed. Our results indicate that the growing season has a significant impact on the major nutrients in lentils such as the concentration of fat, ashes, fibers, and fructose and to a lesser extent proteins and sucrose. In addition, the two different soil types in this study do not seem to affect any of the parameters analyzed.

The Effects of the Progressive Replacement of Meat with Texturized Pea Protein in Low-Fat Frankfurters Made with Olive Oil.

There is growing interest in using healthy ingredients for the formulation of meat-based products. Among them, the replacement of pork fat with vegetable oils has attracted much attention. On the other hand, the use of vegetable proteins to replace meat provides multiple possibilities which have not been sufficiently studied. The aim of this study was to produce low-fat frankfurters in which all the pork fat had been replaced with olive oil and then to progressively replace (25%, 50%, 75% and 100%) the pork with textured pea protein. Texture, color, technological properties such as emulsion stability and cooking loss, proximate composition, and the fatty acid profile were analyzed. The results show that frankfurters made only with olive oil were slightly pale; however, they showed better emulsion stability and a healthier lipid profile than the 100%-meat-based frankfurters. Regarding the replacement of meat with texturized pea protein in the frankfurters made with olive oil, it was possible to replace up to 50% of the meat, and although significant differences were observed in terms of moisture, color, and texture, the product obtained showed similar values to other low-fat frankfurters.

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.

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.

Discrimination of seasonality in cheeses by near-infrared technology.

BACKGROUND: Owing to the importance of the season of collection of milk for cheese quality, a study was made of the usefulness of near-infrared spectroscopy (NIRS) for discriminating the seasonal origin (winter or summer) of milk and quantifying the fat content of cheeses, since fat is one of the components most affected by the season of collection of milk for the elaboration of cheeses. RESULTS: In the internal validation, 96% of samples from winter milk and 97% of samples from summer milk were correctly classified, while in the external validation the prediction rate of samples correctly classified was 92%. Moreover, quantitative models allowed the determination of fat in winter, summer and winter + summer cheeses. CONCLUSION: Rapid prediction of the fat content of cheeses and the seasonal origin (winter or summer) of milk was achieved using NIRS without previous destruction or treatment of samples.

Carbon stable isotopes, fatty acids and the use of NIRS to differentiate IBERIAN pigs.

This study explores the viability of the application of Near Infrared Spectrometry (NIR) for the rapid prediction of the ratio of 13C/12C stable isotopes and fatty acid composition in Iberian pigs. The potential use of this technique for distinguishing samples according to the duration of the montanera period was also studied. Subcutaneous fat samples from 50% and 100% Iberian pigs allowed to feed freely during different montanera periods were analyzed: 24 biopsies were taken prior to the montanera and 106 samples were taken after this feeding period. The results show significant correlations between δ13C (‰) and several fatty acids. Furthermore, it is possible to differentiate samples taken from pigs reared using different feeding regimes by analyzing the data obtained from the NIR spectra or by applying an Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) on data on δ13C (‰) and fatty acids in subcutaneous fat.

Phytochemical and Antioxidant Profile of Pardina Lentil Cultivars from Different Regions of Spain.

Lentils (Lens culinaris spp.) are an important food consumed worldwide given their high protein, fiber, mineral, and phytochemical contents, and can be used as a potential source of good nutrition for many people. With the purpose of valuing the Pardina variety, the quality brand from a protected geographical indication "Lenteja de Tierra de Campos", a full assessment of the nutritional, chemical, and antioxidant properties of 34 samples from this variety was carried out. Besides its actual rich nutritional profile, three phenolic compounds by high performance liquid chromatography equipped with photodiode array detection-mass (HPLC-DAD-ESI/MS) were identified (kaempferol derivatives) with slight differences between them in all extracts. Sucrose by high-performance liquid chromatography with a refraction index detector (HPLC-RI) and citric acid by ultra-fast liquid chromatography coupled with a photodiode array detector (UFLC-PDA) were the major identified sugar and organic acid components, respectively, as well as α-tocopherol and γ-tocopherol isoforms (HPLC-fluorescence). Additionally, all the extracts presented excellent antioxidant activity by the oxidative hemolysis inhibition assay (OxHLIA/TBARS). Briefly, Pardina lentils from this quality brand are a good source of nutritional and chemical components and should therefore be included in a balanced diet.