Discrimination between washed Arabica, natural Arabica and Robusta coffees by using near infrared spectroscopy, electronic nose and electronic tongue analysis.

BACKGROUND: The aim of this study is to investigate the feasibility of a 'holistic' approach, using near infrared (NIR) spectroscopy and electronic devices (electronic nose and electronic tongue), as instrumental tools for the classification of different coffee varieties. Analyses were performed on green coffee, on ground roasted coffee and on coffee beverage. Principal component analysis was applied on spectral and sensory data to uncover correlations between samples and variables. After variable selection, linear discriminant analysis was used to classify the samples on the basis of the three coffee classes: Robusta, natural Arabica and washed Arabica. RESULTS: Linear discriminant analysis demonstrates the practicability of this approach: the external test set validation performed with NIR data showed 100% of correctly classified samples. Moreover, a satisfying percentage of correct classification in cross-validation was obtained for the electronic devices: the average values of correctly classified samples were 81.83% and 78.76% for electronic nose and electronic tongue, respectively. CONCLUSION: NIR spectroscopy was shown to be a very reliable and useful tool to classify coffee samples in a fast, clean and inexpensive way compared to classical analysis, while the electronic devices could assume the role of investigating techniques to depict the aroma and taste of coffee samples.

Advances in NIR Spectroscopy Analytical Technology in Food Industries.

Industry 4 [...].

Effects of housing system and age of laying hens on egg performance in fresh pasta production: pasta cooking behaviour.

BACKGROUND: Very few studies concern the effects of layer housing systems and age on egg technological properties. Thus the aim of this work was to study the influence of these two factors on egg performance in fresh pasta production, focusing on pasta cooking behaviour. Samples of pasta subjected to analysis were prepared with eggs laid by Hy-Line Brown hens (from 27 to 68 weeks old) housed in cage, barn and organic systems. RESULTS: Higher average values of weight increase and matter loss during pasta cooking were observed for samples prepared with eggs laid by older hens. Such cooking behaviour indicated the development of a weaker pasta protein network, resulting from a decrease in the quantity of albumen protein and an increase in fat content, which is due to the reduction in albumen/yolk ratio during hen aging. The housing system had a significant effect only on matter loss in cooking water, but differences between samples were so small as to be unlikely perceived by consumers. CONCLUSION: Both hen age and housing system significantly affected pasta cooking behaviour, but the greatest effect was exerted by the hen age.

A FT-NIR Process Analytical Technology Approach for Milk Renneting Control.

The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA). Reconstituted skimmed milk and commercial pasteurized skimmed milk were mixed at two different ratios (60:40 and 40:60). Each mix ratio was prepared in six replicates and used for coagulation trials, monitored by fundamental rheology, as a reference method, and NIRS by inserting a probe directly in the coagulation vat and collecting spectra at two different acquisition times, i.e., 60 s or 10 s. Furthermore, three failure coagulation trials were performed, deliberately changing temperature or rennet and CaCl2 concentration. The comparison with fundamental rheology results confirmed the effectiveness of NIRS to monitor milk renneting. The reduced spectral acquisition time (10 s) showed data highly correlated (r > 0.99) to those acquired with longer acquisition time. The developed decision trees, based on PC1 scores and T2 MSPC charts, confirmed the suitability of the proposed approach for the prediction of coagulation times and for the detection of possible failures. In conclusion, the work provides a robust but simple PAT approach to assist cheesemakers in monitoring the coagulation step in real-time.

Influence of Two Innovative Packaging Materials on Quality Parameters and Aromatic Fingerprint of Extra-Virgin Olive Oils.

The performance of two innovative packaging materials was investigated on two Sardinian extra-virgin olive oils (Nera di Gonnos and Bosana). In particular, a transparent plastic film loaded with a UV-blocker (packaging B) and a metallized material (packaging C) were compared each other and to brown-amber glass (packaging A). During accelerated shelf-life tests at 40 and 60 °C, the evolution of quality parameters (i.e., acidity, peroxide value, K270, and phenolic content) was monitored, together with the aromatic fingerprint evaluated by electronic nose. Packaging B resulted in the best-performing material in protecting oil from oxidation, due to its lower oxygen transmission rate (0.1 ± 0.02 cm3/m2 24 h) compared to packaging C (0.23 ± 0.04 cm3/m2 24 h). At the end of storage, phenolic reduction was on average 25% for packaging B and 58% for packaging C, and the aromatic fingerprint was better preserved in packaging B. In addition, other factors such as the sanitary status of the olives at harvesting and the storage temperature were demonstrated to have a significant role in the shelf life of packaged extra-virgin olive oil.

Near Infrared Spectroscopy as a Green Technology for the Quality Prediction of Intact Olives.

Poorly emphasized aspects for a sustainable olive oil system are chemical analysis replacement and quality design of the final product. In this context, near infrared spectroscopy (NIRS) can play a pivotal role. Thus, this study aims at comparing performances of different NIRS systems for the prediction of moisture, oil content, soluble solids, total phenolic content, and antioxidant activity of intact olive drupes. The results obtained by a Fourier transform (FT)-NIR spectrometer, equipped with both an integrating sphere and a fiber optic probe, and a Vis/NIR handheld device are discussed. Almost all the partial least squares regression models were encouraging in predicting the quality parameters (0.64 < R2pred < 0.84), with small and comparable biases (p > 0.05). The pair-wise comparison between the standard deviations demonstrated that the FT-NIR models were always similar except for moisture (p < 0.05), whereas a slightly lower performance of the Vis/NIR models was assessed. Summarizing, while on-line or in-line applications of the FT-NIR optical probe should be promoted in oil mills in order to quickly classify the drupes for a better quality design of the olive oil, the portable and cheaper Vis/NIR device could be useful for preliminary quality evaluation of olive drupes directly in the field.

Environmental Impact of Food Preparations Enriched with Phenolic Extracts from Olive Oil Mill Waste.

Reducing food waste as well as converting waste products into second-life products are global challenges to promote the circular economy business model. In this context, the aim of this study is to quantify the environmental impact of lab-scale food preparations enriched with phenolic extracts from olive oil mill waste, i.e., wastewater and olive leaves. Technological (oxidation induction time) and nutritional (total phenols content) parameters were considered to assess the environmental performance based on benefits deriving by adding the extracts in vegan mayonnaise, salad dressing, biscuits, and gluten-free breadsticks. Phenolic extraction, encapsulation, and addiction to the four food preparations were analyzed, and the input and output processes were identified in order to apply the life cycle assessment to quantify the potential environmental impact of the system analyzed. Extraction and encapsulation processes characterized by low production yields, energy-intensive and complex operations, and the partial use of chemical reagents have a non-negligible environmental impact contribution on the food preparation, ranging from 0.71% to 73.51%. Considering technological and nutritional aspects, the extraction/encapsulation process contributions tend to cancel out. Impacts could be reduced approaching to a scale-up process.

Control and Monitoring of Milk Renneting Using FT-NIR Spectroscopy as a Process Analytical Technology Tool.

Failures in milk coagulation during cheese manufacturing can lead to decreased yield, anomalous behaviour of cheese during storage, significant impact on cheese quality and process wastes. This study proposes a Process Analytical Technology approach based on FT-NIR spectroscopy for milk renneting control during cheese manufacturing. Multivariate Curve Resolution optimized by Alternating Least Squares (MCR-ALS) was used for data analysis and development of Multivariate Statistical Process Control (MSPC) charts. Fifteen renneting batches were set up varying temperature (30, 35, 40 °C), milk pH (6.3, 6.5, 6.7), and fat content (0.1, 2.55, 5 g/100 mL). Three failure batches were also considered. The MCR-ALS models well described the coagulation processes (explained variance ≥99.93%; lack of fit <0.63%; standard deviation of the residuals <0.0067). The three identified MCR-ALS profiles described the main renneting phases. Different shapes and timing of concentration profiles were related to changes in temperature, milk pH, and fat content. The innovative implementation of MSPC charts based on T2 and Q statistics allowed the detection of coagulation failures from the initial phases of the process.

Influence of dietary protein content on the chemico-physical profile of dry-cured hams produced by pigs of two breeds.

The use of low-protein (LP) feeds is a good strategy to reduce the environmental release of N compounds, but their influence on the quality of the products must be considered. This study explored the influence of LP diet and two pig breeds (BR) with different lean growth ability on the quality traits of dry-cured hams. We analysed 40 left dry-cured hams from pigs of two BR [Duroc-Danbred crosses (Danbred) and Duroc × Large White crosses (Anas)] fed either conventional (147 to 132 g/kg, crude protein) or LP diet. The LP had a crude protein content reduced by 20% with respect to the conventional. The differences in ham quality resulting from protein reduction were small, with a decrease of the protein and an increase of the lipid content of the ham slice in Anas, but not in Danbred (BR × Diet interaction; P = 0.043). Therefore, the use of LP would be feasible and sustainable, without detrimental effects on products. It was found the pig genotypes with different potentials for lean growth may affect the initial ham weight, fat cover and seasoning losses of hams, but they appear to affect little other chemical, physical and textural quality traits of the dry-cured hams.

Studies on proofing of yeasted bread dough using near- and mid-infrared spectroscopy.

Dough proofing is the resting period after mixing during which fermentation commences. Optimum dough proofing is important for production of high quality bread. Near- and mid-infrared spectroscopies have been used with some success to investigate macromolecular changes during dough mixing. In this work, both techniques were applied to a preliminary study of flour doughs during proofing. Spectra were collected contemporaneously by NIR (750-1100 nm) and MIR (4000-600 cm(-1)) instruments using a fiberoptic surface interactance probe and horizontal ATR cell, respectively. Studies were performed on flours of differing baking quality; these included strong baker's flour, retail flour, and gluten-free flour. Following principal component analysis, changes in the recorded spectral signals could be followed over time. It is apparent from the results that both vibrational spectroscopic techniques can identify changes in flour doughs during proofing and that it is possible to suggest which macromolecular species are involved.

Handheld NIR device: A non-targeted approach to assess authenticity of fish fillets and patties.

This study evaluates the reliability of a handheld NIR device in distinguishing fillets and patties of Atlantic cod (n = 80) from those of haddock (n = 90), in comparison with a FT-NIR benchtop spectrometer. The authentication issue was faced by Linear Discriminant Analysis (LDA) and Soft Independent Modelling of Class Analogy (SIMCA), pre-treating spectral data with different algorithms, and validating models both internally and externally. The best LDA models gave 100% correct classification in prediction. Sensitivity >65% and specificity >74% in prediction were calculated for the best SIMCA models. No significant differences (P > .05) were found between the two instruments by McNemar test. Thus, the work demonstrated that a handheld NIR device can be a simple, cost-effective, and reliable alternative to benchtop spectrometers in fish fillet and patty authentication. These important findings can help in improving commercial fraud fight, extending the possibility to authenticate fish species also in processed products.

Effect of low-protein diets in heavy pigs on dry-cured ham quality characteristics.

The present work aimed at evaluating if heavy pig low-protein diets balanced for amino acid (AA) profile affect the quality characteristics of dry cured hams. To the aim, 40 hams obtained by Italian Duroc×Italian Large White pigs fed three different dietary crude protein and indispensable AA levels were compared with those obtained by a conventional Parma ham Protected Designation of Origin diet (C). No physico-chemical (aw, pH), chemical (gross composition, NaCl, lipid peroxidation, non-protein nitrogen, total volatile bases) or sensory characteristics of hams were systematically affected by the administered diet, animal sex or their interaction with the exception of total and subcutaneous fat (the latter measured by an image analysis procedure). Considering gilts, low-protein diets resulted in samples with higher fat content and subcutaneous fat thickness with respect to hams obtained with C diet. In conclusion, low protein diets in the finishing phase of pig breeding could reduce the environmental impact due to nitrogen excretion without significantly affecting ham quality.

Comparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms.

The main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of interest in acerola fruits.

Effect of fresh pork meat conditioning on quality characteristics of salami.

The aim of this work was to evaluate the effect of pork meat conditioning under different relative humidity (RH) values on salami quality characteristics. During a 6days conditioning period at 0°C under two levels of RH (95% vs. 80%), meat pH and weight loss were measured. Salami characteristics (moisture, weight loss, texture, appearance properties) were evaluated during 20days of ripening. Results showed that conditioning at 80% RH yielded a significantly drier meat, being the weight loss rate 1.6 times higher than at 95% RH. The lower water content of meat allowed a shorter salami ripening phase, guaranteeing an appropriate weight loss and the development of the desired texture, while maintaining good appearance properties. The acceleration of this production phase represents a clear economic advantage for producers and consumers, leading to higher profit margins and lower retail prices. The possibility of using FT-NIR spectroscopy as a valid tool for the rapid evaluation of salami ripening was also demonstrated.

Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics.

This work aims at the development of a method based on FT-NIR spectroscopy and multivariate analysis for the identification and quantification of minced beef meat adulteration with turkey meat. Samples were analyzed as raw, frozen-thawed and cooked. Different multivariate regression and class-modeling strategies were evaluated. PLS regression models with R(2) in prediction higher than 0.884 and RMSEP lower than 10.8% were developed. PLS-DA applied to discriminate each type of sample in two classes (adulteration threshold=20%) showed values of sensitivity and specificity in prediction higher than 0.84 and 0.76, respectively. Thus, the study demonstrates that FT-NIR spectroscopy coupled with suitable chemometric strategies is a reliable tool for the identification and quantification of minced beef adulteration with turkey meat not only in fresh products, but also in frozen-thawed and cooked samples. This achievement is of crucial importance in the meat industry due to the increasing number of processed meat products, in which technological treatments can mask a possible inter-species adulteration.

Ripening of salami: assessment of colour and aspect evolution using image analysis and multivariate image analysis.

During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection.

Beer fermentation: monitoring of process parameters by FT-NIR and multivariate data analysis.

This work investigates the capability of Fourier-Transform near infrared (FT-NIR) spectroscopy to monitor and assess process parameters in beer fermentation at different operative conditions. For this purpose, the fermentation of wort with two different yeast strains and at different temperatures was monitored for nine days by FT-NIR. To correlate the collected spectra with °Brix, pH and biomass, different multivariate data methodologies were applied. Principal component analysis (PCA), partial least squares (PLS) and locally weighted regression (LWR) were used to assess the relationship between FT-NIR spectra and the abovementioned process parameters that define the beer fermentation. The accuracy and robustness of the obtained results clearly show the suitability of FT-NIR spectroscopy, combined with multivariate data analysis, to be used as a quality control tool in the beer fermentation process. FT-NIR spectroscopy, when combined with LWR, demonstrates to be a perfectly suitable quantitative method to be implemented in the production of beer.

Evaluation of freshness decay of minced beef stored in high-oxygen modified atmosphere packaged at different temperatures using NIR and MIR spectroscopy.

Meat freshness has been monitored by various microbiological, chemical and sensorial indices. However, these methods are slow and not suited to automation. Infrared spectroscopy is one of the most convenient analytical tools which could be used to monitor the evolution of food quality. The aim of this work was to investigate the ability of both NIR (Near Infrared) and MIR (Mid Infrared) spectroscopy to follow meat freshness decay. The minced beef was packaged in high-oxygen modified atmosphere (30% CO2 and 70% O2) and stored at three temperatures. Spectra were collected by Fourier-Transformation (FT)-NIR and FT-IR instruments. PCA, applied to the data, was able to discriminate samples on the basis of storage time and temperature. The modelling of PC scores versus time allowed the setting of the time of initial freshness decay for the samples (6-7 days at 4.3°C, 2-3 days at 8.1°C and less than 1 day at 15.5°C).

Preliminary study on application of mid infrared spectroscopy for the evaluation of the virgin olive oil "freshness".

The freshness of virgin olive oils (VOO) from typical cultivars of Garda regions was evaluated by attenuated total reflectance (ATR) and Fourier transform infrared (FTIR) spectroscopy, in combination with multivariate analysis. The olive oil freshness decreased during storage mainly because of oxidation processes. In this research, 91 virgin olive oils were packaged in glass bottles and stored either in the light or in the dark at room temperature for different periods. The oils were analysed, before and after storage, using both chemical methods and spectroscopic technique. Classification strategies investigated were partial least square discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and soft independent modelling of class analogy (SIMCA). The results show that ATR-MIR spectroscopy is an interesting technique compared with traditional chemical index in classifying olive oil samples stored in different conditions. In fact, the FTIR PCA results allowed a better discrimination among fresh and oxidized oils, than samples separation obtained by PCA applied to chemical data. Moreover, the results obtained by the different classification techniques (PLS-DA, LDA, SIMCA) evidenced the ability of FTIR spectra to evaluate the olive oil freshness. FTIR spectroscopy results are in agreement with classical methods. The spectroscopic technique could be applied for the prediction of VOOs freshness giving information related to chemical modifications. The great advantages of this technique, compared to chemical analysis, are related to rapidity, non-destructive characteristics and low cost per sample. In conclusion, ATR-MIR represents a reliable, cheap and fast classification tool able to assess the freshness of virgin olive oils.