Authentication of P.G.I. Gragnano pasta by near infrared (NIR) spectroscopy and chemometrics

Firmani, Patrizia; Piscopia, Giuseppe La; Bucci, Remo; Marini, Federico; Biancolillo, Alessandra

doi:10.1016/j.microc.2019.104339

Cited by 25 publications

(12 citation statements)

References 31 publications

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“…This variability was probably related to the different growing zones, latitudes, and moisture conditions of the wheat used for manufacturing the samples analyzed in the present study, as reported elsewhere [8,9,42]. These results also confirmed those reported by Firmani et al [32,33] that investigated the variable importance in projection indices to examine which variables were mainly involved in the discrimination between Gragnano and non-Gragnano pasta samples and between durum semolina varieties harvested in different Italian macro-areas. They found that the most relevant spectral zones were around 4000, 5000, and 7000 cm −1 .…”

Section: Pcasupporting

confidence: 92%

“…Finally, the band between 4900 and 4500 cm −1 arose from the combination of C = O stretch second overtone and C-N stretching and N-H in-plane bend of both proteins and carbohydrates [34,40,41] (Figure 1). These outcomes confirmed those reported by other authors applying NIR spectroscopy to the traceability of wheat and pasta [24,27,28,[30][31][32][33].…”

Section: Spectral Informationsupporting

confidence: 91%

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Rapid Authentication of 100% Italian Durum Wheat Pasta by FT-NIR Spectroscopy Combined with Chemometric Tools

Girolamo

Cervellieri

Mancini

et al. 2020

Foods

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Italy is the country with the largest durum wheat pasta production and consumption. The mandatory labelling for pasta indicating the country of origin of wheat has made consumers more aware about the consumed pasta products and is influencing their choice towards 100% Italian wheat pasta. This aspect highlights the need to promote the use of domestic wheat as well as to develop rapid methodologies for the authentication of pasta. A rapid, inexpensive, and easy-to-use method based on infrared spectroscopy was developed and validated for authenticating pasta made with 100% Italian durum wheat. The study was conducted on pasta marketed in Italy and made with durum wheat cultivated in Italy (n = 176 samples) and on pasta made with mixtures of wheat cultivated in Italy and/or abroad (n = 185 samples). Pasta samples were analyzed by Fourier transform-near infrared (FT-NIR) spectroscopy coupled with supervised classification models. The good performance results of the validation set (sensitivity of 95%, specificity and accuracy of 94%) obtained using principal component-linear discriminant analysis (PC-LDA) clearly demonstrated the high prediction capability of this method and its suitability for authenticating 100% Italian durum wheat pasta. This output is of great interest for both producers of Italian pasta pointing toward authentication purposes of their products and consumer associations aimed to preserve and promote the typicity of Italian products.

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Section: Pcasupporting

confidence: 92%

Section: Spectral Informationsupporting

confidence: 91%

Rapid Authentication of 100% Italian Durum Wheat Pasta by FT-NIR Spectroscopy Combined with Chemometric Tools

Girolamo

Cervellieri

Mancini

et al. 2020

Foods

View full text Add to dashboard Cite

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“…The authors further noted that more uniform particle sizes aided in quantitative analysis (i.e., 100 mesh > 70 mesh > 40 mesh > full granules). Another subject of frequent food fraud, Gragnano pasta from the homonym Italian town, was identified against imposter products by coupling NIR spectra with two classifiers, partial least squares discriminant analysis and soft independent modeling of class analogies [91]. With a test set of 200 samples, the resulting models correctly classified all Gregnano pasta with only a single misclassification of an imposter sample.…”

Section: Grains and Floursmentioning

confidence: 99%

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Bwambok

Siraj

Macchi

et al. 2020

Sensors

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Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.

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“…These two instrumental techniques were chosen because they are relatively rapid, non-destructive, and they have demonstrated to be suitable allies against frauds in food matrices [7][8][9][10][11]. On the other hand, the choice of the classifier fell on data fusion (DF) approaches because, when applicable, multi-block methodologies are expected to perform better than the disjoint analysis of the individual data blocks [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Sequential Data Fusion Techniques for the Authentication of the P.G.I. Senise (“Crusco”) Bell Pepper

et al. 2021

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Bell pepper is the common name of the berry obtained from some varieties of the Capsicum annuum species. This agro-food is appreciated all over the world and represents one of the key ingredients of several traditional dishes. It is used as a fresh product, or dried and ground as a seasoning (e.g., paprika). Specific varieties of sweet pepper present organoleptic peculiarities and they have been awarded by quality marks as a further confirmation of their unicity (e.g., Piment d’Espelette, Pimiento de Herbón, Peperone di Senise). Due to the market value of this aliment, it can be subjected to frauds, such as adulterations and sophistication. The present study lays on these considerations and aims at developing a spectroscopy-based approach for authenticating Senise bell pepper and for detecting its adulteration with common paprika. In order to achieve this goal, 60 pure samples of bell pepper from Senise were analyzed by mid- and near-infrared spectroscopies. Then, in order to mimic the adulteration, 40 mixtures of Senise bell pepper and paprika were prepared and analyzed (by the same spectroscopic techniques). Eventually, two different multi-block classification approaches (sequential and orthogonalized partial least squares linear discriminant analysis and sequential and orthogonalized covariance selection linear discriminant analysis) were used to discriminate between pure and adulterated Senise bell pepper samples. Both proposed procedures achieved extremely successful results in external validation, correctly classifying all the (thirty-five) test samples, indicating that both approaches represent a winning solution for the investigated classification problem.

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Authentication of P.G.I. Gragnano pasta by near infrared (NIR) spectroscopy and chemometrics

Cited by 25 publications

References 31 publications

Rapid Authentication of 100% Italian Durum Wheat Pasta by FT-NIR Spectroscopy Combined with Chemometric Tools

Rapid Authentication of 100% Italian Durum Wheat Pasta by FT-NIR Spectroscopy Combined with Chemometric Tools

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Sequential Data Fusion Techniques for the Authentication of the P.G.I. Senise (“Crusco”) Bell Pepper

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