A simple design for the validation of a FT-NIR screening method: Application to the detection of durum wheat pasta adulteration

Girolamo, Annalisa De; Arroyo, Marcia Carolina; Lippolis, Vincenzo; Cervellieri, Salvatore; Cortese, Marina; Pascale, Michelangelo; Logrieco, Antonio F.; Holst, Christoph von

doi:10.1016/j.foodchem.2020.127449

Cited by 11 publications

(5 citation statements)

References 13 publications

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“…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%

“…Furthermore, very recently, an EU validation procedure for screening methods was successfully applied to a multivariate FT-NIR spectroscopic method for durum wheat pasta authentication. The results of this proof-of-concept strategy demonstrated that FT-NIR is an attractive and suitable tool for the detection of durum wheat pasta adulteration [31].…”

Section: Supervised Classification Modelsmentioning

confidence: 94%

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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: Spectral Informationsupporting

confidence: 91%

Section: Supervised Classification Modelsmentioning

confidence: 94%

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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“…This methodology yielded an overall accuracy of 84%, which makes the model potentially suitable for on-line application. Girolamo et al [124] used for the first time a European (EU) validation model for screening of mycotoxins coupled with multivariate Fourier transform near infrared (FT-NIR) spectroscopy for wheat adulteration analysis. The statistical modeling used in this study enhanced the reliability of the model validation compared to screening methods based on binary results.…”

Section: Cassava and Wheatmentioning

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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“…La autenticidad de los alimentos es de interés primordial tanto para los consumidores como para los fabricantes, ya que las cadenas de suministro de alimentos se han vuelto cada vez más complejas, es necesario garantizar la calidad de los alimentos y velar por el cumplimiento de la legislación nacional e internacional. [1] En Perú se produce anualmente alrededor de 193.000 toneladas métricas (TM), pero la industria molinera demanda poco más de 2 millones de TM de trigo, siendo abastecido mayormente por importaciones [2].…”

Section: Introductionunclassified

Determination of semolina adulteration by NIR spectroscopy

Oblitas¹,

Cieza²,

Castro³

2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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T he objective was to implement a semolina percentage recognition system using near-infrared spectroscopy (NIR) and multivariate data analysis. For this purpose, 6 samples were an aly zed with different percentages of semolina (20, 4 0, 6 0, 80 an d 100 %) . Samples were repeated 20 times. T he observed NI R sp ect r um was absorbance in the range of 1100 and 2500 nm. In order to reduce the data, the analysis of main components was used by testing 24 classification models, from which the one that reached the highest level of precision was the Linear Support Vector Machine (SVM) algorithm, reaching 98.8%, achieving fairly satisfactory discriminatio n with values of PC1 (99.7%), PC2 (0.3%) and PC3 (0.1%), reachin g a total cumulative variation of the contribution of th e f ir st 3 P Cs of 99.9%. Partial Least Regression (PLS) models applied to NIR-spectra showed R2 between 0.9388. T hese values demonstrated that NIR spectroscopy can be used for the identification and quantif ication of fiber added to semolina.

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A simple design for the validation of a FT-NIR screening method: Application to the detection of durum wheat pasta adulteration

Cited by 11 publications

References 13 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

Determination of semolina adulteration by NIR spectroscopy

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