Traceability of Protected Geographical Indication (PGI) Interdonato lemon pulps by chemometric analysis of the mineral composition

Potortì, Angela Giorgia; Bella, Giuseppa Di; Mottese, Antonio Francesco; Bua, Giuseppe Daniel; Fede, Maria Rita; Sabatino, Giuseppe; Salvo, Andrea; Somma, Roberta; Dugo, Giacomo; Turco, Vincenzo Lo

doi:10.1016/j.jfca.2018.03.001

Cited by 37 publications

(17 citation statements)

References 31 publications

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“…PC rotation can be orthogonal and nonorthogonal. In simplest terms, in the orthogonal rotation the variables are assumed to be uncorrelated; conversely, nonorthogonal rotation methods assume that the variables are correlated, relaxing the orthogonality constraint to gain simplicity in the visual interpretation (Potortì et al., ). The biplot of the first two PCs resulting after oblimin (nonorthogonal) rotation is reported in Figure .…”

Section: Resultsmentioning

confidence: 99%

“…Demand for high levels of quality and safety in agriculture has increased significantly in recent decades, due not only to changes in eating habits and consumer behavior, but also to an increasing number of food frauds caused by the globalization of food supply chain (Di Bella et al., ; Mottese et al, ; Potortì, Di Bella, Turco, Rando, & Dugo, ). Combining high‐throughput techniques with multivariate analysis has proved to be an appealing strategy for studying food quality and provenance (Albergamo et al., , ; Bua et al., ; Gomes, Albergamo, Costa, Mondello, & Dugo, ; Potortί et al., , ; Vadalà et al., ).…”

Section: Introductionmentioning

confidence: 99%

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Discrimination of the Sicilian Prickly Pear (Opuntia Ficus‐Indica L., CV. Muscaredda) According to the Provenance by Testing Unsupervised and Supervised Chemometrics

Albergamo

Mottese

Bua

et al. 2018

Journal of Food Science

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Different multivariate techniques were tested in an attempt to build up a statistical model for predicting the origin of prickly pears (Opuntia ficus-indica L., cv. Muscaredda) from several localities within the Sicilian region. Specifically, two areas known for producing fruits marked respectively by TAP (traditional agri-food product) and PDO (protected designation of origin) brands, and three sites producing non-branded fruits, were considered. A validated inductively coupled plasma mass spectrometry (ICP-MS) method allowed to obtain elemental fingerprints of prickly pears, which were subsequently elaborated by unsupervised tools, such as hierarchical clustering analysis (HCA) and principal component analysis (PCA), and supervised techniques, such as stepwise-canonical discriminant analysis (CDA) and partial least squares-discriminant analysis (PLS-DA). With the exception of HCA, which was not enough powerful to correctly cluster all selected samples, PCA successfully investigated the effect of subregional provenance on prickly pears, thus, differentiating labeled products from the non-labeled counterpart. Also, stepwise CDA and PLS-DA allowed to build up reliable models able to correctly classify 100% of fruits on the basis of the production areas, by exploiting a restricted pool of metals. Both statistical models, including unsupervised (PCA) and supervised techniques (stepwise CDA or PLS-DA), may guarantee the provenance of prickly pears protected by quality labels and safeguard producers and consumers.Practical Application: Based on elemental analysis and chemometrics, the reliable traceability models herein proposed, could be applied to commercial Sicilian prickly pears protected by TAP and PDO logos to guarantee their provenance and, at the same time, to safeguard producers and consumers.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discrimination of the Sicilian Prickly Pear (Opuntia Ficus‐Indica L., CV. Muscaredda) According to the Provenance by Testing Unsupervised and Supervised Chemometrics

Albergamo

Mottese

Bua

et al. 2018

Journal of Food Science

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“…Dther elements such as K, S, Zn, and Cu also develop an important role in the maintenance of good organism function. Multi-element determination through spectrometric techniques after acid digestion procedure has often been employed for mineral composition evaluation of several fruit and fruit based-product samples (Caidan et al, 2014;Pacheco et al, 2017;Potortí et al, 2018;Rodríguez-Solana et al, 2014;Santos et al, 2016). Onductively coupled plasma optical emission spectrometry (OCP DES) is considered an efficient technique for multi-element determination due to the possibility of simultaneous analysis and low detection limits (LDD).…”

Section: Quality Pattern Evaluation Of Frozen Soursop Pulps: An Assesmentioning

confidence: 99%

Quality pattern evaluation of frozen soursop pulps: an assessment based on chemical composition and chemometric analysis

et al. 2020

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On the present study, the physicochemical properties and mineral composition of commercially-frozen soursop pulps from the southern region of the state of Bahia, Brazil, were evaluated. The physicochemical parameters such as soluble solids (°Brix), acidity and pH were determined according to reference methodologies. For mineral composition evaluation, samples were digested in a closed microwave system and the elements K, P, S, Ca, Mg, Fe, Cu, Zn, and Mn were quantified through inductively coupled plasma optical emission spectrometry (OCP DES). Soluble solids content ranged from 4.77 to 15.37 °Brix among the different brands of analyzed frozen pulps. Titratable acidity (equivalent to citric acid) and pH ranged from 0.49 to 1.00 and 3.61 to 4.57, respectively. Some samples presented irregularities in regard to quality pattern established in the Brazilian legislation. The following range of concentration, in μg g -1 , were found for essential elements: 0.30-0.88) and Zn (0.36-0.84). The use of principal component analysis (PCA) enabled a more in-depth data analysis, performing correlations between different variables and frozen pulp brands.Practical Application: The majority of recently published studies on soursop pulps only address evaluation of physicochemical properties and/or antioxidant activity. Thus, the innovative feature of this work is the assessment of quality pattern of frozen soursop pulps, correlating physicochemical properties with their mineral composition. For this, chemometric tools and a large number of samples have been used.

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“…Many studies have examined the authentication of food and agricultural products, such as onions [ 5 ], sechium edule [ 6 ], pomelos [ 7 ], rice [ 8 , 9 ], winter wheat [ 10 ], potatoes [ 11 ], wolfberry [ 12 ], sesame seeds [ 13 ], lemon [ 14 ], artichoke [ 15 ], olive oils [ 16 ], tomato [ 17 ], honeysuckle [ 18 ], and polygala tenuifolia [ 19 ]. In terms of the discrimination of tea leaves origin, a variety of methods have been applied, including high-performance liquid chromatography (HPLC) coupled with spectrophotometry [ 20 ], 1 H nuclear magnetic resonance ( 1 HNMR) spectroscopy [ 21 ], Fourier transform near-infrared spectroscopy (FT-NIRS) [ 22 ], gas chromatography-mass spectrometry (GC-MS) [ 23 ], taste sensor techniques [ 24 ], and stable isotope signature (C, H, O, N, Sr, and B) technology [ 3 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

Multielemental Analysis Associated with Chemometric Techniques for Geographical Origin Discrimination of Tea Leaves (Camelia sinensis) in Guizhou Province, SW China

et al. 2018

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This study aimed to construct objective and accurate geographical discriminant models for tea leaves based on multielement concentrations in combination with chemometrics tools. Forty mineral elements in 87 tea samples from three growing regions in Guizhou Province (China), namely Meitan and Fenggang (MTFG), Anshun (AS) and Leishan (LS) were analyzed. Chemometrics evaluations were conducted using a one-way analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that the concentrations of the 28 elements were significantly different among the three regions (p < 0.05). The correct classification rates for the 87 tea samples were 98.9% for LDA and 100% for OPLS-DA. The variable importance in the projection (VIP) values ranged between 1.01–1.73 for 11 elements (Sb, Pb, K, As, S, Bi, U, P, Ca, Na, and Cr), which can be used as important indicators for geographical origin identification of tea samples. In conclusion, multielement analysis coupled with chemometrics can be useful for geographical origin identification of tea leaves.

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Traceability of Protected Geographical Indication (PGI) Interdonato lemon pulps by chemometric analysis of the mineral composition

Cited by 37 publications

References 31 publications

Discrimination of the Sicilian Prickly Pear (Opuntia Ficus‐Indica L., CV. Muscaredda) According to the Provenance by Testing Unsupervised and Supervised Chemometrics

Discrimination of the Sicilian Prickly Pear (Opuntia Ficus‐Indica L., CV. Muscaredda) According to the Provenance by Testing Unsupervised and Supervised Chemometrics

Quality pattern evaluation of frozen soursop pulps: an assessment based on chemical composition and chemometric analysis

Multielemental Analysis Associated with Chemometric Techniques for Geographical Origin Discrimination of Tea Leaves (Camelia sinensis) in Guizhou Province, SW China

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