Chemometrics and innovative multidimensional data analysis (MDA) based on multi-element screening to protect the Italian porcino (Boletus sect. Boletus) from fraud

Blockchain technology and traceability in the agrifood industry

“…The object of traceability is defined as Traceable Resource Unit (TRU) (Aung & Chang, 2014) and each agrifood supply chain has its own TRU, as it depends on the structure of the supply chain itself and on national regulations (Albergamo et al., 2018; Badia‐Melisa, Mishra, & Ruiz‐Garcia, 2015; Freitas, Vaz‐Pires, & Câmara, 2020; Mottese et al., 2018; Mottese et al., 2020; Qian et al., 2020). In case of ham supply chain, for instance, the TRU is the pork leg and it can be traced from the farm to the market shelf; a similar approach can also be applied to beef, lamb, and chicken meat.…”

“…Traceability can be performed by means of various technologies and under various aspects, such as origin authentication, adulteration, and species or cultivar substitution (Albergamo et al., 2018; Badia‐Melisa et al., 2015; Freitas et al., 2020; Mottese et al., 2018; Mottese et al., 2020; Qian et al., 2020), and BCTs could improve food traceability in each phase (Kamilaris, Fonts, & Prenafeta‐Boldù, 2019). Indeed, as recently revised by Kamilaris et al.…”

Contribution of soil compositions, harvested times and varieties on chemical fingerprint of Italian and Turkish citrus cultivars

“…Hence, to define and to create a genetic map of food (Firmanda Al Riza et al ., 2021) and evaluate the rare earth elements (REEs) content as well as the micro–macro elements (Gaiad et al ., 2016; Potortì et al ., 2017; Mottese et al, 2020a, 2020b; Amaral, 2021; Gajek et al ., 2021; Pérez‐Rodríguez et al ., 2021), several multivariate analysis have been employed.…”

The Use of SPME-GC-MS IR and Raman Techniques for Botanical and Geographical Authentication and Detection of Adulteration of Honey

“…Chemometric tools are applied in targeted and non-targeted approaches for the identification of food adulteration or verification of their botanical or geographical origin [ 18 , 53 , 55 , 66 , 67 , 68 , 69 , 70 ]. The most common unsupervised methods, used for exploratory analysis in food authentication, include honey authentication, are principal component analysis (PCA) and hierarchical clustering analysis (HCA) [ 28 , 59 , 71 , 72 , 73 , 74 , 75 ]. For discrimination and classification purposes, linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), k-nearest neighbor (k-NN), principal component regression (PCR), multiple linear regression (MLR), or partial least squares regression (PLS-R) were commonly performed as supervised methods [ 28 , 57 , 72 , 73 , 74 , 76 , 77 ].…”

“…The most common unsupervised methods, used for exploratory analysis in food authentication, include honey authentication, are principal component analysis (PCA) and hierarchical clustering analysis (HCA) [ 28 , 59 , 71 , 72 , 73 , 74 , 75 ]. For discrimination and classification purposes, linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), k-nearest neighbor (k-NN), principal component regression (PCR), multiple linear regression (MLR), or partial least squares regression (PLS-R) were commonly performed as supervised methods [ 28 , 57 , 72 , 73 , 74 , 76 , 77 ]. For the botanical and geographical characterization of honey, most of the aforementioned chemometric tools have been reported such as PCA, HCA, LDA, and PLS-R, either combined with GC-MS [ 47 , 48 , 77 , 78 , 79 ] or with IR and Raman spectroscopy [ 9 , 16 , 54 , 56 , 63 , 80 ].…”