A novel and simple method based on the chemometric treatment of UV–visible spectra of acetonitrile extracts to detect plant-derived adulterants in saffron (Crocus sativus L.)
Martina Foschi , Francesca Di Donato , Alessandra Biancolillo , Francesco D’Emilia , Maria Anna Maggi , Angelo Antonio D’Archivio
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引用次数: 0
Abstract
We developed a UV–visible spectroscopic method, inspired by ISO-3632 normative conventionally adopted for grading saffron, to detect the adulteration of this spice by Calendula officinalis L. petals (calendula), Carthamus tinctorius L. petals (safflower), and Curcuma longa L. powdered rhizomes (turmeric). To enhance the spectral visibility of these adulterants relative to saffron, we tested various solvents, identifying acetonitrile as the most suitable extraction medium. We analyzed 40 genuine and 123 adulterated saffron samples, each containing 5–10 % w/w contamination (41 samples for each type of adulterant), using acetonitrile extraction. The resulting UV–visible spectra were processed using unsupervised multivariate statistical methods to distinguish between authentic and adulterated saffron. The Sequential Pre-processing through Orthogonalization (SPORT) algorithm, based on sequential and orthogonalized partial least squares (SO-PLS), was first applied to differentiate the two groups. Using a calibration set of 122 samples, the SPORT model correctly classified 37 of 38 external test samples, regardless of the type or level of contamination. Additionally, a class model for genuine saffron was developed using SIMCA (Soft Independent Modelling of Class Analogies), under the same calibration and validation conditions as the SPORT model. SIMCA accurately identified all test samples, with the exception of one pure saffron and one adulterated sample.
期刊介绍:
The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects.
The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.