Classification of honey applying high performance liquid chromatography, near-infrared spectroscopy and chemometrics

Nasab, Shima Ghanavati; Yazd, Mehdi Javaheran; Marini, Federico; Nescatelli, Riccardo; Biancolillo, Alessandra

doi:10.1016/j.chemolab.2020.104037

Cited by 21 publications

(14 citation statements)

References 38 publications

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“…Increasing honey consumption can be attributed to the consumer interest in natural foods with health benefits [1,2]. The properties derive from its particular chemical composition, as well as its sensorial characteristics and depend mainly on the flowers and biogeographical regions involved in its production [1][2][3][4][5][6]. Although they are also affected by processing, manipulation, packaging, and storage time [3,4,7], hence ensuring product quality is essential.…”

Section: Introductionmentioning

confidence: 99%

“…Accurate identification is aided by standards and pollen databases [13]. Nevertheless, this approach is time-consuming and strongly dependent on the qualifications and experience of the analyst [1,6,13]. Although for exact determination of honey origin, sensory, and physicochemical properties are also needed [12,14,15].…”

Section: Introductionmentioning

confidence: 99%

“…NIR technology has been described as a successful tool in analytical instrumentation and quality control in various fields such as food adulteration, authenticity control, the assessment of physicochemical attributes, rheological, or technological properties [1,13,[23][24][25][26], as well as in petrochemical industries, plastic contaminants, pharmaceuticals, cosmetics, and medical applications [22,27]. This method has been widely used in the field of honey quality detection, such as in the determination of 5-hydroxymethylfurfural [24,[28][29][30], diastase activity [7], moisture and reducing sugar content [23,24,28,31], compounds with antioxidant activity such polyphenols or minerals [1,25], floral origin discrimination [5,6,32], and honey adulteration [33,34].…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing

Escuredo

Meno

Seijo

2021

Foods

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There is an increase in the consumption of natural foods with healthy benefits such as honey. The physicochemical composition contributes to the particularities of honey that differ depending on the botanical origin. Botanical and geographical declaration protects consumers from possible fraud and ensures the quality of the product. The objective of this study was to develop prediction models using a portable near-Infrared (MicroNIR) Spectroscopy to contribute to authenticate honeys from Northwest Spain. Based on reference physicochemical analyses of honey, prediction equations using principal components analysis and partial least square regression were developed. Statistical descriptors were good for moisture, hydroxymethylfurfural (HMF), color (Pfund, L and b* coordinates of CIELab) and flavonoids (RSQ > 0.75; RPD > 2.0), and acceptable for electrical conductivity (EC), pH and phenols (RSQ > 0.61; RDP > 1.5). Linear discriminant analysis correctly classified the 88.1% of honeys based on physicochemical parameters and botanical origin (heather, chestnut, eucalyptus, blackberry, honeydew, multifloral). Estimation of quality and physicochemical properties of honey with NIR-spectra data and chemometrics proves to be a powerful tool to fulfil quality goals of this bee product. Results supported that the portable spectroscopy devices provided an effective tool for the apicultural sector to rapid in-situ classification and authentication of honey.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing

Escuredo

Meno

Seijo

2021

Foods

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“…According to Variable Importance in Projection (VIP), NIR spectroscopy did not achieve particularly good classification between the seven different varieties of honey samples. However, the mid-level data approach performed a more accurate prediction of the honey samples belonging to the alternative class “Others”, providing fewer false positives than the other strategies and improvement in the overall classification rates [ 99 ].…”

Section: Authentication Of Honey Using Ir Spectroscopymentioning

confidence: 99%

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

Sotiropoulou

Xagoraris

Revelou

et al. 2021

Foods

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The aim of this review is to describe the chromatographic, spectrometric, and spectroscopic techniques applied to honey for the determination of botanical and geographical origin and detection of adulteration. Based on the volatile profile of honey and using Solid Phase microextraction-Gas chromatography-Mass spectrometry (SPME-GC-MS) analytical technique, botanical and geographical characterization of honey can be successfully determined. In addition, the use of vibrational spectroscopic techniques, in particular, infrared (IR) and Raman spectroscopy, are discussed as a tool for the detection of honey adulteration and verification of its botanical and geographical origin. Manipulation of the obtained data regarding all the above-mentioned techniques was performed using chemometric analysis. This article reviews the literature between 2007 and 2020.

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“…In particular, recent studies have focused on the possibility of authenticating high value-added products, in most cases with a protected designation of origin, by coupling near-infrared spectroscopy and chemometric classification strategies. Examples of such product involve walnuts, 2 almonds, 3 hazelnuts, 4 Darjeeling black tea, 5 honey 6 , 7 or pasta, 8 just to cite a few.…”

mentioning

confidence: 99%

Classification of honey applying high performance liquid chromatography, near-infrared spectroscopy and chemometrics

Cited by 21 publications

References 38 publications

Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing

Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing

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

Analytical chemistry and chemometrics group, Department of Chemistry – University of Rome “La Sapienza”

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