Relation Between Near-Infrared Spectroscopy and Physicochemical Parameters for Discrimination of Honey Samples from Jatai weyrauchi and Jatai angustula Bees

Leme, Luiza Mariano; Montenegro, Hercules Rocha; Santos, Larissa da Rocha dos; Sereia, Maria Josiane; Valderrama, Patrícia; Março, Paulo Henrique

doi:10.1007/s12161-018-1148-7

Cited by 15 publications

(11 citation statements)

References 19 publications

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“…The viscosity values found in our study were higher than the values reported by Leme et al [ 168 ] (0.41–1.61). This author investigated honey samples harvested from Roraima, in the north of Brazil, and Paraná, in the south of Brazil.…”

Section: Resultscontrasting

confidence: 91%

The Influence of Chemical Contaminants on the Physicochemical Properties of Unifloral and Multifloral Honey

Scripcă

Amariei

2021

Foods

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The aim of this study was to evaluate and compare the effect of antibiotic and pesticide residues on the physicochemical properties of unifloral and multifloral honey. The mineral elements content of honey was analyzed and correlated with antibiotic and pesticide residues, and a positive correlation was found between manganese and neonicotinoids. Potassium was found to be the most abundant mineral compound. Correlations were found between mineral content, color, and the content of antibiotic and pesticide residues of honey. In meadow honey, residues of antibiotics and pesticides were undetectable. In some of the other types of honey, the maximum residue limits regulated by European legislation were exceeded. Endosulfan residue was found in mint and rapeseed, honey with 0.42 and 5.14 ng/g, respectively. Neonicotinoids were found in 27% of the analyzed honey samples. Chloramphenicol was identified only in rapeseed honey, with concentrations ranging from 0.2 ng/g to 0.8 ng/g. Nitrofurans were found in 14%, and nitroimidazoles were found in 6% of the analyzed samples. According to EU legislation that is in force, the use of antibiotics in beekeeping is not allowed. The MRLs for neonicotinoids are 50 ng/g, and for coumaphos, the maximum limit is 100 ng/g. For the other pesticide residues, the maximum limit is 10 ng/g. The results of statistical analysis obtained using principal component analysis (PCA) showed a major difference in the levels of contamination of raspberry and meadow honey and the other types of honey.

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Section: Resultscontrasting

confidence: 91%

The Influence of Chemical Contaminants on the Physicochemical Properties of Unifloral and Multifloral Honey

Scripcă

Amariei

2021

Foods

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“…In the present study, none of the honey samples contained a detectable level of E. coli by MPN method. Similar to the present study, Leme et al (2018) and Combarros-Fuertes et al (2019) reported not to have detected E. coli in any of the honey samples they analyzed. On the other hand, Dümen et al (2013) reported to have detected E. coli in 18 (3.6%) out of 500 honey samples, and determined that the number of E. coli ranged from <10 cfu/g to 3.4x10 1 cfu/g.…”

Section: Discussionsupporting

confidence: 89%

Assessment of the Microbiological Profile, Species Diversity and Antimicrobial Susceptibility of Recovered Bacteria from Retail Honeys in Turkey

Guran

Durukan

Mann

2021

J Hellenic Vet Med Soc

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The aim of this study was to assess the microbiological profile, coliform and staphylococcal species diversity, and the antimicrobial susceptibility of coliform and other Gram-negative bacteria recovered from retail honeys in Turkey. A total of 150 honey samples, including extracted honey and comb honey samples, were purchased from honey sellers. The honey samples were analyzed for total mesophilic aerobic bacteria (TMAB), total mesophilic anaerobic bacteria (TMAnB), coliforms, Escherichia coli (E. coli), Staphylococcus spp., lactic acid bacteria (LAB), yeasts, and molds. All presumptive coliform and Staphylococcus isolates were identified at species level and then Gram-negative isolates were screened for antimicrobial susceptibility. TMAB, TMAnB, LAB, yeasts and molds mean counts (log cfu/g) in the samples were 3.26±1.08, 3.0±0.89, 2.93±0.52, 2.90±0.83, 1.80±0.53, respectively. Eighteen point seven percent and 15.3% of extracted and comb honey contained coliform and Staphylococcus spp., respectively, with a mean count (MPN/g) of 8.06±1.23 and 0.71±0.66. TMAB, Staphylococcus spp. and yeast contamination rates were significantly higher in the extracted honeys (P<0.05). Presumptive coliform and Staphyloccus spp. isolates were mostly identified as Klebsiella pneumoniae, Proteus mirabilis, Serratia marcescens, and Staphylococcus hominis and Staphylococcus epidermidis, respectively. Among coliform and non-coliform Gram-negative recovered isolates, antimicrobial resistance was highest against ceftriaxone (92.4%) and cefepime (91.5%) followed by tigecyclin (46.2%). The results obtained in this study provide insight on the microbiological profile of honey and the diversity of coliform and Staphylococcus species in honey samples. Moreover, these results show that honey, which is considered beneficial for human health, may contain antibiotic-resistant bacteria.

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“…The increasing consumption of natural products demands authenticity evaluations [ 33 ]. The first step in authenticity is the knowledge of a common pattern in samples with the same botanical and geographical origin.…”

Section: Discussionmentioning

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%

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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Relation Between Near-Infrared Spectroscopy and Physicochemical Parameters for Discrimination of Honey Samples from Jatai weyrauchi and Jatai angustula Bees

Cited by 15 publications

References 19 publications

The Influence of Chemical Contaminants on the Physicochemical Properties of Unifloral and Multifloral Honey

The Influence of Chemical Contaminants on the Physicochemical Properties of Unifloral and Multifloral Honey

Assessment of the Microbiological Profile, Species Diversity and Antimicrobial Susceptibility of Recovered Bacteria from Retail Honeys in Turkey

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

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