Classical and correlative analytical methods for origin identification of Hungarian honeys

Bodor, Zsanett; Benedek, Csilla; Kaszab, Timea; Zaukuu, John‐Lewis Zinia; Kertész, I.; Kovács, Zoltán

doi:10.1556/066.2019.48.4.9

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…The classification of chestnut, canola, acacia, and sunflower honeys from different botanical and geographical origin from Hungary was also assessed using a potentiometric E-tongue with high classification accuracies of 92.1% and 91.8% for training and cross-validation for the botanical origin, and higher than 90% for the geographical origin of the samples per honey type [ 228 ].…”

Section: Electronic Tongue: Historical Background and Food Qualitymentioning

confidence: 99%

Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview

Aouadi

Zaukuu

Vitális

et al. 2020

Sensors

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Amid today’s stringent regulations and rising consumer awareness, failing to meet quality standards often results in health and financial compromises. In the lookout for solutions, the food industry has seen a surge in high-performing systems all along the production chain. By virtue of their wide-range designs, speed, and real-time data processing, the electronic tongue (E-tongue), electronic nose (E-nose), and near infrared (NIR) spectroscopy have been at the forefront of quality control technologies. The instruments have been used to fingerprint food properties and to control food production from farm-to-fork. Coupled with advanced chemometric tools, these high-throughput yet cost-effective tools have shifted the focus away from lengthy and laborious conventional methods. This special issue paper focuses on the historical overview of the instruments and their role in food quality measurements based on defined food matrices from the Codex General Standards. The instruments have been used to detect, classify, and predict adulteration of dairy products, sweeteners, beverages, fruits and vegetables, meat, and fish products. Multiple physico-chemical and sensory parameters of these foods have also been predicted with the instruments in combination with chemometrics. Their inherent potential for speedy, affordable, and reliable measurements makes them a perfect choice for food control. The high sensitivity of the instruments can sometimes be generally challenging due to the influence of environmental conditions, but mathematical correction techniques exist to combat these challenges.

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Section: Electronic Tongue: Historical Background and Food Qualitymentioning

confidence: 99%

Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview

Aouadi

Zaukuu

Vitális

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…These spectrometers, which are miniature versions of vibrational spectroscopy equipment, have made it possible for the food industry to do on-site and real-time evaluations of food quality and food production processes. They have been used for authentication and detection of adulterants in several foods [ 19 , 20 , 21 ], food product development [ 22 , 23 ], and geographical discrimination of food [ 24 , 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Multiple NIR Spectrometers for Detecting Low-Concentration Nitrogen-Based Adulteration in Protein Powders

Lukacs,

Zaukuu,

Bazar

et al. 2024

Molecules

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Protein adulteration is a common fraud in the food industry due to the high price of protein sources and their limited availability. Total nitrogen determination is the standard analytical technique for quality control, which is incapable of distinguishing between protein nitrogen and nitrogen from non-protein sources. Three benchtops and one handheld near-infrared spectrometer (NIRS) with different signal processing techniques (grating, Fourier transform, and MEM—micro-electro-mechanical system) were compared with detect adulteration in protein powders at low concentration levels. Whey, beef, and pea protein powders were mixed with a different combination and concentration of high nitrogen content compounds—namely melamine, urea, taurine, and glycine—resulting in a total of 819 samples. NIRS, combined with chemometric tools and various spectral preprocessing techniques, was used to predict adulterant concentrations, while the limit of detection (LOD) and limit of quantification (LOQ) were also assessed to further evaluate instrument performance. Out of all devices and measurement methods compared, the most accurate predictive models were built based on the dataset acquired with a grating benchtop spectrophotometer, reaching R2P values of 0.96 and proximating the 0.1% LOD for melamine and urea. Results imply the possibility of using NIRS combined with chemometrics as a generalized quality control tool for protein powders.

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“…Result of the partial least square regression models built to regress on the added syrup concentration of sugar syrups adapted from Bodor Z. (2022)[32].…”

mentioning

confidence: 99%

Detection of Low-Level Adulteration of Hungarian Honey Using near Infrared Spectroscopy

et al. 2023

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Honey adulteration is a worldwide problem; however, its detection is a challenge for researchers and authorities. There are numerous ways of honey counterfeiting; amongst them, direct adulteration is one of the most common methods. Correlative techniques, such as near-infrared spectroscopy (NIRS), are useful tools in the detection of honey adulteration; however, this method has not been applied to Hungarian honeys. The aim of this research was to investigate the performance of NIRS for the detection of sugar syrup addition to Hungarian honeys at lower concentration levels (<10% w/w). Acacia, rape, forest, sunflower, and linden honeys were mixed with high-fructose-content sugar syrup, rice syrup, or self-made glucose fructose syrup in 3%, 5%, and 10% w/w. NIRS analysis was performed in the spectral range of 950–1650 nm. Principal component analysis was coupled with linear discriminant analysis and partial least square regression models were built for the classification and prediction of adulteration levels, respectively. Our results showed that the performance of NIRS highly depends on both type of syrup and honey. PCA-LDA models provided the 100% correct classification of control in the case of all the models, while PLSR results could predict the added sugar syrup content in the case of rice and F40 syrup models, obtaining >2.2 RPDCV value.

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Classical and correlative analytical methods for origin identification of Hungarian honeys

Cited by 4 publications

References 17 publications

Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview

Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview

Comparison of Multiple NIR Spectrometers for Detecting Low-Concentration Nitrogen-Based Adulteration in Protein Powders

Detection of Low-Level Adulteration of Hungarian Honey Using near Infrared Spectroscopy

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