Electrical impedance to easily discover undeclared freeze-thaw cycles in slaughtered bovine meat

Dell'Osa, A; Battacone, Gianni; Pulina, Giuseppe; Fois, Andrea; Tocco, Filippo; Loviselli, Andrea; Concu, Alberto; Velluzzi, Fernanda

doi:10.2478/joeb-2021-0002

Cited by 5 publications

(3 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4c,f show that the impedance of beef samples increased with increasing number of freeze–thaw cycles at both low and high frequencies. However, some previous studies (Wei et al ., 2017; Dell'Osa et al ., 2021) reported that the rapid formation of ice crystals during freezing damages the fibres organisation of muscles, leading to altered insulating properties of cellular membranes. This resulted in increased ion mobility and low impedance.…”

Section: Resultsmentioning

confidence: 99%

Rapid beef quality detection using spectra pre‐processing methods in electrical impedance spectroscopy and machine learning

Qiu,

Lin,

et al. 2024

Int J of Food Sci Tech

View full text Add to dashboard Cite

SummaryThe fraudulent practice of beef adulteration is a growing concern, as it violates consumer rights. Electrical impedance spectroscopy (EIS) combined with machine learning has emerged as a widely used approach to identify low‐quality meat. Unlike traditional biochemical methods that require expensive instruments, complex sample preparation, and chemical reagents, EIS is a cost‐effective alternative. However, EIS data are susceptible to temperature fluctuations, requiring a waiting period under consistent temperature conditions for data stabilisation before measurements. This process becomes impractical when dealing with a large number of samples. To overcome this limitation, standardisation, normalisation, and smoothing methods were introduced in the meat quality detection based on EIS data. A recognition model for detecting carrageenan adulteration in beef was established. Under an inconsistent temperature condition, by applying the spectra pre‐processing methods to the prediction dataset, the model accuracy reached 84%, whereas the accuracy of the unprocessed prediction dataset dropped to 54%. This study demonstrates that acquiring EIS data under consistent temperature conditions is unnecessary if proper spectra pre‐processing methods are applied. By eliminating the waiting time for data stabilisation, this practical approach enhances the efficiency and accuracy of meat quality detection.

show abstract

Section: Resultsmentioning

confidence: 99%

Rapid beef quality detection using spectra pre‐processing methods in electrical impedance spectroscopy and machine learning

Qiu,

Lin,

et al. 2024

Int J of Food Sci Tech

View full text Add to dashboard Cite

show abstract

“…The electrical properties of meat are dependent on frequency and closely related to other physical properties such as moisture content (Yang et al, 2013), meat freshness (Nguyen & Nguyen, 2015), and ice fraction (Ding et al, 2020). Furthermore, numerous studies have assessed the properties of fresh and frozen-thawed meat using the bioelectrical impedance method (Dell'Osa et al, 2021). The disruption of the cell membrane caused by the freezing and thawing process increases the number of free electrolytes in the tissues, thereby affecting the bioelectrical impedance characteristics of meat (Chen et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the suitable thawing endpoint of the frozen chicken breast using video recording analysis, shear force, and bioelectrical impedance measurement

Feng,

Zhu,

Wang

et al. 2023

Journal of Texture Studies

View full text Add to dashboard Cite

This study focuses on analyzing the texture properties and bioelectrical impedance characteristics of frozen chicken breasts during low‐temperature thawing, meanwhile, we also compared the differences in physiochemical properties. Frozen chicken breasts were thawed at 4 ± 2°C for 2, 4, 6, 8, and 10 h separately, then the physiochemical properties (color, pH, water‐holding capacity, water distribution), the texture properties (easy‐to‐cut level), and the bioelectrical impedance were determined and analyzed. The easy‐to‐cut level of the samples was evaluated by the sensory panel and two indexes, one is Warner‐Bratzler shear force measured by texture analysis machine, and the other is cutting speed value calculated by the consumer‐oriented cutting behavior analysis using frame‐by‐frame video recording analysis method. These two methods were used to characterize the easy‐to‐cut level of the frozen samples during thawing from the industrial processing and home cooking standpoint. Strong correlations were observed between the easy‐to‐cut level and the bioelectrical impedance of the frozen chicken breasts during thawing. The impedance magnitude at 100 kHz showed a high correlation coefficient (R2 = .9417) with Warner‐Bratzler shear force, and the impedance magnitude at 50 Hz showed a high correlation coefficient (R2 = .8658) with cutting speed. Our results indicated the acceptability of using bioelectrical impedance to evaluate the easy‐to‐cut thawing endpoint for both industry processing and home cooking.

show abstract

“…Electrical impedance spectroscopy has been used to monitor various agricultural products and food materials such as fruits [ 12 , 13 , 14 ], vegetables [ 15 , 16 ], meat [ 17 , 18 ], and edible oils [ 19 , 20 , 21 ]. This technique measures the electrical properties of samples as a function of a wide range of frequencies.…”

Section: Introductionmentioning

confidence: 99%

Electrical Impedance Spectroscopy for Moisture and Oil Content Prediction in Oil Palm (Elaeis guineensis Jacq.) Fruitlets

Chin-Hashim

Khaled

Jamaludin

et al. 2022

Plants

View full text Add to dashboard Cite

The global palm oil industry is targeting an increased oil extraction rate in oil palm milling to meet global demand. This can be achieved through the certification of mills and adherence to bunch grading as part of ensuring that only high-quality and ripe fresh fruit bunches are accepted and processed at all mills. However, the current grading process requires the analysis of oil palm bunches, which is laborious and tedious or prone to error due to human subjectivity. This paper introduces a non-destructive technique to predict the moisture and oil content in oil palm fruitlets using electrical impedance spectroscopy. In total, 90 samples of oil palm fruitlets at different stages of ripeness were acquired. Electrical impedance measurement of each fruitlet was done using electrocardiogram (ECG) electrodes connected to an LCR meter at frequencies of 1 kHz, 10 kHz, 20 kHz, and 100 kHz. The actual oil content in the fruitlets was determined using the Soxhlet extraction method, while the actual moisture content was determined using a standard oven-drying method. The variation of electrical impedance values at each frequency was analyzed. At 100 kHz, the correlation coefficients relating the electrical impedance to the moisture and oil content were around −0.84 and 0.80, respectively. Predictions of the moisture and oil content using linear regression of the impedance measurements at 100 kHz gave RMSE values of 5.85% and 5.71%, respectively. This information is useful for oil palm fruit grading and oil yield production estimation in the palm oil industry.

show abstract

Electrical impedance to easily discover undeclared freeze-thaw cycles in slaughtered bovine meat

Cited by 5 publications

References 27 publications

Rapid beef quality detection using spectra pre‐processing methods in electrical impedance spectroscopy and machine learning

Rapid beef quality detection using spectra pre‐processing methods in electrical impedance spectroscopy and machine learning

Analysis of the suitable thawing endpoint of the frozen chicken breast using video recording analysis, shear force, and bioelectrical impedance measurement

Electrical Impedance Spectroscopy for Moisture and Oil Content Prediction in Oil Palm (Elaeis guineensis Jacq.) Fruitlets

Contact Info

Product

Resources

About