Impact of drying temperature and salt pre-treatments on drying behavior and instrumental color and investigations on spectral product monitoring during drying of beef slices

Gersdorff, Gardis von; Kirchner, Sascha; Hensel, Oliver; Sturm, Barbara

doi:10.1016/j.meatsci.2021.108525

Cited by 15 publications

(11 citation statements)

References 54 publications

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“…One of the most recent investigated non‐destructive techniques is a hyperspectral imaging (HSI) which is capable to generate both spectral information and a spatial map simultaneously at a certain range of wavelengths and the acquired spectra are qualitatively related to the physical and chemical properties of the product. The key principle of HSI is by integrating both imaging technology coupled with spectrophotometry and this new hybrid technology has been comprehensively studied for evaluating the physical properties and internal qualities of fruits and vegetables during drying (Arefi et al, 2021; von Gersdoff et al, 2021; Sturm et al, 2020; Yu et al, 2020: Amjad et al, 2019; Liu et al, 2017). Recently, the potential usage of hyperspectral imaging was also documented for the identification of saccharin jujube (Zhang et al, 2020) and the retention of anthocyanin in purple‐fleshed sweet potato during convective and microwave drying (Tian et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non‐invasive hyperspectral imaging technique

Saleh

Kulig

Arefi

et al. 2022

Food Processing Preservation

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The objective of this paper was to evaluate the performance of Partial Least Square Regression (PLSR) model and to assess the statistical agreement between two different measurement techniques, that is, Vis–NIR hyperspectral imaging (HSI) and standard laboratory methods for quality evaluation of dried carrots throughout the hot‐air drying process. Carrots at commercial maturity of 3.5 months after planting were harvested in two seasons (2017 and 2018) and dried in a convective hot air dryer at 50°C, 60°C, and 70°C. Quality measurements were examined at intervals of 30 minutes. PLSR was performed as a regression model to predict quality attributes in carrots, while Passing–Bablok and Deming regressions alongside Blant–Altman analysis were applied as method comparisons. Excellent prediction performance for moisture content was observed with high R2T and R2v at 0.92 and 0.90 with values of RMSET and RMSEv at 8.15% and 8.16%. Satisfactory prediction accuracies were observed for total carotenoids (R2v = 0.64 and RMSEv = 32.62) μg/g, L* (R2v = 0.68 and RMSEv = 32.62), a* (R2v = 0.69 and RMSEv = 1.18), and b* (R2v = 0.60 and RMSEv = 1.45). Selected wavelengths for total carotenoids, moisture content, L*, a*, and b* based on the highest score of VIP loadings were 531, 973, 531, 531, and 680 nm, respectively. An adequate agreement of Blant–Altman analysis between the two methods within the upper and lower limits of 95% confidence interval (CI) were obtained for total carotenoids from 95.68 μg/g to 82.34 μg/g, moisture content (25.18% to 22.93%), L* (2.88 to −3.30), a* (4.15 to 3.43), and b* (4.53 to −3.11) with mean differences at 6.67, 1.12, −0.21, 0.36, and 0.71, respectively. Good correlation coefficients (r) were also observed at 0.89, 0.91, 0.78, and 0.83 for moisture content, L*, a*, and b* with a moderate correlation of total carotenoids at 0.69. The results indicate the potential feasibility of using non‐invasive measurement of quality attributes using hyperspectral imaging during the drying of carrots. Novelty impact statement non‐invasive measurement using hyperspectral imaging for quality determination in carrots during convective drying demonstrated promising results. Multivariate analysis of Partial Least Square Regression showed a good modeling performance for quality prediction in dried carrots. A good statistical agreements between non‐invasive quality measurements using hyperspectral imaging and standard laboratory analysis were achieved by comparative analysis using Blant–Altman plot, Deming, and Passing–Bablok regression.

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Section: Introductionmentioning

confidence: 99%

Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non‐invasive hyperspectral imaging technique

Saleh

Kulig

Arefi

et al. 2022

Food Processing Preservation

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“…This application can fulfill the demand for canning meat under different cutting methods. Regarding various us drying methods, HSI (400–1000 nm) was used to predict the moisture content and colour parameters of dried beef samples ( von Gersdorff et al, 2021 ). This application will enhance the future development of simple and cost-effective tools regarding monitoring systems for beef drying processes ( von Gersdorff et al, 2021 ).…”

Section: Potential Applications Of Hsi In the Meat Supply Chainmentioning

confidence: 99%

“…Regarding various us drying methods, HSI (400–1000 nm) was used to predict the moisture content and colour parameters of dried beef samples ( von Gersdorff et al, 2021 ). This application will enhance the future development of simple and cost-effective tools regarding monitoring systems for beef drying processes ( von Gersdorff et al, 2021 ). Besides, Hitchman et al (2021) expanded the HSI application on detecting IMF value of lamb storing for one to five years.…”

Section: Potential Applications Of Hsi In the Meat Supply Chainmentioning

confidence: 99%

Hyperspectral Imaging (HSI) for meat quality evaluation across the supply chain: Current and future trends

Jia

Ruth

Scollan

et al. 2022

Current Research in Food Science

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“…The literature reports food-related studies in which hyperspectral technology was also applied to detect fungal contamination, bruising in apples, faecal contamination, skin tumours in chicken carcasses, grain inspections and so on [ 19 ]. The use of HSI technology for measuring the MC of agricultural products during the drying process has been extensively explored [ 6 , 20 , 21 , 22 , 23 ]. The need for fast and careful methods has led to the application of the HSI technology for MC control during the drying process.…”

Section: Introductionmentioning

confidence: 99%

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

2023

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Drying is one of the common procedures in the food processing steps. The moisture content (MC) is also of crucial significance in the evaluation of the drying technique and quality of the final product. However, conventional MC evaluation methods suffer from several drawbacks, such as long processing time, destruction of the sample and the inability to determine the moisture of single grain samples. In this regard, the technology and knowledge of hyperspectral imaging (HSI) were addressed first. Then, the reports on the use of this technology as a rapid, non-destructive, and precise method were explored for the prediction and detection of the MC of crops during their drying process. After spectrometry, researchers have employed various pre-processing and merging data techniques to decrease and eliminate spectral noise. Then, diverse methods such as linear and multiple regressions and machine learning were used to model and predict the MC. Finally, the best wavelength capable of precise estimation of the MC was reported. Investigation of the previous studies revealed that HSI technology could be employed as a valuable technique to precisely control the drying process. Smart dryers are expected to be commercialised and industrialised soon by the development of portable systems capable of an online MC measurement.

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Impact of drying temperature and salt pre-treatments on drying behavior and instrumental color and investigations on spectral product monitoring during drying of beef slices

Cited by 15 publications

References 54 publications

Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non‐invasive hyperspectral imaging technique

Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non‐invasive hyperspectral imaging technique

Hyperspectral Imaging (HSI) for meat quality evaluation across the supply chain: Current and future trends

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

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