Organic apples (cv. Elstar) quality evaluation during hot-air drying using Vis/NIR hyperspectral imaging

Shrestha, Luna; Moscetti, Roberto; Crichton, Stuart; Hensel, Oliver; Sturm, Barbara

doi:10.4995/ids2018.2018.7689

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…Further studies using hyperspectral imaging on apples [11], meat [12] and potatoes [13,14] show similarly promising results. A reduction of the wavelengths needed for detection of product features will allow for the transfer to simpler systems, e.g.…”

Section: Fig 2: Normalised Moisture Distribution For Apple Slices Befmentioning

confidence: 85%

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

Sturm

Moscetti

Crichton

et al. 2018

Proceedings of 21th International Drying Symposium

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Drying is a complex, dynamic, unsteady and nonlinear process that, when not optimized on a system level, may be responsible for (1) significant quality degradation and (2) energy wastage. Consequently, new drying technologies must be designed combining non-invasive at-/on-/in-line advanced measurement and control systems with models cross-linking all relevant aspects of product quality changes and heat and mass transfer phenomena. This paper presents preliminary results on the use of RGB imaging, NIR spectroscopy and Vis-NIR hyperspectral imaging for real-time monitoring of physicochemical changes of apples and carrots during drying. Keywords: chemometrics, artificial intelligence, deep learning

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Section: Fig 2: Normalised Moisture Distribution For Apple Slices Befmentioning

confidence: 85%

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

Sturm

Moscetti

Crichton

et al. 2018

Proceedings of 21th International Drying Symposium

Self Cite

View full text Add to dashboard Cite

show abstract

“…In another study, the application of the HSI system and the partial least squares regression model was examined for the measurement and detection of MC and colour of the apple slices during the drying process. The results indicated that the wavelengths of 580, 750 and 970 nm can predict MC with high accuracy [ 59 ].…”

Section: Comparison Of Various Techniques For Prediction Of Moisture ...mentioning

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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“…It is mainly based on heat convection from air and conduction from the tray. However, due to the low thermal conductivity of most agriculture and food material, such drying techniques usually result in energy-intensive drying and low-quality products [2].…”

Section: Introductionmentioning

confidence: 99%

A Terahertz time-domain spectroscopy-based intelligent microwave vacuum dehydration system for in-situ monitoring of real-time moisture migration during dehydration of agricultural products

Ren

Sun

2023

Active and Passive Smart Structures and Integrated Systems XVII

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Microwave vacuum drying (MVD) as a novel and advanced drying technology is wildly applied in the agri-food, pharmaceutical, and electronics industry, etc. However, achieving in-situ analyses of the realtime moisture content (MC) of products during MVD is still a huge challenge. This research aims to build an intelligent dehydration system by integrating a Terahertz time-domain spectroscopy (THz-TDS) into an MVD system to achieve in-situ monitoring of real-time moisture content (MC) in agrifood products. During dehydration, the THz-TDS continuality captured the spectra from a polyethene (PE) air hose containing the exhaust water vapor from the glass desiccator. Chemometric analysis of Gaussian process regression was applied to correlate the real-time MC loss of products with the corresponding numerical integration of THz absorption coefficients of vapor. The real-time MC content was accurately calculated based on the prediction. The result shows that the THz-TDS is able to sense the dynamic vapor changes within the MVD system by penetrating the PE air hose, and the established intelligent dehydration system combined with chemometric analyses achieved a satisfied MC loss and MC prediction, with R 2 of 0.95 and 0.98, and RMSE of 0.002 and 0.031, respectively. The THz-TDS technique shows great potential to be integrated into an MVD system to achieve in-situ real-time MC evaluation, optimize dehydration condition, and predict the dehydration endpoint. The established intelligent dehydration system also provides a novel sensing strategy using THz-TDS to monitor the gas exchange within a closed system by penetrating a PE air hose in the system, and further widen the application of THz-TDS in the agri-food industry.

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Organic apples (cv. Elstar) quality evaluation during hot-air drying using Vis/NIR hyperspectral imaging

Cited by 7 publications

References 8 publications

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

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

A Terahertz time-domain spectroscopy-based intelligent microwave vacuum dehydration system for in-situ monitoring of real-time moisture migration during dehydration of agricultural products

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