Quality assessment of microwave-vacuum dried material with the use of computer image analysis and neural model

Koszela, Krzysztof; Otrząsek, J.; Zaborowicz, Maciej; Boniecki, P.; Mueller, W.; Raba, Barbara; Lewicki, Andrzej; Przybył, Krzysztof

doi:10.1117/12.2064274

Cited by 21 publications

(14 citation statements)

References 19 publications

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“…High influence on the development of artificial neural networks had a technical evolution in the field of neuroprocessors construction, which are analog hardware applications. In recent years, the artificial neural networks have been used in agricultural engineering [11][12], eco-energetics [13][14] and environmental engineering [15][16]. The obtained rewarding results in terms of classification and prediction were used to construct the expert systems working in real-time, effectively supporting the decision-making processes in many sectors of agriculture, food processing and biofuel production [17][18].…”

Section: Introductionmentioning

confidence: 99%

Energy and economic potential of maize straw used for biofuels production

Zbytek

Dach

Pawłowski

et al. 2016

MATEC Web of Conferences

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Abstract. The paper presents the energy and economic comparison of two technologies of maize straw utilization: solid biofuel production (briquettes) and methane fermentation. The research experiments have shown that maize straw is the material which can be efficiently implemented in both technologies. Maize straw usage as briquettes can generate more energy (10.956 GJ Mg -1 ) than methane fermentation (9.74). In Europe, biogas is used in co-generation units for production of electric and heat energy. Due to higher price of electricity, economic profitability of maize straw usage for biogas production is over twice higher (182 USD) than in case of briquettes production (96 USD).

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Section: Introductionmentioning

confidence: 99%

Energy and economic potential of maize straw used for biofuels production

Zbytek

Dach

Pawłowski

et al. 2016

MATEC Web of Conferences

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“…The objective in drying of biological materials is the reduction of the amount of free-water in the solids to such a level, at which deteriorative processes caused mainly by microbiological growth, chemical reactions, and enzymatic activity are greatly minimalized. Due to the initial moisture content of approximately 74-90% w.b., vegetables and fruits are particularly susceptible to deteriorative processes [3].…”

Section: Introductionmentioning

confidence: 99%

Apple Cubes Drying and Rehydration. Multiobjective Optimization of the Processes

Winiczenko¹,

Górnicki²,

Kaleta³

et al. 2018

Sustainability

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The effect of convective drying temperature (Td), air velocity (v), rehydration temperature (Tr), and kind of rehydrating medium (pH) was studied on the following apple quality parameters: water absorption capacity (WAC), volume ratio (VR) color difference (CD). To model, simulate, and optimize parameters of the drying and rehydration processes hybrid methods artificial neural network and multiobjective genetic algorithm (MOGA) were developed. MOGA was adapted to the apple tissue, where the simultaneous minimization of CD and VR and the maximization of WAC were considered. The following parameters range were applied, 50 ≤ Td ≤ 70 °C and 0.01 ≤ v ≤ 6 m/s for drying and 20 ≤ Tr ≤ 95 °C for rehydration. Distilled water (pH = 5.45), 0.5% solution of citric acid (pH = 2.12), and apple juice (pH = 3.20) were used as rehydrating media. For determining the rehydrated apple quality parameters the mathematical formulas were developed. The following best result was found. Td = 50.1 °C, v = 4.0 m/s, Tr = 20.1 °C, and pH = 2.1. The values of WAC, VR, and CD were determined as 4.93, 0.44, and 0.46, respectively. Experimental verification was done, the maximum error of modeling was lower than 5.6%.

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“…Fruits and vegetables are particularly susceptible to deteriorative processes, since their initial water content range is from 74-90% w/w [2], and then, water activity allows microbial growth (>0.60). Drying, then, can positively affect fruits' and vegetables' shelf-life.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Optimization of the Process of Drying Fruits and Vegetables Using Computer Vision: A Review

et al. 2017

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An overview is given regarding the most recent use of non-destructive techniques during drying used to monitor quality changes in fruits and vegetables. Quality changes were commonly investigated in order to improve the sensory properties (i.e., appearance, texture, flavor and aroma), nutritive values, chemical constituents and mechanical properties of drying products. The application of single-point spectroscopy coupled with drying was discussed by virtue of its potentiality to improve the overall efficiency of the process. With a similar purpose, the implementation of a machine vision (MV) system used to inspect foods during drying was investigated; MV, indeed, can easily monitor physical changes (e.g., color, size, texture and shape) in fruits and vegetables during the drying process. Hyperspectral imaging spectroscopy is a sophisticated technology since it is able to combine the advantages of spectroscopy and machine vision. As a consequence, its application to drying of fruits and vegetables was reviewed. Finally, attention was focused on the implementation of sensors in an on-line process based on the technologies mentioned above. This is a necessary step in order to turn the conventional dryer into a smart dryer, which is a more sustainable way to produce high quality dried fruits and vegetables.

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Quality assessment of microwave-vacuum dried material with the use of computer image analysis and neural model

Cited by 21 publications

References 19 publications

Energy and economic potential of maize straw used for biofuels production

Energy and economic potential of maize straw used for biofuels production

Apple Cubes Drying and Rehydration. Multiobjective Optimization of the Processes

Monitoring and Optimization of the Process of Drying Fruits and Vegetables Using Computer Vision: A Review

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