Acoustic Properties of Foods

Lewicki, Piotr P.; Marzec, Agata; Ranachowski, Z.

doi:10.1201/9781420003093.ch24

Cited by 18 publications

(37 citation statements)

References 28 publications

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“…An acoustogram presents collected data of the process of a product deformation and is a three‐dimensional graph. The horizontal axis represents time, the vertical axis indicates the spectral characteristic of the measured signal, and the signal intensity is visualized using color coding (Lewicki et al . 2009).…”

Section: Resultsmentioning

confidence: 99%

“…Such products are characterized by a wide frequency spectrum where the majority of sound energy stays within the range of 1–15 kHz. Each product may possess a characteristic frequency model but those frequency ranges, which are present in all sounds emitted by these products of interest (Lewicki et al . 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Such products are characterized by a wide frequency spectrum where the majority of sound energy stays within the range of 1-15 kHz. Each product may possess a characteristic frequency model but those frequency ranges, which are present in all sounds emitted by these products of interest (Lewicki et al 2009). Drake (1965) and Dacremont (1995) demonstrated that brittleness is evaluated at the first bite of a product on the basis of amplitude and frequency of the sound signal.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Instrumental and Sensory Texture Attributes of Microwave–convective Dried Apples

Marzec¹,

Kowalska

Zadrożna

2010

Journal of Texture Studies

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The aim of this study was investigation of the influence of microwave‐convective drying parameters, like microwave power on quality of dried apple slices. Experiments were carried out under different microwave power levels (100–300 W) at temperature of 30 and 40C. The scope of the study comprised measurement of instrumental features and sensory attributes of the texture of dried. The results showed that the values of instrumental texture properties of dried apple slices depend on the parameters of the drying process. At both of the analyzed apple drying temperatures along with an increase of microwave power there was also an increase in the value of acoustic emission events and the partition power spectrum slope. Sensory analysis of texture characteristics showed that along with an increase in the microwave power the dehydrated apple had darker color and its hardness increased. High correlations between the instrumental and sensory parameters of dried apple were observed. PRACTICAL APPLICATIONS New technologies are being sought – technologies that would be more effective and would provide a high quality product. The microwave drying of apples is an alternative method that might bring many benefits, including improvement in dehydrated apple quality. Microwave drying requires a choice of adequate drying parameters for apple varieties. Texture is one of the most important quality attributes of food products. Analysis of mechanical and acoustic properties will make it possible to for on objective opinion on the quality of the final product, witch along with sensory analysis of texture assures acceptance by consumers.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of Instrumental and Sensory Texture Attributes of Microwave–convective Dried Apples

Marzec¹,

Kowalska

Zadrożna

2010

Journal of Texture Studies

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“…The acoustic emission method can be a sensitive tool to record small fractures and breaks that are a source of acoustic waves not transmitted by air. It is important because an acoustic emission signal contains information related to the microstructure and texture of products (Lewicki et al, 2009). …”

Section: Texture Of Extruded Rye Bread With and Without Phytosterolsmentioning

confidence: 99%

The effect of phytosterols addition on the textural properties of extruded crisp bread

Jakubczyk

Linde

Gondek

et al. 2015

Journal of Food Engineering

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“…Finally, 365 10 s samples of the AE signal were obtained (Table 2). Four different parameters characterising AE events were determined: single AE energy (mJ), AE counts, AE amplitude (mV), and AE duration (µs) defined as (Marzec et al, 2007b) using PC applications for sound analysis (Lewicki et al, 2009). The parameters were determined for each bread type in four different water activities: initial a wi , amounting to 0.362 for rye, 0.377 for corn, and 0.371 for graham bread, 0.432, 0.529, and 0.648 labelled as a w4 , a w5 , and a w6 , respectively.…”

Section: Methodsmentioning

confidence: 99%

Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

Świetlicka¹,

Muszyński²,

Marzec³

2015

International Agrophysics

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A b s t r a c t. The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

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Acoustic Properties of Foods

Cited by 18 publications

References 28 publications

Analysis of Instrumental and Sensory Texture Attributes of Microwave–convective Dried Apples

Analysis of Instrumental and Sensory Texture Attributes of Microwave–convective Dried Apples

The effect of phytosterols addition on the textural properties of extruded crisp bread

Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

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