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Determination of Compression Response for Various Dried Vegetables

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New Trends in Engineering Research (CNNTech 2023)

Abstract

The texture of food plays a vital role in its overall quality, affecting both sensory experience and functional aspects, such as processing and preservation. To study texture in the field of food science and technology, various analytical methods are used to measure mechanical properties such as hardness, cohesiveness, and viscosity. One widely utilized technique for evaluating the texture of solid foods, particularly those with high firmness or brittleness such as dried vegetables, is compression testing. Here, a force is applied to a food sample until it deforms or fractures. In this particular study, dried onions, carrots, and peppers were chosen as test samples to investigate their texture and compression properties. To perform the tests, the researchers employed a Shimadzu AGS-X universal testing machine equipped with a 1 kN load cell capacity. This machine allowed them to compress the samples and measure the force required to achieve a specific deformation. The obtained results revealed that the texture and compression properties of the dried vegetables were significantly influenced by the specific part of the vegetable being tested. For instance, when examining the dried onions, a notable disparity was observed between the inner and outer parts. The basal plate of the onion, in particular, exhibited much greater hardness compared to the middle portion of the dried onion. Consequently, breaking the sample required a higher compression force. This discovery implies that the texture and compression properties of dried vegetables are closely tied to their inherent characteristics, internal structure, and composition.

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Correspondence to Ivana Jevtić .

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Milošević, M., Jevtić, I., Trajković, I., Zlatanović, I., Mladenović, G., Korolija, N. (2024). Determination of Compression Response for Various Dried Vegetables. In: Mitrovic, N., Mladenovic, G., Mitrovic, A. (eds) New Trends in Engineering Research. CNNTech 2023. Lecture Notes in Networks and Systems, vol 792. Springer, Cham. https://doi.org/10.1007/978-3-031-46432-4_8

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