Applied Food Research (Jun 2024)

Non-destructive three-dimensional characterization of micronized pulse seeds using X-ray microcomputed tomography

  • Bailey Paziuk,
  • Maheshika Jayasinghe,
  • Chyngyz Erkinbaev

Journal volume & issue
Vol. 4, no. 1
p. 100394

Abstract

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Non-destructive quality evaluation techniques are vital in 3D visualization and quantification of microstructural changes in micronized pulse kernels. The effects of micronization (infrared heating) on pulse microstructure are highly dependent on its treatment efficiency. This study employed X-ray micro-computed tomography (micro-CT) to characterize, visualize, and quantify the microstructural changes non-destructively. Four major pulses, chickpeas, fava beans, lentils, and yellow peas, were subjected to micronization at 180 °C of surface temperature for four different infrared (IR) exposure times (60, 80, 100, and 120 s). All samples were pre-conditioned at 20 % moisture content before the micronization process. Morphometric parameters (pore size, diameter, and pore distribution) were qualitatively measured using the reconstructed 2D and 3D images acquired by the X-ray micro-CT. Physico-chemical parameters, including loss of moisture (%), total porosity (%), volumetric expansion/shrinkage (%), and density (%) were quantified using Micro-CTAn software. The results showed that the porosity is significantly increased (p < 0.05) in all pulse types ranging from 0.60 ± 0.42 % to 12.1 ± 2.68 %, at prolonged IR exposure time. Significant volume expansion ranging from 3.82 %–33.56 % was shown by chickpeas and yellow peas, while fava beans and lentils showed volume shrinkage ranging from 4.26 %–24.31 % after micronization. Furthermore, density was decreased ranging from 0.79 ± 0.25% to 33.49 ± 0.42 % with increased IR time for all pulses except fava beans. The authors found that the microstructural changes in all tested pulses were optimum at 100 s–120 s of exposure time. Results emphasize the higher potential in modifying the microstructure of pulses using micronization processing. Therefore, future studies are suggested on developing predictive models to explore the relationships between microstructural changes and techno-functional properties.

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