Advertisement

Food and Bioprocess Technology

, Volume 1, Issue 4, pp 410–414 | Cite as

An Approach for Monitoring the Moisture Content Changes of Drying Banana Slices with Laser Light Backscattering Imaging

  • Giuseppe Romano
  • László Baranyai
  • Klaus Gottschalk
  • Manuela Zude
Communication

Abstract

Moisture content is an important quality attribute that directly influences storability of fruits and vegetables. The main goal of the present work was to test laser light backscattering imaging technique as a monitoring tool during drying of banana (Musa × cavendishii L.) slices. Laser diode emitting at 670 nm was used as the light source, whereas a charge-coupled device camera served as detector. The photon migration into the tissue was recorded as the average profile of the intensity gradient and expressed by two parameters, the size of the total illuminated area (square centimeters) on the surface and the radius (centimeters) of this area. The two attributes correlated with each other (r = 0.97–0.98). Backscattering images of slices were acquired each hour during the drying process at three different temperatures: 53, 58, and 63 °C. The two parameters of the intensity profile responded sensitively to changing moisture content. Significant relationship was found between changes in backscattering area and moisture content, especially at lower temperatures (r = 0.76, T = 53 °C), when almost no tissue browning occurred. At higher temperatures, correlations were observed between the parameters extracted by image processing and a* standard color index, especially at increased drying temperature due to the browning of the tissue.

Keywords

Banana Backscattering images Laser Drying Moisture content 

Notes

Acknowledgments

The authors wish to thank the Department of Agricultural Engineering, University of Catania, Italy and the Leibniz-Institut für Agrartechnik Potsdam-Bornim ATB, Department of Postharvest Technology and Department of Horticultural Engineering, Potsdam, Germany for financial support and technical assistance.

References

  1. Duprat, F., Chen, H., Grotte, M., et al. (1995). Laser light based machine vision system for nondestructive ripeness sensing of Golden apples. Proceedings of 1st IFAC/CIGR/EURAGENG/ISHS workshop of control applications in postharvest and processing technology, CAPPT, 85–93.Google Scholar
  2. Krokida, M. K., Kiranoudis, C. T., Maroulis, Z. B., & Marinos-kouris, D. (2000). Effect of pre-treatment on color of dehydrated products. Drying Technology, 18(6), 1239–1250. doi: 10.1080/07373930008917774.CrossRefGoogle Scholar
  3. Lu, R. (2004). Multispectral imaging for predicting firmness and soluble solids content of apple fruit. Postharvest Biology and Technology, 31(2), 147–57. doi: 10.1016/j.postharvbio.2003.08.006.CrossRefGoogle Scholar
  4. Peng, Y., & Lu, R. (2005). Modelling multispectral scattering profiles for prediction of apple fruits firmness. Transactions of the ASAE, 48, 235–242.Google Scholar
  5. Peng, Y., & Lu, R. (2006). An Lctf-based multispectral imaging system for estimation of apple fruit firmness: acquisition and characterization of scattering images. Am Soc Agric Biol Engineers, 49, 259–267.Google Scholar
  6. Peng, Y., & Lu, R. (2007). Prediction of apple fruit firmness and soluble solids content using characteristics of multispectral scattering images. Journal of Food Engineering, 82, 142–152. doi: 10.1016/j.jfoodeng.2006.12.027.CrossRefGoogle Scholar
  7. Prachayawarakorn, S., Warunee, T., Plyto, N., & Soponronnarit, S. (2008). Drying kinetics and quality attributes of low-fat banana slices dried at high temperature. Journal of Food Engineering, 85(4), 509–517. doi: 10.1016/j.jfoodeng.2007.08.011.CrossRefGoogle Scholar
  8. Qing, Z. S., Ji, B. P., & Zude, M. (2007). Predicting soluble solids content and firmness in apple fruit by means of laser light backscattering image analysis. Journal of Food Engineering, 82, 58–67. doi: 10.1016/j.jfoodeng.2007.01.016.CrossRefGoogle Scholar
  9. Torricelli, A. (2008). Determination of optical properties in turbid media. In: Optical Methods for Monitoring Fresh and Processed Agricultural Crops. CRC Press 450 (pp. 67).Google Scholar

Copyright information

© Springer Science + Business Media, LLC 2008

Authors and Affiliations

  • Giuseppe Romano
    • 1
  • László Baranyai
    • 2
  • Klaus Gottschalk
    • 3
  • Manuela Zude
    • 3
  1. 1.Department of Agricultural EngineeringUniversity of CataniaCataniaItaly
  2. 2.Department of Physics and Control ProcessCorvinus University of BudapestBudapestHungary
  3. 3.Leibniz-Institute for Agricultural EngineeringPotsdamGermany

Personalised recommendations