1. Adamiak, A., A. Zdunek, A. Kurenda, and K. Rutkowski. 2012. Application of the biospeckle method for monitoring bull’s eye rot development and quality changes of apples subjected to various storage methods-preliminary studies. Sensors 12: 3215-3227.
2. Alves Braga Junior, R., B. Oliveira Silva, G. Rabelo, R. Marques Costa, A. Machado Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan. 2007. Reliability of biospeckle image analysis. Optics and Lasers in Engineering 45: 390-395.
3. Amaral, I. C., R. A. Braga Jr, E. M. Ramos, A. L. S. Ramos, and E. A. R. Roxael. 2013. Application of biospeckle laser technique for determining biological phenomena related to beef aging. Journal of Food Engineering 119: 135-139.
4. Ansari, M. D., and A. K. Nirala. 2013. Biospeckle activity measurement of Indian fruits using the methods of cross-correlation and inertia moments. Optik 124: 2180-2186.
5. Arizaga, R., M. Trivi, and H. Rabal. 1999. Speckle time evolution characterization by the co-occurrence matrix analysis. Optics and Laser Technology 31: 163-169.
6. Borah, S., E. L. Hines, and M. Bhuyan. 2007. Wavelet transform based image texture analysis for size estimation applied to the sorting of tea granules. Journal of Food Engineering 79: 629-639.
7. Braga, R. A., C. M. B. Nobre, A. G. Costa, T. Safadi, and F. M. Da Costa. 2011. Evaluation of activity through dynamic laser speckle using the absolute value of the differences. Optics Communications 284: 646-650.
8. Braga, R. A., L. Dupuy, M. Pasqual, and R. R. Cardoso. 2009. Live biospeckle laser imaging of root tissues. European Biophysics Journal 38: 679-686.
9. Briers, J. D. 1975. Wavelength dependence of intensity fluctuations in laser speckle patterns from biological specimens. Optics Communications 13: 324-326.
10. Gonzalez, R. C., and R. E. Woods. 2002. Digital Image Processing. Second Ed. Prentice Hall, New Jersey.
11. Harker, F. R., E. M. Kupferman, A. B. Marin, F. A. Gunson, and C. M. Triggs. 2008. Eating quality standards for apples based on consumer preferences. Postharvest Biology and Technology 50: 70-78.
12. Jamshidi, B., S. Minaei, E. Mohajerani, and H. Ghassemian. 2014. Prediction of soluble solids in oranges using visible/near-infrared spectroscopy: Effect of peel. International Journal of Food Properties 17: 1460-1468.
13. Lu, R. 2007. Nondestructive measurement of firmness and soluble solids content for apple fruit using hyperspectral scattering images. Sensing and Instrumentation for Food Quality and Safety 1: 19-27.
14. Lu, R. 2004. Multispectral imaging for predicting firmness and soluble solids content of apple fruit. Postharvest Biology and Technology 31: 147-157.
15. Lu, R., J. Qin, and Y. Peng. 2006. Measurement of the optical properties of apples by hyperspectral imaging for assessing fruit quality. ASAE Annual International Meeting, USA.
16. Mendoza, F., R. Lu, D. Ariana, H. Cen, and B. Bailey. 2011. Integrated spectral and image analysis of hyperspectral scattering data for prediction of apple fruit firmness and soluble solids content. Postharvest Biology and Technology 62: 149-160.
17. Mollazade, K. 2013. Non-destructive evaluation of some greenhouse products during sorting process using laser-light backscattering imaging and ANFIS. Ph.D. Thesis. University of Tehran. (In Farsi).
18. Nobre, C. M. B., R. A. Braga Jr, A. G. Costa, R. R. Cardoso, W. S. da Silva, and T. Safadi. 2009. Biospeckle laser spectral analysis under inertia moment, entropy and cross-spectrum methods. Optics Communications 282: 2236-2242.
19. Pajuelo, M., G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi. 2003. Bio-speckle assessment of bruising in fruits. Optics and Lasers in Engineering 40: 13-24.
20. Peng, Y., and R. Lu. 2005. Modeling multispectral scattering profiles for prediction of apple fruit firmness. Transactions of the ASAE 48 (1): 235-242.
21. Peng, Y., and R. Lu. 2006. Improving apple fruit firmness predictions by effective correction of multispectral scattering images. Postharvest Biology and Technology 41: 266-274.
22. Peng, Y. and R. Lu. 2007. Prediction of apple fruit firmness and soluble solids content using characteristics of multispectral scattering images. Journal of Food Engineering 82: 142-152.
23. Qing, Z., B. Ji, and M. Zude. 2007. Wavelength selection for predicting physicochemical properties of apple fruit based on near‐infrared spectroscopy. Journal of Food Quality 30: 511-526.
24. Qing, Z., B. Ji, and M. Zude. 2008. Non-destructive analyses of apple quality parameters by means of laser-induced light backscattering imaging. Postharvest Biology and Technology 48: 215-222.
25. Rabelo, G. F., R. A. Braga Júnior, and I. Fabbro. 2005. Laser speckle techniques in quality evaluation of orange fruits. Revista Brasileira de Engenharia Agricola e Ambiental 9: 570-575.
26. Romano, G., M. Nagle, D. Argyropoulos, and J. Müller. 2011. Laser light backscattering to monitor moisture content, soluble solid content and hardness of apple tissue during drying. Journal of Food Engineering 104: 657-662.
27. Song, J., W. Deng, R. M. Beaudry, and P. R. Armstrong. 1997. Changes in chlorophyll fluorescence of apple fruit during maturation, ripening, and senescence. HortScience 32: 891-896.
28. Szymanska-Chargot, M., A. Adamiak, and A. Zdunek. 2012. Pre-harvest monitoring of apple fruits development with the use of biospeckle method. Scientia Horticulture 145: 23-28.
29. Valero, C. 2001. Aplicacion de la espectroscopia laser de reflectancia difusa (ERDT) a la medida de calidad interna de frutas y hortalizas. Doctoral Thesis. Universidad Politecnica de Madrid.
30. Wang, S., M. Huang. and Q. Zhu. 2012. Model fusion for prediction of apple firmness using hyperspectral scattering image. Computers and Electronics in Agriculture 80: 1-7.
31. Zdunek, A., and J. Cybulska. 2011. Relation of biospeckle activity with quality attributes of apples. Sensors 11: 6317-6327.
32. Zdunek, A., and W. B. Herppich. 2012. Relation of biospeckle activity with chlorophyll content in apples. Postharvest Biology and Technology 64: 58-63.
33. Zdunek, A., A. Adamiak, P. M. Pieczywek, and A. Kurenda. 2014. The biospeckle method for the investigation of agricultural crops: A review. Optics and Lasers in Engineering 52: 276-285.
34. Zdunek, A., L. Muravsky, L. Frankevych, and K. Konstankiewicz. 2007. New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life. International Agrophysics 21: 305-310.
)
ارسال نظر در مورد این مقاله