Prediction of firmness in peach fruit by means of laser light backscattering imaging system

Document Type : Research Paper


1 senior Exper, Department of Biosystem Engineering, University ofTabriz

2 Associate Professor, Department of Biosystem Engineering, University of Tabriz

3 Assistant Professor, Department of Biosystem Engineering, University of Kordestan

4 Instructor, Department of Biosystem Engineering, University ofTabriz


Quality evaluation is one of the effective activities in trade, economy and the health of communities. For this purpose, non-destructive methods are increasingly used, as they are faster and more economical in comparison with destructive ones. This study investigated the feasibility of predicting firmness by laser light backscattering imaging system, as a new non-destructive method for one cultivar of peaches. Thus, a laser imaging system was assembled for capturing backscattering images, which consisted of one laser diode at 650 nm. After taking images, essential information of intensity and texture based statistical features was obtained by image analysis techniques, to build two types of calibration models. Non-linear regression and artificial neural network were developed in order to find the best prediction models. Consequently, final models based on the non-linear regression, gave the highest correlation coefficient of r = 0.89 to predict firmness.


Main Subjects

Aalami, M. T., Sadeghfam, S., Fazelifard, M. H. Naghipour, L. (2013) Data Series Modeling. (1th ed.). Tabriz University Publications. (In Farsi).
Abu-Khalaf, N. Bennedsen, B. S. (2002). Plum-Tasting Using Near Infra-Red (Nir) Technology. International Agrophysics, 16, 83-89.
Behjat, A. (2002) Laser, Principles and Applications. (1th ed.). Yazd University Publications. (In Farsi).
Dobrzanski, B. Rabcewicz, J. Rybczynski, R. (2006) Handling of Apple: Transport TechniquesandEfficiencyVibration. Damage and Bruising Texture. Firmness and Quality. Institute of Agrophysics of  Polish Academy of Sciences.
Fan, G. Zha, J. Du, R. Gao, L. (2009). Determination of Soluble Solids and Firmness of Apples by Vis/Nir Transmittance. Journal of Food Engineering, 93, 416-420.
Liu, Y. Sun, X.  Zhang, H. Aiguo, O. (2010). Nondestructive Measurement of Internal Quality of Nanfeng Mandarin Fruit by Charge Coupled Device Near Infrared Spectroscopy. Computers and Electronics in Agriculture, 71, 10-14.
Lu, R. Peng, Y. (2006). Hyperspectral Scattering for Assessing Peach Fruit Firmness. Biosystems Engineering, 93(2), 161-171.
Moghimi, A. Aghkhani, M. H. Sazgarnia, A. Sarmad, M. (2010). Vis/Nir Spectroscopy and Chemometrics for the Prediction of Soluble Solids Content and Acidity (Ph) of Kiwifruit. Biosystems Engineering, 106, 295-302.
Mollazade, K. Omid, M. Akhlaghian, T. F. Mohtasebi, S. S. (2012). Principles and Applications of Light Backscattering Imaging in Quality Evaluation of Agro-Food and Products: A Review. Food Bioprocess Technology, 5, 1465-1485.
Mollazade, K. Omid, M. Akhlaghian, T. F. Rezaei, K. Y. Mohtasebi, S. S. Zude, M. (2013). Analysis of  Texture-Based Features for Predicting Mechanical Properties of  Horticultural Products by Laser Light Backscattering Imaging. Computers and Electronics in Agriculture, 98, 34-45.
Qing, Z. Ji, B. Zude, M. (2007). Predicting Soluble Solid Content and Firmness in Apple Fruit by Means of Laser Light Backscattering Image Analysis. Journal of Food Engineering, 82, 58-67.
Romano, G. Nagle, M. Argyropoulos, D. Muller, J. (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.
Udomkun, P. Nagle, M. Mahayothee, B. Muller, J. (2014). Laser-Based Imaging System for Non-Invasive Monitoring of Quality Changes of Papaya During Drying. Food Control, 42, 225-233.