- Ahmadi, H.R. and Amiri Parian., J. 2015. Orange recognition on tree using image processing method based on lighting density pattern. Journal of Agricultural Machinery, 5(1): 92-100. (in Persian with English abstract)
- Beale, R., and Jackson, T. 2001. Neural computing: An introduction. Alborzi, M. Institute of Scientific Publications, Sharif University of Technology. 1st Printing, Tehran, Iran. 137 Pages. (in Persian)
- Dadvar, A.A., Khojastepoor, M., and Sadrnya, H. 2013. Comparison of orange mass determination models based on geometric characteristics required for design of grading machine. 7th Student Conference of Mechanical Engineering. 20-22 February 2013. Mechanical Engineering Faculty, University of Tehran, Iran. (in Persian)
- DeltaT Devices Company. 1998. WinDias 2.0 area meter. http://www.delta-t.co.uk (Accessed November 2014).
- Izadi, H., Kamgar, S., and Raoufat, M.H. 2016. Defect detection and grading of tomato using machine vision technology and neuro-fuzzy networks. Journal of Agricultural Machinery, (in press), (in Persian with English abstract).
- Jafarlou, M. and Farrokhi Teimourlou, R. 2014. Estimation of apple volume and its shape indentation using image processing technique and neural network. Journal of Agricultural Machinery, 4(1): 57-64. (in Persian with English abstract)
- Kia, S.M. 2010. Soft computing using MATLAB (4 in 1). Kian Rayaneh Sabz Publishing, 1st Printing, Tehran, Iran. 623 Pages. (in Persian)
- Mahmoudi, A., Khalesi, S., Hoseinpoor, A., and Alipoor, A.H. 2010. Audio identification of walnut genotypes using artificial neural networks. 6th National Congress on Agricultural Machinery Engineering and Mechanization, 15-16 September 2010, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. (in Persian)
- Mohsenin, N.N. 1986. Physical properties of plant and animal materials. Second revised. Gordon and Breach Sci. Publ, New York, USA.
- Motavali, A., Minaei, S., Khoshtaqaza, M.H., Kazemi, M., and Nikbakht, A.M. 2010. Comparison of mathematical and neural networks models prediction for pomegranate seed drying. 6th National Congress on Agricultural Machinery Engineering and Mechanization, 15-16 September 2010, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. (in Persian)
- Nasiri, A., Mobli, H., Rafiee, S., and Rezaei, K. 2014. Kinetic model simulation of thin-layer drying of thyme (Thymus vulgaris L.) using adaptive neuro-fuzzy inference system (ANFIS). Journal of Agricultural Engineering, 36(2): 37-48. (in Persian with English abstract)
- Rohani, A., Saedi, S.I., Grailu, H., and Aghkhani, M.H. 2015. Prediction of lateral surface, volume and sphericity of pomegranate using MLP artificial neural network. Journal of Agricultural Machinery, 5(2): 292-301. (in Persian with English abstract)
- Sajjadi, S.J., Ghazanfari Moghaddam, A., and Rostami, A. 2010. Using wavelet transformation and neural network for detecting blank (hollow) pistachio nuts. Iranian Journal of Biosystem Engineering, 40(2): 155-161. (in Persian with English abstract)
14. Stroshine, R., and hamann, D. 1994. Physical properties of agricultural materials and food products. Copyright 1994 (August) by Richard Stroshine.
15. Tabatabaeefar, A., Vefagh-Nematolahee, A., and Rajabipour, A. 2000. Modeling of orange mass based on dimensions. Journal of Agricultural Science and Technology, 2: 299–305.
, A., Topakci
, M., Canakci
, M., Akinci
, I., and Ozdemir
, F. 2005. Physical and nutritional properties of four orange varieties. Journal of Food Engineering, 66(4): 519–523.
17. Zarifneshat, S., Rohani, A., Ghassemzadeh, H.R., Sadeghi, M., Ahmadi, E., and Zarifneshat, M. 2012. Predictions of apple bruise volume using artificial neural network. Computers and Electronics in Agriculture, 82: 75-86.