References
- Alchanatis, V., Peleg, K., Ziv, M. (1993). Classification of tissue culture segments by color machine vision. JAER, 55, 299-311.
- Al-Juhaimi, F.Y., Ghafoor, K. (2013). Bioactive compounds, antioxidant and physico-chemical properties of juice from lemon, mandarin and orange fruits cultivated in Saudi Arabia. Pakistan Journal Botany, 45(4), 1193-1196.
- Anders, A., Markowski, P., Kaliniewicz, Z. (2014). Badanie właściwości geometrycznych i fizycznych owoców wybranych odmian gruszy na podstawie modeli numerycznych uzyskanych za pomocą skanera 3D. Zeszyty Problemowe Postępów Nauk Rolniczych, 577, 3-12.
- Baradaran Motie, J., Miraei Ashtiani, S. H., Abbaspour-Fard, M. H., Emadi, B. (2014). Modeling physical properties of lemon fruits for separation and classification. International Food Research Journal, 21(5), 1901-1909.
- Bozokalfa, M. K., Kilic, M. (2010). Mathematical modeling in the estimation of pepper (Capsicum annum L.) fruit volume. Chilean Journal of Agricultural Research, 70(4), 626-632.
- Burt, S.A. (2004). Essential oils: Their antibacterial properties and potential applications in foods: Av review. International Joutnal of Food Microbiology, 94, 223-253.
- Ghulam, M. (2015). Date Fruites Classification Using Texture Descriptors and Shape-Size Features. Engineering Applications of Artificial Intelligence, 37, 361-367.
- Growe, T. G., Delwiche, M. J. (1996). A system for fruit defect detection in real-time. AGENG, 96F-023.
- Guyer, D.E., Miles, G. E., Gaultney, L. D., Schereiber, M. M. (1993). Application of machine vision to shape analysis in leaf and plant identification, TASAE, 36(1), 163-171.
- Ho, Q. (2011). A Three-Dimensional Multiscale Model for Gas Exchange in Fruit. Plant Physiology, 155(3), 1158-1168.
- Iqbal, S., Gopal, A., Sarma, A. (2011). Volume Estimation of Apple Fruits Using Image Processing. 2011 International Conference on Image Information Processing, Himachal Pradesh, 1-6.
- Kakadiya, D., Shah, R., Shah, N., Kachariya, C., Patel, M., Sukhwani, K. (2015). Shape Extraction Methods for Fruits: Technical Review. International Journal of Computer Applications, 111(1), 43-48.
- Khojastehnazhand, M., Omid, M., Tabatabaeefar, A. (2010). Development of a lemon sorting system based on color and size. African Journal of Plant Science, 4(4), 122-127.
- Lalitha, K., Muthulakshmi, K., Vinothini, A. (2015). Proficient acquaintance based system for citrus leaf disease recognition and categorization. International Journal of Computer Science and Information Technologies, 6(3), 2519-2524.
- Lino, A.C.L., Sanches, J., Fabbro, I.M.D. (2008). Image processing techniques for lemons and tomatoes classification. Bragantia, Campinas, 67(3), 785-789.
- Mebatsion, H.K., Boudon, F., Godin, C., Pradal, C., Génard, M., Goz-Bac, C., Bertin, N. (2011). A novel profile based model 415 for virtual representation of quasi-symmetric plant organs. Computers and Electronics in Agriculture, 75(1), 113-124.
- Miller, B. K., Delwiche, M. J. (1991). Peach defect detection with machine vision. TASAE, 34(6), 2588-2597.
- Mohanapriya, M., Ramaswamy, L., Rajendran, R. (2013). Health and medicinal properties of lemon (Citrus limonum). International Journal Of Ayurvedic And Herbal Medicine, 3(1), 1095-1100.
- Moltó, E., Aleixos, N., Ruiz, L. A., Vázquez, J., Juste, F. (1996). An artificial vision system for fruit quality assessment. AGENG 96, Madrid, 96F-078.
- Moreda, G.P., Muñoz, M.A., Ruiz-Altisent, M., Perdigones, A. (2012). Shape determination of horticultural produce using two-dimensional computer vision–A review. Journal of Food Engineering, 108(2), 245-261.
- Ortuño, A.A., Baidez, P., Gomez, M.C., Arcas, I., Porras, A.G., Del Rio, J.A. (2006). Citrus paradise and Citrus sinensis flavonoids: Their influence in the defence mechanism against Penicilliumdigitatum. Food Chemistry, 98(2), 351-358.
- Rakun, J. (2012). Detecting Natural Objects by Means of 2D and 3D Shape Analysis. Optija, Croatia, 345-354.
- Rondeau-Mouroa, C., Bouchetb, B., Pontoirea, B., Roberta, P., Mazoyerc, J., Buléona, A. (2003). Structural features and potential texturising properties of lemon and maize cellulose microfibrils. Carbohydrate Polymers, 53, 241-252.
- Ruiz, L. A., Moltó, E., Juste, F., Aleixos, N. (1995). Aplicación de métodosópticos para la inspecciónautomática de productoshortofrutícolas, VI Congreso de la Sociedad Española de Ciencias Hortícolas, Barcelona.
- Sarkar, N., Wolfe, R.R. (1985). Feature extraction techniques for sorting tomatoes by computer vision. TASAE, 28(3), 970-974.
- Satya Priya, N., Nivetha, E., Khilar, R. (2016). Efficient Knowledge Based System to Detect Diseases in Lemon Leaf. Imperial Journal of Interdisciplinary Research (IJIR), 2(5), 275-280.
- Seng, W.C., Mirisaee, S.H. (2009). A new method for fruits recognition system. Conference: Electrical Engineering and Informatics. ICEEI '09. International Conference on, 01, 130-134.
- Swapnil, S.P., Dale, M.P. (2016). Computer vision based fruit detection and sorting system. Special Issue on International Journal of Electrical, Electronics and Computer Systems, ISSN (Print): 2347-2820 V-4 I-2. For 3rd National Conference on Advancements in Communication, Computing and Electronics Technology [ACCET-2016]
- Taheri-Garavand, A., Nassiri, A. (2010). Study on some morphological and physical Characteristics of sweet lemon used in mass models. International Journal of Environmental Sciences, 1(4), 580-590.
- Tao, Y., Morrow, C. T., Heinemann, P. H., Sommer, J. H. (1990). Automated machine vision inspection of potatoes. American Society of Agricultural Engineers, 90-3531, 23-27.
- Uyar, R., Erdoğdu, F. (2009). Potential use of 3-dimensional scanners for food process modeling. Journal of Food Engineering, 93, 337-343.