Akanbi C.T., Adeyemi R.S., Ojo A. (2006): Drying characteristics and sorption isotherm of tomato slices. Journal of Food Engineering, 73: 141-146.
Arazuri S., Jaren C., Arana J. I., Perez de ciriza J. J. (2007): Influence of mechanical harvest on the physical properties of processing tomato (Lycopersicon esculentum Mill.). Journal of Food Engineering. 80(1): 190-198.
Azizi G., Alimardani L., Siahmargoei A. (2011): Evaluation of Relation of chlorophyll meter’s number with chlorophyll content, photosynthesis and nitrogen content of soybean’s leaf. (6)23. 34-40.
Faizollahzadeh Ardabili S., Mahmoudi A., Mesri Gundoshmian T. (2016): Modeling and simulation controlling system of HVAC using fuzzy and predictive (radial basis function, RBF) controllers. Journal of Building Engineering. (6): 301–308.
FAO. (2010): Pyrrolizidine alkaloids in foods and animal feeds. FAO Consumer Protection Fact Sheets. (2): 1-6.
FAO, W. (2012). The state of food insecurity in the world. 8-11.
Li Z. (2011): Physical and mechanical properties of tomato fruits as related to robot’s harvesting." Journal of Food Engineering 103(2): 170-178.
Li Z., Ly K., Wang Y., Zhao B., Yang Z. (2015): Multi-scale engineering properties of tomato fruits related to harvesting, simulation and textural evaluation. Food Science and Technology. 61(2): 444-451.
Moody J., Darken C. J. (1989): Fast learning in networks of locally-tuned processing units. Neural computation. 1(2): 281-294.
Nagamani P. V., Chauban P., Dwivedi R. M. (2007): Estimation of chlorophyll-A concentration using an artificial neural network (ANN) based algorithm with oceansatI OCM data. Journal of the Indian Society of Remote Sensing. V: 35, Issue 3, pp 201207.
Samli R., Sivri N., Sevgen S., Kiremetci V. Z. (2014): Applying Artificial Neural Networks for the estimation of Chlorophyll-A concentrations along the Istanbul coast. Pol. J. Enviro. Stu. V: 23. No 4. 1281-1287.
Soyguder S., Alli H. (2009): An expert system for the humidity and temperature control in HVAC systems using ANFIS and optimization with Fuzzy Modeling Approach. Energy and Buildings. 41(8): 814-822.
Soyguder S., Alli H. (2009): Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system. Expert Systems with Applications. 36(3): 4566-4573.
Wen X. L., Wang H.T., Wang H. (2012): Prediction model of flow boiling heat transfer for R407C inside horizontal smooth tubes based on RBF neural network. Procedia Engineering. 31: 233-239.
Zhang J., Huang W., Zhou Q. (2014): Reflectance Variation within the In-Chlorophyll Centre Waveband for Robust Retrieval of Leaf Chlorophyll Content. PLoS ONE 9(11): e110812. doi:10.1371/journal.,pone.0110812