Amiri, R., Shojaaddini, M., Motazedian, N., & Zibayee, K. (2014). Degree-day and pheromone traps in control timing of codling moth, Cydia pomonella L. (Lepidoptera: Olethreutidae). Agricultural Pest Management, 1(2): 34-40.
Ariana, D. P., & Lu, R. (2008). Quality evaluation of pickling cucumbers using hyperspectral reflectance and transmittance imaging - Part II. Performance of a prototype. Sensing and Instrumentation for Food Quality and Safety, 2(3), 152-160.
Butz, P., Hofmann, C., & Tauscher, B. (2005). Recent Developments in Noninvasive Techniques for Fresh Fruit and Vegetables Internal Quality Analysis. Journal of Food Science, 70(9), 131-141.
Dyck, V. A. (2010). Rearing codling moth for SIT. FAO Plant Production and Protection.
Greenwood, P. (2000). Pests and diseases. DK Publishing, NY.
Hansen, J. D., Carlton, R., Adams, S., & Lacey, L., A. (2008). Infrared Detection of Internal Feeders of Deciduous Tree Fruits. Journal of Entomology Science, 43(1), 52-56.
Huang, M., & Lu, R. (2010). Apple mealiness detection using hyperspectral scattering technique. Postharvest Biology and Technology, 58(3), 168-175.
Lu, R., )2003(. Detection of bruises on apples using near–infrared hyperspectral imaging. Transactions of the ASAE, 46, 523-535.
Lu, R., & Peng, Y. (2006). Hyperspectral scattering for assessing peach fruit firmness. Biosystems Engineering, 93(2), 161-171.
Lu, R., & Ariana, D. P. (2013). Detection of fruit fly infestation in pickling cucumbers using a hyperspectral reflectance/transmittance imaging system. Postharvest Biology and Technology, 81, 44-50.
Mehl, P. M., Chen, Y. R., Kim, M. S., & Chan, D. E. (2004). Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations. Journal of Food Engineering, 61(1), 67-81.
Rady, A., Guyer, D., & Lu, R. (2015). Evaluation of Sugar Content of Potatoes using Hyperspectral Imaging. Food and Bioprocess Technology, 8(5), 995-1010.
Ranjbar Aghdam, H., & Ataran, M. (2014). Biological control of codling moth using parasitoid wasps Trichogramma embryophagumbased on time-degree forecasting models. Biological control of pests and plant diseases. 3(2), 87-96.
Ruiz-Altisent, M., Ruiz-Garcia, L., Moreda, G. P., Lu, R., Hernandez-Sanchez, N., Correa, E. C., & García-Ramos, J. (2010). Sensors for product characterization and quality of specialty crops-A review. Computers and Electronics in Agriculture, 74(2), 176-194
Saranwong, S., Haff, R. P., Thanapase, W., Janhiran, A., Kasemsumran, S., & Kawano, S. (2011). A feasibility study using simplified near infrared imaging to detect fruit fly larvae in intact fruit. J. Near Infrared Spectrosc., 19, 55-60.
Schatzki, T. F., Haff, R. P., Young, R., Can, I., Le, L-C., & Toyofuku, N. (1997). Defect detection in apples by means of X-ray imaging. Transactions of the ASAE, 40(5), 1407-1415.
Shahabi, A., & Malakouti, M. (2010). The effect of concentration and time of application of calcium chloride on texture and quality characteristics of red apples of Esfahan Semirom area. Journal of water and soil, 12(8). In Farsi.
Vetrekar, N. T., Gad, R. S., Fernandes, I., Parab, J. S., Desai, A. R., Pawar, J. D., & Umapathy, S. (2015). Non-invasive hyperspectral imaging approach for fruit quality control application and classification: case study of apple, chikoo, guava fruits. Journal of Food Science and Technology, 52(11), 6978-6989.
Wang, H., Peng, J., Xie, C., Bao, Y.,& Yong, He. (2015). Fruit Quality Evaluation Using Spectroscopy Technology: A Review. Sensors,15, 11889-11927.
Wang, J., Nakano, K., Ohashi, S., Kubota, Y., Takizawa, K., & Sasaki, Y. (2011). Detection of external insect infestations in jujube fruit using hyperspectral reflectance imaging. Biosystems Engineering, 108(4), 345-351.
Wang, N., & ElMasry, G. (2010). Bruise Detection of Apples using Hyperspectral Imaging. Hyperspectral Imaging for Food Quality Analysis and Control, 295-320.
Wang, S., Tang, J., &Cavalieri, R. )2001(. Modeling fruit internal heating rates for hot air and hot water treatments. Postharvest Biology and Technology, 22, 257-270.
Xing, J., Guyer, D., Ariana, D., & Lu, R. (2008). Determining optimal wavebands using genetic algorithm for detection of internal insect infestation in tart cherry. Sensing and Instrumentation for Food Quality and Safety, 2(3), 161-167.
)
