Murat Kacira

Interests

Teaching

Biosystems Thermal Engineering (Thermodynamics, Heat Transfer, Fluid Mechanics), Applied Instrumentation and Autonomous Data Acquisition

Research

Phytomonitoring, machine vision for plant health and growth monitoring, resource use optimization in CEA systems, aerodynamics analysis of CEA systems using computational fluid dynamics, alternative energy integrated CEA systems.

Courses

Scholarly Contributions

Chapters

• Kacira, M., & Zhang, Y. (2021). Environmental Control. In Plant Factory Basics, Applications and Advances. Elsevier.
• Zhang, Y., & Kacira, M. (2019). Air Distribution and Its Uniformity. In Smart Plant Factory: The Next Generation Indoor Vertical Farms(pp 153-166). Springer Nature Singapure Pte Ltd. doi:https://doi.org/10.1007/978-981-13-1065-2_10
• Zhang, Y., & Kacira, M. (2018). Air Distribution and Its Uniformity. In Smart Plant Factory: The Next Generation Indoor Vertical Farms. Singapure: Springer Verlag.
• Montero, J., Teitel, I., Baeza, E., Lopez, J., & Kacira, M. (2013). Greenhouse Design and Covering Materials. In Good Agricultural Practices (GAP) for Greenhouse Vegetable Production in the Mediterranean Region.(p. 640). ISBN 978-92-5-107649-1: FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS.

Journals/Publications

• Ciriello, M., Formisano, L., Rouphael, Y., De Pascale, S., & Kacira, M. (2023). Effects of daily light integral and photoperiod with successive harvests on basil yield, morpho-physiological characteristics, and mineral composition in vertical farming. Scientia Horticulturae, 322, 112396. doi:https://doi.org/10.1016/j.scienta.2023.112396
• Shasteen, K., & Kacira, M. (2023). Predictive Modeling and Computer Vision-Based Decision Support to Optimize Resource Use in Vertical Farms. Sustainability, 15(10), 7812. doi:https://doi.org/10.3390/su15107812
• Waller, R., Anderson, M., Rattcliff, E., & Kacira, M. (2021). Emerging opportunities for organic photovoltaics (OPV) applications to greenhouse systems: an inter-scalar review. Journal For Cleaner Production.
• Waller, R., Kacira, M., Magadley, E., Teitel, M., & Yehia, I. (2022). Evaluating the Performance of Flexible, Semi‐Transparent Large‐Area Organic Photovoltaic Arrays Deployed on a Greenhouse. AgriEngineering, 4, 969-992. doi:https://doi.org/10.3390/agriengineering4040062
• Zhang, Y., & Kacira, M. (2022). Analysis of climate uniformity in indoor plant factory system with computational fluid dynamics (CFD). Biosystems Engineering,, 220, 73-86. doi:https://doi.org/10.1016/j.biosystemseng.2022.05.009
• Kacira, M., Magadley, E., Yehia, I., Teitel, M., Friman-Peretz, M., Waller, R., & Kacira, M. (2020). Comparison of organic photovoltaics installed inside and outside a greenhouse and the effect on output and lifetime.. TBD.
• Kacira, M., Teitel, M., Friman-Peretz, M., Ozer, S., Levi, A., Magadley, E., Yehia, I., Geola, F., & Kacira, M. (2021). Energy partitioning and spatial variability of air temperature, VPD and radiation in a greenhouse tunnel shaded by semi-transparent organic PV modules. Solar Energy, 220, 578-589.
• Magadley, E., Kabla, R., Dakka, M., Teitel, M., Friman-Peretz, M., Kacira, M., Waller, R., & Yehia, I. (2021). Organic photovoltaic modules integrated inside and outside a polytunnel roof. Renewable Energy, 182, 163-171. doi:https://doi.org/10.1016/j.renene.2021.10.012
• Waller, R., Kacira, M., Magadle, E., Teitell, M., & Yehia, I. (2021). Semi-Transparent Organic Photovoltaics Applied as Greenhouse Shade for Spring and Summer Tomato Production in Arid Climate. Agronomy, 11(6), 1152. doi:https://doi.org/10.3390/agronomy11061152
• van Delden, S., SharathKumar, M., Butturini, M., Graamans, L. J., Heuvelink, E., Kacira, M., Kaiser, E., Klamer, R. S., Klerkx, G., Kootstra, A., Loebe, A., Schouten, R. E., Stanghellini, C., van Ieperen, W., Verdonk, J. C., Vialet-Chabrand, S., Woltering, E. J., van de Zedde, R., Zhang, Y., & Marcelis, L. F. (2021). Current status and future challenges in implementing and upscaling vertical farming systems. Nature Food, 2, 944–956. doi:https://doi.org/10.1038/s43016-021-00402-w
• Friman-Peretz, M., Ozer, S., Geoola, F., Magadley, E., Yehia, I., Levi, A., Brikman, R., Gantz, S., Levy, A., Kacira, M., & others, . (2020). Microclimate and crop performance in a tunnel greenhouse shaded by organic photovoltaic modules--Comparison with conventional shaded and unshaded tunnels. Biosystems Engineering, 197, 12--31.
• Magadley, E., Teitel, M., Peretz, M. F., Kacira, M., & Yehia, I. (2020). Outdoor behaviour of organic photovoltaics on a greenhouse roof. Sustainable Energy Technologies and Assessments, 37, 100641.
• Montoya, A. P., Obando, F. A., Osorio, J. A., Morales, J. G., & Kacira, M. (2020). Design and implementation of a low-cost sensor network to monitor environmental and agronomic variables in a plant factory. Computers and Electronics in Agriculture, 178, 105758.
• Orsini, F., Marcelis, L., & Kacira, M. (2020). Special Issue of eJHS - VertFarm. European Journal of Horticultural Sciences, 85(5).
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  Co--Editor for this Special Issue of European Journal of Horticultural Sciences.
• Zhang, Y., & Kacira, M. (2020). Comparison of energy use efficiency of greenhouse and indoor plant factory system. European Journal of Horticultural Science, 85(5), 310--320.
• Zhang, Y., Kacira, M., An, L., Giacomelli, G., & Li, P. (2019). Comparison of energy use efficiency of greenhouse and indoor plant factory system. TBD.
• Peretz, M. F., Geoola, F., Yehia, I., Ozer, S., Levi, A., Magadley, E., Brikman, R., Rosenfeld, L., Levy, A., Kacira, M., & Teitel, M. (2019). Testing organic photovoltaic modules for application as greenhouse cover or shading element. BIOSYSTEMS ENGINEERING, 184, 24-36.
• Rojano, F., Bournet, P., Hassouna, M., Robin, P., Kacira, M., & Choi, C. Y. (2019). Modelling the impact of air discharges caused by natural ventilation in a poultry house. BIOSYSTEMS ENGINEERING, 180, 168-181.
• Teitel, M., Ozer, S., Kacira, M., Magadley, E., Levi, A., Geoola, F., Levy, A., Yehia, I., Brikman, R., & Peretz, F. (2019). Testing organic photovoltaic modules for application as greenhouse cover or shading elements. Biosystems Engineering.
• Cruz, I. L., Fitz-Rodruguez, E., Salazar-Moreno, R., Rojano-Aguilar, A., & Kacira, M. (2018). Development and analysis of dynamical mathematical models of greenhouse climate: A review. European Journal of Horticultural Scince, 83(5), 269-280. doi:10.17660/eJHS.2018/83.5.1
• Kacira, M., Lopez-Cruz, I., Fitz-Rodriguez, E., Salazar-Moreno, R., & Rojano-Aguilar, A. (2017). Development and analysis of dynamical mathematical models of greenhouse climate: a review. European Journal of Horticultural Science.
• Rojano, F., Bournet, P., Hassouna, M., Robin, P., Kacira, M., & Choi, C. Y. (2018). Assessment using CFD of the wind direction on the air discharges caused by natural ventilation of a poultry house. ENVIRONMENTAL MONITORING AND ASSESSMENT, 190(12).
• Zhang, G., Choi, C., Bartzanas, T., Lee, I., & Kacira, M. (2018). Computational Fluid Dynamics (CFD) research and application in Agricultural and Biological Engineering. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 149, 1-2.
• Ishii, M., Sase, S., Moriyama, H., Okushima, L., Ikeguchi, A., Hayashi, M., Kurata, K., Kubota, C., Kacira, M., & Giacomelli, G. A. (2016). Controlled Environment Agriculture for Effective Plant Production Systems in a Semiarid Greenhouse. JARQ-JAPAN AGRICULTURAL RESEARCH QUARTERLY, 50(2), 101-113.
• Katsoulas, N., Elvanidi, A., Ferentinos, K. P., Kacira, M., Bartzanas, T., & Kittas, C. (2016). Crop reflectance monitoring as a tool for water stress detection in greenhouses: A review. BIOSYSTEMS ENGINEERING, 151, 374-398.
• Rojano, F., Bournet, P. E., Hassouna, M., Robin, P., Kacira, M., & Choi, C. (2014). Modelling Heat and Mass Transfer of a Broiler House Using Computational Fluid Dynamics. Biosystems Engineering.
• Rojano, F., Bournet, P., Hassouna, M., Robin, P., Kacira, M., & Choi, C. Y. (2015). Assessment of gas dispersion inside and outside of a poultry house by means of a 3D CFD model. Computers and Electronics in Agriculture.
• Rojano, F., Bournet, P., Hassouna, M., Robin, P., Kacira, M., & Choi, C. Y. (2016). Computational modelling of thermal and humidity gradients for a naturally ventilated poultry house. BIOSYSTEMS ENGINEERING, 151, 273-285.
• Zhang, Y., Kacira, M., & An, L. (2015). A CFD Study on Improving Air Flow Uniformity in Indoor Plant Factory System. Biosystems Engineering.
• Zhang, Y., Kacira, M., & An, L. (2016). A CFD study on improving air flow uniformity in indoor plant factory system. BIOSYSTEMS ENGINEERING, 147, 193-205.
• Jia, F., Kacira, M., & Ogden, K. L. (2015). Multi-Wavelength Based Optical Density Sensor for Autonomous Monitoring of Microalgae. SENSORS, 15(9), 22234-22248.
• Jia, F., Kacira, M., & Ogden, K. L. (2015). Multi-wavelength based optical density sensor for autonomous monitoring of microalgae sensors. Sensors, 15(9), 22234-22248. doi:10.3390/s150922234
• Rojano, F., Bournet, P., Hassouna, M., Robin, P., Kacira, M., & Choi, C. Y. (2015). Modelling heat and mass transfer of a broiler house using computational fluid dynamics. BIOSYSTEMS ENGINEERING, 136, 25-38.
• Story, D. L., & Kacira, M. (2014). Design and Implementation of a Computer Vision Guided Greenhouse Crop Diagnostics System. Journal of Machine Vision and Applications, 26(4), 495–506.
• Story, D., & Kacira, M. (2015). Design and implementation of a computer vision-guided greenhouse crop diagnostics system. MACHINE VISION AND APPLICATIONS, 26(4), 495-506.
• Bartzanas, T., Kacira, M., Zhu, H., Karmakar, S., Tamimi, E., Katsoulas, N., Lee, I. B., & Kittas, C. (2013). Computational fluid dynamics applications to improve crop production systems. Computers and Electronics in Agriculture, 93, 151-167.
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  Abstract: Computational fluid dynamics (CFD), numerical analysis and simulation tools of fluid flow processes have emerged from the development stage and become nowadays a robust design tool. It is widely used to study various transport phenomena which involve fluid flow, heat and mass transfer, providing detailed information for spatial and temporal distributions of flow speed and direction, pressure, temperature and species concentration. The CFD tools provide a cost-effective way of carrying out equipment and process design and optimization, and can reduce risk in equipment modification and process scale-up. In recent years, CFD modeling has been gaining attraction from the agri-food industry. The present paper provides a state-of-the-art review on various CFD applications to improve crop farming systems such as, soil tillage, sprayers, harvesting, machinery, and greenhouses. The challenges faced by modelers using CFD in precision crop production are discussed and possibilities for incorporating the CFD models in decision support tools for Precision Farming are highlighted. © 2012 Elsevier B.V.
• Kacira, M. -., Villarreal-Guerrero, F., Kacira, ., , E., Linker, R., Giacomelli, G., Arbel, A., & Kubota, C. (2013). Implementation of a greenhouse cooling strategy with natural ventilation and variable fogging rates. Transactions of ASABE.
• Lee, I., Pascual, J., Hong, S., Seo, I., Kwon, K., Bartzanas, T., & Kacira, M. (2013). The past, present and future of CFD for agro-environmental applications. Computers and Electronics in Agriculture, 93, 168-183.
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  Abstract: Computational fluid dynamics (CFD) is a proven simulation tool which caters to almost any field of study. The CFD technique is utilized to simulate, analyze, and optimize various engineering designs. In this review, the discussion is focused on the application of CFD in the external atmospheric processes as well as modeling in land and water management. With respect to its application in environmental investigations, numerous CFD studies have been done in the atmospheric processes where generally only the fluid flow characteristics are investigated. The application of CFD to soil and water management is still limited. However, with the present demand for conservation and sustainable management of our soil and water resources, CFD application in this field is fast emerging especially in structure designs of dams and reservoirs where CFD offers fast reliable results with less labor and cost. Every CFD model should be validated in order to be considered accurate and reliable. However, a benchmark or standard procedures in validating CFD models is not yet available. This probably answers why the success of the CFD models is still mostly attributed to the user's skills and experience. At present, the degree of application of CFD to the agro-environmental field is limited by the computing power and software used, however, the fast ever computing power of PCs continually expands the potential of CFD and can be generally more flexible at accounting for the unique aspects of every CFD project. This allows easy access to conduct simulation studies from simple to complex models. In this paper, after a state of art analysis of the past and present application of CFD in the agro-environmental applications, its future directions were discussed, in order to potentially serve as a guide for researchers and engineers on what project or investigations can be conducted. © 2012 Elsevier B.V.
• Tamimi, E., & Kacira, M. (2013). Analysis of climate uniformity in a naturally ventilated greenhouse equipped with high pressure fogging system using computational fluid dynamics. Acta Horticulturae, 1008, 177-184.
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  Abstract: High pressure fogging systems and control strategies in naturally ventilated (NV) greenhouses has been investigated as an alternative cooling mechanism to mechanical ventilation systems with aims of saving energy and water and potentially helping to improve climate uniformity in the greenhouse. Studies on analyzing the climate uniformity under NV with fogging, including the analysis of greenhouse aerodynamics, climate uniformity lacks. A 3D Computational Fluid Dynamics (CFD) analysis was used to simulate environment conditions of a NV greenhouse equipped with high pressure fogging. The study utilized models including porous media to simulate crop canopy, the Solar Load model and the Discrete Ordinates radiation model to simulate solar radiation, the species transport and the discrete phase to simulate evaporation of droplets and evapotranspiration. Experimental data collected from a single-span greenhouse was used to validate combined model. Simulated environmental variables are compared between a scenario with fogging activated and the same scenario without fogging. The simulated temperature and relative humidity at 21 points were compared to corresponding experimental measurements with percentage errors of 6-16% and 14-27%, respectively (99% confidence). There were no statistically significant differences between the simulated and experimental data sets determined by ANOVA (á=0.1). The results showed that there is a significant effect of fogging on temperature and VPD uniformity. In addition, it was shown that the air flow pattern had a significant effect on the internal environmental variables. The positions and angels of the fogging nozzle affected the interior climate.
• Tamimi, E., Kacira, M. -., Choi, C., & An, L. (2013). Analysis of climate uniformity in a naturally vented greenhouse equipped with high pressure fogging system using computational fluid dynamics. Transactions of ASABE, 56(3), 1241-1254.
• Tamimi, E., Kacira, M. -., Choi, C., & An, L. -. (2013). Analysis of microclimate uniformity in a naturally vented greenhouse with a high-pressure fogging system. Transactions of the ASABE, 56, 1241-1254.
• Tamimi, E., Kacira, M., Choi, C. Y., & An, L. (2013). Analysis of microclimate uniformity in a naturally vented greenhouse with a high-pressure fogging system. Transactions of the ASABE, 56(3), 1241-1254.
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  Abstract: Controlled environments have long played an important role in the field of agriculture because they enable growers to more precisely regulate not only the quantity of a crop but the quality as well. Currently, most controlled environments rely on mechanical systems to regulate temperature and relative humidity within the controlled space, but these systems can be costly to install and operate. For this reason, researchers have begun investigating the efficacy of using high-pressure fogging systems and their associated control strategies in naturally ventilated greenhouses as an alternative to mechanical cooling methods. However, conducting detailed analyses of a greenhouse's aerodynamics requires carefully arrayed instruments, a consideration of many different scenarios, and a significant amount of time to compile data, not to mention the monetary cost of experimental analysis. The objective of this study, then, was to develop a 3D computational fluid dynamics (CFD) model capable of more efficiently analyzing the movement of air in a naturally ventilated greenhouse equipped with a high-pressure fogging system. The overall model included five subunits: (1) a porous media model to simulate the ways that a crop canopy will affect airflow, (2) a solar load model and (3) a discrete ordinates radiation model to simulate solar radiation, (4) a species transport and discrete phase model to simulate evaporation of droplets, and (5) an evapotranspiration (ET) model integrated with a user-defined function (UDF). The overall model predicted temperature and relative humidity within the greenhouse with percentage errors for temperature and relative humidity of 5.7% to 9.4% and 12.2% to 26.9%, respectively (given a 95% confidence interval). The average percent error between the simulated and measured ET was around 8%, and the CFD-simulated stomatal and aerodynamic resistances agreed well and were within the ranges indicated by earlier research. Having validated the overall model with experimental data, we then used a 24 full-factorial design to determine the effects on climate uniformity produced by four factors: position of the side vent, position of the vertical sprayer nozzles, position of the horizontal sprayer nozzles, and angle of the nozzle. On the basis of our statistical analysis, we concluded that "horizontal nozzle position" was the most significant factor for climate uniformity, while the least significant factor among those evaluated was "side vent opening.". © 2013 American Society of Agricultural and Biological Engineers.
• Boscheri, G., Kacira, M., Patterson, L., Giacomelli, G., Sadler, P., Furfaro, R., Lobascio, C., Lamantea, M., & Grizzaff, . (2012). Modified energy cascade model adapted for a multicrop lunar greenhouse prototype. Advances in Space Research, 50, 941-95.
• Crowe, B., Attalah, S., Agrawal, S., Waller, P., Ryan, R., Van, W. J., Chavis, A., Kyndt, J., Kacira, M., Ogden, K., & Huesemann, M. (2012). A comparison of Nannochloropsis salina growth performance in two outdoor pond designs: conventional raceways versus the ARID pond with superior temperature management. International Journal of Chemical Engineering, 2012.
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  doi:10.1155/2012/92060
• Kacira, M. -., Bartzanas, T., KaciraM, ., Zhu, H., Karmakar, S., Tamimi, E., Katsoulas, N., LeeI, ., & Kittas, C. (2012). Computational fluid dynamics applications to improve crop production systems. Computers and Electronics in Agriculture.
• Kacira, M. -., Yang, Z., Kubota, ., Chia, P., & Kacira, . (2012). Effect of end-of-day far-red light from a movable LED fixture on squash rootstock hypocotyl elongation. Scientia Horticulturae, 136, 81-86.
• Lee, I., Bitog, J., Hong, S., Seo, I., Kwon, K., Bartzanas, T., & Kacira, M. (2012). The past, present and future of CFD for agro-environmental applications. Computers and Electronics in Agriculture, 93, 168-183.
• Sase, S., Kacira, M., Boulard, ., & Okushima, L. (2012). Determination of porosity parameters for tomato canopy: An experimental study in a wind tunnel. Transactions of the ASABE, 55(5), 1921-1927.
• Sase, S., Kacira, M., Boulard, T., & Okushima, L. (2012). Wind tunnel measurement of aerodynamic properties of a tomato canopy. Transactions of the ASABE, 55(5), 1921-1927.
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  Abstract: This study was conducted to determine the drag coefficient and the relationship between permeability (K) and momentum loss coefficients (C f) of a tomato canopy for various leaf area densities. The experiments were conducted in a large-scale wind tunnel system with a tomato canopy. The static pressures and air velocity measurements were performed at several heights in the y-direction and various positions in the z-direction in the wind tunnel test section. The relationship between pressure drop and air velocity across the tomato canopy was determined using a porous medium approach. A drag coefficient of 0.31 was obtained for the tomato canopy used in the experiment. The permeability of the tomato canopy ranged from 0.006 to 0.65 for a leaf area density (L) of 4 (m2 m-3), from 0.004 to 0.41 for L = 5, and from 0.003 to 0.3 for L = 6 as Cf changed from 0.1 to 1. Thus, a mature tomato canopy having L = 6 could be used with a canopy permeability of K = 0.017 and a momentum loss coefficient of Cf = 0.245. © 2012 American Society of Agricultural and Biological Engineers.
• Villarreal-Guerrero, F., Kacira, M. -., Kacira, M., Villarreal-Guerrero, F., , E., Kacira, ., Linker, R., , E., Kubota, C., Linker, R., Giacomelli, G., Kubota, C., Arbel, A., Giacomelli, G., & Arbel, A. (2012). Simulated performance of a greenhouse cooling control strategy with natural ventilation and fog cooling. Biosystems Engineering, 111, 217-228.
• Villarreal-Guerrero, F., Kacira, M., , E., Kubota, C., Giacomelli, ., Linker, R., & Arbel, A. (2012). Comparison of three evapotranspiration models for a greenhouse cooling strategy with natural ventilation and variable high pressure fogging. Scientia Horticulturae, 134, 210-221.
• Villarreal-Guerrero, F., Kacira, M., Rodriguez, E. F., Kubota, C., Giacomelli, G., Linker, R., & Arbel, A. (2012). Comparison of three evapotranspiration models for a greenhouse cooling strategy with natural ventilation and variable high pressure fogging. Scientia Horticulturae, 134, 210-221.
• Waller, P., Ryan, R., Kacira, M., & Li, P. (2012). The algae raceway integrated design for optimal temperature managemen. Biomass and Bioenerg, 46, 702-709.
• Yang, Z., Kubota, C., Chia, P. L., & Kacira, M. (2012). Effect of End-of-Day Far-Red Light from a Movable LED Fixture on Squash Rootstock Hypocotyl Elongation. Scientia Horticulturae.
• Baeza, E. J., Pérez-Parra, J., López, J., Gázquez, J., Kacira, M., & Montero, J. I. (2011). Validation of CFD simulations for three dimensional temperature distributions of a naturally ventilated multispan greenhouse obtained by wind tunnel measurements. Acta Horticulturae, 893, 571-580.
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  Abstract: In the last decade there has been an exponential increase in the number of research works using computational fluid dynamic simulations to study natural ventilation processes in greenhouses. The main reasons for this are that Computational Fluid Dynamics (CFD) simulations can provide a vast amount of information in a cost effective way in a reasonable time period compared to experimental techniques. It also provides designers and researchers a very fast and reliable tool to improve natural ventilation designs by studying the effects of multiple combinations of vent cases and external climatic conditions. However, the main limiting factor of the simulations is that validation studies must be performed with some source of experimental data, which are normally very scarce, due to high costs of time and money. In the present work, a CFD package has been used to perform simulations of a set of previous experiments conducted in a wind tunnel with naturally ventilated multi-span greenhouse with scaled models. The main focus of the current study was to compare three dimensional temperature distributions obtained for different ventilation cases from wind tunnel study with CFD simulations to validate the model. After a first set of simulations the quantitative agreement found for the temperature distribution in the middle vertical plane of the greenhouse for the four vent cases studied was only approximate, whereas for the mid horizontal plane the agreements was less good, with values in all cases lower than in the experiments. The qualitative comparison of the temperature distribution on both middle planes (vertical and horizontal) showed fairly good agreement for cases in which side vents were opened in combination with the roof vents whereas the agreements for those cases in which only roof vents opened was not similar. In view of this, two new turbulence models were used checking the effect on the agreement with experimental results, in order to have a better knowledge of the simulations set up for future validations.
• Kacira, M. -., Striemer, G., StoryDL, ., Akoglu, A., & KaciraM, . (2011). A Node and Network Level Self-Recovering Distributed Wireless Sensor Architecture for Real-Time Crop Monitoring in Greenhouses. Transactions of ASABE, 54(4), 1521-1527.
• Linker, R., Arbel, A., Kacira, M., & Gutman, O. (2011). Design and validation of robust controllers for fog and ventilation in mechanically ventilated greenhouses. American Society of Agricultural and Biological Engineers Annual International Meeting 2011, 7, 5793-5811.
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  Abstract: This work presents the development and validation of robust controllers for greenhouses equipped with a climate control system that consists of variable-pressure fogging and variable-speed extracting fans. The controllers were designed using the robust control method "Quantitative Feedback Theory" that guarantees adequate performance of the controlled system despite large modeling uncertainties and disturbances. The design of the controllers and their initial validation were performed in a small experimental greenhouse, and the same controllers were later implemented in a much larger greenhouse located in a warmer and drier region. Good tracking performances were observed in both greenhouses.
• Linker, R., Kacira, M., & Arbel, A. (2011). Robust climate control of a greenhouse equipped with variable-speed fans and a variable-pressure fogging system. Biosystems Engineering, 110(2), 153-167.
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  Abstract: A climate control system for a small greenhouse equipped with a variable-pressure fogging system and variable-speed extracting fans was developed and validated. The controllers were designed using the robust control method quantitative feedback theory (QFT) that guarantees adequate performance of the controlled system despite large modelling uncertainties and disturbances. In order to simplify the design of the controllers and achieve better performances, partial decoupling between the two control loops was achieved by describing the greenhouse climate in terms of air enthalpy and humidity ratio. This led to using ventilation for achieving the desired air enthalpy, and fogging for achieving the desired humidity ratio, assuming that the ventilation rate was approximately known. The implementation results demonstrated the good performance of the controllers, with mean tracking errors of ~100 J kg-1 [dry air] and ~0.1 g [water] kg-1 [dry air] for enthalpy and humidity ratio, respectively. For practical applications, the desired climate was expressed in terms of air temperature and relative humidity, which were converted into enthalpy and humidity ratio using the psychrometric relationships. In this case, the mean tracking errors were ~0.2 °C air temperature and less than 1% relative humidity, and the maximum mean deviations over a 10-min period with constant setpoints were 2.5 °C air temperature and 5% relative humidity. © 2011 IAgrE.
• Linker, R., Kacira, M., & ArbelA, . (2011). Robust climate control of a greenhouse equipped with variable-speed fans and a variable-pressure fogging system. Biosystems Engineering, 110(2), 153-167.
• Bascetincelik, A., Ozturk, H. H., Ekinci, K., Kaya, D., Kacira, M., & Karaca, C. (2009). Assessment of the applicability of EU biomass technologies in Turkey. Energy Exploration and Exploitation, 27(4), 295-306.
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  Abstract: An assessment of the applicability of EU biomass technologies in Turkey is presented. SWOT analysis was applied for the implementation of EU biomass technology in Turkey. Market overview, EU biomass technologies implementation in Turkey, market competition and comparison with competing fuels, manufacturers-distribution channels-sales networks, application areas, investment incentives-financing techniques, the changing market conditions and critical success factors were assessed in this study. An ultimate objective of this study is to transfer the European experience and practices relative to the overall framework of managing agricultural waste.
• Bascetincelik, A., Ozturk, H., Ekinci, K., Kaya, D., Kacira, M., & Karaca, C. (2009). Strategy development and determination of barriers for thermal energy and electricity generation from agricultural biomass in Turkey. Energy Exploration and Exploitation, 27(4), 277-294.
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  Abstract: The present work deals with determining barriers for thermal energy and electricity generation from agricultural biomass in Turkey. Strategy development and determination of barriers were investigated in accordance with the work program requirements for the project entitled ''Exploitation of Agricultural Waste in Turkey'' under the European Life Third Countries Program. The study has been organized and presented according to the following three phases: (i) market barriers for electricity and thermal energy generation (ii) identification of barriers to the promotion of agricultural waste exploitation in Turkey, and (iii) conclusions for strategy development.
• Şimşek, M., Tonkaz, T., Kaçira, M., Çömlekçioǧlu, N., & Doǧan, Z. (2005). The effects of different irrigation regimes on cucumber (Cucumbis sativus L.) yield and yield characteristics under open field conditions. Agricultural Water Management, 73(3), 173-191.
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  Abstract: A study was conducted to determine the effects of different drip irrigation regimes on yield and yield components of cucumber (Cucumbis sativus L.) and to determine a threshold value for crop water stress index (CWSI) based on irrigation programming. Four different irrigation treatments as 50 (T-50), 75 (T-75), 100 (T-100) and 125% (T-125) of irrigation water applied/cumulative pan evaporation (IW/CPE) ratio with 3-day-period were studied. Seasonal crop evapotranspiration (ETc) values were 633, 740, 815 and 903 mm in the 1st year and were 679, 777, 875 and 990 mm in the 2nd year for T-50, T-75, T-100 and T-125, respectively. Seasonal irrigation water amounts were 542, 677, 813 and 949 mm in 2002 and 576, 725, 875 and 1025 mm in 2003, respectively. Maximum marketable fruit yield was from T-100 treatment with 76.65 t ha-1 in 2002 and 68.13 t ha-1 in 2003. Fruit yield was reduced significantly, as irrigation rate was decreased. The water use efficiency (WUE) ranged from 7.37 to 9.40 kg m-3 and 6.32 to 7.79 kg m-3 in 2002 and 2003, respectively, while irrigation water use efficiencies (IWUE) were between 7.02 and 9.93 kg m-3 in 2002 and between 6.11 and 8.82 kg m -3 in 2003. When the irrigation rate was decreased, crop transpiration rate decreased as well resulting in increased crop canopy temperatures and CWSI values and resulted in reduced yield. The results indicated that a seasonal mean CWSI value of 0.20 would result in decreased yield. Therefore, a CWSI = 0.20 could be taken as a threshold value to start irrigation for cucumber grown in open field under semi-arid conditions. Results of this study demonstrate that 1.00 IW/CPE water applications by a drip system in a 3-day irrigation frequency would be optimal for growth in semiarid regions. © 2004 Elsevier B.V. All rights reserved.
• Kacira, M., Sase, S., & Okushima, L. (2004). Effects of side vents and span numbers on wind-induced natural ventilation of a gothic multi-span greenhouse. Japan Agricultural Research Quarterly, 38(4), 227-233.
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  Abstract: In this paper, the effects of wind speed, side ventilators and span numbers on gothic type multi-span greenhouse natural ventilation were studied by numerical simulation using the Computational Fluid Dynamics (CFD) approach. The realizable k-ε model was used for the turbulence model in the simulations. The results showed that the maximum greenhouse ventilation rate was achieved when both side and roof vents were used for ventilation. Without the existence of buoyancy effect in the computations, it was found that the ventilation rate increased linearly with the external wind speed in all the cases studied. The ratio of the opening of the ventilator area to the greenhouse floor area, 9.6%, was found to be small compared to the recommended ratios of 15-25%. The results showed that a significant reduction in ventilation rate was determined as the number of spans was increased and an exponential decay explained the relationship between the ventilation rate and the number of spans.
• Kacira, M., Sase, S., & Okushima, L. (2004). Optimization of vent configuration by evaluating greenhouse and plant canopy ventilation rates under wind-induced ventilation. Transactions of the American Society of Agricultural Engineers, 47(6), 2059-2067.
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  Abstract: The effects of greenhouse vent configurations, plant existence, and external wind speeds on ventilation rates and airflow patterns in a greenhouse and plant canopy zone under wind-induced ventilation were investigated. The optimization of traditional vent configuration for a two-span glasshouse for better air renewal, especially in the plant canopy zone, was attempted by three-dimensional numerical simulations using a computational fluid dynamics (CFD) approach. The realizable k-ε model was used for a turbulent model, and the existence of the plants in the greenhouse was modeled by a porous medium method. Prior to the optimization, the CFD model was verified with the results of an experimental study of natural ventilation. The CFD model adequately matched those results. The ventilation rates, both in the greenhouse and in the plant canopy zone, were proportional to external wind speed. Maximum greenhouse ventilation rates were achieved when rollup type side vents were used in the side walls and both side and roof vents were fully open (case 3). For example, the ventilation rate for this vent configuration was 6.03 m3 m-2 min-1 at an external wind speed of 1.5 m s-1. The greenhouse ventilation rate for this vent configuration was almost the same as when the butterfly-type side and roof vents were fully open (case 1). However, the use of a rollup side vent considerably improved the ventilation rate in the plant canopy zone. This showed that ventilation in the plant canopy zone was significantly affected by internal airflow patterns caused by different vent configurations. © 2004 American Society of Agricultural Engineers.
• Kacira, M., Simsek, M., Babur, Y., & Demirkol, S. (2004). Determining optimum tilt angles and orientations of photovoltaic panels in Sanliurfa, Turkey. Renewable Energy, 29(8), 1265-1275.
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  Abstract: The performance of a photovoltaic (PV) panel is affected by its orientation and its tilt angle with the horizontal plane. This is because both of these parameters change the amount of solar energy received by the surface of the PV panel. A mathematical model was used to estimate the total solar radiation on the tilted PV surface, and to determine optimum tilt angles for a PV panel installed in Sanliurfa, Turkey. The optimum tilt angles were determined by searching for the values of angles for which the total radiation on the PV surface was maximum for the period studied. The study also investigated the effect of two-axis solar tracking on energy gain compared to a fixed PV panel. This study determined that the monthly optimum tilt angle for a PV panel changes throughout the year with its minimum value as 13° in June and maximum value as 61° in December. The results showed that the gains in the amount of solar radiation throughout the year received by the PV panel mounted at monthly optimum tilt angles with respect to seasonal optimum angles and tilt angel equal to latitude were 1.1% and 3.9%, respectively. Furthermore, daily average of 29.3% gain in total solar radiation results in an daily average of 34.6% gain in generated power with two-axis solar tracking compared to a south facing PV panel fixed at 14° tilt angle on a particular day in July in Sanliurfa, Turkey. © 2003 Elsevier Ltd. All rights reserved.
• Şimşek, M., Kaçira, M., & Tonkaz, T. (2004). The effects of different drip irrigation regimes on watermelon [Citrullus lanatus (Thunb.)] yield and yield components under semi-arid climatic conditions. Australian Journal of Agricultural Research, 55(11), 1149-1157.
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  Abstract: This study was conducted to investigate the effects of drip irrigation on yield and yield components of watermelon [Citrullus lanatus (Thunb.) Crimson Tide F1] under semiarid conditions in the Southeastern Anatolian Project Region, Harran Plain, Şanliurfa, Turkey, during 2002 and 2003. Using a 4-day irrigation period, 4 different irrigation regimes were applied as ratios of irrigation water/cumulative pan evaporation (IW/CPE): 1.25 (I 125), 1.00 (I100), 0.75 (I75), and 0.50 (I 50). Seasonal crop evapotranspiration (ETc.) rates were 720, 677, 554, and 449 mm in the first year and 677, 617, 519, and 417 mm in the second year for irrigation treatments I125, I100, I 75, and I50, respectively. Amounts of irrigation water applied to the 4 respective treatments were 764, 642, 520, and 398 mm in 2002 and 709, 591, 473, and 355 mm in 2003. Maximum yield was obtained from I 125, with 84.1 t/ha in 2002 and 88.6 t/ha in 2003. Yield was reduced significantly as the irrigation water was reduced. The values of water use efficiency ranged from 9.6 to 11.7 kg/m3 in 2002 and 10.8 to 13.1 kg/m3 in 2003. The unstressed I125 treatment produced 10.1 kg marketable watermelons/m3 irrigation in 2002, and 11.3 kg/m 3 in 2003. By comparison, the least irrigated (I50) treatment produced 12.4 kg/m3 in 2002, and 14.9 kg/m3 in 2003. A yield response factor (ky) value of 1.15 was determined based on averages of 2 years, and watermelon was found to be sensitive to water stress. This result showed that yield loss (1 - Ya/Ym) is more important than evapotranspiration deficit (1 - ETa/ET m). The study demonstrates that 1.25 IW/CPE water applications by a drip system in a 4-day irrigation frequency might be optimal for watermelon grown in semi-arid regions similar to those in which the work was conducted.
• Kacira, M., Ling, P. P., & Short, T. H. (2002). Establishing crop water stress index (CWSI) threshold values for early, non-contact detection of plant water stress. Transactions of the American Society of Agricultural Engineers, 45(3), 775-780.
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  Abstract: Early, non-contact, non-destructive, and quantitative detection of plant water stress with the application of infrared thermometry using a crop water stress index (CWSI) was established. A CWSI model for plants grown under controlled environments was developed using thermodynamic principles and energy balance of the plant. CWSI threshold values were established with a parametric approach. The effectiveness of the sensing technique was evaluated using timing of the stress detection by a grower. The CWSI-based technique was able to detect the stress one to two days prior to the time of stress detection by visual observation. Overall results of this study suggested that pre-visual and non-contact detection of plant water stress with infrared thermometry application using CWSI is feasible.
• Kacira, M., Ling, P. P., & Short, T. H. (2002). Machine vision extracted plant movement for early detection of plant water stress. Transactions of the American Society of Agricultural Engineers, 45(4), 1147-1153.
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  PMID: 14674430;Abstract: A methodology was established for early, non-contact, and quantitative detection of plant water stress with machine vision extracted plant features. Top-projected canopy area (TPCA) of the plants was extracted from plant images using image-processing techniques. Water stress induced plant movement was decoupled from plant diurnal movement and plant growth using coefficient of relative variation of TPCA (CRVTPCA) and was found to be an effective marker for water stress detection. Threshold value of CRVTPCA as an indicator of water stress was determined by a parametric approach. The effectiveness of the sensing technique was evaluated against the timing of stress detection by an operator. Results of this study suggested that plant water stress detection using projected canopy area based features of the plants was feasible.
• Kacira, M., & Ling, P. P. (2001). Design and development of an automated and non-contact sensing system for continuous monitoring of plant health and growth. Transactions of the American Society of Agricultural Engineers, 44(4), 989-996.
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  PMID: 12026934;Abstract: An automated system was designed and built to continuously monitor plant health and growth in a controlled environment using a distributed system approach for operational control and data collection. The computer-controlled system consisted of a motorized turntable to present the plants to the stationary sensors and reduce microclimate variability among the plants. Major sensing capabilities of the system included machine vision, infrared thermometry, time domain reflectometry, and micro-lysimeters. The system also maintained precise growth-medium moisture levels through a computer-controlled drip irrigation system. The system was capable of collecting required data continuously to monitor and to evaluate the plant health and growth.
• Kacira, M., Ling, P. P., & Short, T. H. (2000). Establishing crop water stress index (CWSI) threshold values for early and non-contact detection of plant water stress. 2000 ASAE Annual International Meeting, Technical Papers: Engineering Solutions for a New Century, 2, 5243-5254.
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  Abstract: A methodology was established for early, non-contact, non-destructive, and quantitative detection of plant water stress with the application of infrared thermometry using a crop water stress index (CWSI). A CWSI model for plants grown under controlled environments was developed using thermodynamic principles and energy balance of the plant. CWSI threshold values were established with a parametric approach. The effectiveness of the sensing technique was evaluated using timing of the stress detection by a grower. The CWSI based technique was able to detect the stress one to two days prior to the time of stress detection by the grower. Overall results of this study suggested that pre-visual and non-contact detection of plant water stress with infrared thermometry application using CWSI is feasible.
• Kacira, M., Ling, P. P., & Short, T. H. (2000). Plant Water Stress Detection Using Machine Vision Extracted Plant Movement. 2000 ASAE Annual International Meeting, Technical Papers: Engineering Solutions for a New Century, 1, 239-252.
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  Abstract: A methodology was established for early, non-contact, and quantitative detection of plant water stress with machine vision extracted plant features. Top projected canopy area (TPCA) of the plants was extracted from plant images using image processing techniques. Water stress induced plant movement was decoupled from plant diurnal movement and plant growth using coefficient of variation of TPCA (COV TPCA) and was found to be effective for the water stress detection. Threshold value of COV TPCA as an indicator of water stress was determined by a parametric approach. The effectiveness of the sensing technique was evaluated against the timing of stress detection by a grower. Results of this study suggested that the objective water stress detection using projected canopy area based feature of the plants was feasible.
• Kacira, M., Short, T. H., & Stowell, R. (1999). Modeling naturally ventilated greenhouse designs for mediterranean climates. Acta Horticulturae, 491, 113-118.
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  Abstract: A computational fluid dynamics program, FLUENT V4, was used to determine ventilation rates and air flow patterns of a multi-span sawtooth greenhouse for various roof and side vent openings and outside wind speeds. The combined effects of roof and windward side openings resulted in ventilation rates up to four times standard fan recommendations. The program adequately, simulated previous wind tunnel and computational studies of natural ventilation designs.
• Kacira, M., Short, T. H., & Stowell, R. R. (1998). A CFD evaluation of naturally ventilated, multi-span, sawtooth greenhouses. Transactions of the American Society of Agricultural Engineers, 41(3), 833-836.
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  Abstract: A computational fluid dynamics (CFD) program, Fluent V4, was used to predict natural ventilation rates and airflow patterns of a multi-span sawtooth greenhouse for various roof and side vent openings and outside wind speeds. Predicted rates were found to be both well above and well below a standard volumetric air exchange rate of l.0 A.C. min-1. The maximum and most acceptable ventilation rates were obtained with the combined use of a windward side vent and leeward roof vents on all multi-span sections. Ventilation rates ranged from 1.4 to 4.01 A.C. min-1 for the best two-span case and 0.14 to 2.0 A.C. min-1 for the similar four-span case for outside wind speeds of 0. 5 and 2.0 m s-1, respectively. Predicted ventilation rates ranged from 0.17 to 0.7 A.C. min-1 when no side vent was used and the roof vents were fully open.
• Kacira, M., Short, T. H., & Stowell, R. R. (1997). Fluid dynamic evaluation of naturally ventilated gutter-connected greenhouses. Paper - American Society of Agricultural Engineers, 3.
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  Abstract: A computer simulation program, FLUENT V4, was used to determine ventilation rates and air flow patterns of a multi-span sawtooth greenhouse under various roof and side vent opening configurations and outside wind speeds. The analytical method used was based on computational aerodynamics. The combined effects of roof and windward side openings resulted in ventilation rates up to four times recommended for average wind speeds. The method and the software used adequately simulated previous wind tunnel and computational studies of natural ventilation designs and the results of multi-span sawtooth simulations exceeded the recommended ventilation rates found in the literature.

Proceedings Publications

• Shasteen, K., Seong, J., Souza, S. V., Kubota, C., & Kacira, M. (2023, May). Optimal planting density: effects on harvest time and yield. In XXXI International Horticultural Congress (IHC2022): International Symposium on Advances in Vertical Farming, 1369, 41-48..
• Kacira, M., & Tuzel, Y. (2021, December). Recent developments in protected cultivation. In VIII South-Eastern Europe Symposium on Vegetables and Potatoes, 1-14.
• Chief, K., Kacira, M., Simmons-Potter, K., Arnold, R. G., Ratcliff, E., Ogden, K., Colombi, B., Shirley, V., & Litson, B. (2020, September). Indigenous Food, Energy, and Water Security and Sovereignty (Indige-FEWSS). In AGU Fall Meeting 2020.
• Kacira, M., Boyaci, F., Hemming, S., & Tuzel, Y. (2020, March). Proceedings of the III International Symposium on Innovation and New Technologies in Protected Cultivation. In III International Symposium on Innovation and New Technologies in Protected Cultivation, 1271.
• Montaya, A., Kacira, M., & Obando, F. A. (2019, August). Design and implementation of low a cost microcontroller in controlled environment agriculture. In XXI International Horticultural Congress on Horticulture.
• Montoya, A., Kacira, M., & Abando, F. A. (2020, Spring). Design and implementation of a low cost microcontroller in controlled environment agriculture. In II Symposium on Mechanization, Precision Horticulture, and Robotics, 1279, 287-294.
• Zhang, Y., & Kacira, M. (2020, March). Enhancing Resource Use Efficiency in Plant Factory. In XXX International Horticultural Congress on Horticulture, 1271, 307-314.
• Giacomelli, G., Jensen, M., Kacira, M., & Kubota, C. (2019, September). Agricultural plastics secure CEA ubiquitous applications in 21st century. In XXI International Congress on Plastics in Agriculture: Agriculture, Plastics and Environment, 1252, 163-172.
• Baeza, E., & Kacira, M. (2015, July). Greenhouse technology for cultivation in arid and semi-arid regions. In GreenSys 2015.
• Bartzanas, T., Kacira, M., Boulard, T., Roy, J. C., Fatnassi, H., Bournet, P. E., Katsoulas, N., & Kittas, C. (2014, May). The use of user define functions in CFD simulations for greenhouse environment.. In ActaHorticulturae, 1037.
• Kacira, M., Jensen, M., Robie, T., Tollefson, S., & Giacomelli, G. A. (2015, December). Use resources wisely: Waste Management and Organic Liquid Fertilizer Use in Greenhouse Production System. In III International Symposium on Organic Greenhouse Horticulture.
• Kacira, M., Jensen, M., Robie, T., Tollefson, S., & Giacomelli, G. A. (2016, April). Use resources wisely: waste management and organic liquid fertilizer use in greenhouse production system. In III International Symposium on Organic Greenhouse Horticulture.
• Okada, K., Yehia, I., Teitel, M., & Kacira, M. (2017, August). Crop Production and Energy Generation in a Greenhouse Integrated with Semi-transparent Organic Photovoltaics film. In GreenSys 2017 - International Symposium on New Technologies for Environment Control, Energy-Saving and Crop Production in Greenhouse and Plant Factory..
• Romero, E. J., & Kacira, M. (2015, July). Greenhouse technology for cultivation in arid and semi-arid regions. In GreenSys2015.
• Ying, Z., & Kacira, M. (2017, August). Analysis of Environmental Uniformity in a Plant Factory Using CFD Analysis. In GreenSys 2017 - International Symposium on New Technologies for Environment Control, Energy-Saving and Crop Production in Greenhouse and Plant Factory..
• Baeza, E., & Kacira, M. (2017, July). Greenhouse technology for cultivation in arid and semi-arid regions. In Actahorticulturae, 1170, 17-30.
• Kacira, M., Jensen, M., Robie, T., Tollefson, S., & Giacomelli, G. (2016, April). Use resources wisely: waste management and organic liquid fertilizer use in greenhouse production system.. In 3rd International Symposium on Organic Greenhouse Horticulture, 1164, 541-548.
• Giacomelli, G. A., Kacira, M., Furfaro, R., Patterson, L., & Sadler, P. (2014, 08/2014). Plant production, energy balance and monitoring-control-telepresence in a recirculating hydroponic vegetable crop production system: prototype lunar greenhouse. In International Symposium on Innovation and New Technologies in Protected Cropping, 53-60.
• Giacomelli, G. A., Kacira, M., Furfaro, R., Patterson, L., & Sadler, P. (2015, November). Plant production, energy balance and monitoring-control-telepresence in a recirculating hydroponic vegetable crop production system: prototype lunar greenhouse. In International Symposium on Innovation and New Technologies in Protected Cropping, 1107, 53-60.
• Boscheri, G., Lamantea, M., Lobascio, C., Patterson, L., Hernandez, E., Jensen, T., & Kacira, M. (2014, July). Poly-Culture Food Production Mass Balances Prediction in a Semi-Closed Lunar Greenhouse Prototype (LGH). In International Conference on Environmental Systems (ICES 2014).
• Fatnassi, H., Boulard, T., Bartzanas, T., Katsoulas, N., Kacira, M., & Poncet, C. (2014, May). CFD modeling of microclimate in the leaf boundary layer, ecological niche of pests. In ActaHorticulturae, 1037, 1027-1034.
• Guerrero, F. V., Kacira, M. -., & Velazcues, J. F. (2014, May). Comparative performance of a greenhouse cooling strategy with natural ventilation and fogging under different outside climates. In ActaHorticulturae, 1037, 57-64.
• Ishi, M., Okushima, L., Moriyama, H., Sase, S., Takakura, T., & Kacira, M. (2014, May). Effects of natural ventilation rate on temperature and relative humidity in a naturally ventilated greenhouse with high pressure fogging system. In ActaHOrticulturae, 1037, 1127-1132.
• Juang, P., & Kacira, M. -. (2014, May). System dynamics of a photovoltaic integrated greenhouse. In ActaHorticulturae, 1037, 99-104.
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  Peer reviewed Proceedings paper. Invited presentation paper fin Greensys2013 Symposium.
• Kittas, C., Katsoulas, N., Bartzanas, T., Kacira, M., & Boulard, T. (2014, May). Exposure of greenhouse workers to pesticide. In ActaHorticulturae, 1037, 1133-1138.
• Rojano, F., Bournet, P. E., Robin, P., Hassouna, M., Choi, C., & Kacira, M. (2014, July). Predicting sensible and latent heat generation with CFD in animal housing for dairy cattle. In AgEng2014.
• Story, D. L., & Kacira, M. -. (2014, May). Automated machine vision guided plant monitoring system for greenhouse crop diagnostics. In ActaHorticulturae, 1037, 635-641.
• Story, D., Hall, C., & Kacira, M. (2014, July). Decision support system enabled lunar greenhouse system monitoring, control and management. In International Conference on Environmental Systems (ICES 2014).
• Fitz-Rodriguez, E., Kacira, M., Villarreal-Guerrero, F., Giacomelli, G., Kubota, C., Linker, R., & Arbel, A. (2012, Fall). Neural Network Predictive Control in a Naturally Ventilated and Fog Cooled Greenhouse. In ActaHorticulturae, 952, 45-52.
• Kacira, M., Giacomelli, G., Patterson, L., Furfaro, R., Sadler, P., Boscheri, G., Lobascio, C., Lamantea, M., Wheeler, R., & Rossignoli, S. (2012, Fall). System Dynamics and Performance Factors of a Lunar Greenhouse Prototype Bioregenerative Life Support System. In ActaHorticulturae, 952, 575-582.
• Patterson, R., Giacomelli, G., Kacira, M., Sadler, P., & Wheeler, R. (2012, Fall). Description, Operation and Production of the South Pole Food Growth Chamber (SPFGC). In ActaHorticulturae, 952, 589-596.
• Sadler, P., Giacomelli, G., Patterson, L., Kacira, M., Furfaro, R., Boscheri, G., Lobascio, C., Lamanteo, M., Pirolli, M., Rossignoli, S., & DePascal, S. (2012, Fall). Bio-regenerative Life Support System Development for Lunar/Mars Habitats. In 42nd International Conference on Environmental Systems (AIAA-ICES 2012).
• Sadler, P., Giacomelli, G., Patterson, L., Kacira, M., Furfaro, R., Boscheri, G., Lobascio, C., Lamanteo, M., Pirolli, M., Rossignoli, S., & DePascale, S. (2012, Fall). Bio-regenerative Life Support System Development for Lunar/Mars Habitats. In 42ns International Conference on Environmental Systems (AIAA-ICES 2012).
• Tamimi, E., & Kacira, M. -. (2012, August). Analysis of climate uniformity in a naturally vented greenhouse equipped with high pressure fogging system using CFD. In CIGR-EuroAgEngr 2012, 1008, 177-183.
• Villarreal-Guerrero, F., Kacira, M., & Fitz-, R. E. (2012, Spring). Simulation of Fixed and Variable Pressure Fogging in Naturally Ventilated Greenhouse, Water and Energy Savings and Stability of Climate. In ActaHorticulturae, 952, 37-44.
• Baeza, E., Parra, J. P., Lopez, J. C., Gazquez, C., Kacira, M. -., & Montero, J. I. (2011, .). Validation of CFD simulations for three dimensional temperature distributions of a naturally ventilated multispan greenhouse obtained by wind tunnel measurements. In ActaHorticulturae, 893, 571-579.
• Sadler, P., Giacomelli, G., Patterson, L., Kacira, M., Furfaro, R., Lobascio, C., Boscheri, G., Lamantea, M., Grizzaffi, L., Rossignoli, S., Prirolli, M., & DePascale, S. (2011, Fall). Bio-regenerative Life Support Systems for Space Surface Applications. In 41st International Conference on Environmental Systems.
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  (AIAA-ICESS 2011)
• Sadler, P., Giacomelli, G., Patterson, L., Kacira, M., Furfaro, R., Lobascio, C., Boscheri, G., Lamantea, M., Grizzaffi, L., Rossignoli, S., Prirolli, M., & DePascale, S. (2011, Fall). Bio-regenerative Life Support Systems for Space Surface Applications. In Proceedings of 41st International Conference on Environmental Systems (AIAA-ICESS 2011).
• Story, D., Kacira, M. -., Kubota, C., & Akoglu, A. (2011, .). Morphological and textural plant feature detection using machine vision for intelligent plant health, growth and quality monitoring. In ActaHorticulturae, 893, 299-306.

Presentations

• Kacira, M. (2023, April). Controlled Environment Agriculture and Impacts on Arizona Agriculture. Ag100 Council Annual Meeting. The UNiversity of Arizona: College of Agriculture Life and Environmental Sciences.
• Kacira, M. (2023, August). Controlled Environment Agriculture. Arizona Public Services (APS) Clean Energy Innovation Summit. Virtual (Zoom): Arizona Public Services (APS).
• Kacira, M. (2023, December).

  Advancement of plant sensing technology for sustainable crop production under

  controlled environment. The 5th Annual Conference Controlled Environment Horticulture. Virtual (Zoom): Texas A&M University.
• Kacira, M. (2023, July). Advancement of Plant Sensing Technology for Sustainable Crop Production Under Controlled Environment. Ohio State University CEAC Conference: Advancement of Sustainable Controlled Environment Crop Production Sciences & Technologies. Columbus, Ohio: The Ohio State University.
• Kacira, M. (2023, July). Hydroponic Systems. Workshop on Hydroponics at Cultivate 2023. Columbus, Ohio: Cultivate 23, American Hort.
• Kacira, M. (2023, March). Monitoring Greenhouse Environments. 22nd UA-CEAC Annual Greenhouse Crop Production and Engineering Design Short Course. Controlled Environment Agriculture Center: The University of Arizona Controlled Environment Agriculture Center.
• Kacira, M. (2023, March). Resource use Efficient and Precision-Controlled Environment Agriculture. Cornell University Ezra Round Table Seminar Series. Virtual (Zoom): Cornell University.
• Kacira, M. (2023, November). Controlled-Environment Agriculture. Forum on Urban Agriculture and Food Security. Virtual (Zoom): The North American Network for Human Development, Gobierne de Mexico, CONAHCYT, Mexico.
• Kacira, M. (2022, June). Innovative Technologies for Small-Scale Farmers. FAO & ISHS Joint Webinar. Webinar: FAO and International Society for Horticultural Sciences.
• Kacira, M. (2022, March).

  Monitoring Your Greenhouse Environment: Simple Tools to Technology

  Trends. UA-CEAC Annual Greenhouse Crop Production and Engineering Design Short Course. Tucson, Arizona: UArizona-CEAC.
• Kacira, M. (2022, May). Optimizing air distribution in CEA. Indoor AgScience Cafe. Webinar: USDA-SCRI project OptimIA.
• Kacira, M. (2022, May). Sustaining the future with precision horticulture and engineering focusing on resource use efficiency. Annual South Korean Society for Bio-Environment Control. Webinar, Seoul, South Korea: South Korean Society for Bio-Environment Control.
• Kacira, M. (2022, September). New Technologies for Future of Agriculture. XIII Symposium on Vegetable Horticulture. Webinar, Izmir, Turkey: Turkish Horticultural Society and Egen University.
• Kacira, M. (2021, August). Speaking Plant – Modern Sensing Technologies for Controlled Environment Research and Applications.. ASHS Workshop on "Integrating Engineering Principles with Plant Biological Requirements in Controlled Environment Horticulture Research and Education". Denver, Colorado: American Society of Horticultural Sciences.
• Kacira, M. (2021, July). Resource Use Efficient CEA Systems: From Phenotyping to Sensing & Environmental Control. Bayer Crop Science Conference. Virtual: Bayer Crop Science.
• Kacira, M. (2021, June). Analysis and Enhancement of Environmental Uniformity in CEA Production System. 2021 ASHRAE Annual Conference. Virtual: American Society of heating, Refrigeration, Air Conditioning Engineers.
• Kacira, M. (2021, June). Precision and Resource Use Efficient Controlled Environment Agriculture. CALS 4-H Seminar. Virtual: UArizona CALS.
• Kacira, M. (2021, June). Sustaining the future through Controlled Environment Agriculture. KAUST and UArizona Summer Seminar Series. Virtual: King Abdullah University of Science and Technology.
• Kacira, M. (2021, June). Sustaining the future through Controlled Environment Agriculture. UArizona's Associate Deans for Research Meeting. Virtual: UArizona's Associate Deans for Research Meeting.
• Kacira, M. (2021, March). Monitoring Your Controlled Environments: Simple Tools to Technology Trends. CEAC Annual Greenhouse Crop Production and Engineering Design Short Course. Virtual: Controlled Environment Agriculture Center.
• Kacira, M. (2021, November). Plants as Sensors for Controlling Environment and Lighting in Controlled Environment Agriculture Systems. 2021 Plant Lighting Short Course. Virtual: GLASE-Greenhouse Lighting and Systems Engineering Consortium.
• Kacira, M. (2021, November). Resource use efficient and precision controlled environment agriculture. 2021 South Korean Society for Citrus and Subtropical Climate Fruits International Symposium. Virtual: 2021 South Korean Society for Citrus and Subtropical Climate Fruits.
• Kacira, M. (2021, October). Enhancing Resource Use Efficiency in Vertical Farming. Canadian Greenhouse Conference. Virtual: Canadian Greenhouse Conference.
• Kacira, M. (2021, September). Sensing and Automation in Vertical Farms: Optimizing Resource Use Efficiency. Hans Eisenmann-Forum -12. HEF Symposium on The Limits of Food Production - Vertical Farming. Virtual: Hans Eisenmann-Forum.
• Kacira, M. (2020, April). Sustainable Solutions for the Apocalypse: UA-Controlled Environment Agriculture. UA Foundation University Development Program Regional Development and Discovery Team Meeting. Virtual Meeting Presentation: UA Foundation University Development Program.
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  Presented about UA-CEAC Programs and Envisioned Directions for Research, Education and Outreach for potential funding opportunities.
• Kacira, M. (2020, December). Panel: Advancing Sustainability in CEA through Technology and Design. Agritecture Xchange-Toronto Conference. Virtual Conference: Agritecture.
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  Panel member with E. Mattos (GLASE), Corine Wilder (FluenceOsram), and Josh Hollab (Ceres Greenhosue Solutins).
• Kacira, M. (2020, February). Panel: The Future of Precision Agriculture: Can the use of data & technology continue to enhance production practices and the bottom line?. Southwest AgSummit. Arizona Western College, Yuma, Arizona.
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  Presented in this panel along with industry participants Alexey Rostapshov, John Deere Laboratories; Hank Giclas, Western Growers; Simon Belin, Naio Technologies, 200+ attendees.
• Kacira, M. (2020, February). Resource Use Efficient CEA Systems: From Phenotyping to Smart Sensing & Environmental Control. Phenom 2020 Conference. Tucson Convention Center: Plant Phenomics Network.
• Kacira, M. (2020, February). The Use Of Precision Agriculture Controlled Environments. Southwest AgSummit. Arizona Western College, Yuma, Arizona: Southwest AgSummit.
• Kacira, M. (2020, March). Controlled Environment Agriculture Programs. CALS Alumni Council Board of Directors Annual Meeting. The Property Conference Center, Casa Grande, Arizona.: CALS Alumni Council Board of Directors.
  More info

  Presented about CEAC programs and need for support for research, educational programs, facilities and opportunities.
• Kacira, M., & Shasteen, K. (2020, December). Crop Growth Monitoring and Simulation Based Resource Use Optimization. Indoor AgCafe- USDA-SCRI funded project OptimIA Outreach Webinar SeriesUSDA-SCRI funded project OptimIA Outreach Webinar Series.
• Kacira, M. (2019, January). Controlled Environment Agriculture. 2019 American Seed Trade Organization Conference. Orlando, Florida: American Seed Trade Organization Conference.
• Kacira, M. (2019, January). Environmental Uniformity and Climate Control in Plant Factory with Artificial Lighting. Plant Factory 2019: International Symposium on Smart Plant Factory. Seoul National University, South Korea: Seoul Ntional University.
• Kacira, M. (2019, March). Monitoring Your Greenhouse Environment: Simple Tools to Technology Trends. 18th CEAC Short Course. Tucson, Aizona: UA CEAC.
• Kacira, M. (2019, March). Sensors and Controls, and Food Production in Vertical Farming System. 18th CEAC Short Course. Tucson, Arizona: UA CEAC.
• Kacira, M. (2019, November). Climate Management and Control in Controlled Environment Agriculture Systems. 3rd International Congress on Controlled Environment Agriculture. Panama City, Panama..
• Kacira, M. (2019, October). Climate Control in Vertical Farming. 1. First ISHS International Workshop on Vertical Farming. Wageningen University, The Netherlands: International Society of Horticultural Sciences (ISHS).
• Kacira, M. (2019, September). Engineering Challenges and Opportunities in CEA. USDA-NIFA AzCEA Conference. UA-Biosphere 2: USDA NIFA.
• Kacira, M., Potter, K., Arnold, R. G., & Chief, K. (2019, June). Water Purification Unit Demonstration and Information. Community Outreach Event. Tsaile, AZ: Diné College Land Grant Office and University of Arizona Indige-FEWSS NRT Program.
  More info

  Chief, K., R. Arnold, K. Simmons-Potter, and M. Kacira. 2019. Water Purification Unit Demonstration and Information. Diné College Land Grant Office and University of Arizona Indige-FEWSS NRT Program Community Outreach Event, June 7, 2016, Tsaile, AZ.
• Kacira, M. (2018, August). My CEA Travelogue 2018: Learning & Sharing Recent Advances in Controlled Environment Agriculture. CEAC Covering Environments Seminar Series. Tucson, Arizona: Controlled Environment Agriculture Center.
• Kacira, M. (2018, March). Airflow and Uniformity Considerations. CEAC Annual Crop Production and Greenhouse Engineering Short Course. Tucson, Arizona: Controlled Environment Agriculture Center.
• Kacira, M. (2018, March). Monitoring Your Greenhouse Environment: Simple Tools to Technology Trends. CEAC Annual Crop Production and Greenhouse Engineering Short Course. Tucson, Arizona: Controlled Environment Agriculture Center.
• Kacira, M. (2018, November). Innovating Controlled Environment Agriculture. Ag 100. Phoenix, Arizona: University of Arizona and Ag100 Council.
• Kacira, M. (2018, October). Environmental Uniformity & Climate Control in Plant Factory with Artificial Lighting. Canadian Greenhouse Conference. Niagara Falls, Canada: Canadian Greenhouse.
• Montoya, A., Kacira, M., & Obando, F. A. (2018, August). Design and implementation of low a cost microcontroller in controlled environment agriculture. 2nd International symposium on Mechanization, Precision Horticulture, and Robotics. Istanbul, Turkey: International Society of Horticultural Sciences.
• Ying, Z., & Kacira, M. (2018, August). Optimization of HVAC systems selection for indoor plant factory. 3rd International Symposium on Innovation and New Technologies in Protected Cultivation. Istanbul, Turkey: International Society for Horticultural Sciences.
• Kacira, M. (2017, August). Climate Control and Environmental Uniformity in Plant Factories with Artificial Lighting. Greensys 2017 - International Symposium on New Technologies for Environment Control, Energy-Saving and Crop Production in Greenhouse and Plant Factory. Beijing, China: International Society of Horticultural Sciences.
• Kacira, M. (2017, November). Innovations and Emerging Trends in Controlled Environment Agriculture. The Future of Arizona Agriculture 10 Years and Beyond. The University of Arizona: The University of Arizona, Global Initiative for Strategic Agriculture in Drylands (GISAD).
• Kacira, M. (2017, October). Resource use efficient controlled environment agriculture systems. University of Missouri, Division of Plant Sciences Seminar Series. Columbia, Missouri: University of Missouri, Division of Plant Sciences Seminar Series.
• Kacira, M. (2016, December). What if we gro food vertically. Biospgere 2 "What If" Technical Seminar Series. Biosphere 2, Tucson, AZ: Biosphere 2.
• Kacira, M. (2016, July). Greenhouse Environmental Control. XI International Tomato Congress.. San Luis Potosi, Mexico.: Meister Media.
• Kacira, M. (2016, June). Sensors and Controls in Controlled Environment Agriculture Systems. UA-COE Summer Engineering Academy. UA-CEAC, Tucson: UA Colege of Engineering.
• Kacira, M. (2016, March). Greenhouse Structures and Design. UA-CEAC Greenhouse Crop Production and Engineering Shortcourse. Tucson, AZ: The University of Arizona.
• Kacira, M. (2016, March). Sensors and Controls in CEAC systems. UA-CEAC Annual Greenhouse Engineering and Crop Production Shortcourse, Hands-On Workshop. UA-CEAC, Tucson: The University of Arizona.
• Kacira, M. (2015, April). Alternative energy applications in Controlled Environment Agriculture Plant Production Systems. 2015 Annual UA-CEAC Greenhouse Crop Production and Engineering Short Course. Tucson, Arizona: The University of Arizona.
• Kacira, M. (2015, April). Engineering CEA systems for a sustainable future. 2015 High-level International Forum on Protected Horticulture. Shouguang, China: Chinese Academy of Agricultural Sciences.
• Kacira, M. (2015, June). Advances and challenges in CFD applications for optimizing CEA systems. GreenSys2015 - International Symposium on New Technologies and Management for Greenhouses. Evora, Portugal: International Society of Horticultural Science.
• Zhang, Y., & Kacira, M. (2015, July). Improvement of aerodynamics in an indoor plant factory. GreenSys2015 - International Symposium on New Technologies and Management for Greenhouses. Evora, Portugal: International Society of Horticultural Science.
• Giacomelli, G., Furfaro, R., Kacira, M., Patterson, L., & Sadler, P. (2014, August). Plant Production, Solar Energy Balance and Monitoring, Control, Telepresence in a Recirculating Hydroponic Vegetable Crop Production System. The 29th International Horticultural Congress (IHC 2014). Brisbane, Australia: International Society of Horticultural Sciences.
• Kacira, M. (2014, April). Greenhouse environmental control. Greenhouse Crop Production and Engineering Design Short Course. Tucson, AZ: CALS. ABE, UA-CEAC.
• Kacira, M. (2014, April). Greenhouse structures and design. Greenhouse Crop Production and Engineering Design Short Course. Tucson, AZ: CALS, ABE, UA-CEAC.
• Kacira, M. (2014, April). Plants as sensors for autonomous crop diagnostics. Washington State University Seminars. Pulman, WA: Washington State University.
• Kacira, M. (2014, April). Sensor and control basics: Data acquisition and instrumentation in controlled environment agriculture. Greenhouse Crop Production and Engineering Design Short Course. Tucson, AZ: CALS, ABE, UA-CEAC.
• Kacira, M. (2014, July). Energy Flows for the Indoor Environment. Realities of Growing Plants Indoors Short Course. Tucson, AZ: CALS, ABE, UA-CEAC.
• Kacira, M. (2014, July). Providing the Environment for the Plants.. Realities of Growing Plants Indoors Short Course. Tucson, AZ: CALS, ABE, UA-CEAC.
• Kacira, M. (2014, June). Engineering CEA systems for sustainable future. Chinese Academy of Agricultural Sciences Seminars. Beijing, China: Chinese Academy of Agricultural Sciences.
• Kacira, M. (2014, June). Engineering CEA systems for sustainable future. Shangdong Agricultural University Seminars. Shangdong Agricultural University, Tai an, China: Chinese Academy of Agricultural Sciences.
• Kacira, M. (2014, June). Scientific Writing. Chinese Academy of Agricultural Sciences Seminars. Beijing, China: Chinese Academy of Agricultural Sciences.
• Whalen, M., Kubota, C., Kacira, M., Hall, C., Li, W., & Meyer, P. (2014, July). Lettuce Growth and Morphology in a Red-rich low PAR Light Environment in a Greenhouse. 2014 ASHS International Conference. Orlando, Florida: American Society of Horticultural Science (ASHS).
• Kacira, M. -. (2013, April). Greenhouse Structures and Design (Lecture). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. -. (2013, April). Sensors and Controls (Lecture and Hands-on Session). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. (2012). Engineering CEA Systems for a Sustainable Future: Status, Challenges, and Opportunities. The Japan-America Frontiers of Engineering (JAFOE) Conference. Irvine, CA: (JAFOE).
• Kacira, M. (2012, April). Greenhouse Environmental Control. Greenhouse Crop Production and Engineering ZDesign Short Course.. Tucson, Arizona.
• Kacira, M. (2012, April). Greenhouse Structures and Design. Greenhouse Crop Production and Engineering Short Course. Tucson, Arizona.
• Kacira, M. (2012, April). Sensor and Control Basics: Data Acquisition and Instrumentation in Controlled Environment Agriculture. Greenhouse Crop Production and Engineering Design Short Course. Tucson, Arizona.
• Kacira, M. (2012, February). Advanced Monitoring and Control of Greenhouse System for Optimized Resource Use Efficiency. Agronomy Week Conference. San Luis Potosi, Mexico.: Faculty of Agronomy, University of San Luis Potosi.
• Kacira, M. -. (2012, April). Greenhouse Climate Control (Lecture). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. -. (2012, April). Greenhouse Structures and Design (Lecture). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. -. (2012, April). Sensors and Controls (Lecture and Hands-on Session). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. (2011). Greenhouse Production in US: Status, Challenges, and Opportunities. CIGR International Conference on "Sustainable Bioproduction - Water, Energy, and Food. Tokyo, Japan: CIGR.
• Kacira, M. (2011). Resource Use Efficient Greenhouse Production in Semiarid Climate. CIGR International Conference on "Sustainable Bioproduction - Water, Energy, and Food. Tokyo, Japan: CIGR.
• Kacira, M. -. (2011, April). Greenhouse Climate Control (Lecture). UA-CEAC Greenhouse Engineering and Crop Production Short Course.
• Kacira, M. -. (2011, April). Greenhouse Environmental Control. Greenhouse Crop Production and Engineering ZDesign Short Course. Tucson, Arizona.
• Kacira, M. -. (2011, April). Greenhouse Structures and Design (Lecture). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. -. (2011, April). Greenhouse Structures and Design. Greenhouse Structures and Design. Greenhouse Crop Production and Engineering Short Course. Tucson, Arizona.
• Kacira, M. -. (2011, April). Sensor and Control Basics: Data Acquisition and Instrumentation in Controlled Environment Agriculture. Greenhouse Crop Production and Engineering Design Short Course. Tucson, Arizona.
• Kacira, M. -. (2011, April). Sensors and Controls (Lecture and Hands-on Session). UA-CEAC Greenhouse Engineering and Crop Production Short Course. Tucson, AZ: UA-CEAC.
• Kacira, M. -. (2011, September). Plant factory production systems in the United States. CIGR International Conference on "Sustainable Bioproduction - Water, Energy, and Food. (Invited Speaker). Tokyo, apan: CIGR.
• Kacira, M. -. (2011, September). Resource use efficient greenhouse production in semiarid climate.. Chinese and Japanese Society Concurrent Meeting, CIGR International Conference on "Sustainable Bioproduction - Water, Energy, and Food. (Invited Speaker). Tokyo, apan: CIGR.
• Linker, R., Kacira, M. -., & Arbel, A. (2011, July). Robust climate control of a greenhouse equipped with forced ventilation.. ASABE Annaual International Meeting. Reno, Nevada: ASABE.

Poster Presentations

• Jia, F., Kacira, M., Ogden, G., Ogden, K., & Brown, J. (2017, March 22). Autonomous and timely detection of suboptimal microalgal growth in controlled environments and open pond based systems. CALS Poster ForumUA-CALS.
• Zhang, Y., & Kacira, M. (2017, March). Computational and experimental studies for improved climate uniformity in greenhouses and vertical farm systems. CALS Poster Forum. Tucson: UA-CALS.
• Jia, F., Kacira, M., & Ogden, K. (2015, June). Multi-wavelength laser diodes based real time optical sensor for microalgae production application. 5th International Conference on Algal Biomass, Biofuels and Bioproducts. San Diego, CA, USA.

Creative Productions

• Giacomelli, G., Kacira, M., Furfaro, R., Sheehy, C., Sadler, P., Giacomelli, G., Kacira, M., Furfaro, R., Sheehy, C., & Sadler, P. (2014. "EARTHLIGHT" Documentary. Tucson Loft Theater viewing; DVD format released; online at CALS website. University of Arizona: College of Agriculture and Life Sciences. http://cals.arizona.edu/earthlight/
  More info

  Earthlight documentary released in July 2014 to bring awareness about the need for sustainable food systems on earth and the possibility of creating such systems in the future on our moon or other planets.This documentary was awarded an Emmy in October, 2015. See Cody Sheehy accepting the award here: https://twitter.com/EarthlightDoc/status/657621949137448960/photo/1

Others

• Kacira, M. -. (2013, Jan). Choose The Right Greenhouse Style,. Greenhouse Growers Magazine.
• Story, D., Giacomelli, G., & Kacira, M. -. (2013, Fall). NASA Steckler Grant Project: Lunar Greenhouse Prototype Project website. Under UA website. http://ag.arizona.edu/lunargreenhouse
• Story, D., Kacira, M. -., & Giacomelli, G. (2013, April). Lunar Greenhouse Project Website.
• Both, A. J., Hansen, R., & Kacira, M. -. (2012, May). Hydroponics Give Growers Control.. Greenhouse Grower Magazine. http://www.greenhousegrower.com/article/27924/hydroponics-give-growers-control?browserPass=1
• Giacomelli, G., Kubota, C., Kacira, M., & Rorabaugh, P. (2012, Fall). No Ordinary Tomorrows. SciTechReports. http://www.youtube.com/watch?v=V02-msDXat
• Kacira, M. (2012, Fall). Foresight and Integrating Vision Systems. SciTechReports. http://www.youtube.com/watch?v=YKAbyKIr99Q