Publications

Smart Irrigation Publications – Popular Press

• In a Flash –  Irrigation Today
• Irrigator Pro Update – Southeast Peanut Farmer (pg. 11)
• Irrigation is Next Frontier in Precision Agriculture – Southeast Farm Press
• Can Soil Sensors Save Georgia Waterways from Drought? – Scientific American
• Crop Data Gives Drought-Stricken Farmers a Leg Up on Getting by With Less – The Guardian
• Sensing Soil to Improve Watering – Georgia Public Broadcasting
• New Technology Reduces Agricultural Water Consumption – Forbes
• Irrigation Scheduling Tools Seen as a Key to Conserving Water in Southwest Georgia – Southeast Farm Press
• Computer-linked Soil Moisture Sensors Living Up to Their Promise – Southeast Farm Press
• Cotton Irrigation App Helps Manage Water Usage – Southeast Farm Press

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Smart Irrigation Publications – Research

• Kukal, M. S., Kukal, S., Irmak, S., & Vellidis, G. (2023.). Drivers of enhanced evaporative demand in U.S. croplands: Determining relative contribution using constrained input scenarios. JAWRA Journal of the American Water Resources Association.
• Bondesan, L., B.V. Ortiz, F. Morlin, G. Morata, L. van Santen, B. Lena, G. Vellidis. 2023. A comparison of precision and conventional irrigation in corn production in Southeast Alabama. Precision Agriculture 24, 40–67.
• Lacerda, L. N., J. Bo, Y. Cohen, V. Liakos, M. Levi, G. Vellidis. 2022. Correlation of UAV and satellite-derived vegetation indices with cotton physiological parameters and their use as a tool for scheduling variable rate irrigation in cotton. Precision Agriculture 23:2089–2114.
• Lacerda, L. N., Snider, J. L., Cohen, Y., Liakos, V., Gobbo, S., Vellidis, G. 2021. Using UAV-based thermal imagery to detect crop water status variability in cotton. Smart Agricultural Technology, 100029.
• Ermanis, A., S. Gobbo, J.L. Snider, Y. Cohen, V. Liakos, L. Lacerda, C.D. Perry, M.A. Bruce, G. Vellidis. 2020. Defining physiological contributions to yield loss in response to irrigation in cotton. Journal of Agronomy and Crop Science 207(2):186-196.
• Zurweller B, D. Rowland, M. Mulvaney, B. Tillman, K. Migliaccio, D. Wright, J. Erickson, P. Payton, G. Vellidis. 2019. Optimizing cotton irrigation and nitrogen management using a soil water balance model and in-season nitrogen applications. Agricultural Water Management 216:306-314.
• Miller, L., G. Vellidis, Mohawesh, O, Coolong, T. 2018. Comparing a smartphone irrigation scheduling application with water balance and soil moisture-based irrigation methods: Part I—Plasticulture-grown tomato. HortTechnology 28(3):354-361.
• Miller, L., G. Vellidis, Coolong, T. 2018. Comparing a smartphone irrigation scheduling application with water balance and soil moisture-based irrigation methods: Part II—Plasticulture-grown watermelon. HortTechnology 28(3):362-369.
• Liakos V, Porter W, Liang X, Tucker MA, McLendon A, Vellidis G. 2017. Dynamic variable rate irrigation – a tool for greatly improving water use efficiency. Advances in Animal Biosciences 8(02):557-563. http://dx.doi.org/10.1017/S2040470017000711.  
• Bondesan, L., F. Morari, G.T. Morata, G. Vellidis, B.V. Ortiz, A.F. Jimenez. 2019. Evaluating and improving soil sensor-based variable rate irrigation scheduling on farmers’ fields in Alabama. In: J.V. Stafford (Ed.), Precision Agriculture ’19 – Papers Presented the 12th European Conference on Precision Agriculture (12ECPA), Montpellier, France, Wageningen Academic Publishers, p649-656. (Peer Reviewed)
• Zancanaro, E., G. Vellidis, F. Morari, A. Gertsis, F. Marinello. 2019. Developing crop canopy model for irrigation of high density olive groves by using UAV imagery. In: J.V. Stafford (Ed.), Precision Agriculture ’19 – Papers Presented the 12th European Conference on Precision Agriculture (12ECPA), Montpellier, France, Wageningen Academic Publishers, p421-427. (Peer Reviewed)
• Liakos, V., G. Vellidis, M. Tucker, and C. Cox. 2018. The First Application of Dynamic Variable Rate Irrigation to Cotton in Georgia: A Case Study. In S. Boyd, M. Huffman and B. Robertson (eds) Proceedings of the 2018 Beltwide Cotton Conferences, San Antonio, January 3-5, 2018, National Cotton Council, Memphis, TN, paper 16778, p.395-403.
• Vellidis, G., V. Liakos, W. Porter, M. Tucker, X. Liang. 2016. A Dynamic Variable Rate Irrigation Control System. In Proceedings of the 13th International Conference on Precision Agriculture. Monticello, IL: International Society of Precision Agriculture.
• Vellidis, G., V. Liakos, J.H. Andreis, C.D. Perry, W.M. Porter, E.M. Barnes, K.T. Morgan, C. Fraisse, K.W. Migliaccio. 2016. Development and Assessment of a Smartphone Application for Irrigation Scheduling in Cotton. Computers and Electronics in Agriculture 127:249–259, http://dx.doi.org/10.1016/j.compag.2016.06.021.
• Vellidis, G., Liakos, V., C. Perry, W. Porter, and M. Tucker. 2016. Irrigation Scheduling for Cotton Using Soil Moisture Sensors, Smartphone Apps and Traditional Methods. In S. Boyd, M. Huffman and B. Robertson (eds) Proceedings of the 2016 Beltwide Cotton Conference, New Orleans, LA, National Cotton Council, Memphis, TN, paper 16779, p.772-780.
• Liang, X., V. Liakos, O. Wendroth, and G. Vellidis. 2016. Scheduling Irrigation using an Approach Based on the van Genuchten Model. Agricultural Water Management 176:170–179, http://dx.doi.org/10.1016/j.agwat.2016.05.030.
• Migliaccio, K.W., K.T. Morgan, C. Fraisse, G. Vellidis, L. Zotarelli, C. Fraisse, B. A. Zurweller, J. H. Andreis, J. H. Crane, and D. Rowland. 2015. Smartphone Apps for Irrigation Scheduling. Trans of the ASABE. 59(1):291-301, http://dx.doi.org/10.13031/trans.59.11158.
• Liakos, V., G. Vellidis, M. Tucker, C. Lowrance, X. Liang. 2015. A Decision Support Tool for Managing Precision Irrigation with Center Pivots. In: J.V. Stafford (Ed.), Precision Agriculture ’15 – Papers Presented the 10th European Conference on Precision Agriculture (10ECPA), Tel Aviv, Israel, p677-683, http://dx.doi.org/10.3920/978-90-8686-814-8.
• Vellidis, G., V. Liakos, M. Tucker, C. Perry, J. Andreis, C. Fraisse, K. Migliaccio. 2015. A Smartphone App for Precision Irrigation Scheduling in Cotton. In: J.V. Stafford (Ed.), Precision Agriculture ’15 – Papers Presented the 10th European Conference on Precision Agriculture (10ECPA), Tel Aviv, Israel, p701-708, http://dx.doi.org/10.3920/978-90-8686-814-8.
• Migliaccio, K.W., K.T. Morgan, C. Fraisse, G. Vellidis, and J.H. Andreis. 2015. Performance Evaluation of Urban Turf Irrigation Smartphone App. Computers and Electronics in Agriculture 118:136–142, http://dx.doi.org/10.1016/j.compag.2015.08.015.
• Vellidis, G., Tucker, M., Perry, C., Reckford, D, Butts, C., Henry, H., Liakos, V., Hill, R.W., and Edwards, W. 2013. A Soil Moisture Sensor-Based Variable Rate Irrigation Scheduling System. In: J.V. Stafford (Ed.), Precision Agriculture 2013 – Proceedings of the 9th European Conference on Precision Agriculture (9ECPA), Lleida, Spain, p.713-720. http://dx.doi.org/10.3920/978-90-8686-778-3.

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Precision Agriculture Publications – Popular Press

• Farming by the Numbers – from Georgia Trend
• Auto-steer Driving Peanut Grower Profits – from the Southeast Farm Press website
• Yield Maps Considered Entrance and Final Exam for Precision Agriculture – from the Southeast Farm Press website
• Cotton Yield Maps: Tools for Increasing Efficiency and Profitability – Cotton Incorporated and Plant Management Network ‘Focus on Cotton’ webcast.

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Precision Agriculture Publications – Research

• Hatum de Almeida, S.L, J.B. Costa Souza, C. Pilon, A.H. de Castro Teixeira, A.F. dos Santos, M.N. Sysskind, G. Vellidis, R.P. da Silva. 2023. Performance of the SAFER model in estimating peanut maturation. European Journal of Agronomy 147 (10p), 126844.
• Bondesan, L., B.V. Ortiz, F. Morlin, G. Morata, L. van Santen, B. Lena, G. Vellidis. 2023. A comparison of precision and conventional irrigation in corn production in Southeast Alabama. Precision Agriculture 24, 40–67, .
• Lacerda, L. N., J. Bo, Y. Cohen, V. Liakos, M. Levi, G. Vellidis. 2022. Correlation of UAV and satellite-derived vegetation indices with cotton physiological parameters and their use as a tool for scheduling variable rate irrigation in cotton. Precision Agriculture 23:2089–2114.
• Santos A.F., Lacerda L.N., Rossi C., Moreno L.d.A., Oliveira M.F., Pilon C., Silva R.P., Vellidis G. 2022. Using UAV and multispectral images to estimate peanut maturity variability on irrigated and rainfed fields applying linear models and artificial neural networks. Remote Sensing 14(1):93.
• Lacerda, L. N., Snider, J. L., Cohen, Y., Liakos, V., Gobbo, S., Vellidis, G. 2021. Using UAV-based thermal imagery to detect crop water status variability in cotton. Smart Agricultural Technology, 100029.
• Lacerda, L., Y. Cohen, J. Snider, H. Huryna, V. Liakos, G. Vellidis. 2021. Field scale assessment of the TsHARP technique for thermal sharpening of MODIS satellite images using VENµS and Sentinel-2 Derived NDVI. Remote Sensing 13(6), 1155-1180.
• dos Santos, A.F., L.N. Corrêa, L.N. Lacerda, D. Tedesco-Oliveira, C. Pilon, G. Vellidis, R.P. da Silva. 2021. High-resolution satellite image to predict peanut maturity variability in commercial fields. Precision Agriculture 22(5), 1464–1478,
• dos Santos, A., R. Da Silva, S. Gobbo, L. Lacerda, A. Toffanin, G. Vellidis. 2019. Using remote sensing to map in-field variability of peanut maturity. In: J.V. Stafford (Ed.), Precision Agriculture ’19 – Papers Presented the 12th European Conference on Precision Agriculture (12ECPA), Montpellier, France, Wageningen Academic Publishers, p605-611, (Peer Reviewed).
• Liakos, V., W. Porter, J. Kilcher, A. Sawyer, A. D. Pavlou, Orfanou, G. Vellidis. 2019. A model for precision irrigation scheduling of soybeans for the southeastern U.S. In: J.V. Stafford (Ed.), Precision Agriculture ’19 – Papers Presented the 12th European Conference on Precision Agriculture (12ECPA), Montpellier, France, Wageningen Academic Publishers, p943-950. (Peer Reviewed)
• Marinello, F., B. Stenberg, D.S. Paraforos, S. Fountas, B. Tisseyre, C.G. Sorensen, J.A. Martinez-Cassanovas, S.G. Vougioukas, Y. Cohen, K. Sudduth, L. Sartori, M. Karkee, G. Vellidis. 2019. Agriculture and digital sustainability: A digitization footprint. In: J.V. Stafford (Ed.), Precision Agriculture ’19 – Papers Presented the 12th European Conference on Precision Agriculture (12ECPA), Montpellier, France, Wageningen Academic Publishers, p83-89, . (Peer Reviewed)
• Aru, F. G. Vellidis, A. Gertsis, F. Morari. 2019. Investigation of spraying efficiency of an aerial spraying system in a super-high density olive grove in Greece. In: J.V. Stafford (Ed.), Precision Agriculture ’19 – Papers Presented the 12th European Conference on Precision Agriculture (12ECPA), Montpellier, France, Wageningen Academic Publishers, p357-363, . (Peer Reviewed)
• Bevington, J., E. Scudiero, G. Vellidis, P. Teatini, F. Morari. 2018. Factorial kriging analysis leverages soil physical properties and exhaustive data to predict distinguished zones of hydraulic properties. Computers and Electronics in Agriculture 156:426-438.
• Vellidis G, Morari F, Battisti A, Berti A, Borin M, Broder J, Cabrera M, Cattarinussi R, Franklin D, McMaken V et al. 2017. From a precision agriculture consortium to a dual master’s degree in sustainable agriculture. Advances in Animal Biosciences 8(02):738-742. . 
• Liakos V, Porter W, Liang X, Tucker MA, McLendon A, Vellidis G. 2017. Dynamic variable rate irrigation – a tool for greatly improving water use efficiency. Advances in Animal Biosciences 8(02):557-563. .  
• Porter E, Vellidis G, Liakos V, Porter W, Branch B. 2017. An optical yield monitor for peanuts – Proof of concept and evaluation. Advances in Animal Biosciences 8(02):199-203. .
• Lowrance, C., S. Fountas, V. Liakos, and G. Vellidis. 2016. EZZone – An Online Tool for Delineating Management Zones . In Proceedings of the 13th International Conference on Precision Agriculture July 31 – August 3, 2016, St. Louis, Missouri, USA., International Society of Precision Agriculture, Monticello, IL.
• Lowrance, C., S. Fountas, V. Liakos, and G. Vellidis. 2016. EZZone – An Online Tool for Delineating Management Zones. In Proceedings of the 13th International Conference on Precision Agriculture. Monticello, IL: International Society of Precision Agriculture.
• Bevington, J., D. Piragnolo, P. Teatini, G. Vellidis, F. Morari. 2015. On the spatial variability of soil hydraulic properties in a Holocene coastal farmland. Geoderma 262:294–305 http://dx.doi.org/10.1016/j.geoderma.2015.08.025.
• Vellidis, G., B. Ortiz, J. Beasley, R. Hill, H. Henry, and H. Brannen. 2014. Reducing digging losses by using automated steering to plant and invert peanuts. Agronomy 4(3):337-348; http://dx.doi.org/10.3390/agronomy4030337.
• Davis, R.F, S.K. Aryal, C.D. Perry, D.G. Sullivan, P. Timper, B.V. Ortiz, K.L. Stevenson, G. Vellidis, G. Hawkins. 2013. Utilizing management zones for Rotylenchulus reniformis in cotton: Effects on nematode levels, crop damage, and Pasteuria sp. Crop Protection 50 (2013) 53-60.
• Ortiz, B.V., Perry, C., D. Sullivan, Lu, P., Kemerait, R., Davis, R.F., Smith, A., G. Vellidis, R. Nichols. 2012. Variable Rate Application of Nematicides on Cotton Fields: A Promising Site-Specific Management Strategy. Journal of Nematology 44(1):31–39.
• Ortiz, B.V., D. Sullivan, C. Perry, and G. Vellidis. 2011. Delineation of management zones for southern root-knot nematode using fuzzy clustering of terrain and edaphic field characteristics, Communications in Soil Science and Plant Analysis, 42(16):1972-1994.
• Ortiz, B.V., C. Perry, G. Vellidis, D. Sullivan, and P. Goovaerts. 2010. Geostatistical modeling of the spatial variability and risk areas of southern root-knot nematodes in relation to soil properties. Geoderma 156(3-4):243-252, http://dx.doi.org/10.1016/j.geoderma.2010.02.024.
• Vellidis, G., M. Tucker, C. Perry, C. Kvien, and C. Bednarz. 2008. A real-time wireless smart sensor array for scheduling irrigation. Computers and Electronics in Agriculture 61(1):44-50.
• Ortiz, B.V., G. Hoogenboom, G. Vellidis, K. Boote, R.F. Davis, C. Perry. 2009. Adapting the CROPGRO-cotton model to simulate cotton biomass and yield under southern root-knot nematode parasitism. Transactions of ASABE 52(6):2129-2140.
• Vellidis, G., M.A. Tucker, C.D. Perry, T. Wells, and C. Kvien. 2004. Predictive cotton lint yield maps from aerial photographs. Precision Agriculture 5(6):547–564.
• Vellidis, G., C.D. Perry, G. Rains, D.L. Thomas, N. Wells, C.K. Kvien. 2003. Simultaneous assessment of cotton yield monitors. Applied Engineering in Agriculture 19(3):259-272.
• Vellidis, G., C.D. Perry, J.S. Durrence, D.L. Thomas, R.W. Hill, C.K. Kvien, T.K. Hamrita, and G.C. Rains. 2001. The peanut yield monitoring system. Transactions of the ASAE 44(4):775-785.

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Other Topics – Popular Press

• In a Flash –  Irrigation Today

Other Topics – Research

• Lawson, B., Snider, J. L., Hand, L. C., Porter, W., Vellidis, G., Lee, J. M., Chalise, D. P., Parkash, V., Pokhrel, A., & Kaur, N. 2023. Effect of irrigation termination times on cotton cultivars with contrasting maturities. Agronomy Journal, 115, 2950–2963.
• Pokhrel, A., J.L. Snider, S. Virk, H.Y. Sintim, L.C. Hand, G. Vellidis, V. Parkash, D.P. Chalise, J.M. Lee. 2023. Quantifying physiological contributions to nitrogen-induced yield variation in field-grown cotton. Field Crops Research 299 , 9pp, .
• Chalise, D.P., J.L. Snider, L.C. Hand, P. Roberts, G. Vellidis, A. Ermanis, G.D. Collins, L.N. Lacerda, Y. Cohen, A. Pokhrel, V. Parkesh, J.M. Lee. 2022. Cultivar, irrigation management, and mepiquat chloride strategy: Effects on cotton growth, maturity, yield, and fiber quality. Field Crops Research 286, 108633, .
• Liang, X., G. Hoogenboom, S. Voulgaraki, K.J. Boote, G. Vellidis. 2021. Deriving genetic coefficients from variety trials to determine sorghum hybrid performance using the CSM-CERES-Sorghum model. Agronomy Journal 113(3):2591-2606.  
• Ermanis, A., S. Gobbo, J.L. Snider, Y. Cohen, V. Liakos, L. Lacerda, C.D. Perry, M.A. Bruce, G. Vellidis. 2020. Defining physiological contributions to yield loss in response to irrigation in cotton. Journal of Agronomy and Crop Science 207(2):186-196.
• Debbie, L., M. Tertuliano, C. Harris, G. Vellidis, K. Levy, T. Coolong. 2019. Salmonella survival in soil and transfer onto produce via splash events. Journal of Food Protection 82(12):2023-2037.
• Lee, D., M. Tertuliano, G. Vellidis, C. Harris. M.K. Grossman, S. Rajeev, K. Levy. 2018. Evaluation of grower-friendly, science-based sampling approaches for the detection of Salmonella in ponds used for irrigation of fresh produce. Foodborne Pathogens and Disease, Published Online: 01 Oct 2018,
• Harris, C., Tertuliano, M., Rajeev, S., Vellidis, G. and Levy, K. 2018. Impact of storm runoff on Salmonella and Escherichia coli prevalence in irrigation ponds of fresh produce farms in southern Georgia. J Appl Microbiol, 124: 910-921. .
• Bao, Y., G. Hoogenboom, R.W. McClendon, G. Vellidis. 2017. A comparison of the performance of the CSM-CERES-MAIZE and EPIC models using maize variety trial data. Agricultural Systems 150:109–119.

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