10/02/2024

California

• Villacrés, Vougioukas, S. G. (2024). Assessing a Multi-Camera System for Enhanced Fruit Visibility. Computers and Electronics in Agriculture - Special Issue on " AI-driven Agriculture". 224, 109164.


• Fu, K., Vougioukas, S. G., Bailey, B. (2024). Computer-aided design and optimization of a shake-catch fruit catching and retrieval soft fruit harvester. Computers and Electronics in Agriculture. Computers and Electronics in Agriculture, 225, 109334.


• Rui, Z. Zhang, M. Zhang, A. Azizi, C. Igathinathane, H. Cen, S. Vougioukas, H. Li, J. Zhang, Y. Jiang, X. Jiao, M. Wang, Y. Ampatzidis, O.I. Oladele, M. Ghasemi-Varnamkhasti, Radi Radi. (2024) High-throughput proximal ground crop phenotyping systems – A comprehensive review. Computers and Electronics in Agriculture, 224, 109108.


• Peng, C., Wei, P., Fei, Z., Zhu, Y. & Vougioukas, S.G. (2024) Optimization-based motion planning for autonomous agricultural vehicles turning in constrained headlands. Journal of Field Robotics, 1–25.


• Fei, Z., & Vougioukas, S. G. (2024). A robotic orchard platform increases harvest throughput by controlling worker vertical positioning and platform speed. Computers and Electronics in Agriculture, 218, 108735.


• van Henten, E., Montenegro, C., Popovic, M., Vougioukas, S. G., Daniel, A., & Han, G. (2023). Embracing Robotics and Intelligent Machine Systems for Smart Agricultural Applications [From the Guest Editors]. IEEE Robotics & Automation Magazine, 30(4), 8-112.


• Arikapudi R., Vougioukas, S.G. (2023). Robotic Tree-fruit Harvesting with Arrays of Cartesian Arms: A Study of Fruit Pick Cycle Times. Computers and Electronics in Agriculture (211), 108023.


• Araujo, G. D. M., Kouhanestani, F. K., & Fathallah, F. A. (2023). Ability of youth operators to reach agricultural all-terrain vehicles controls. Journal of safety research, 84, 353-363.


• Khorsandi, F., De Moura Araujo, G., & Fathallah, F. (2023). A systematic review of youth and all-terrain vehicles safety in agriculture. Journal of agromedicine, 28(2), 254-276.


• De Moura Araujo, G., Khorsandi Kouhanestani, F., & Fathallah, F. (2023). Forces required to operate controls on agricultural all-terrain vehicles: implications for youth. Ergonomics, 66(9), 1280-1294.


• Gibbs, J., Sheridan, C., Khorsandi, F., & Yoder, A. M. (2023). Emphasizing safe engineering design features of quad bikes in agricultural safety programs.121-127


• Sorensen, J. A., Milkovich, P. J., Khorsandi, F., Gorucu, S., Weichelt, B. P., Scott, E., & Johnson, A. (2024). Tractors, Trees, and Rollover Protective Structures: A Cause for Concern. Journal of Agromedicine, 29(2), 162-167.


• Araujo, G. D. M., Khorsandi, F., & Fathallah, F. A. (2024). Limitations in the field of vision of young operators of utility all-terrain vehicles. Journal of safety research, 88, 303-312.


• dos Santos, F. F. L., & Khorsandi, F. (2024). Riding into Danger: Predictive Modeling for ATV-Related Injuries and Seasonal Patterns. Forecasting, 6(2), 1-13.


• Khorsandi, F., Araujo, G. D. M., & dos Santos, F. F. L. (2024). AgroGuardian: An All-Terrain Vehicle Crash Detection and Notification System. Journal of Agricultural Safety and Health, 0. (In-press)


• Khorsandi, F., Araujo, G. D. M., & dos Santos, F. F. L. (2024). Artificial Intelligence-Driven All-Terrain Vehicle Crash Prediction and Prevention System. Journal of Agricultural Safety and Health, 0. (In-press)


• Khan, F. A., Khorsandi, F., Ali, M., Ghafoor, A., Raza Khan, R. A., Umair, M., ... & Hussain, Z. (2024). Spray drift reduction management in agriculture: A review. Progress in Agricultural Engineering Sciences. (In-press)


• Peanusaha, S., Pourreza, A., Kamiya, Y., Fidelibus, M., W., & Chakraborty, M. (2024). Nitrogen retrieval in grapevine (Vitis vinifera L.) leaves by hyperspectral sensing. Remote Sensing of Environment, 302, 113966.


• Farajpoor, P., Pourreza, A., & Fidelibus, M. W. (2024). Advancing Grapevine Nutrient Sensing through a CNN-Based Multi-Trait Analytical Approach. Presented at the 2024 ASABE Annual International Meeting.


• H Kamangir, BS Sams, N Dokoozlian, L Sanchez, JM Earles (2024). Large-scale spatio-temporal yield estimation via deep learning using satellite and management data fusion in vineyards. Computers and Electronics in Agriculture 216, 108439


• Ahmadi A., Kazemi M.H., Daccache A, Snyder R.(2024). SolarET: A generalizable machine learning approach to estimate reference evapotranspiration from solar radiation, Agricultural Water Management, Volume 295, 108779, ISSN 0378-3774.


• Arman Ahmadi, Andre Daccache, Mojtaba Sadegh, Richard L. Snyder (2023). Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency. Computers and Electronics in Agriculture, Volume 215, 108424.


• Anokye-Bempah, L., Styczynski, T., Teixeira Fernandes, N.A., Gervay-Hague, J., K., Ristenpart, W., & Donis-González, I.R. 2024. How Roast Profile Affects the Dynamics of Titratable Acidity during Coffee Roasting. Scientific Reports 14:8237. Doi: https://doi.org/10.1038/s41598-024-57256-y.

Florida

• Kim, D.W., S.J. Jeong, W.S. Lee, H. Yun, Y.S., Chung, Y.-S. Kwon, and H.-J. Kim. 2023. Growth monitoring of field-grown onion and garlic by CIE L*a*b* color space and region-based crop segmentation of UAV RGB images. Precision Agric 24, 1982–2001. https://doi.org/10.1007/s11119-023-10026-8.


• Zhou, C., W. S. Lee, O. E. Liburd, I. Aygun, X. Zhou, A. Pourreza, J. K. Schueller, Y. Ampatzidis. 2023. Detecting two-spotted spider mites and predatory mites in strawberry using deep learning. Smart Agricultural Technology, Volume 4, 100229. https://doi.org/10.1016/j.atech.2023.100229.


• Kondaparthi AK, Lee WS, Peres NA. Utilizing High-Resolution Imaging and Artificial Intelligence for Accurate Leaf Wetness Detection for the Strawberry Advisory System (SAS). Sensors. 2024; 24(15):4836. https://doi.org/10.3390/s24154836.


• Congliang Zhou, Won Suk Lee, Shuhao Zhang, Oscar E. Liburd, Alireza Pourreza, John K. Schueller, Yiannis Ampatzidis. A smartphone application for site-specific pest management based on deep learning and spatial interpolation. Computers and Electronics in Agriculture, Volume 218, 2024, 108726, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2024.108726.


• imaging robot and deep learning. In the Proceedings of the 14th European Conference on Precision Agriculture (ECPA), July 2-6, 2023, Bologna, Italy.


• Lee, W. S. 2023. Strawberry plant wetness detection using color imaging and artificial intelligence for the Strawberry Advisory System (SAS). 2023 Annual Strawberry AgriTech Conference, Plant City, FL, May 17, 2023.


• Zhou, X., Y. Ampatzidis, W. S. Lee, S. Agehara, and J. K. Schueller. 2023. AI-based inspection system for mechanical strawberry harvesters. AI in Agriculture: Innovation and discovery to equitably meet producer needs and perceptions Conference, Orlando, FL, April 17-19, 2023.


• Zhou, C., W. S. Lee, W. Kratochvil, J. K. Schueller, and A. Pourreza. 2023. A portable imaging device for twospotted spider mite detection in strawberry. ASABE Annual Meeting, Omaha, NE, July 9-12, 2023.


• Zhou, C., W. S. Lee, N. Peres, B. S. Kim, J. H. Kim, and H. C. Moon. 2023. Strawberry flower and fruit detection based on an autonomous imaging robot and deep learning. 14th European Conference on Precision Agriculture, Bologna, Italy, July 2-6, 2023.


• Lee, W. S., T. Burks, and Y. Ampatzidis. 2023. Precision agriculture in Florida, USA – The Beginning, Progress, and Future. Chungnam National University, Daejeon-si, Korea. May 24, 2023.


• Lee, W. S., T. Burks, and Y. Ampatzidis. 2023. Precision agriculture in Florida, USA – The Beginning, Progress, and Future. Department of Agricultural Engineering, Division of Smart Farm Development, National Institute of Agricultural Sciences, Jeonju-si, Korea. May 25, 2023.


• Lee, W. S., T. Burks, and Y. Ampatzidis. 2023. Precision agriculture in Florida, USA – The Beginning, Progress, and Future. Seoul National University, Seoul, Korea. May 31, 2023.


• Lee, W. S., Y. Ampatzidis, and D. Choi. 2023. University of Florida 2023 W-3009 Report (presented via Zoom). Cornell AgriTech, Cornell University, Geneva, NY. June 20-21, 2023.


• Teshome F.T., Bayabil H.K., Schaffer B., Ampatzidis Y., Hoogenboom G., 2024. Improving soil moisture prediction with deep learning and machine learning Models. Computers and Electronics in Agriculture, 226, 109414, https://doi.org/10.1016/j.compag.2024.109414.


• Ojo I., Ampatzidis Y., Neto A.D.C., Guan H., Batuman O., 2024. Oxytetracycline injection using automated trunk injection compared to manual injection systems for HLB-affected citrus trees. Computers and Electronics in Agriculture, 226, 109430, https://doi.org/10.1016/j.compag.2024.109430.


• Trentin C., Ampatzidis Y., Lacerda C., Shiratsuchi L., 2024. Tree crop yield estimation and prediction using remote sensing and machine learning: A systematic review. Smart Agricultural Technology, 100556, https://doi.org/10.1016/j.atech.2024.100556.


• da Cunha V.A.G., Pullock D., Ali M., Neto A.D.C., Ampatzidis Y., Weldon C., Kruger K., Manrakhan A., Qureshi J., 2024. Psyllid Detector: a web-based application to automate insect detection utilizing image processing and artificial intelligence. Applied Engineering in Agriculture, 40(4), 427-438. https://doi.org/10.13031/aea.15826.


• Teshome F.T., Bayabil H.K., Schaffer B., Ampatzidis Y., Hoogenboom G., Singh A., 2024. Simulating soil hydrologic dynamics using crop growth and machine learning models. Computers and Electronics in Agriculture, 224, 109186, https://doi.org/10.1016/j.compag.2024.109186.


• Ojo I., Ampatzidis Y., Neto A.D.C., Bayabil K.H., Schueller K.J., Batuman O., 2024. Determination of needle penetration force and pump pressure for the development of an automated trunk injection system for HLB-affected citrus trees. Journal of ASABE, 67, 4, https://doi.org/10.13031/ja.15975.


• Rui Z., Zhang Z., Zhang M., Azizi A., Igathinathane C., Cen H., Vougioukas S., Li H., Zhang J., Jiang Y., Jiao X., Wang M., Ampatzidis Y., Oladele O.I., Ghasemi-Varnamkhasti M., Raid R., 2024. High-throughput proximal ground crop phenotyping systems – A comprehensive review. Computers and Electronics in Agriculture, 224, 109108, https://doi.org/10.1016/j.compag.2024.109108.


• Javidan S.M., Banakar A., Rahnama K., Vakilian K.A., Ampatzidis Y., 2024. Feature engineering to identify plant diseases using image processing and artificial intelligence: a comprehensive review. Smart Agricultural Technology, 8, 100480, https://doi.org/10.1016/j.atech.2024.100480.


• Barbosa Júnior M.D., Moreira B.R.A., Carreira V.S., Brito Filho A.L., Trentin C., Souza F.L.P., Tedesco D., Setiyono T., Flores J.P., Ampatzidis Y., Silva R.P., Shiratsuchi L.S., 2024. Precision Agriculture in the United States: A comprehensive meta-review inspiring further research, innovation, and adoption. Computers and Electronics in Agriculture, 221, 108993, https://doi.org/10.1016/j.compag.2024.108993.


• Ojo I., Ampatzidis Y., Neto A.D.C., Bayabil K.H., Schueller K.J., Batuman O., 2024. The development and evolution of trunk injection mechanisms – A review. Biosystems Engineering, 240, 123-141, https://doi.org/10.1016/j.biosystemseng.2024.03.002.


• Ojo I., Ampatzidis Y., Neto A.D.C., Batuman O., 2024. Development of an automated needle-based trunk injection system for HLB-affected citrus trees. Biosystems Engineering, 240, 90-99, https://doi.org/10.1016/j.biosystemseng.2024.03.003.


• Zhou C., Lee W.S., Zhang S., Liburd O.E., Pourreza A., Schueller J.K., Ampatzidis Y., 2024. A smartphone application for site-specific pest management based on deep learning and spatial interpolation. Computers and Electronics in Agriculture, 218, 108726, https://doi.org/10.1016/j.compag.2024.108726.


• Javidan S.M., Banakar A., Vakilian K.A., Ampatzidis Y., Rahnama K., 2024. Diagnosing the spores of tomato fungal diseases using microscopic image processing and machine learning. Multimedia Tools and Applications, 1-19, https://doi.org/10.1007/s11042-024-18214-y.


• Zhang L., Ferguson L., Ying L., Lyons A., Laca E., and Ampatzidis Y., 2024. Developing a web-based pistachio nut growth prediction system for orchard management. HortTechnology, 34,1, 1-7, https://doi.org/10.21273/HORTTECH05270-23.


• Liu X., Zhang Z., Igathinathane C., Flores P., Zhang M., Li H., Han X., Ha T., Ampatzidis Y., Kim H-J., 2024. Infield corn kernel detection using image processing, machine learning, and deep learning methodologies. Expert Systems with Applications, 238 (part E), 122278, https://doi.org/10.1016/j.eswa.2023.122278.


• Mehdizadeh S.A., Noshad M., Chaharlangi M., Ampatzidis Y., 2023. Development of an innovative optoelectronic nose for detecting adulteration in quince seed oil. Foods, 12(23), 4350, https://doi.org/10.3390/foods12234350.


• Abdulridha J., Bashyal M., Ampatzidis Y., and Kanissery R., 2023. Steam application with paraquat to control goat weed (Scoparia dulcis) in citrus orchards. Smart Agricultural Technology, 6, 100355, https://doi.org/10.1016/j.atech.2023.100355.


• Vijayakumar V., Ampatzidis Y., Schueller J.K., Burks T., 2023. Smart spraying technologies for precision weed management: a review. Smart Agricultural Technology, 6, 100337, https://doi.org/10.1016/j.atech.2023.100337.


• da Cunha V.G., A. Hariharan J., Ampatzidis Y., Roberts P., 2023. Early detection of tomato bacterial spot disease in transplant tomato seedlings utilizing remote sensing and artificial intelligence. Biosystems Engineering, 234, 172-186, https://doi.org/10.1016/j.biosystemseng.2023.09.002.


• Teshome F.T., Bayabil H.K., Schaffer B., Ampatzidis Y., Hoogenboom G., Singh A., 2023. Exploring deficit irrigation as a water conservation strategy: Insights from field experiments and model simulation. Agricultural Water Management, 289, 108490, https://doi.org/10.1016/j.agwat.2023.108490.


• Teshome F.T., Bayabil H.K., Hoogenboom G., Schaffer B., Singh A., Ampatzidis Y., 2023. Unmanned aerial vehicle (UAV) imaging and machine learning applications for plant phenotyping. Computers and Electronics in Agriculture, 212, 108064, https://doi.org/10.1016/j.compag.2023.108064.


• Zhou C., Lee W.S., Liburd O.E., Aygun I., Zhou X., Pourreza A., Schueller J.K., Ampatzidis Y., 2023. Detecting two-spotted spider mites and predatory mites in strawberry using deep learning. Smart Agricultural Technology, 100229, https://doi.org/10.1016/j.atech.2023.100229.


• Javidan S.M., Banakar A., Vakilian K.A., Ampatzidis Y., 2023. Tomato leaf diseases classification using image processing and weighted ensemble learning. Agronomy Journal, http://doi.org/10.1002/agj2.21293.


• Hariharan J., Ampatzidis Y., Abdulridha J., Batuman O., 2023. An AI-based spectral data analysis process for recognizing unique plant biomarkers and disease features. Computers and Electronics in Agriculture, 204, 107574, https://doi.org/10.1016/j.compag.2022.107574.


• Momeny M., Neshat A.A., Jahanbakhshi A., Bakhtoor M.., Ampatzidis Y., Radeva P., 2023. Grading and fraud detection of Saffron via learning-to-augment incorporated inception-v4 CNN. Food Control, 109554, https://doi.org/10.1016/j.foodcont.2022.109554.


• Panta S., Zhou B., Zhu L., Maness N., Rohla C., Costa L., Ampatzidis Y., Fontainer C., Kaur A., Zhang, L., 2023. Selecting non-linear mixed effect model for growth and development of pecan nut. Scientia Horticulturae, 309, 111614, https://doi.org/10.1016/j.scienta.2022.111614.


• Poudyal C., Sandhu H., Ampatzidis Y., Odero D.C., Arbelo O.C., Cherry R.H., Costa L., 2023. Prediction of morho-physiological traits in sugarcane using aerial imagery and machine learning. Smart Agricultural Technology, 100104, https://doi.org/10.1016/j.atech.2022.100104.


• Vijayakumar V., Ampatzidis Y., Costa L., 2023. Tree-level Citrus Yield Prediction Utilizing Ground and Aerial Machine Vision and Machine Learning. Smart Agricultural Technology, 100077, https://doi.org/10.1016/j.atech.2022.100077.


• Javidan S.M., Banakar A., Vakilian K.A., Ampatzidis Y., 2023. Diagnosis of grape leaf diseases using automatic K-means clustering and machine learning. Smart Agricultural Technology, 100081, https://doi.org/10.1016/j.atech.2022.100081.


• Dutt, N., & Choi, D. (2024). A Computer Vision System for Mushroom Detection and Maturity Estimation using Depth Images. 2024 ASABE Annual International Meeting.


• Ilodibe, U., & Choi, D. (2024). Evaluating The Performance of a Mite Dispensing System for Biological Control of Chilli Thrips in Strawberry Production in Florida. 2024 ASABE Annual International Meeting.


• Mirbod, O., & Choi, D. (2023). A Strategy for Rapid Development of Machine Vision Systems for Strawberry Farms Through Digital Twins and Synthetic Data, Computer and Electronics in Agriculture. Under Review.


• Mirbod, O., & Choi, D. (2023). Synthetic Data-Driven AI Using Mixture of Rendered and Real Imaging Data for Strawberry Yield Estimation. In 2023 ASABE Annual International Meeting. American Society of Agricultural and Biological Engineers.


• Mirbod, O., Choi, D., Heinemann, P. H., Marini, R. P., & He, L. (2023). On-tree apple fruit size estimation using stereo vision with deep learning-based occlusion handling. Biosystems Engineering, 226, 27-42.


• Mahmud, M. S., He, L., Zahid, A., Heinemann, P., Choi, D., Krawczyk, G., & Zhu, H. (2023). Detection and infected area segmentation of apple fire blight using image processing and deep transfer learning for site-specific management. Computers and Electronics in Agriculture, 209, 107862.


• Mahmud, M. S., He, L., Heinemann, P., Choi, D., & Zhu, H. (2023). Unmanned aerial vehicle based tree canopy characteristics measurement for precision spray applications. Smart Agricultural Technology, 4, 100153.


• Liu W., Ampatzidis Y., Wilkinson B., 2024. LiDAR-based point cloud classification and tree extraction for citrus crops. ASABE Annual International Meeting, Anaheim, California, USA, July 28-31, 2024.


• Cho Y., Yu Z., Ampatzidis Y., Wu S., Zhang C., 2024. Blockchain innovation for transparent forest carbon markets. ASABE Annual International Meeting, Anaheim, California, USA, July 28-31, 2024.


• Ojo I., Neto A.D.C., Ampatzidis Y., Batuman O., 2024. Needle-based, automated trunk injection system for HLB-affected citrus trees. ASABE Annual International Meeting, Anaheim, California, USA, July 28-31, 2024.


• Vijayakumar V., Neto A.D.C., Ampatzidis Y., 2024. A robotic precision smart sprayer based on machine vision and PI-controlled spraying system for specialty crops. ASABE Annual International Meeting, Anaheim, California, USA, July 28-31, 2024.


• Zhou C., Pullock D., Ampatzidis Y., Weldon C., Manrakhan A., 2024. Citrus pest detection using computer vision and deep. ASABE Annual International Meeting, Anaheim, California, USA, July 28-31, 2024.


• Ampatzidis Y., 2024. Can AI and automation transform specialty crop production? 16th International Conference on Precision Agriculture (ICPA), International Symposium on robotics and Automation, Manhattan, Kansas, USA, July 21-24.


• Zhou C. and Ampatzidis Y., 2024. AI-enabled 3D vision system for rapid and accurate tree trunk detection and diameter estimation. 16th International Conference on Precision Agriculture (ICPA), Manhattan, Kansas, USA, July 21-24.


• Zhou C., Ampatzidis Y., Guan H., and Neto A.D.C., Kunwar S., Batuman O., 2024. Agrosense: AI-enabled sensing for precision management of tree crops (poster). 16th International Conference on Precision Agriculture (ICPA), Manhattan, Kansas, USA, July 21-24.


• Banakar A., Javidan S.M., Vakilian K.A., Ampatzidis Y., 2024. Detection of spectral signature and classification of Alternaria alternata and Alternaria solani diseases in tomato plant by analysis of hyperspectral images and support vector machine. AgEng International Conference of EurAgEng, Agricultural Engineering Challenges in Existing and New Agrosystems, Athens, Greece, July 1-4, 2024.


• Lacerda C., and Neto A.D.C., Ampatzidis Y., 2024. Agroview: enhance satellite imagery using super-resolution and generative AI for precision management in specialty crops. AgEng International Conference of EurAgEng, Agricultural Engineering Challenges in Existing and New Agrosystems, Athens, Greece, July 1-4, 2024.


• Ampatzidis Y., Ojo I., Neto A.D.C., Batuman O., 2024. Automated needle-based trunk injection system for HLB-affected citrus trees. AgEng International Conference of EurAgEng, Agricultural Engineering Challenges in Existing and New Agrosystems, Athens, Greece, July 1-4, 2024.


• Ampatzidis Y., Vijayakumar V., Pardalos P., 2024. AI-enabled robotic spraying technology for precision weed management in specialty crops. Optimization, Analytics, and Decision in Big Data Era Conference (in honor of the 70th birthday of Dr. Panos Pardalos), Halkidiki, Greece, June 16-21.


• Cho Y., Yu, Z., Ampatzidis Y., Nam J., 2024. Blockchain-enhanced security and data management in smart agriculture. 6th CIGR International Conference, Jeju, Korea, May 19–23, 2024.


• Vijayakumar V., Ampatzidis Y., 2024. Development of a machine vision and spraying system of a robotic precision smart sprayer for specialty crops. 3rd Annual AI in Agriculture and Natural Resources Conference, College Station, TX, April 15-17, 2024.


• Zhou C., Ampatzidis Y., Pullock D., 2024. Detecting citrus pests from sticky traps using deep learning. 3rd Annual AI in Agriculture and Natural Resources Conference, College Station, TX, April 15-17, 2024.


• Trentin C., Lacerda C.M.F., Shiratsuchi L., Ampatzidis Y., 2024. AI in orchard: improving sustainability through predictive yield in trees. 3rd Annual AI in Agriculture and Natural Resources Conference, College Station, TX, April 15-17, 2024.


• Cho Y., Yu, Z., Ampatzidis Y., 2024. Blockchain-Enhanced Data Management in AI-Driven Agriculture: A Pathway to Efficiency and Transparency. 3rd Annual AI in Agriculture and Natural Resources Conference, College Station, TX, April 15-17, 2024.


• Tulu B.B., Bayabil H.K., Ampatzidis Y., 2024. Enhancing agricultural water management: A desktop application integrating UAV imagery and ground sensing for precision irrigation. 3rd Annual AI in Agriculture and Natural Resources Conference, College Station, TX, April 15-17, 2024.


• Ojo I., Neto A.D.C., Ampatzidis Y., Batuman O., Albrecht U., 2024. Needle-based, automated trunk injection system for HLB-affected citrus trees. International Research Conference on Huanglongbing VII, Riverside, CA, March 26-29, 2024.


• Tulu B.B., Bayabil H.K., Ampatzidis Y., 2024. IrrigSense: A decision support tool to streamline precision irrigation. UF/ABE Poster Competition, Gainesville, FL, March 6, 2024.


• Javidan S.M., Ampatzidis Y., Vakilian K.A., Mohammadzamani D., 2024. A novel approach for automated strawberry fruit varieties classification using image processing and machine learning. 10th International Conference on Artificial Intelligence and Robotics, IEEE-QICAR2024 Qazvin Islamic Azad University, February 29, 2024, https://doi.org/10.1109/QICAR61538.2024.10496652


• Tulu B.B., Bayabil H.K., Ampatzidis Y., 2024. Streamlining precision irrigation: Developing a web-based decision support tool for sensor data processing. 9th biennial UF Water Institute Symposium, Gainesville, FL, February 20-21, 2024.


• Ampatzidis Y., 2024. Agroview and Agrosense for AI-enhanced precision orchard management. SE Regional Fruit and Vegetable Conference, Savannah, GA, January 11-14, 2024


• Ampatzidis Y., 2023. Emerging and advanced technologies in agriculture. Link (Linking Industry Networks through Certifications; High School Teachers Training) Conference, Daytona Beach, FL, October 10-12, 2023.


• Ampatzidis Y., 2023. AI and Extension. Possibilities and Challenges. 2023 SR-PLN Middle Managers Conference, Next Generation: Evolving the Extension Enterprise, Orlando, FL, August 22-24.


• Ampatzidis Y., 2023. AI-Enhanced Technologies for Precision Management of Specialty Crops. Sustainable Precision Agriculture in the Era of IoT and Artificial Intelligence, Bard Ag-AI Workshop, Be’er Sheva, Israel, July 18-20, 2023.


• Ojo I., de Oliveira Costa Neto A., Ampatzidis Y., 2023. Automated Injection System for Therapeutic Materials Using Nonpassive, Needle-Based Trunk Injection to Treat HLB-affected Citrus Trees. ASABE Annual International Meeting, Omaha, Nebraska, USA, July 8-12, 2023.


• Vijayakumar V., Ampatzidis Y., Silwal A., Kantor G., 2023. 2023. Development of a machine vision and spraying system of an autonomous robotic sprayer for specialty crops. ASABE Annual International Meeting, Omaha, Nebraska, USA, July 8-12, 2023.


• Kunwar S., Babar M. A., Ampatzidis Y., Mcbreen J., Khan N., Acharya J., Adewale S., Costa L., and Cunha V., 2023. Determining yield, harvest index and associated complex biomass partitioning traits in wheat using UAV-based hyperspectral sensor and machine learning. Annual Meeting of the Western Crop Science Society (WCSSA), Honolulu, Hawaii, June 26-28, 2023.


• Ampatzidis Y., 2023. Solutions to critical issues facing field and specialty crop production. Integrative Precision Agriculture – Local Solutions Through Global Advances International Conference, Athens, Georgia, May 18-19, 2023.


• Hariharan J., Ampatzidis Y., Abdulridha J., Batuman O., 2023. An AI-Based Spectral Data Analysis Process for Recognizing Unique Plant Biomarkers and Disease Features. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Kunwar S., Babar Md. A., Ampatzidis Y., 2023. Potential use of UAV-based remote sensing tools for indirect assessment of harvest index and associated complex biomass partitioning traits in wheat. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Vijayakumar V., Ampatzidis Y., Silwal A., Kantor G., 2023. Specialty crop-specific robotic precision smart sprayer based on machine vision and PWM-controlled spraying system. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Costa L. and Ampatzidis Y., 2023. Building reliability: development of a prototype to production for a smart citrus tree sprayer using sensor fusion and artificial intelligence. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Zhou X., Ampatzidis Y., Lee W.S., Agehara S., Schueller J.K., Crane C., 2023. AI-based Inspection System for Mechanical Strawberry Harvesters. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Lacerda C., Costa L, Ampatzidis Y., 2023. The process of optimizing a cloud based software infrastructure: Agroview, a case of study. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Andrade Gontijo da Cunha V., de Oliveira Costa Neto A., Costa L., Ampatzidis Y., 2023. ACP Detection System on Sticky Traps Images Utilizing Artificial Intelligence. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Liu W. and Ampatzidis Y., 2023. Mapping citrus orchards utilizing aerial imagery with Agroview and Lidar. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Ojo I., Lucas F., de Oliveira Costa Neto A., Ampatzidis Y., 2023. AI-based Operator-assisted Positioning of Automated Trunk Injection Mechanism using Sensor Fusion. AI in Agriculture Conference: Innovation and Discovery to Equitably meet Producer Needs and Perceptions, Orlando, FL, April 17-19, 2023.


• Liu W., Costa L., Ampatzidis Y., 2023. Precisely Mapping Citrus Orchards utilizing UAV-based LiDAR and Imagery with a Cloud-based AI system Agroview. ABE/UF Poster Competition. Gainesville, FL, March 9, 2023.


• Ampatzidis Y., 2023. “Agrifood systems in a Circular Economy Framework: Unlocking the Future”. 11th Agrotechnology Conference, American Hellenic Chamber of Commerce, Thessaloniki, Greece, February 17, 2023.


• Kunwar S., Babar M. A., and Ampatzidis Y., 2023. Potential use of UAV-based remote sensing tools for indirect assessment of harvest index, biomass partitioning dynamics and associated complex traits in wheat. PSC Symposium (poster), January 30-31, 2023.


• Ampatzidis Y., 2023. AI-enhanced smart machinery for precision scouting and spraying. Annual Meeting and Ag Expo of the National Alliance of Independent Crop Consultants (NAICC), Nashville, TN, January 23-27, 2023.


• Hou, J., X. Wang, B. Park. C. Li. 2024. A multiscale computation study on bruise susceptibility of blueberries from mechanical impact. Postharvest Biology and Technology. 208: 112660.


• Li, Z., Li, C., & Munoz, P. Blueberry yield estimation through multi-view imagery with YOLOv8 object detection. ASABE Annual International Meeting Paper No 2300883. Omaha, Nebraska July 9-12, 2023.


• Perkins-Veazie, P., C. Li, H. Oh, M. Iorizzio. Fruit bruising, firmness, and estimation of cell membrane damage across blueberry genotypes. ASHS Conference. July 31-August 4, 2023, Orlando, Florida.


• Uthman, Q.O.G, D.M. Kadyampakeni, J.A. Leiva, J.D. Judy and P. Nkedi-Kizza. 2024. Sorption and


• degradation processes of imidacloprid in Florida soils. PLoS ONE 19(9): e0305006. https://doi.org/10.1371/journal.pone.0305006


• Chuang, A.p, D. Kadyampakeni, T. Liesenfelt, C. Vincent, M. Dewdney, and L.


• 2024. Comparison of tools to support healthy young citrus plantings in a region with endemic huanglongbing, CLas, and Asian citrus psyllid (Diaphorina citri). Crop Protection, https://doi.org/10.1016/j.cropro.2024.106871


• Donovan, M.P, C. Chanes, D. Gholson, D.M. Kadyampakeni, M.E. Swisher, and T. Connor


• Managing agricultural water resources in the southern region: perspectives of crop growers. Water 16(13), 1841; https://doi.org/10.3390/w16131841


• Atta, A.A.P, K.T. Morgan, S. Hamido, and D.M. Kadyampakeni. 2024. Irrigation optimization enhances water management and tree performance in commercial citrus groves on sandy soil. Irri. Sci. https://doi.org/10.1007/s00271-024-00938-2


• Agyin-Birikorang, S., D.M. Kadyampakeni, A.R.A. Fuseini; R. Chambers, I. Tindjina, and R. Adu-


• 2024. Sulfur availability minimizes nitrate leaching losses in vulnerable agricultural soils. J. Plant Nut. 47(15):2389-2405, https://doi.org/10.1080/01904167.2024.2354171


• Brewer, M.P, D.M. Kadyampakeni, R. Kanissery, and S. KwakyeP. 2024. Evaluation of the nitrogen uptake efficacy of daikon radish under greenhouse conditions on sandy soils. Agrosyst. Geosci. Environ., https://doi.org/10.1002/agg2.20508


• Uthman, Q.O.G, M. Vasconez, D.M. Kadyampakeni, Y. Wang, D. Athienitis, and J.A. Qureshi. 2024. Imidacloprid uptake and leaching in the critical root zone of a Florida Entisol. Agrochem. 3:94–106. https://doi.org/10.3390/agrochemicals3010008


• Agyin-Birikorang, S., C. Boubakry, D.M. Kadyampakeni, R. Adu-Gyamfi, R.A. Chambers, I. Tindjina, and A.R.A. Fuseni. 2024. Synergism of sulfur availability and agronomic nitrogen use efficiency. Agron. J. 116(2):753-764. https://doi.org/10.1002/agj2.21535


• Chinyukwi, T.G, D.M. Kadyampakeni, and L. Rossi. 2024. Optimization of macronutrient and micronutrient concentrations in roots and leaves for Florida HLB-affected sweet orange trees. J. Plant Nutr. 47(2):226–239. https://doi.org/10.1080/01904167.2023.2275068


• Agyin-Birikorang, S., R. Adu-Gyamfi, D.M. Kadyampakeni, R.A. Chambers, I. Tindjina, and H.W. Dauda. 2024. Lime Microdosing: A new liming strategy for increased productivity in acid soils. Soil Sci. Soc. Am. J. 88(1):136-151, https://doi.org/10.1002/saj2.20610


• Fenn, R.A.G, D.M. Kadyampakeni, R. Kanissery and J. Judy. 2024. Citrus phosphorus uptake dynamics with glyphosate under greenhouse conditions. J. Plant Nutr. 47(5):776-785. https://doi.org/10.1080/01904167.2023.2280154


• Timilsina, N.g, O. Batuman, F. Alferez, D. Kadyampakeni, R. Tiwari and R. Kanissery, 2023. Nontarget effects of preemergence herbicide Diuron in Hamlin and Valencia sweet orange (Citrus sinensis L. Osbek) in Florida. HortSci. 58(12):1492–1497. https://doi.org/10.21273/HORTSCI17359-23


• Brewer, M.G, R.G. Kanissery, S.L. Strauss, and D.M. Kadyampakeni. 2023. Impact of cover cropping on temporal nutrient distribution and availability in the soil. Horticult. 2023, 9, 1160. https://doi.org/10.3390/horticulturae9101160


• Kadyampakeni, D.M., T. ChinyukwiG, S. KwakyeP and L. Rossi. 2023. Varied macro- and micronutrient fertilization rates impact root growth and distribution and fruit yield of huanglongbing-affected Valencia orange trees. HortSci. 58(12):1498–1507. https://doi.org/10.21273/HORTSCI17372-23


• Fenn, R.A.G, D.M. Kadyampakeni, R.G. Kanissery, J. Judy, and M. Bashyalp. 2023. Phosphorus and glyphosate adsorption and desorption trends across different depths in sandy soil. Agrochem. 2:503–516. https://doi.org/10.3390/agrochemicals2040028


• Hallman, L.M.g, D.M. Kadyampakeni, R.S. Ferrarezi, A.L. Wright, M.A. Ritenour and L. Rossi. 2023. Uptake of micronutrients in severely HLB-affected grapefruit trees grown on Florida Indian River flatwood soils. J. Plant Nutr. 46(17):4110–4124. https://doi.org/10.1080/01904167.2023.2221287


• Ghoveisi, H.P, D.M. Kadyampakeni, J. Qureshi, and L. Diepenbrock. 2023. Water use efficiency in young citrus trees on metalized UV reflective mulch compared to bare ground. Water 15, 2098. https://doi.org/10.3390/w15112098


• Kwakye, S.P and D.M. Kadyampakeni. 2023. Impact of deficit irrigation on growth and water relations of HLB-affected citrus trees under greenhouse conditions. Water 15, 2085. https://doi.org/10.3390/w15112085


• Hussain, M.P, S. Iqbal, M. Shafiq, R.M. Balal, J. Chater, D. Kadyampakeni, F. Alferez, A. Sarkhosh and M.A. Shahid. 2023. Silicon-induced hypoxia tolerance in citrus rootstocks associated with modulation in polyamine metabolism. Sci. Hort. 318:112118, https://doi.org/10.1016/j.scienta.2023.112118


• Atta, A.A.P, K.T. Morgan M.A. Ritenour and D.M. Kadyampakeni. 2023. Nutrient management impacts on HLB-affected ‘Valencia’ citrus tree growth, fruit yield, and postharvest fruit quality. Hortsci. 58(7):725–732. https://doi.org/10.21273/HORTSCI17110-23  


• Santiago, J.M.g, D.M. Kadyampakeni, J.P. Fox, A.L. Wright, S.M. Guzmán, R.S. Ferrarezi, and L. Rossi. 2023. Grapefruit root and rhizosphere responses to varying planting densities, fertilizer concentrations and application methods. Plants 12, 1659. https://doi.org/10.3390/plants12081659

Massachusetts

• Higgins, G. 2023. Winter High Tunnel Spinach Variety Trial Results, 2022-23. Vegetable Notes. August 17, 2023. Vol. 35:18


• Higgins, G. 2024. Improving Production & Yield of Winter Spinach in the Northeast. Vegetable Notes. January 2024. Vegetable Notes 2024 Vol. 36:1


• Higgins, G. 2023. Improving Germination and Stand in Winter High Tunnel Spinach. Vegetable Notes. September 14, 2023. Vegetable Notes 2023 Vol. 35:21

Michigan

• Xu, J., Lu, Y., 2024. Prototyping and evaluation of a novel machine vision system for real-time, automated quality grading of sweetpotatoes. Computers and Electronics in Agriculture 219, 108826.


• Xu, J., Lu, Y., 2024. Design and preliminary evaluation of automated sweetpotato sorting mechanisms. AgriEngineering 6 (3), 3058-3069.


• Ahmed, T., Wijewardane, N., Lu, Y., Jones, D., Kudenov, M., Williams, C., Villordon, A., Kamruzzaman, M., 2024. Advancing sweetpotato quality assessment with hyperspectral imaging and explainable artificial intelligence. Computers and Electronics in Agriculture 220, 108855.


• Deng, B., Lu, Y., Xu, J., 2024. Weed database development: An updated survey of public weed datasets and cross-season weed detection adaptation. Ecological Informatics, 102546.


• Xu, J., Lu, Y., Deng, B., 2024. OpenWeedGUI: an open-source graphical tool for weed Imaging and YOLO-based weed detection. Electronics 13 (9), 1699.


• Deng, B., Lu, Y., Stafne, E., 2024. Fusing spectral and spatial features of hyperspectral reflectance imagery for differentiating between normal and defective blueberries. Smart Agricultural Technology, 100473.


• Li, J., Lu, Y., Lu, R., 2024. Identification of early decayed oranges using structured-illumination reflectance imaging coupled with fast demodulation and improved image processing algorithms. Postharvest Biology and Technology 207, 112627.


• Dong, Y., Werling, B., Cao, Z., Li, G., (2024). Implementation of an In-Field IoT Systems for Precision Irrigation Management. Frontiers in Water. 6, 1353597.


• Dong, Y., Hansen, H., (2024). Design of an Internet of Things (IoT)-Based Photosynthetically Active Radiation (PAR) Monitoring System. AgriEngineering. 6 (1), 773-785.


• Dong, Y., Sloan, G., Chappuies, J., (2024). Open-source time-lapse thermal imaging camera for canopy temperature monitoring. Smart Agricultural Technology. 100430.


• Mane, S., Das, N., Singh, G., Cos, M., Dong, Y., (2024). Advancements in dielectric soil moisture sensor Calibration: A comprehensive review of methods and techniques. Computers and Electronics in Agriculture. 218, 108686.


• Xu, J., Lu, Y., Deng, B., 2024. Design, prototyping, and evaluation of a machine vision-based automated sweetpotato grading and sorting System. ASABE Annual International Meeting Paper 2400102.


• Deng, B., Lu, Y., Brainard, D., 2024. Development and Preliminary Evaluation of a Vision-Guided Smart Sprayer Prototype towards Precision Vegetable Weeding. ASABE Annual International Meeting Paper 2400089.


• Deng, B., Lu, VanderWeide, J., 2024. Development and preliminary evaluation of a deep learning-based fruit counting mobile application for high-bush blueberries. ASABE Annual International Meeting Paper 2401022.


• Lu, Y., Mohammadi, P., Xu, J., 2024. Automated asparagus harvesting technology: a review of the past 60 years of research and developments in the United States and beyond. ASABE Annual International Meeting Paper 2401062.


• Xu, J., Lu, Y, 2024. Design and preliminary evaluation of a machine vision-based automated sweetpotato sorting system. Sensing for Agriculture and Food Quality and Safety XVI Proceedings Volume PC13060.


• Deng, B., Lu, Y., 2024. Weed image augmentation by controlNet-added stable diffusion. SPIE Defense + Commercial Sensing, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II

Missouri

• Rifat, S. M., Zhou, J., & Thomas, A. 2024. The Effects of Shaking Frequency and Amplitude on Vibratory Harvesting of American Elderberry. In 2024 ASABE Annual International Meeting. American Society of Agricultural and Biological Engineers.

Mississippi

• Karkee, M.*, Zhang, Q., Bhattarai, U., & Zhang, X. (2024). Chapter 19 – Advances in the use of robotics in orchard operations. In Advances in Agri-Food Robotics (van Henten, E., & Edan, Y. ed.), Springer Book Series: Agriculture Automation and Control. (http://dx.doi.org/10.19103/AS.2023.0124.23)


• Zhang, X.* (2023). Robotics and Automation Technologies: Plant-machine interface. In Encyclopedia of Smart Agriculture Technologies (Zhang, Q. ed.), Springer. (https://doi.org/10.1007/978-3-030-89123-7_124-1)


• Zhang, X.*, Thayananthan, T., Usman, M., Liu, W., & Chen, Y. (2023, June). Multi-ripeness level blackberry detection using YOLOv7 for soft robotic harvesting. In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VIII (Vol. 12539, pp. 85-96). SPIE. (https://doi.org/10.1117/12.2663367)


• He, L.*, Zhang, X., & Zahid, A. (2023). Chapter 2 – Mechanical management of modern planar fruit tree canopies. In Advanced Automation for Tree Fruit Orchards and Vineyards (Vougioukas, S. G., & Zhang, Q. ed.), Springer Book Series: Agriculture Automation and Control. (https://doi.org/10.1007/978-3-031-26941-7_2)


• Chakraborty, M., Pourreza, A.*, Zhang, X., Jafarbiglu, H., Shackel, K. A., & DeJong, T. (2023). Early almond yield forecasting by bloom mapping using aerial imagery and deep learning. Computers and Electronics in Agriculture, 212, 108063. (https://doi.org/10.1016/j.compag.2023.108063)


• He, Z., Khanal, S. R., Zhang, X., Karkee, M.*, & Zhang, Q. (2023). Real-time strawberry detection based on improved YOLOv5s architecture for robotic harvesting in open-field environment. arXiv. (https://doi.org/10.48550/arXiv.2308.03998)


• Azizkhani, M., Gunderman, A. L., Qiu, A. S., Hu, A. P., Zhang, X., & Chen, Y.* (2023). Design, modeling, and redundancy resolution of soft robot for effective harvesting. arXiv. (https://doi.org/10.48550/arXiv.2303.08947)


• Divyanth, L. G., Rathore, D., Senthilkumar, P., Patidar, P., Zhang, X., Karkee, M., Machavaram, R., & Soni, P.* (2023). Estimating depth from RGB images using deep-learning for robotic applications in apple orchards. Smart Agricultural Technology, 6, 100345. (https://doi.org/10.1016/j.atech.2023.100345)

Pennsylvania

• Mu, X., Hussain, M., He, L., Heinemann, P., Schupp, J., Karkee, M., & Zhu, M. (2023). An advanced robotic system for precision chemical thinning of apple blossoms. Journal of the ASABE 66(5).


• Hua, W., He, L., Heinemann, P., & Yuan, W. (2023). CFD simulation of porous canopy heat transfer in apple orchard frost protection. Journal of the ASABE 66(4), 825-837.


• Kang, C., He, L., & Zhu, H. (2024). Assessment of spray patterns and efficiency of an unmanned sprayer used in planar growing systems. Precision Agriculture, July, 2024.


• Hua, W., Heinemann, P.H., & He, L. (2024). Canopy protection cyber-physical system (CPCPS) for smart agricultural management of frost damage in apple orchards. Computers and Electronics in Agriculture, 217, 108611.


• Mao, W., Murengami, B., Jiang, H., Li, R., He, L., & Fu, L. (2024). UAV-Based High-Throughput Phenotyping to Segment Individual Apple Tree Row Based on Geometrical Features of Poles and Colored Point Cloud. Journal of the ASABE, 67(5), 1231-1240.


• He, L., Han, K., & Peter, K. (2023). Smartphone-Assisted Apple Diseases Identification and Quantification using Artificial Intelligence. Pennsylvania Fruit News. February 2024.


• Arthur, L., He, L., & Brunharo, C. (2024). An Overview of Advanced Weed Management Technologies for Orchards. Penn State Extension.


• Kang, C. & He, L. (2024). Introduce and Evaluate an Unmanned Ground Sprayer for Vineyards and Orchards. Penn Stage Extension.


• Magni Hussain (2023). Robotic Green Fruit Thinning for Apple Production. PhD Dissertation. The Pennsylvania State University.


• Xinyang Mu (2023). Advanced Robotic Approaches to Precision Apple Crop Load Management in Blossom Thinning Stage. PhD Dissertation. The Pennsylvania State University.


• Weiyun Hua (2024). Development of A Precision Heating Strategy for Smart Frost Management in Apple Orchards. PhD Dissertation. The Pennsylvania State University.


• Juan Arguijo (2024). Vision System for the Detection of Apples in the Green Fruit Stage. MS Thesis. The Pennsylvania State University.

Texas

• Majeed, Y., Ojo, M. O., and Zahid, A. 2024. Standalone edge AI-based solution for Tomato diseases detection, Smart Agricultural Technology, 100547


• Ojo, M. O., Zahid, A., and Masabni, J. 2024. Estimating hydroponic lettuce phenotypic parameters for efficient resource allocation, Computers and Electronics in Agriculture, 218, 108642


• Ahamed M. S., Sultan, M., Monfet, D., Rahman, M.S., Zhang, Y., Zahid, A., Aleem, M., Achour, Y., and Ahsan, T. M. A. 2023. Thermal environment controls and sustainability challenges in indoor vertical farming, Journal of Cleaner Production, 425, 138923


• Bashir, A., Majeed, Y., and Zahid, A. 2024. Development of an End-effector for Robotic Harvesting of Hydroponic Lettuce, In 2024 ASABE Annual International Meeting, Paper Number: 2400401