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

11/04/2025

Arizona:

• Kocher, M.F., Smith, J.A., Arnett, G., Werning, J.L., Siemens, M.C., & Hanna, M.H. (2025). ASABE S658 Planter test standard: 1. Row unit test. Appl. Eng. Agric. (In press)


• Parmar, S., Lou, W., McGinnis, E., Didan, K., Siemens, M.C. & Haiquan, L. (2025). Integrating box-based deep learning with zero-shot segmentation for improved weed and crop classification in lettuce fields. Agric., MDPI (Submitted) doi: 10.20944/preprints202506.0642.v1


• Kocher, M.F., Smith, J.A., Arnett, G., Werning, J.L., Siemens, M.C., & Hanna, M.H. (2025). ASABE S658 Planter test standard: 2. Monitor system test. Appl. Eng. Agric. (Accepted)

California:

• Anokye-Bempah, L., Styczynski, T., Ristenpart, W.D., & Donis-González, I.R. 2025. A universal color curve for roasted arabica coffee. Scientific Report 15 (24192). doi: https://doi.org/10.1038/s41598-025-06601-w.


• 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.


• Arman Ahmadi, Andre Daccache, Minxue He, Peyman Namadi, Alireza Ghaderi Bafti, Prabhjot Sandhu, Zhaojun Bai, Richard L. Snyder, Tariq Kadir (2025). Enhancing the accuracy and generalizability of reference evapotranspiration forecasting in California using deep global learning, Journal of Hydrology: Regional Studies, Volume 59,102339.


• Chouaib El Hachimi, Salwa Belaqziz, Saïd Khabba, Andre Daccache, Bouchra Ait Hssaine, Hasan Karjoun, Youness Ouassanouan, Badreddine Sebbar, Mohamed Hakim Kharrou, Salah Er-Raki, Abdelghani Chehbouni (2025). Physics-informed neural networks for enhanced reference evapotranspiration estimation in Morocco: Balancing semi-physical models and deep learning, Chemosphere, Volume 374, 2025,144238


• de Oca, A., Magney, T., Vougioukas, S.G., Racan, D., Torrez-Orozco, A., Fennimore, S. Martin, F., Earles, M.  (2024) Strawberry fruit yield forecasting using image-based time-series plant phenological stages sequences. Computers and Electronics in Agriculture. 237, Part B, 110516.


• Donis-González, I.R., Zakharov, F., Bruhn, C.M., Cantwell, M.I., Reid, M.S., Slaughter, D.C., & Kader, A. 2025. Book chapter: Postharvest Technology of Horticultural Crops, 4th Edition.  Kader, A., Thompson, J.F. & Salveit, M. (ed) – ANR publication 21658. Quality Factors and Their Evaluation, Vol. 4, Davis, CA. pp. 61.


• F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz, Convolutional neural networks for accurate estimation of canopy cover, Smart Agricultural Technology, Volume 10, 2025, 100750, ISSN 2772-3755,

• Farajpoor, P., Pourreza, A., Narimani, M., El-kereamy, A., & Fidelibus, M. W. Leaf spectral reflectance prediction using multihead attention neural networks. Proceedings Volume 13475, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping X; 134750V (2025) https://doi.org/10.1117/12.3061298

• Fu, K., Zhu, Y., Frehner, E., Rizzo, K., Vougioukas, S. G., Bailey, B. (2025). Analysis of the Potential Improvement of Mechanical Fresh-Market Fruit Harvesting Efficiency Utilizing a Dynamically Adjustable Multi-Level Fruit Catching and Retrieval System. Smart Agricultural Technology, 12, 101228.


• Karkee, M., Vougioukas, S. G., Devadoss, S., Bhusal, S. (2025) Mechanization Efforts in Fruit Tree Pruning and Thinning. Choices, 2nd Quarter 40(2), 10-15


•  Khan, F. A., Khorsandi, F., Ali, M., Ghafoor, A., Khan, R. A. R., Umair, M., Shahzaib, Rehman, A., & Hussain, Z. (2025). Spray drift reduction management in agriculture: A review. Journal Name, 20(1), 1–36.


•  Khorsandi, F., Farhadi, P., Denning, G., Grzebieta, R., Gibbs, J., Godler, Y., Heydinger, G., Hicks, D., Jennissen, C., Lundqvist, P., McIntosh, A., Rechnitzer, G., Simmons, K., & Yoder, A. (2025). Advancing all-terrain vehicle safety in agriculture: Insights and innovations from global experts. Journal Name, 31(3), 173–202.


• Khorsandi, F., Wong, J., & de Moura Araujo, G. (2025). Is it safe for children to ride youth-sized all-terrain vehicles? Journal Name, 94, 216–228.


• Lincoln, J., Gorucu, S., Khorsandi, F., Aby, G. R., Elliott, K. C., Shutske, J., & Issa, S. (2025). Occupational safety research needs in the field of robotics and automated equipment in agriculture. Journal Name, 31(3), 217–230.

• 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.


• Pourreza, A., Kamiya, Y., Peanusaha, S., Jafarbiglu, H., Moghimi, A., & Fidelibus, M. W. (2025). Nitrogen retrieval in grapevine canopy by hyperspectral imaging. Computers and Electronics in Agriculture, 229, 109717.

• Shutske, J., Issa, S. S., Johnson, T., Gorucu, S., Lincoln, J., Khorsandi, F., Pate, M., Smith, E., Versweyveld, J., Aaron, M. A., & Aby, G. R. (2025). SAFERAG – Risk assessment, standards, and regulation: Needs and recommendations. Journal Name, 31(1), 1–13.


• Vougioukas, S. G., Karkee, M., Devadoss, S., Gallardo, K., Charlton, D. (2025) Mechanization Efforts in Fruit Harvesting. Choices, 2nd Quarter 40(2), 3-9


• Wei, P., Peng, C., Lu, W., Zhu, Y., and Vougioukas, S.G. (2025) Efficient and Safe Trajectory Planning for Autonomous Agricultural Vehicle Headland Turning in Cluttered Orchard Environments. IEEE Robotics and Automation Letters 10(3) 2574-2581.


• Wong, C., & Moghimi, A. (2025). Stakeholder mapping of precision weeding commercialization ecosystem in California. Agricultural Systems, 222, 104152. https://doi.org/10.1016/J.AGSY.2024.104152


• Mesgaran, M. (2024, December). Web of Weeds: Tracking Online Sales of Noxious Weed in the US. In AGU Fall Meeting Abstracts (Vol. 2024, pp. IN24A-01)


• Mesgaran, M., P. Robeck, L. Blank. 2024. Digital Menace: Quantifying the Online Sale of Noxious Weeds in the US and EU. Weed Day Workshop, June 20204, Davis.

 

Florida:

Journal Publications

• Chen, Y., A. Shu, Z. Liu, Y. Chen, W.S. Lee, and Y. Zhang. 2025. SP-RTSD: A lightweight real-time strawberry detection on edge devices for onboard robotic harvesting. Journal of Field Robotics, 2025; 1-19. https://onlinelibrary.wiley.com/doi/10.1002/rob.22582.


• Tapia, R., W.S. Lee, V.M. Whitaker, and S. Lee. 2025. Multiple methods for predicting strawberry powdery mildew severity from field canopy reflectance data. PhytoFrontiers https://doi.org/10.1094/PHYTOFR-06-24-0063-SC.


• Kim, J.-H., Y.-H. Cho, K.-M. Kim, C.-Y. Lee, W. S. Lee, and J.-S. Nam. 2025. Sweet potato farming in the USA and South Korea: A comparative study of cultivation pattern and mechanization status. Journal of Biosystems Engineering (2025) 50:210–224. https://doi.org/10.1007/s42853-025-00260-5.


• Huang, Z., W. S. Lee, P. Yang, Y. Ampatzidis, S. Agehara, and N. A. Peres. 2025. Advanced canopy size estimation in strawberry production: a machine learning approach using YOLOv11 and SAM. Computers and Electronics in Agriculture 236 (2025), 110501. https://doi.org/10.1016/j.compag.2025.110501.


• Huang, Z., W. S. Lee, P. Zhang, H. Jeon, and H. Zhu. 2025. SASP: segment any strawberry plant, an end-to-end strawberry canopy volume estimation. Smart Agricultural Technology 11 (2025) 101017. https://doi.org/10.1016/j.atech.2025.101017.


• Pardo-Beainy, C., C. Parra, L. Solaque, and W. S. Lee. 2025. Deep learning and georeferenced RGB-D imaging for hydroponic strawberry yield mapping. Smart Agricultural Technology 12 (2025) 101293. https://doi.org/10.1016/j.atech.2025.101293.


• Liu, S., Ampatzidis, Y., Zhou, C., & Lee, W. S. 2025. AI-driven time series analysis for predicting strawberry weekly yields integrating fruit monitoring and weather data for optimized harvest planning. Computers and Electronics in Agriculture, 233, 110212.


• Uthman, Q.O., R. Muñoz-Carpena, A. Ritter, and D.M. Kadyampakeni. 2025. Differential water and imidacloprid transport under unsaturated Florida citrus field conditions. Vadose Zone J. https://doi.org/10.1002/vzj2.70043


• Fort, J., V. Sharma, M. Dukes, S. Agehara, D. Kadyampakeni, and C.A. Chase. 2025. Micro-irrigation systems for water conservation during establishment and freeze protection in Florida strawberry production. Sci. Hortic. https://doi.org/10.1016/j.scienta.2025.114368


• De Souza Junior, J.P., and D.M. Kadyampakeni. 2025. Differential nutrient dynamics in cowpea and sunn hemp under organic orange peel powder fertilization. Nutr. Cycl. Agroecosyst. https://doi.org/10.1007/s10705-025-10432-6


• Barbosa, I.J., J.P. Souza Junior, M. Garcia Costa, J.C. Barbosa Lúcio, D.M. Kadyampakeni, P.L. Gratão, L. Bianco de Carvalho, R. de Mello Prado, S. Bianco. 2025. Silicon-enhanced non-enzymatic antioxidant defense mechanisms in young orange trees under glyphosate-induced stress. BMC Plant Biology https://doi.org/10.1186/s12870-025-07054-z


• Kadyampakeni, D.M., E. Scudiero, and R. Shrestha. 2025. Advances in precision irrigation management in the twenty-first century. Irrigation Science 43, XXX-XXX. https://doi.org/10.1007/s00271-025-01038-5


• Costa, M.G., R. de Amorim Cordeiro, J.K. Rodrigues das Merces, L.S. de Medeiros, A.M. Cardoso, R. de Mello Prado, D.M. Kadyampakeni, M.T. Siqueira Lacerda, and J.P. de Souza JuniorP. 2025. Silicon can attenuate glyphosate-induced stress in young Handroanthus albus by improving photosynthetic efficiency and decreasing cellular electrolyte leakage. Scientific Reports 15:23077. https://doi.org/10.1038/s41598-025-07527-z


• Sambani, D., A.A. Atta and D.M. Kadyampakeni. 2025. Evaluation of various fertilizer products for improved performance of HLB-affected citrus trees. J. Plant Nutr. 48(16):2882-2897. https://doi.org/10.1080/01904167.2025.2502146


• Kadyampakeni, D.M., R.G. Anderson, and M.P. Schmidt. 2025. Advancing salinity and nutrient management for irrigation science. Irrig. Sci. 43:321–327, https://doi.org/10.1007/s00271-025-01023-y


• De Souza Junior, J.P., D.M. Kadyampakeni, M.A. Shahid, R. de Mello Prado, and J.L. Prieto FajardoG. 2025. Mitigating abiotic stress in citrus: the role of silicon for enhanced productivity and quality. Plant Stress 16:100837,


• https://doi.org/10.1016/j.stress.2025.100837


• Januarie, C.J. and D.M. Kadyampakeni. 2025. Nitrogen fertilization dynamics on one-year-old Dendrocalamus asper (Schult. & Schult.f.) Backer bamboo in Florida, Adv. Bamboo Sci. 11:100150. https://doi.org/10.1016/j.bamboo.2025.100150.


• Bautista, A.S., A. Agenjos, A. Martínez, A.I. Escudero, P. García-Arizo, R. Simeón, C. Meyer, and D.M. Kadyampakeni. 2025. Osmolyte regulation as an avocado crop management strategy for improving productivity under high temperature. Horticult. 11, 245. https://doi.org/10.3390/horticulturae11030245.


• Brewer, M., S.L. Strauss, R. Kanissery, and D.M. Kadyampakeni. 2025. The impacts of legume and non-legume cover crops on the performance of HLB-affected citrus trees. Journal of Plant Nutrition, 48(13):2235-2249. https://doi.org/10.1080/01904167.2025.2474031.


• Sambani, D., T. Vashish, D.B. Bright, and D.M. Kadyampakeni. 2025. The influence of soil pH on citrus root morphology and nutrient uptake efficiency. HortSci. 60(5):657–666. https://doi.org/10.21273/HORTSCI18486-25


• Brewer, M., S.L. Strauss, C. Chase, B. Sellers, D.M. Kadyampakeni, E. van Santen, and R. Kanissery. 2025. Effects of cover crops on weed suppression in the inter-row of citrus orchards. Weed Sci. 73(e15):1-11. https://doi.org/10.1017/wsc.2024.72


• Atta, A.A., K.T. Morgan, S. Hamido, and D.M. Kadyampakeni. 2025. Irrigation optimization enhances water management and tree performance in commercial citrus groves on sandy soil. Irri. Sci. 43:329–346, https://doi.org/10.1007/s00271-024-00938-2


• Liu, D., Li, Z., Wu, Z., and C. Li. 2024. Digital Twin/MARS-CycleGAN: Improved object detection for MARS phenotyping robot.  Journal of Field Robotics. https://doi.org/10.1002/rob.22473


• Jiang, L., L. Fu, and C. Li. 2024. Apple tree architectural trait phenotyping with organ-level instance segmentation from point cloud. Computers and Electronics in Agriculture. 229, 109708.


• Rodriguez-Sanchez, J., J. Snider, K. Johnsen, and C. Li. 2024. Spatiotemporal registration of terrestrial laser scanning data for time-series field phenotyping. Frontiers in Plant Science. 15: 1436120.


• Petti, D., S. Li, and C. Li. 2024. Graph neural networks for lightweight plant organ tracking. Computers and Electronics in Agriculture. 225: 109294.


• Tan, C., J. Sun, A. Paterson, H. Song, C. Li. 2024. Three-View Cotton Flower Counting through Multi-Object Tracking and RGB-D Imagery. Biosystems Engineering. 246: 233-247


• Chen, Y., Xiao, Z., Pan, Y., Zhao, L., Dai, H., Wu, Z., Li, C., Zhang, T., Li, C., Zhu, D. and Liu, T., 2024. Mask-Guided Vision Transformer for Few-Shot Learning. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2024.3418527.


• 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.


• Ye Chu, Josh Clevenger, Kendall Lee, Jing Zhang, Changying Li. Genetic breeding to improve freeze tolerance in blueberries, a review. Horticulturae. 11(6).


• Monica Borghi, C. Li, et al. 2025. Enhancing entomophilous pollination for sustainable crop production. Horticultural Research. 122(4), e70234.


• Tan, C., C. Li, P. Perkins-Veazie, H. Oh, R. Xu, M. Iorizzo. 2025. High throughput assessment of blueberry fruit internal bruising using deep learning models. Frontiers in Plant Science. 16, 1575038.


• Li, Z., R. Xu, C. Li, L. Fu. 2025. Visual Navigation and Crop Mapping of a Phenotyping Robot MARS-PhenoBot in Simulation. Smart Agricultural Technology. 11:100910.


• Li, Z., R. Xu, C. Li, P. Munoz, F. Takeda, and B. Leme. 2025. In-field blueberry fruit phenotyping with a MARS-PhenoBot and customized BerryNet. Computers and Electronics in Agriculture. 232, 110057.

 

Conference Papers/Presentations/Posters

• Huang, Z., and W. S. Lee. 2025. A state space model with tree topology for strawberry detection. AI in Agriculture Conference: The Role of AI in Autonomous Agricultural Systems and Socioeconomic Effects. Starkville, MS, March 31 to April 2, 2025.


• Liu S., Ampatzidis Y., Lee W.S., Zhou C., 2025. Optimizing strawberry harvest planning through machine vision and AI-enabled predictive analytics. AI in Agriculture Conference: The Role of AI in Autonomous Agricultural Systems and Socioeconomic Effects. Starkville, MS, March 31 to April 2, 2025.


• Huang, Z., W.S. Lee, and M. Le. 2025. AI-driven plant tracking and segmentation for precise canopy estimation in strawberry field. ASABE Paper No. 202500347. St. Joseph, MI.: ASABE.


• Kamsikiri, K., A. Atta and D.M. Kadyampakeni. 2025. Comparison of conventional drip and microspinkler irrigation in citrus production systems on Florida sandy soils. ASABE Annual Meeting Conference Proceedings, Toronto, Canada. pp 1-13. https://doi.org/10.13031/aim.202500888


• Kamsikiri K., A. Atta, and D.M. Kadyampakeni. 2025. Comparison of Conventional and Drip Irrigation Systems for Young HLB-Affected Citrus Trees. 136th Florida State Horticultural Society (FSHS) Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Bonda L.F. and D.M. Kadyampakeni. 2025. Impact of nitrogen rates on growth and biomass accumulation of young macadamia trees. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Thompson, T.R. and D.M. Kadyampakeni. 2025. Impacts of nutrient ratios of calcium and zinc on citrus growth and root development. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• de Souza Junior, J.P. and D.M. Kadyampakeni. 2025. Comparative analysis of stabilized and non-stabilized silicon sources on photosynthetic performance of young orange trees. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Ritenour, M.A., A.A. Atta, C. Hu, A. Beany, and D.M. Kadyampakeni. 2025. Tree nutrition effects on postharvest fruit quality and shelf life of ‘Hamlin’ sweet orange. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Iqbal, S., D. Kadyampakeni and M.A. Shahid. 2025. Developing site-specific recommendations on nitrogen application rates and timing for satsuma mandarin production in north Florida. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Atta A., K.T. Morgan, M.A. Ritenour, M.A. Shahid, A. Wright, K. Morgan, M. Zekri, C. Oswalt, D. Williams and D.M. Kadyampakeni. 2025. The impact of phosphorus rates on HLB-affected tree health and performance in sandy soils. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Basar N.U., M.A. Shahid and D.M. Kadyampakeni. 2025. Impact of variable nitrogen rates on the growth and yield of HLB-affected sweet orange trees. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Prieto Fajardo, J.L.G, M. Shahid, W. Hammond, L. Diepenbrock and D.M. Kadyampakeni. 2025. Exploring the potential of silicon nanoparticles to mitigate water stress in citrus. 136th FSHS Annual Meeting, June 8-10, 2025. Bonita Springs, FL. (volunteered)


• Basar, N.U., M.A. Shahid and D.M. Kadyampakeni. 2025. Evaluating the impact of biostimulants on young sweet orange trees grafted onto different rootstocks. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Peddapuli, M., A. AttaP and D.M. Kadyampakeni. 2025. Optimizing nitrogen and phosphorus management for HLB-affected sweet orange. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Agunbiade, L.GM. Nunes and D.M. Kadyampakeni. 2025. Assessing the effects of varying rates of irrigation and potassium fertilization on the growth of Dendrocalamus asper bamboo in Florida. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Sambani, D., T. Vashisth and D.M. Kadyampakeni. 2025. The influence of soil pH on citrus root morphology and nutrient uptake efficiency. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Prieto, J. and D.M. Kadyampakeni. 2025. Exploring the potential of silicon nanoparticles to mitigate water stress in citrus. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Saleem, Y., S. Agehara and D.M. Kadyampakeni. 2025. Effects of reclaimed water on blueberry seedling growth and root morphology. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Kamsikiri, K. and D.M. Kadyampakeni. 2025. Optimizing molybdenum fertilization for young HLB-affected citrus trees. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Thompson, T. and D.M. Kadyampakeni. 2025. Impacts of nutrient ratios of calcium and zinc on citrus growth and root development. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)


• Januarie, C.J., L. Sharma, J. Vendramini, and D.M. Kadyampakeni. 2025. Variable rate fertilization of phosphorus in young Dendrocalamus asper bamboo in Florida. 17th SWES Research Forum, Gainesville, FL. Feb. 10, 2025. (volunteered)

• Petti, D. and C. Li. Active Learning for Real-Time Flower Counting with a Ground Mobile Robot. ASABE Annual International Meeting. Paper Number: 202400607. July 28-31, 2024, Anaheim, California.


• Muller. J, D. Petti, C. Li, S. Gorucu, M. Pilz, and B. Weichelt. Investigating the use of large language models in agricultural injury surveillance. ASABE Annual International Meeting. Paper Number: 202400572. July 28-31, 2024, Anaheim, California

 

Georgia:

• Rayamajhi, A., Lu, G., Tollner, E. W., Williams-Woodward, J., & Mahmud, M. S. (2025). Assessing ornamental tree maturity and spray requirements using depth sensing and LiDAR technologies. Smart Agricultural Technology, 101120.


• Rayamajhi, A., Jahanifar, H., & Mahmud, M. S. (2024). Measuring ornamental tree canopy attributes for precision spraying using drone technology and self-supervised segmentation. Computers and Electronics in Agriculture, 225, 109359.


• Rayamajhi, A. (2024). Precision Sprayer Technologies for Enhanced Ornamental Crop Management (Master's thesis, University of Georgia).

 

Kentucky:

• Dvorak, J. (2025). AI Tools and Text Embedding for Session Organization at ASABE’s Annual International Meeting. Journal of the ASABE, (in press). https://doi.org/10.13031/ja.16328


• Dvorak, J. (2024). Utilizing Super Capacitors to Improve Battery Performance in Electric Mobile Machinery. Applied Engineering in Agriculture, 40(6), 669–677. https://doi.org/10.13031/aea.16062


• Dvorak, J., Smith, B.*. (2024). Powering In-Field Continuous Robotic Systems Using Solar Energy Systems. 67(3): 617-630. Journal of the ASABE. doi: 10.13031/ja.15579

 

Michigan:

Journal Publications

• Xu, J., Lu, Y., 2025. 3D vision-based perception and length estimation of green asparagus for selective harvesting. Journal of the ASABE 68 (2), 239-256.


• Lu, Y., Mohammadi, P., 2025. Automated asparagus harvesting technology: A review of research and developments since the 1950s in the United States and beyond. Computers and Electronics in Agriculture 237, 110744


• Deng, B., Lu, Y., Vander Weide, J., 2025. Development and preliminary evaluation of a YOLO-based fruit counting and maturity evaluation mobile application for blueberries. Applied Engineering in Agriculture 41(3), 391-399.


• Deng, B., Lu, Y., 2025. Weed image augmentation by ControlNet-added stable diffusion for multi-class weed detection. Computers and Electronics in Agriculture 232, 110123.


• Mu, X., Y. Lu, 2025. Non-destructive detection of spotted wing Drosophila infestation in blueberry fruit using hyperspectral imaging technology. Agricultural Communications 3(3), 100096.


• Xu, J., Lu, Y., Deng, B., 2024. Design, prototyping, and evaluation of a new machine vision-based automated sweetpotato grading and sorting system. Journal of the ASABE 67 (5), 1369-1380.


• Deng, B., Lu, Y., Li, Z., 2024. Detection, counting, and maturity assessment of blueberries in canopy images using YOLOv8 and YOLOv9. Smart Agricultural Technology 9, 100620.


• Wade, C., Check, J., Chilvers, M., Dong, Y., (2025). Monitoring leaf wetness dynamics in corn and soybean fields using an IoT (Internet of Things)-based monitoring system. Smart Agricultural Technology. 11, 100919.


• Spafford, J., Hausbeck, M., Werling, B., Tucker, S., Dong, Y., (2025). Development of an Internet of Things (IoT)-Based Disease Forecaster to Manage Purple Spot On Asparagus Fern. Smart Agricultural Technology. 11, 100941.


• Kumari, S., Ali, N., Dagati, M., Dong, Y. (2025). IoT-Enabled Soil Moisture and Conductivity Monitoring Under Controlled and Field Fertigation Systems. AgriEngineering. 7 (7). 207.


• Dong, Y., Tucker, S., Singh, G., Ali, N., Yazdanpanah, N., Vander Wide, J., Sears, M., (2025). Optimizing Soil Moisture Sensor Placement Through Spatial Variability Analysis in Orchards. Smart Agricultural Technology. 10. 101273

 

Conference Papers/Other Publications

• Mu, X., Lu, Y., Deng, , 2025. A comparative benchmark of real-time detectors for blueberry detection towards precision orchard management. arXiv preprint: 2509.20580.


• Xu, J., Lu, Y., 2025. Development and evaluation of a multispectral vision-based automated sweet potato sorting system. Sensing for Agriculture and Food Quality and Safety XVII, 1348402. 


• Deng, B., Lu, Y., Brainard, D., 2025. Semi-Supervised Weed Detection in Vegetable Fields: In-domain and Cross-domain Experiments. arXiv preprint:2502.17673. Paper presented at the 2025 AgriControl Conference.


• Deng, B., Lu, Y., 2025. Weed image augmentation by IP-adapter-based stable diffusion for multiclass weed detection. Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications III; 1345909.


• Deng, B., Lu, Y., Brainard, Improvements and Evaluation of a Smart Sprayer Prototype for Weed Control in Vegetable Crops. 2025 ASABE Annual International Meeting 2500323


• Singh, N., Lu, Y., 2025. Development and laboratory assessment of cutting and snapping mechanisms for green asparagus harvesting. 2025 ASABE Annual International Meeting 2500323.

 

Mississippi:

• Li, Jiajia, Xinda Qi, Seyed Hamidreza Nabaei, Meiqi Liu, Dong Chen, Xin Zhang, Xunyuan Yin, and Zhaojian Li. "A survey on 3D reconstruction techniques in plant phenotyping: from classical methods to neural radiance fields (NeRF), 3D Gaussian splatting (3DGS), and beyond." arXiv preprint arXiv:2505.00737 (2025).


• Chen, Dong, and Yanbo Huang. "Integrating Reinforcement Learning and Large Language Models for Crop Production Process Management Optimization and Control through A New Knowledge-Based Deep Learning Paradigm." Computers and Electronics in Agriculture (2025).


• A Comparative Study of Deep Reinforcement Learning for Crop Production Management Joseph Balderas, Chen, Dong, Yanbo Huang, Li Wang, Ren-Cang Li, Smart Agriculture Technology, 2025


• Seyed Hamidreza Nabaei, Ryan Lenfant, Viswajith Govinda Rajan, Dong Chen, Michael P Timko, Bradford Campbell, Arsalan Heydarian, “Detecting Plant VOC Traces Using Indoor Air Quality Sensors”, Indoor Air (2025)

 

New York:

• Kanaley, K., Murdock, M.J., Qiu, T. et al. Maui: modular analytics of UAS imagery for specialty crop research. Plant Methods 21, 65 (2025). https://doi.org/10.1186/s13007-025-01376-7


• Liu, E., Gold, K. M., Cadle‐Davidson, L., Kanaley, K., Combs, D., & Jiang, Y. (2025). PhytoPatholoBot: Autonomous Ground Robot for Near‐Real‐Time Disease Scouting in the Vineyard. Journal of Field Robotics.


• Kanaley, K., Combs, D. B., Paul, A., Jiang, Y., Bates, T., & Gold, K. M. (2024). Assessing the capacity of high-resolution commercial satellite imagery for grapevine downy mildew detection and surveillance in New York state. Phytopathology®, 114(12), 2536-2545.


• Kanaley, K., Murdock, M., Liu, E., Romero, F., Paul, A., Chadwick, D., ... & Gold, K. (2024, December). Leveraging Thermal, Multi-and Hyperspectral UAS Data to Monitor Disease Impacts on Grapevine Physiology. In AGU Fall Meeting Abstracts (Vol. 2024, pp. GC32A-01).


• Yu, J., Jakubowski, R., Bates, T., Jiang, Y., & Chen, C. (2024). Integrating Hyperspectral Imaging and Machine Learning for Non-Destructive Damage Detection of Grapes. In 2024 ASABE Annual International Meeting (p. 1). American Society of Agricultural and Biological Engineers.

 

Pennsylvania:

Journal Articles:

• Pawikhum, K., Yang, Y., He, L., & Heinemann, P. (2025). Development of a machine vision system for apple bud thinning in precision crop load management. Computers and Electronics in Agriculture 236, 110479.


• Hua, W., Heinemann, P., & He, L. (2025). Frost management in agriculture with advanced sensing, modeling, and artificial intelligent technologies: A review. Computers and Electronics in Agriculture 231, 110027.


• Li, J., Lammers, K., Yin, X., Yin, X., He, L., Sheng, J., Lu, R., & Li, Z. (2025). MetaFruit meets foundation models: Leveraging a comprehensive multi-fruit daaset for advancing agricultural foundation models. Computers and Electronics in Agriculture 231, 109908.


• Kang, C., Mu, X., Seffrin, A.N., Di Gioia, F., & He, L. (2025). A recursive segmentation model for bok choy growth monitoring with Internet of Things (IoT) technology in controlled environment agriculture. Computers and Electronics in Agriculture 230, 109866.


• Hua, W., He, L., Heinemann, P., & Zhu, M. (2025). Precision heating strategy based dynamic heater path planning for frost protection in apple orchards. Biosystems Engineering 250: 117-132.


• Yang, Y., Mali, P., Arthur, L., Molaei, F., Atsyo, S., Geng, J., He, L., & Ghatrehsamani, S., (2025). Advanced technologies for precision tree fruit disease management: A review. Computers and Electronics in Agriculture 229, 109704.


• Pawikhum, K., He, L., Heinemann, P., & Bock, R.G. (2025). Design of End-Effectors for Thinning Apple in the Green Fruit Stage. Journal of the ASABE 68(2), 465-476.


• Majeed, Y., Fu, L., & He, L. (2024). Artificial intelligence-of-things (AIoT) in precision agriculture. Frontiers in Plant Science 15, 1369791.


• Kang, C., He, L., & Zhu, H. (2024). Assessment of spray patterns and efficiency of an unmanned sprayer used in planar growing systems. Precision Agriculture 25(5), 2271-2291.


• Hussain, M., He, L., Schupp, J., Lyons, D., & Heinemann, P. (2024). Green fruit‐stem pairing and clustering for machine vision system in robotic thinning of apples. Journal of Field Robotics 2024: 1-28.


• Hua, W., Heinemann, P., & He, L. (2024). Heat transfer modeling with fixed and mobile heaters for frost protection in apple orchards. Computers and Electronics in Agriculture 227, 109525.


• Mu, X., He, L., Heinemann, P., Schupp, J., Karkee, M., & Zhu, M. (2024). UGV‐based precision spraying system for chemical apple blossom thinning on trellis trained canopies. Journal of Field Robotics 2024: 1-12.

Extension Articles:

• Kang, C., He, L., and Peter, K. (2024). A low-cost microclimate monitoring system for orchard disease management. Pennsylvania Fruit News. 


• Arthur, L., Brunharo, C., Hussain, M., and He, L. (2024). Precision weed management in tree fruit orchards. Pennsylvania Fruit News.


• Mahnan, S., He, L., and Pecchia, J. (2025). Overview of button mushroom harvesting technologies. Penn State Extension.

Thesis and Dissertation:

• Basnet, Akash. (2024). Design of machine vision system and an end-effector for robotic apple harvesting in orchards. MS Thesis. The Pennsylvania State University.


• Yang, Yanqiu. (2025). Innovative integrated pest management: Data-driven approaches and noninvasive technologies for enhanced monitoring and decision-making in specialty crops. PhD Dissertation. The Pennsylvania State University.


• Geng, Jiarui. (2025). Multi-system framework for insect monitoring: From laboratory imaging to field applications. MS Thesis. The Pennsylvania State University.

 

Texas:

• Kuruppuarachchi, Chamika, Fnu Kulsoom, Hussam Ibrahim, Hamid Khan, Azlan Zahid, and Mazhar Sher. 2024. “Advancements in Plant Wearable Sensors.” Computers and Electronics in Agriculture 229: 109778.


• Majeed, Yaqoob, Mike O. Ojo, and Azlan Zahid. 2024. “Standalone Edge AI-Based Solution for Tomato Diseases Detection.” Smart Agricultural Technology 9: 100547.


• Ikram, Muhammad, Sikander Ameer, Fnu Kulsoom, Mazhar Sher, Ashfaq Ahmad, Azlan Zahid, and Young Chang. 2024. “Flexible Temperature and Humidity Sensors of Plants for Precision Agriculture: Current Challenges and Future Roadmap.” Computers and Electronics in Agriculture 226:109449.


• Bashir, Al, Yaqoob Majeed, and Azlan Zahid. 2024. “Development of an End-Effector for Robotic Harvesting of Hydroponic Lettuce.” In 2024 ASABE Annual International Meeting, Paper Number: 2400401 doi:10.13031/aim.202400401


• Ojo, Mike O., Azlan Zahid, and Joseph G. Masabni. 2024. “Estimating Hydroponic Lettuce Phenotypic Parameters for Efficient Resource Allocation.” Computers and Electronics in Agriculture 218: 108642.

 

 

09/20/2026

Michigan State University

Journal Publications

• Xu, J., Lu, Y., 2026. A Machine Vision-Based Online Apple Grading System toward Infield Sorting. Journal of the ASABE 69(5): 699-710.


• Deng, B., Lu, Y., 2026. Toward Generalizable Crop-Weed Detection with Vision-Language Models. Smart Agricultural Technology 15, 102512.


• Deng, B., Lu, Y., 2026. DINOv3 meets YOLO26 for enhanced crop-weed detection toward precision vegetable weeding. Computers and Electronics in Agriculture 255, 112344.


• Deng, B., Lu, Y, Siemens, M., Brainard, D., 2026. Dye-Based Field Evaluation of an Integrated High-Precision Smart Sprayer for Weed Control in Vegetables. Precision Agriculture 27, 124.


• Deng, B., Lu, Y., Brainard, D., 2026. Improvements and evaluation of a smart sprayer prototype for weed control in vegetable crops. Journal of the ASABE 69 (1), 149-163.


• Mu, X., Lu, Y., Deng, B., 2026. A Comparative Benchmark of Real-time Detectors for Canopy Image-Based Blueberry Detection toward Precision Orchard Management. Sensors 26(14), 4373.


• Deng, B., Lu, Y., Brainard, D., 2026. Development and Preliminary Evaluation of a Machine Vision-Guided Smart Sprayer Prototype towards Precision Vegetable Weeding. Journal of Field Robotics 43(3), 1973-1987.


• Xu, J., Lu, Y., 2026. Development and Systematic Evaluation of An Innovative Multispectral Vision-Based Sweetpotato Grading and Sorting System. Smart Agricultural Technology 14, 102204.


• Singh, N., Lu, Y., 2026. Development and Laboratory Assessment of Automatic Selective Harvesting Mechanisms of Green Asparagus. Smart Agricultural Technology 14, 102022.


• Singh, N., Lu, Y., Tian, Y., Islam, M.K., 2026. A Deep Learning-based Framework with Geometric-Prior Fusion for 3D Vision-Based Online Sweetpotato Volume Estimation. Food Bioscience 81, 109164.


• Singh, N., Lu, Y., 2026. Non-destructive Detection of Pits in Cherries using Shortwave Infrared Hyperspectral Transmittance Imaging. Food BioScience 75, 108201.


• Deng, B., Lu, Y., Brainard, D., 2025. Semi-Supervised weed detection in vegetable fields: in-domain and cross-domain experiments. IFAC-PapersOnLine 59 (23), 96-101.

Conference Papers

• Singh, N., Lu, Y., 2026. Detection of pits in cherries using shortwave- infrared (SWIR) hyperspectral imaging. 2026 SPIE LASE, Photonic Technologies in Plant and Agricultural Science III, 1388706.


• Deng, B., Lu, Y., 2026. Fundamental vision-language models for crop- weed detection. 2026 SPIE Defense + Security, Multimodal Image Exploitation and Learning, 140270J.


• Singh, N., Lu, Y., 2026. Preliminary development and evaluation of a vision-guided automated chestnut picking with a Delta arm and vacuum end-effector. 2026 SPIE Defense + Security, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping XI; 1404509.


• Yeafi, A., Lu, Y., Rett-Cadman, S., Vander Weide, J., Miles, T., 2026. Hyperspectral structured-illumination reflectance imaging for early- stage rot detection in blueberries. 2026 SPIE Defense + Security, Sensing for Agriculture and Food Quality and Safety XVIII, 1405303.


• Zhang, J., Lu, Y., 2026. A 3D-Guided Deep Learning Pipeline for Apple Grading Under Stem/Calyx-Defect Ambiguity. 2026 SPIE Defense + Security, Sensing for Agriculture and Food Quality and Safety XVIII, 1405309.


• Tian, Y., Lu, Y., 2026. Deep learning-enabled hyperspectral imaging for detecting light bruises in apples toward in-field grading. 2026 SPIE Defense + Security, Sensing for Agriculture and Food Quality and Safety XVIII, 140530E


• Islam, M.K., Lu, Y., Brainard, D., 2026. Using 3D vision for differential height-based mechanical weeding of vegetables. 2026 SPIE Defense + Security, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping XI, 1404503.


• Liu, D., Lu, Y., 2026. RGB-D Perception for Selective Harvesting of Field-Grown Asparagus with Dual-Path Detection and Point-Cloud-Free Measurement. 2026 ASABE Annual International Meeting 2600512.


• Kong, Z., Lu, Y., 2026. Preliminary Evaluation of 3D Machine Vision for Online Inspection and Grading of Green Asparagus. 2026 ASABE Annual International Meeting 2600766.


• Yeafi, A., Lu, Y., Rett-Cadman, S., Vander Weide, J., 2026. From Hyperspectral to Multispectral Light Scattering Imaging for Blueberry Rot Detection. 2026 ASABE Annual International Meeting


• Mu, X., Lu, Y., 2026. Development and Evaluation of an Integrated, Selective Harvesting System for Green Asparagus. 2026 ASABE Annual International Meeting 2600263.


• Tian, Y., Lu, Y., 2026. Preliminary Development and Evaluation of A Multispectral Vision-based In-field Apple Grading and Sorting System. 2026 ASABE Annual International Meeting 2600536.


• Zhang, J., Lu, Y., 2026. An Integrated Real-Time Vision System for Apple Grading and Sorting based on Object-Centric DINOv3 Representations. 2026 ASABE Annual International Meeting 2601309.


• Mu, X., Lu, Y., 2026. In-Orchard Detection of Spotted Wing Drosophila Infestation of Blueberries Using A Ground-based Hyperspectral Imaging System. 2026 ASABE Annual International Meeting 2600107.


• Amjad, H., Lu, Y., Tian, Y., 2026. Design and Development of An Open- Source Graphical User Interface for Real-Time Multispectral Apple Grading and Sorting. 2026 ASABE Annual International Meeting 2600080.

Mississippi State University

• Weilong He, Xingjian Li, Yuxi Chen, Prem Raj, Charles Fleming, Dong Chen, Manoj Karkee, and Lirong Xiang. 2026. From Pixels to Physics: A Unified Synthetic Data Generation Framework for Robust Agricultural AI. Artificial Intelligence Review, DOI: 10.1007/s10462-026-11658-8


• Yican Yang, Mohan K. Bista, Alekhya Chakravaram, Nisarga Kodadinne Narayana, Raju Bheemanahalli, Lorin Harvey, Dong Chen, Nuwan K. Wijewardane, Smartphone-Based High-Fidelity 3D Semantic Segmentation of Finger Millet Panicles Using 3D Gaussian Splatting for Automated Phenotyping and Yield Estimation. Smart Agriculture Technology, DOI: 10.1016/j.atech.2026.102252


• Jingyi Wu, Tongyin Li, Jiajia Li, Dong Chen, and Qianwen Zhang. 2026. Horticultural Strategies for Enhancing Yield and Quality in Hydroponic Microgreens: A Comprehensive Review. Horticulturae, DOI: 10.3390/horticulturae12050595


• Jiajia Li, Keyi Zhu, Qianwen Zhang, Dong Chen, Qi Sun, and Zhaojian Li. 2026. Object-Centric 3D Gaussian Splatting for Strawberry Plant Reconstruction and Phenotyping. Smart Agriculture Technology, DOI: 10.1016/j.atech.2026.101810


• Jiajia Li, Xinda Qi, Seyed Hamidreza Nabaei, Meiqi Liu, Dong Chen, Xin Zhang, Xunyuan Yin, Zhaojian Li. 2025. A survey on 3D reconstruction techniques in plant phenotyping: from classical methods to neural radiance fields (NeRF), 3D Gaussian splatting (3DGS), and beyond, Plant Phenomics, DOI: 10.1016/j.plaphe.2025.100137


• Joseph Balderas, Dong Chen, Yanbo Huang, Li Wang, Ren-Cang Li. 2025. A Comparative Study of Deep Reinforcement Learning for Crop Production Management, Smart Agriculture Technology, DOI:10.1016/j.atech.2025.100853


• Cheng Ouyang, Moeen Ul Islam, Kaixiang Zhang, Zhaojian Li, Xiaobo Tan, and Dong Chen. 2026. Deep Reinforcement Learning-Enhanced Event- Triggered Data-Driven Predictive Control for a 3D Cable-Driven Soft Robotic Arm. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)


• Moeen Ul Islam, Cheng Ouyang, Xinda Qi, Azlan Zahid, Xiaobo Tan, Dong Chen. 2026. A Novel Modular Cable-Driven Soft Robotic Arm with Multi- Segment Reconfigurability. IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)


• Ouyang, Cheng, Moeen Ul Islam, Dong Chen, Kaixiang Zhang, Zhaojian Li, and Xiaobo Tan. 2026. Direct Data-Driven Predictive Control for a Three-dimensional Cable-Driven Soft Robotic Arm. IEEE American Control Conference (ACC)

Penn State University

Journal Publications

• Arthur, L., Mahnan, S., He, L., Hussain, M., Heinemann, P., & Brunharo, C. 2025. YOLOv7-CBAM and DeepSORT with pixel grid analysis for real-time weed localization and intra-row density estimation in apple orchards. Computers and Electronics in Agriculture 239, p.111071.


• Kang, C., Kumar, S. K., & He, L. 2025. Integrating computer vision and precision sprayers for targeted green fruit chemical thinning. Precision Agriculture 26(5), 86.


• Pawikhum, K., Yang, Y., He, L., & Heinemann, P. 2025. Development of a machine vision system for apple bud thinning in precision crop load management. Computers and Electronics in Agriculture 236, p.110479.


• Wang, W., Ghatrehsamani, SH. 2026. Early Detection of Plant Pathogens in the Asymptomatic Phase: A Scoping Review of Hyperspectral Imaging Combined with Machine Learning. Smart Agriculture Technology, 14, (2026).


• Bessaad, N., Atsyo, S., Hanjie, D., Walkine, I., Rajveer, D. and He, L., 2026. Autonomous mowing in agriculture: Current status, needs, and future opportunities. Smart Agricultural Technology, p.101796.


• Han, K., Hua, W. and He, L., 2026. What’s next in agri-vision: A review of Vision Transformers and Vision Mamba in crop management. Computers and Electronics in Agriculture, 245, p. 111551.


• Pawikhum, K., Yang, Y., He, L., Pecchia, J.A. and Heinemann, P., 2026. Design and Performance Evaluation of a Vacuum-Based Twist–Bend End-Effector for Automated Mushroom Harvesting with Vision-Based Damage Assessment. AgriEngineering, 8(4), p.151.


• Mahnan, S., Arthur, L., He, L., Ghatrehsamani, S., Heinemann, P. and Pecchia, J., 2026. Development of a decision-making algorithm to identify picking strategies for robotic mushroom harvesting. Computers and Electronics in Agriculture, 247, p.111753.


• Dou, H., Kang, C., Kumar, S.K. and He, L., 2026. AI-driven precision chemical thinning system and evaluation method for variable-rate application in apple orchards. Artificial Intelligence in Agriculture. Available online in June 2026.

Extension articles

• Mahnan, S., He, L. & Pecchia, J. (2025). "An overview of button mushroom harvesting technologies." Penn State Extension.


• Kang, C., He, L., & Peter, K. (2025). "A low-cost microclimate monitoring system for orchard disease management." Pennsylvania Fruit News.


• Arthur, L., Brunharo, C., Hussain, M., & He, L. (2025). "Precision weed management in tree fruit orchards." Pennsylvania Fruit News.

Thesis and Dissertation

• Luke Jeffery. 2026. Overcoming occlusion: comparative evaluation of vacuum end-effectors and airflow-assistance for robotic apple harvesting. MS Thesis. The Pennsylvania State University

 

Texas A&M University

• Wang, Y., Ojo, M. O., Zahid, A. 2026. Automated IoT-Enabled Greenhouse Microclimate Prediction using Multivariate Sequence-to-Sequence LSTM- based   Encoder-Decoder,  Internet of Things, 38, 102015 https://doi.org/10.1016/j.iot.2026.102015


• Bua, C., Ojo, M. O., Wang, Y., Giordano,  ,  and  Zahid,  A.  2026. Virtual Sensor and Reinforcement  Learning-Driven  Digital  Twin  for Multi-Zone Greenhouse  Lighting  Control,  IEEE  Internet  of  Things Journal, doi: 10.1109/JIOT.2026.3711085


• Bua, C., Ojo, M. O., Wang, Y., Giordano, S., and Zahid,    2026.  A Multi-Digital Twin Paradigm using Reinforcement Learning  and  Virtual Sensing  in  Greenhouse  Lighting  Control,   IEEE   Transactions on Industrial Informatics, 1-12. https://doi.org/10.1109/TII.2026.3691992


• Bua, C., Wang, Y., Ojo, M. O., Bashir, A., Giordano, S., and Zahid, A. Modeling PPFD Propagation and Transmittance in ePAR Spectrum for Canopy and Intra-Canopy Adaptive Greenhouse Lighting,  Computers and Electronics in Agriculture, 251, 111969. https://doi.org/https://doi.org/10.1016/j.compag.2026.111969


• Bashir, A., Ghose, P., and Zahid, A. 2026. ALF-PoseNet: An Attention- Based Lightweight Fruit Pose Estimation Network,  Proceedings  of  the IEEE/CVF Conference on Computer Vision and Pattern Recognition  (CVPR) Workshops, 2026, pp. 9692-9701


• Ojo, M., Wang, Y., Bua, C., Sher, M., and  Zahid,    2026.  A  crop digital twin system for  predictive  growth  monitoring  and  adaptive light control  in  controlled  environment  agriculture.  Internet  of Things, 37, 101935. https://doi.org/10.1016/j.iot.2026.101935


• Bua, C., Wang, Y., Ojo, M. O., Giordano,  ,  and  Zahid,  A.  2026. Digital  Twin-Enabled  Multi-Zone Adaptive Lighting   Control in Greenhouses Using Reinforcement Learning Optimization,   Smart Agricultural Technology 14,  101984 https://doi.org/10.1016/j.atech.2026.101984


• Rao, X., Zahid,  ,  Ye,  X.,  Jain,  D.,  and  Duffield,  N.  2026. Controlled Environment Agriculture as Urban Infrastructure:  Advancing a  Public  Agenda for  Spatial  Equity,  Urban  Informatics,  5,  18. https://doi.org/10.1007/s44212-026-00109-y

 

University of Arizona

• Deng, B., Lu, Y., Siemens, M.C., & Brainard, D. (2026). Dye-based field evaluation of an integrated high-precision smart sprayer for weed control in vegetables. Precision Ag., 27:124. https://doi.org/10.1007/s11119-026- 10425-7.


• Deng, B., Yuzhen, L., Siemens, M.C. & Brainard, D. (2025). Field test and evaluation of a smart sprayer for precision weeding. Symposium of Digital Agriculture (SyDAg), Abstr., Purdue University, West Lafyette, Ind. https://doi.org/10.5703/1288284318201.

 

University of Georgia

• Malik, M. E., Basinger, N., Kurum, M., Rains, G., & Mahmud, M. S. (2026). Trajectory-synchronized diode laser actuation and dose-response field evaluation for precision weed control using a delta robot. Computers and Electronics in Agriculture, 255, 112306.


• Rayamajhi, A., Malik, M. E., & Mahmud, M. S. (2026). SpotChecker: A Deep Learning and Language Model-Powered Web Application for Intelligent Leaf Spot Segmentation, Quantification, and Disease Analytics in Dogwood (Cornus spp.). Smart Agricultural Technology, 102162.


• Malik, M. E., & Mahmud, M. S. (2026). 3D sensing and perception for precision weed management: a review of modalities, reconstruction pipelines, and context-aware detection. Computers and Electronics in Agriculture, 240, 111219.


• Thayananthan, T., Zhang, X., Harjono, J., Huang, Y., Liu, W., McWhirt, A. L., Threlfall, R. T., & Chen, Y. (2025). In-field multi-ripeness blackberry detection for soft robotic harvesting. Journal of the ASABE, 68(6), 1073-1089.


• Yang, Y., Wijewardane, N. K., Harvey, L., & Zhang, X. (2025). Beyond flips and rotations: Evaluating NeRF and 3DGS-based synthetic view augmentation: A case study of detecting visual skinning damage on sweetpotato storage roots. Journal of Agriculture and Food Research, 24, 102517.


• Yadav, S. A., Huang, Y., Zhu, K. Q., Haque, R., Young, W., Harvey, L., Hall, M., Zhang, X., Wijewardane, N. K., Qin, R., Feldman, M., Yao, H., & Brooks, J. P. (2025). Deep transfer learning for UAV-based cross-crop yield prediction in root crops. Remote Sensing, 17(24), 4054.

 

University of Kentucky

• Martin, S., Dvorak, J., Semmens, K., Ford, B. (2026). Short-Term Dissolved Oxygen Forecasting in Aquaculture Systems Using a Process-Based Mass-Balance Model. Water, 18(13). https://doi.org/10.3390/w18131618 (Obj 5)


• Oloyede, A. A., Dvorak, J., Adedeji, A. A. (2026). Integration of Hyperspectral Imaging and Machine Learning for Detection of Gluten Source Contamination in Gluten-Free Products. Food Analytical Methods, 19(9), 245. https://doi.org/10.1007/s12161-026-03145-1 (Obj 2)


• Dvorak, J. (2026). Optimizing ASABE AIM Session Creation with Text Clustering and LLMs. Journal of the ASABE, 69(2), 303–317. https://doi.org/10.13031/ja.16435 (Obj 5)


• Dvorak, J., Shacklett, B., Barnes, M. (2025). Thermal Infrared Arrays for Human Presence Perception Systems in Highly Autonomous Agricultural Machinery. Journal of Agricultural Safety and Health, 31(3), 203–216. https://doi.org/10.13031/jash.16175 (Obj 5)

 

University of Tennessee

• Ahmed, S., Michalik, N., Chen, L., Fulcher, A., Gan, H. (2026). An Adaptive Control Strategy for Robotic Harvesting of Pot-in-Pot Nursery Systems. ASABE Annual International Meeting, Indianapolis, IN.


• Michalik, N., Ahmed, S., Chen, L., Fulcher, A., Gan, H. (2026). Development of an Adaptive End-Effector for Production Pot Extraction in Pot-In-Pot Nursery Production. ASABE Annual International Meeting, Indianapolis, IN.


• Chen, L., Ahmed, S., Michalik, N., Fulcher, A., Gan, H. (2026). Per- Tree Autonomous Navigation Method for Pot-in-Pot Nursery Robots Based on Multi-Cue Perception and Lateral Visual Servoing. ASABE Annual International Meeting, Indianapolis, IN.


• Chen, L., Ahmed, S., Michalik, N., Fulcher, A., Gan, H. (2026). Point Cloud Completion for Automated Phenotyping of Nursery Trees Using RGB- D Sensing. ASHS Annual Conference, Dallas, TX.


• Ahmed, S., Michalik, N., Chen, L., Fulcher, A., Gan, H. (2026). Evaluation of Contact Detection Strategies for a Gravity-Based End- Effector in Robotic Pot-in-Pot Harvesting. ASHS Annual Conference, Dallas, TX.

 

Cornell University

Journal publications

• Hosseinzadeh, S., Paul, A., Underhill, A., Cadle-Davidson, L., Duplais, C., Jiang, Y., and Gold, K.M. 2026. Scalable hyperspectral imaging for non-destructive, quantitative, real-time monitoring of fungicide residues on grapevine. Phytopathology. Accepted. Obj. 1, 2.


• Pippi, L., et al. 2026. [Title: hyperspectral pre-symptom sensing of grapevine downy mildew and spray program evaluation]. Plant Disease. Accepted. Obj. 1, 2.


• Yu, et al. HyperBird: an automated hyperspectral imaging platform for high-throughput plant phenotyping. Plant Phenomics. Accepted Obj. 2.

Conference publications

• Jin, D., Gunner, N., Carvajal Janke, N., Baruah, S., Gold, K.M., and Jiang, Y. 2025. Aleks: AI powered multi agent system for autonomous scientific discovery via data-driven approaches in plant science. arXiv:2508.19383. Obj. 5.


• Jin, D., et al. 2026. [Title: Aleks 2.0]. ASABE Annual International Meeting 2026. Obj. 5.

 

University of California, Davis

Journal Publications

• Elliott, A., Anand, S., Craig Heller, H., Orellana, E., Nieves, M. C., Ley, C., ... & Parsonnet, J. (2026). Beyond Water, Rest, and Shade: Advancing Farmworker Heat Protection Through Partnership. American Journal of Industrial Medicine.


• Wong, C., & Moghimi, A. (2025). Stakeholder mapping of precision weeding commercialization ecosystem in California. Agricultural Systems, 222, 104152. https://doi.org/10.1016/J.AGSY.2024.104152


• Xu, N., Daccache, A., Ahmadi, A., Houtz, D., & Perez-Barquero, F. P. (2025). Soil moisture estimation with microwave remote sensing: a systematic review and meta analysis. International Journal of Digital Earth, 18(1), 1–27. https://doi.org/10.1080/17538947.2025.2468413


• Fu, K., Zhu, Y., Frehner, E., Rizzo, K., Vougioukas, S. G., Bailey, B. (2025). Analysis of the Potential Improvement of Mechanical Fresh-Market Fruit Harvesting Efficiency Utilizing a Dynamically Adjustable Multi-Level Fruit Catching and Retrieval System. Smart Agricultural Technology, 12, 101228.


• Wei, P., Peng, C., Lu, W., Zhu, Y., and Vougioukas, S.G. (2025). Efficient and Safe Trajectory Planning for Autonomous Agricultural Vehicle Headland Turning in Cluttered Orchard Environments. IEEE Robotics and Automation Letters, 10(3), 2574–2581.


• Vougioukas, S. G., Karkee, M., Devadoss, S., Gallardo, K., Charlton, D. (2025). Mechanization Efforts in Fruit Harvesting. Choices, 2nd Quarter 40(2), 3–9.


• Karkee, M., Vougioukas, S. G., Devadoss, S., Bhusal, S. (2025). Mechanization Efforts in Fruit Tree Pruning and Thinning. Choices, 2nd Quarter 40(2), 10–15.


• Hosseini, P., Hanson, B. D., Fatino, M., & Mesgaran, M. B. (2026). A growing degree day-based multiphasic model of phenological transitions in branched broomrape (Phelipanche ramosa). Weed Science, 74(1), e10.


• Nansen, C., Lee, H. and Mesgaran, M.B. (2025). Experimental design issues associated with classifications of hyperspectral sensing data. Precision Agriculture, 26(5), p.80.


• Narimani, M., Pourreza, A., Moghimi, A., Farajpoor, P., Jafarbiglu, H. and Mesgaran, M.B. (2025). Early detection of branched broomrape (Phelipanche ramosa) infestation in tomato crops by using leaf spectral analysis and machine learning. IFAC-PapersOnLine, 59(23), 114–119.


• dos Santos, F. F. L., & Khorsandi, F. (2025). Quantifying the Impact of Load Characteristics on the Static Stability of Agricultural All-Terrain Vehicles. Results in Engineering, 29, 108696.


• Khorsandi, F., Wong, J., & de Moura Araujo, G. (2025). Is it Safe for Children to Ride Youth-Sized All-Terrain Vehicles? Journal of Safety Research, 94, 216–228.


• Khorsandi, F., Farhadi, P., Denning, G., Grzebieta, R., Gibbs, J., Godler, Y., Heydinger, G., Hicks, D., Jennissen, C., Lundqvist, P., McIntosh, A., Rechnitzer, G., Simmons, K., & Yoder, A. (2025). Advancing All-Terrain Vehicle Safety in Agriculture: An Insightful Summary from Global Experts. Journal of Agricultural Safety and Health, 31(3), 173–202.


• Lincoln, J., Gorucu, S., Khorsandi, F., Aby, G. R., Elliott, K. C., Shutske, J., & Issa, S. F. (2025). Occupational Safety Research Needs in the Field of Robotics and Autonomous Machines in Agriculture. Journal of Agricultural Safety and Health, 31(3), 217–230.


• Shutske, J. M., Issa, S. F., Johnson, T., Khorsandi, F., Pate, M. L., Gorucu, S., Walsh, J., Yoder, A. M., Dukes, E., Aby, G. R., & Versweyveld, J. (2025). SAFER AG-Risk Assessment, Data, Design Standards, and Regulation: Needs and Recommendations. Journal of Agricultural Safety and Health, 31(1), 1–13.


• Shutske, J. M., Issa, S. F., Khorsandi, F., Pate, M. L., Gorucu, S., Walsh, J., Yoder, A. M., Aby, G. R., & Li, S. (2025). SaferAg-Engineering Safety in Emerging Agricultural Machinery: Risk Assessment, Data Needs, and Standards. Journal of Agricultural Safety and Health, 31(4), 311–324.


• Farajpoor, P., Pourreza, A., Narimani, M., El-Kereamy, A., & Fidelibus, M. W. (2025). Multi-trait spectral modeling for estimating grapevine leaf traits and nutrients. Plant Phenomics, 7, 100142. https://doi.org/10.1016/j.plaphe.2025.100142


• Pourreza, A., Kamiya, Y., Peanusaha, S., Jafarbiglu, H., Moghimi, A., & Fidelibus, M. W. (2025). Nitrogen retrieval in grapevine (Vitis vinifera L.) canopy by hyperspectral imaging. Computers and Electronics in Agriculture, 229, 109717. https://doi.org/10.1016/j.compag.2024.109717


• Chakraborty, M., Pourreza, A., Peanusaha, S., Farajpoor, P., Khalsa, S. D. S., & Brown, P. H. (2025). Integrating hyperspectral radiative transfer modeling and machine learning for enhanced nitrogen sensing in almond leaves. Computers and Electronics in Agriculture, 234, 110195. https://doi.org/10.1016/j.compag.2025.110195


• Oswald, D., Pourreza, A., Chakraborty, M., Khalsa, S. D. S., & Brown, P. H. (2025). 3D radiative transfer modeling of almond canopy for nitrogen estimation by hyperspectral imaging. Precision Agriculture, 26, 12. https://doi.org/10.1007/s11119-024-10207-z

 

University of Florida

• Tan, C., Gao, N., Chu, Y., & Li, C. (2026). BerryFlowerNet: A Customized Convolutional Neural Network for Blueberry Flower Cluster Detection and Flowering Stage Prediction with a Field Phenotyping Robot. Agriculture, 16(11), 1159.


• Wang, X., Choi, D., Adams, D., Ahn, J., Balmant, K., Dias, R., ... & Li, C. (2026). Artificial intelligence‐powered plant phenomics: progress, challenges, and opportunities. The Plant Phenome Journal, 9(1), e70060.


• Lin, Y., Tan, C., Li, C., & Jiang, Y. (2026). SAM-CLIP-Thermal: Leveraging large multimodal models for reliable and scalable annotation in thermal image segmentation for field plant phenotyping. Plant Phenomics, 100264.


• Wang, R. F., Xu, R., Chee, P. W., Wang, H., & Li, C. (2026). A review of visual navigation for agricultural robots in open fields and controlled environments. Computers and Electronics in Agriculture, 248, 111754.


• Balem, Joseph Michael, Chenjiao Tan, Nathália Cássia Ferreira Dias, Mariah Arnold, Sorrel Tran, Paul M. Severns, Paulo José Pereira Lima Teixeira, Changying Li, and Li Yang. "AC‐repeat binding factor–salicylic acid (CBF–SA) module links wound‐induced evaporative cooling to tissue repair in plants." New Phytologist (2026).


• Zhou, Y., Lee, W.S., Gu, Y. et al. Tactile-reactive gripper with an active palm for dexterous manipulation. npj Robot 4, 13 (2026). https://doi.org/10.1038/s44182-026-00079-y.


• Shiyu Liu, Yiannis Ampatzidis, Hengyue Guan, Wenhao Liu, Congliang Zhou, Daeun Choi, Won Suk Lee. 2026. Agrosense v2: An AI-enabled system for precision orchard sensing and tree-level monitoring, Computers and Electronics in Agriculture, 248, 2026, 111797, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2026.111797.


• Kang, S., Lee, W.S. & Ha, Y. Addressing Challenges in Wheat Processing and Storage Through Advanced Approaches. Food Bioprocess Technol 19, 339 (2026). https://doi.org/10.1007/s11947-026-04398-8.


• Huang, Zijing, Won Suk Lee, Ruoyao Qin, Henry Medeiros, Hongyoung Jeon, Heping Zhu. 2026. SDrAwberry: Scale-referenced Depth-Anything-3 long-sequence reconstruction for Strawberry canopy volume estimation. Computers and Electronics in Agriculture. 252, 2026, 112088, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2026.112088.


• Liu, Wenhao, Yiannis Ampatzidis, Benjamin Wilkinson, Won Suk Lee, John K. Schueller. 2026. LiDAR in precision agriculture for orchards and perennial tree crops: bibliometric analysis, sensor technologies, and algorithmic workflows. Computers and Electronics in Agriculture, 254, 2026, 112049, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2026.112049.


• Choi, Chi-Won, Yu-Jin Jeon, Min Jeong Hong, Choon-Tak Kwon, Won Suk Lee, Dae-Hyun Jung. 2026. AI-enhanced hyperspectral imaging approach for precise and non-destructive phase-specific detection of drought stress in Sweet Basil, Smart Agricultural Technology, 15, 2026, 102330, ISSN 2772-3755, https://doi.org/10.1016/j.atech.2026.102330.


• Vijayakumar, V., Costa Neto, A., Ampatzidis Y., Schueller, J., Lee, W. S., & Burks. (2026). Design and evaluation of a PI-controlled robotic smart sprayer for precision herbicide applications with multi-nozzle integration. Precision Agric 27, 2 (2026). https://doi.org/10.1007/s11119-025-10304-7.


• Dutt, N., Choi, D., Ampatzidis, Y., Lee, W. S., Koppal, S. J., & Wang, X. (2026). RD-GuideNet: A Depth-Guided Framework for Robust Detection, Segmentation, and Temporal Tracking of White Button Mushrooms. Sensors, 26(6), 1935. https://doi.org/10.3390/s26061935.


• Zijing Huang, W. S. Lee, Yiannis Ampatzidis, Shinsuke Agehara, Natalia A Peres. (2026). PheMuT: A phenology-informed, multi-modal time-series model for strawberry yield forecasting, Computers and Electronics in Agriculture, Volume 244, 2026, 111526, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2026.111526.


• Sankaramaddi, H., Lee, W. S. & Peres, N. (2026). Time-Series Detection of Leaf Wetness Using a CNN-LSTM-Based Vision System in Strawberry Farming. J. Biosyst. Eng. 51, 19 (2026). https://doi.org/10.1007/s42853-026-00302-6


• Sankaramaddi, H. R., Lee, W. S., Kim, K., & Hong, Y. (2026). 2D-to-3D Image Reconstruction in Agriculture: A Review of Methods, Challenges, and AI-Driven Opportunities. Sensors, 26(6), 1775. https://doi.org/10.3390/s26061775.


• Hallman, L.M.g, J.P. Fox, A.L. Wright, M.A. Ritenour, S.M. Guzman, D.M. Kadyampakeni, and L. Rossi. 2025. Evaluating the impact of cover crops on nutrient uptake, tree growth and juice quality in citrus groves affected by citrus greening: part II – short-term effects in the southeastern United States. J Plant Nutr. https://doi.org/10.1080/01904167.2026.2712975


• Asif, A. , S. Iqbalp, A. Abdullahp, R.M. Balal, F. Avila Rodrigues , J. Pereira de SouzaP, D. Kadyampakeni, Y. Liang, and M.A. Shahid. 2026. Silicon-mediated stress physiology: integrating structural fortification with metabolic reprogramming for resilient agriculture. Plant Stress https://doi.org/10.1016/j.stress.2026.101489


• Abdullah, A.g, S. IqbalP, A. Asifg, K. Leaks, R.M. Balal, D. Kadyampakeni, and M.A. Shahid. 2026. Mitigating freezing stress in citrus: role of seaweed extract in reducing oxidative stress and enhancing metabolic resilience. Scientia Reports https://doi.org/10.1038/s41598-026-60818-x


• Oluwatuyi, T.S.G, D.M. Kadyampakeni, M.G. Lusk. 2026. Harnessing biochar and plant growth-promoting Bacteria for sustainable crop production under reclaimed water irrigation: a review. Journal of Environmental Quality 55:e70209. https://doi.org/10.1002/jeq2.70209


• Shaghaghi, S.G, Golmohammadi, G., Javadi, S.p, Biazar, S.M., Nedhunuri, R.R.g, Mohammadi, K., Bayabil, H., Kadyampakeni, D.M., and Lusk, M.G. 2026. Leveraging advanced deep learning models for large-scale hydrological forecasting in Florida. Stoch Environ Res Risk Assess 40, 122. https://doi.org/10.1007/s00477-026-03259-2


• Saleem, Y.G. and D.M. Kadyampakeni. 2026. Reclaimed water and biochar in southern highbush blueberry production: a review of root-zone chemistry, growth, and solute dynamics. Water 18, 1141, https://doi.org/10.3390/w18101141


• Demard, E.P.p, A. Chuang, J. Burrow, C. Vincent, D. Kadyampakeni, M.M. Dewdney, and L.M. Diepenbrock. 2026. Using extension programming to evaluate tools for the management of huanglongbing (citrus greening) and its associated vector, the Asian citrus psyllid, on young citrus trees in Florida residential landscapes. Horttechnology 36(3):405-417. https://doi.org/10.21273/HORTTECH05840-26


• Bonda, L.F.G, J. Pereira de Souza Jr., A.A. Omar, and D.M. Kadytampakeni. 2026. Physiological and nutritional dynamics of young macadamia trees exposed to nitrogen fertilization under acidic substrate conditions. HortScience 61(5):1017–1025. 2026. https://doi.org/10.21273/HORTSCI19294-26


• St Fort, J.P, D. Kadyampakeni, V. Sharma, M. Dukes, S. Agehara, and C.A. Chase. 2025. Modeling of infiltration dynamics using HYDRUS-1D: Optimizing micro-sprinkler selection for reduced groundwater contamination risk in strawberry production in Florida, USA. Agric. Water Manag. 329:110387. https://doi.org/10.1016/j.agwat.2026.110387


• Hallman, L.M.g, J.P. Fox, A.L. Wright, M.A. Ritenour, S.M. Guzman, D.M. Kadyampakeni, and L. Rossi. 2026. Evaluating the impacts of cover crops in southeast Florida citrus groves affected by citrus greening: part I – effects on soil fertility. J. Plant Nutr. 49(7):1229-1246, https://doi.org/10.1080/01904167.2026.2618671


• Rockwood, D.L., K. Barley, D.M. Kadyampakeni, C.J. JanuarieG, K. KamsikiriG, N.U. BasarG, and C Atchley. 2026. Food and fiber productivity of Asper bamboo in Florida, USA. Agriculture and Food Sciences Research 13(1):1–9. https://doi.org/10.20448/aesr.v13i1.8034.


• Kamsikiri, K.G and D. M. Kadyampakeni. 2026. Variable molybdenum fertilization rate impacts on young HLB-affected citrus trees. HortScience 61(2):263-272. https://doi.org/10.21273/HORTSCI19009-25


• Odogwu J.A.G, M. Lusk, and D.M. Kadyampakeni. 2026. Soil microbial responses to reclaimed water irrigation and implications for soil health. J. Environ. Qual. 55:e70124, https://doi.org/10.1002/jeq2.70124


• Basar, N.U.G, M. Nadeemp, J.S.A. Felix, K. Leaks, N. Qureshig, R.M. Balal, D. Kadyampakeni, and M.A. Shahid. 2026. Influence of nitrogen fertilization rate and application frequency on physical and phytochemical quality of Satsuma Mandarin in north Florida. Scientific Reports 16:92 https://doi.org/10.1038/s41598-025-28848-z

 

University of Massachusetts Amherst

• Clements, J. 2025. ‘Fun’ with Outfield year 3 (continued from years 1 and 2). 2025 Great Lakes Fruit Workers Conference, November 17-19, Grand Rapids, MI. (Poster)


• Clements, J. 2025. ‘Fun’ with Outfield year 3 (continued from years 1 and 2). 2025 Great Lakes Expo, December 9-11, Grand Rapids, MI. (Poster)


• Clements, J. 2025. Using CropvueTM camera traps to monitor those pesky leps in Massachusetts. 2025 Great Lakes Fruit Workers Conference, November 17-19, Grand Rapids, MI. (Poster)


• Clements, J. 2025. Using CropvueTM camera traps to monitor those pesky leps in Massachusetts. 2025 Great Lakes Expo, December 9-11, Grand Rapids, MI. (Poster)


• Clements, J. 2026. Using a UAV to map apple orchard blossom density and fruit variability as a precursor to variable rate spraying for precision apple crop load management. UMass Cold Spring Orchard, July 15, 2026. 120 attendees (growers, government, industry).