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Publications

  1. Pugazhendi, P., Badgujar, C.M,, Ganapathy, M. R., Arumugam, M. (2026) Uncertainty-Aware Deep Learning for Sugarcane Leaf Disease Detection Using Monte Carlo Dropout and MobileNetV3. AgriEngineering, 8(1):31. https://doi.org/10.3390/agriengineering8010031
  2. Kumar, K., Padhiary, M., Hoque, A., Saikia, P., & Badgujar, C. (2025). Self-service innovations in precision agriculture: Redefining farm automation. https://10.4018/979-8-3373-1295-8.ch014    
  3. Gund, R., Badgujar, C., Samiappan, S., Jagadamma, S. (2025). Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review. Agriculture, 15(17), 1799. https://doi.org/10.3390/agriculture15171799 
  4. Badgujar, C. M., Swaminathan, S., & Gerken, A. (2025). Electronic nose for agricultural grain pest detection, identification, and monitoring: A review. Journal of Stored Products Research, 115, 102840. https://doi.org/10.1016/j.jspr.2025.102840
  5. Sapkota, R., Flores-Calero, M., Qureshi, R., Badgujar, C. et.al. (2025). YOLO advances to its genesis: a decadal and comprehensive review of the You Only Look Once (YOLO) series. Artificial Intelligence Review, 58 (9) 274.  https://doi.org/10.1007/s10462-025-11253-3
  6. Yallappa, D., Veerangouda, M., Maski, D., Palled, V., M. Bheemanna, R, S., Ravi, Y., & Badgujar, C., M. (2025). Experimental investigation of drone-based insecticide application for effective pest management in groundnut field crop. Journal of Agricultural Engineering (India), 62(1), 1–15. https://doi.org/10.52151/jae2025621.1916  
  7. Suprabha Raj, A., Badgujar, C. M., Lollato, R., Prasad, P. V. V., & Siliveru, K. (2024). Predicting rheological properties of wheat dough from flour properties using NIR-coupled with artificial neural network. Journal of the ASABE, 67(4), 1023–1035. https://doi.org/10.13031/ja.15851
  8. Praharsha, C. H., Poulose, A., & Badgujar, C. (2024). Comprehensive investigation of machine learning and deep learning networks for identifying multispecies tomato insect images. Sensors, 24(23), 7858. https://www.mdpi.com/1424-8220/24/23/7858
  9. Badgujar, C. M., Gan H., Alwin P. (2024). Agricultural Object Detection with You Only Look Once (YOLO) Algorithm: A Bibliometric and Systematic Literature Review. Computers & Electronics in Agriculture, 223, 109090.  https://doi.org/10.1016/j.compag.2024.109090
  10. Badgujar, C. M., Armstrong, P. R., Gerken, A. R., Pordesimo, L. O., & Campbell, J. F. (2023). Real-time stored product insect detection and identification using deep learning: System integration and extensibility to mobile platforms. Journal of Stored Products Research, 104, 102196. https://doi.org/10.1016/j.jspr.2023.102196
  11. Badgujar, C. M., Armstrong, P. R., Gerken, A. R., Pordesimo, L. O., & Campbell, J. F. (2023). Identifying common stored product insects using automated deep learning methods. Journal of Stored Products Research, 103, 102166. https://doi.org/10.1016/j.jspr.2023.102166
  12. Raj, S. A., Badgujar, C. M., Lollato, R., Prasad, P.V., & Siliveru, K. (2024). Predicting Rheological Properties of Wheat Dough from Flour Properties Using NIR Coupled with Artificial Neural Network. Journal of the ASABE, 67 (4): 1023–35. https://doi.org/10.13031/ja.15851
  13. Biju, J., Badgujar, C., & Poulose, A. (2024). Hybrid horizons: Advancing water potability prediction through hybrid machine learning. 2024 Fifteenth International Conference on Ubiquitous and Future Networks (ICUFN) (pp. 175–180). https://ieeexplore.ieee.org/abstract/document/10625242
  14. Badgujar, C, Das, S., Figueroa, D. M., & Flippo, D. (2023). Application of computational intelligence methods in agricultural soil-machine interaction: A Review. Agriculture, 13(2). https://doi.org/10.3390/agriculture13020357
  15. Badgujar, C, Das, S., Flippo, D., Martinez, D., & Welch, S. (2023). Deep neural network to predict the autonomous ground vehicle behavior on sloping terrain. Journal of Field Robotics. https://doi.org/10.1002/rob.22163
  16. Badgujar, C, Flippo, D., Baldwin, C., & Gunturu, S. (2023). Tree trunk detection of eastern redcedar in rangeland with deep learning technique. Croatian Journal of Forest Engineering. https://doi.org/10.5552/crojfe.2023.2012
  17. Martinez-Figueora, D., Das, S., Badgujar, C., Flippo, D., & Welch, S. J. (2022). A distributed approach for robotic coverage path planning under steep slope terrain conditions. 2022 IEEE Symp. Series on Computational Intelligence (SSCI). https://doi.org/10.1109/SSCI51031.2022.10022252
  18. Schmitz, A., Badgujar, C, Mansur, H., Flippo, D., McCornack, B., & Sharda, A. (2022). Design of a reconfigurable crop scouting vehicle for row crop navigation: A proof-of-concept study. Sensors, 22(16). https://doi.org/10.3390/s22166203
  19. Badgujar, C, Flippo, D., Baldwin, C., & Badua, S. (2022). Development and evaluation of pasture tree cutting robot: Proof-of-concept study. Croatian Journal of Forest Engineering, 44 (1), 11–19. https://doi.org/10.5552/crojfe.2023.1731
  20. Badgujar, C, Flippo, D., Brokesh, E., & Welch, S. (2022). Experimental investigation on traction, mobility & energy usage of the tracked autonomous ground vehicle on a sloped soil bin. Journal of the ASABE.  https://doi.org/10.13031/ja.14860   
  21. Badgujar, C, Flippo, D., & Welch, S. (2022). Artificial neural network to predict traction performance of autonomous ground vehicles on a sloped soil bin and uncertainty analysis. Computers and Electronics in Agriculture, 196, 106867.  https://doi.org/10.1016/j.compag.2022.106867
  22. Badgujar, C, Hui, W., Flippo, D., & Brokesh, E. (2022). Design, fabrication, and experimental investigation of screw auger-type feed mechanism for a robotic wheat drill. Journal of ASABE. https://doi.org/10.13031/ja.15199
  23. Badgujar, C, Mansur, H., & Flippo, D. (2022). Pest-infested soybean leaf image classification with deep learning techniques for integrated pest management (IPM). Conference Proceedings, 2022 ASABE Annual International Meeting, Houston, Texas. https://doi.org/10.13031/aim.202201096  
  24. Badgujar, C., Dhingra, H., Gautam, A., Khurana, R., Mannes, G. (2020). Experimental study on okra planter for sowing of soaked seed. Agricultural Engineering Today, 44 (4) 22-29. https://doi.org/10.52151/aet2020444.1527  
  25. Badgujar, C., Karpe, O., Kalbande, S. (2019). Studies on drying characteristics and techno-economic analysis of sprouted moth beans (Vigna aconitifolia) in solar tunnel dryer. Indian Journal of Agricultural Research, 53 (2). https://doi.org/10.18805/IJARe.A-5180     
  26. Badgujar, C., Dhingra, H., Manes, G., Khurana, R., Gautam, A. (2018). Engineering properties of okra (Abelmoschus esculentus) seed. Journal of Agricultural Research, 55 (4) 722-728. https://doi.org/10.5958/2395-146X.2018.00131.X  
  27. Badgujar, C., Karpe, O., Kalbande, S. (2018). Techno-economic evaluation of solar tunnel dryer for drying of basil (Ocimum sanctum). International Journal of Current Microbiology and Applied Sciences, 7 (07). https://doi.org/10.20546/ijcmas.2018.707.040  
  28. Badgujar, C., Dhingra, H., Manes, G., Khurana, R., (2017). Development and evaluation of inclined plate metering mechanism for soaked okra (Abelmoschus esculentus) Seeds. International Journal of Current Microbiology and Applied Sciences, 6 (12). https://doi.org/10.20546/ijcmas.2017.612.455