Yang, L. B. Application of artificial intelligence in electrical automation control. Procedia Comput. Sci., Proceedings of the 3rd International Conference on Mechatronics and Intelligent Robotics (ICMIR-2019), 166, 292–295 (2020). https://doi.org/10.1016/j.procs.2020.02.097.
Guijarroa, M. et al. Automatic segmentation of relevant textures in agricultural images. Comput. Electron. Agric. 75, 75–83. https://doi.org/10.1016/j.compag.2010.09.013 (2011).
Google Scholar
Civele, C. Development of an IOT based tractor tracking device to be used as a precision agriculture tool for Turkey’s agricultural tractors. Sch. J. Agric. Vet. Sci. 6, 199–203. https://doi.org/10.36347/SJAVS.2019.v06i09.001 (2019).
Google Scholar
Inoue, K., Kaizu, Y., Igarashi, S. & Imou, K. The development of autonomous navigation and obstacle avoidance for a robotic mower using machine vision technique. In IFAC-Paper, 6 IFAC Conference on Sensing, Control and Automation Technologies for Agriculture AGRICONTROL 173–177 (2019). https://doi.org/10.1016/j.ifacol.2019.12.517.
Mogili, U. R. & Deepak, B. B. V. L. Review on application of drone systems in precision agriculture. Procedia Comput. Sci., International Conference on Robotics and Smart Manufacturing (RoSMa2018) 133, 502–509 (2018). https://doi.org/10.1016/j.procs.2018.07.063.
El Hoummaidi, L., Larabi, A. & Alam, K. Using unmanned aerial systems and deep learning for agriculture mapping in Dubai. Heliyon 7, e08154. https://doi.org/10.1016/j.heliyon.2021.e08154 (2021).
Google Scholar
Al-Ali, A. R. et al. IoT-solar energy powered smart farm irrigation system. J. Electron. Sci. Technol. 17, 100017. https://doi.org/10.1016/j.jnlest.2020.100017 (2019).
Google Scholar
Akbarzadeh, S., Paap, A., Ahderom, S., Apopei, B. & Alameh, K. Plant discrimination by support vector machine classifier based on spectral reflectance. Comput. Electron. Agric. 148, 250–258. https://doi.org/10.1016/j.compag.2018.03.026 (2018).
Google Scholar
Wang, A., Zhang, W. & Wei, X. A review on weed detection using ground-based machine vision and image processing techniques. Comput. Electron. Agric. 158, 226–240. https://doi.org/10.1016/j.compag.2019.02.005 (2019).
Google Scholar
Cai, J., Xiao, D., Lv, L. & Ye, Y. An early warning model for vegetable pests based on multidimensional data. Comput. Electron. Agric. 156, 217–226. https://doi.org/10.1016/j.compag.2018.11.019 (2019).
Google Scholar
Karar, M. E., Alsunaydi, F., Albusaymi, S. & Alotaibi, S. A new mobile application of agricultural pests recognition using deep learning in cloud computing system. Alex. Eng. J. 60, 4423–4432. https://doi.org/10.1016/j.aej.2021.03.009 (2021).
Google Scholar
Zuidhof, M. J., Fedorak, M. V., Ouellette, C. A. & Wenger, I. I. Precision feeding: Innovative management of broiler breeder feed intake and flock uniformity. Poult. Sci. 96, 2254–2263. https://doi.org/10.3382/ps/pex013 (2017).
Google Scholar
Ren, G., Lin, T., Ying, Y., Chowdhary, G. & Ting, K. C. Agricultural robotics research applicable to poultry production: A review. Comput. Electron. Agric. 169, 105216. https://doi.org/10.1016/j.compag.2020.105216 (2020).
Google Scholar
Williams, L. R., Moore, S. T., Bishop-Hurley, G. J. & Swain, D. L. A sensor-based solution to monitor grazing cattle drinking behaviour and water intake. Comput. Electron. Agric. 168, 105–141. https://doi.org/10.1016/j.compag.2019.105141 (2020).
Google Scholar
Astill, J., Dara, R. A., Fraser, E. D. G., Roberts, B. & Sharif, S. Smart poultry management: Smart sensors, big data, and the internet of things. Comput. Electron. Agric. 170, 105291. https://doi.org/10.1016/j.compag.2020.105291 (2020).
Google Scholar
Lakhiar, I. A., Gao, J., Syed, T. N., Chandio, F. A. & Buttar, N. A. Modern plant cultivation technologies in agriculture under controlled environment: A review on aeroponics. J. Plant Interactions 131, 338–352 (2018).
Google Scholar
Shamshiri, R. R. et al. Research and development in agricultural robotics: A perspective of digital farming. Int. J. Agric. Biol. Eng. 11, 1–14 (2018).
Shamshiri, R. R. et al. Simulation software and virtual environments for acceleration of agricultural robotics: Features highlights and performance comparison. Int. J. Agric. Biol. Eng. 11(4), 15–31 (2018).
Shamshiri, R. R. et al. Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. Int. J. Agric. Biol. Eng. 11(1), 1–22 (2018).
Xia, Y., Xu, Y., Li, J., Zhang, C. & Fan, S. Recent advances in emerging techniques for non-destructive detection of seed viability: A review. Artif. Intell. Agric. 1, 35–47 (2019).
Liu, W. et al. Development and experimental analysis of an intelligent sensor for monitoring seed flow rate based on a seed flow reconstruction technique. Comput. Electron. Agric. 164, 104899 (2019).
Google Scholar
Jiang, B. et al. Fusion of machine vision technology and AlexNet-CNNs deep learning network for the detection of postharvest apple pesticide residues. Artif. Intell. Agric. 1, 1–8 (2019).
Google Scholar
Zhang, B., Xie, Y., Zhou, J., Wang, K. & Zhang, Z. State-of-the-art robotic grippers, grasping and control strategies, as well as their applications in agricultural robots: A review. Comput. Electron. Agric. 177, 105694 (2020).
Google Scholar
Khadatkar, A., Mathur, S. M., Dubey, K. & BhushanaBabu, V. Development of embedded automatic transplanting system in seedling transplanters for precision agriculture. Artif. Intell. Agric. 5, 175–184. https://doi.org/10.1016/j.aiia.2021.08.001 (2021).
Google Scholar
Khadatkar, A., Mathur, S. M., Dubey, K. & Magar, A. P. Automatic ejection of plug seedlings using embedded system for use in automatic vegetable transplanters. J. Sci. Ind. Res. 80(12), 1042–1048 (2021).
Khadatkar, A., Mehta, C. R. & Sawant, C. P. Application of robotics in changing the future of agriculture. J. Eco-Friendly Agric. 17(1), 48–51. https://doi.org/10.5958/2582-2683.2022.00010.7 (2022).
Google Scholar
Khadatkar, A., Mathur, S. M. & Gaikwad, B. B. Automation in transplanting: A smart way of vegetable cultivation. Curr. Sci. 115(10), 1884–1892. https://doi.org/10.18520/cs/v115/i10/1884-1892 (2018).
Google Scholar
Khadatkar, A. & Mathur, S. M. Design and development of automatic vegetable transplanter using novel rotating finger device with push-type mechanism for plug-type seedlings. Int. J. Veg. Sci. https://doi.org/10.1080/19315260.2020.1848962 (2020).
Google Scholar
Boa, W. The design and performance of an automatic transplanter for field vegetables. J. Agric. Eng. Res. 30(2), 123–130 (1984).
Google Scholar
Ting, K. C., Giacomelli, G. A. & Shen, S. J. Robot workcell for transplanting of seedlings part I-layout and materials flow. Trans. ASAE 33(3), 1005–1010 (1990).
Google Scholar
Simonton, W. Robotic end-effector for handling greenhouse plant material. Trans. ASAE 34(6), 2615–2621 (1991).
Google Scholar
Ting, K. C., Giacomelli, A. & Ling, P. P. Workability and productivity of robotic plug transplanting workcell. In Vitro Cell Dev. Biol. 28, 5–10 (1992).
Google Scholar
Tai, Y. W., Ling, P. P. & Ting, K. C. Machine vision assisted robotic seedling transplanting. Trans. ASAE 37(2), 661–667 (1994).
Google Scholar
Brewer, H. L. Conceptual modeling automated seedling transfer from growing trays to shipping modules. Trans. ASAE 37(4), 1043–1051 (1994).
Google Scholar
Ryu, K. H., Kim, G. & Han, J. S. Development of a robotic transplanter for bedding plants. J. Agric. Eng. Res. 78(2), 141–146 (2001).
Google Scholar
Yang, Y., Ting, K. C. & Giacomelli, G. A. Factors affecting performance of sliding-needles gripper during robotic transplanting of seedlings. Appl. Eng. Agric. 7(4), 493–498 (1991).
Google Scholar
Kim, H. J., Park, S. H. & Kwak, T. Y. Development of an automatic transplanter for cabbage cultivation. In: Korea Automatic Dynamic Analysis of Mechanical Systems Conference, Seoul, Korea, 8–9 Nov (2001).
Choi, W. C., Kim, D. C., Ryu, I. H. & Kim, K. U. Development of a seedling pick-up device for vegetable transplanters. Trans. ASAE 45(1), 13–19 (2002).
Park, S. H. et al. Development of walking type chinese cabbage transplanter. J. Korea Soc. Agric. Mach. 30(2), 80–81 (2005).
Kang, D. H. et al. Development of a vegetable transplanting robot. J. Biosyst. Eng. 37(3), 201–208 (2012).
Google Scholar
Ma, J., Hu, J., Yan, X., Qi, C. & Guan, J. Transplanting path planning and motion functions research of the high-speed tray seedling transplanting robot. Adv. Mater. Res. 694–697, 1747–1752 (2013).
Google Scholar
Mao, H., Han, L., Hu, J. & Kumi, F. Development of a pincette-type pick-up device for automatic transplanting of greenhouse seedlings. Appl. Eng. Agric. 30(4), 547–556 (2014).
Hua, L., Weibin, C., Shufeng, L., Wei, F. & Kaiqiang, L. Kinematic analysis and test on automatic pick-up mechanism for chili plug seedling. Trans. Chin. Soc. Agric. Mach. 31(23), 20–27 (2015).
Han, L., Mao, H., Hu, J. & Tian, K. Development of a doorframe-typed swinging seedling pick-up device for automatic field transplantation. Span. J. Agric. Res. 13(2), 1–14. https://doi.org/10.5424/sjar/2015132-6992 (2015).
Google Scholar
Xin, J. et al. Design and implementation of intelligent transplanting system based on photoelectric sensor and PLC. Future Gen. Comput. Syst. 88, 127–139 (2018).
Google Scholar
Han, L. H., Mao, H. P., Hu, J. & Kumi, F. Development of a riding type fully automatic transplanter vegetable seedlings. Span. J. Agric. Res. 17(3), 1–14 (2019).
Google Scholar
Yu, Y. et al. Design and experimental research on seedling pick-up mechanism of planetary gear train with combined non-circular gear transmission. Chin. J. Mech. Eng. 32, 49 (2019).
Google Scholar
Khadatkar, A., Mathur, S. M., Gaikwad, B. B., Pandirwar, A. & Shrinivas, D. J. Biometric properties of plug vegetable seedlings relevant to the design of vegetable transplanter. J. Agric. Eng. 57(1), 16–24 (2020).
Khadatkar, A. Development of a Tractor Operated Vegetable Transplanter for Plug-Type Seedlings. Unpublished Ph.D. Thesis, CTAE, MPUAT, Udaipur, India (2019).