Open Access
BIO Web Conf.
Volume 37, 2021
International Scientific-Practical Conference “Agriculture and Food Security: Technology, Innovation, Markets, Human Resources” (FIES 2021)
Article Number 00183
Number of page(s) 5
Published online 27 October 2021
  • A. Ovchinnikov, A. Tseplyaev, M. Shaprov, M. Ul’yanov, S. Poltorynkin, A. Sedov, V. Tseplyaev, V. Slavutsky, V. Berdyshev, V. Bocharnikov, I. Borisenko, S. Grigorov, S. Fomin, V. Ol’garenko, The choice of technology of agricultural crops cultivation on the basis of the manual labor costs indicator optimization (for the example of vegetable and melon crops cultivation), ARPN Journal of Engineering and Applied Sciences, 14(22), 33897–3905 (2019) [Google Scholar]
  • M. Ulyanov, A. Ulyanov, The results of laboratory and factory tests of an active type swath maker for cucurbit crops, Bulletin of Orenburg State Agrarian University, 3(31), 98–100 (2011) [Google Scholar]
  • A. Roshanianfard, N. Noguchi, T. Kamata, Design and performance of a robotic arm for farm use, International Journal of Agricultural and Biological Engineering, 12(1), 146–158 (2019) [Google Scholar]
  • X. Xing, F. Liu, J. Gao, Design and implementation of watermelon traceable identification algorithm based on biometric texture information, Nongye Gongcheng Xuebao Transactions of the Chinese Society of Agricultural Engineering, 33, 298–305 (2017) [Google Scholar]
  • S. Sakai, K. Osuka, M. Umeda, Use of a heavy material handling agricultural robot for harvesting watermelons, Proceedings of the International Conference on Automation Technology for Off-road Equipment, ATOE (2004) [Google Scholar]
  • S. Giwa, T. Akanbi, Mechanization of melon processing and novel extraction technologies: A short review, Scientific African, 9, e00478 (2020) [Google Scholar]
  • H. Guo, M. Wang, Y. Dong, Z. Xie, Design and experiment for the header of seed melon combine harvester, International Agricultural Engineering Journal, 29(2), 78–85 (2020) [Google Scholar]
  • Abidzar H. Tawakal, A. Prayoga, The Development of Methods for Detecting Melon Maturity Level Based on Fruit Skin Texture Using the Histogram of Oriented Gradients and the Support Vector Machine, Proceedings of 2019 4th International Conference on Informatics and Computing, ICIC, 8985953 (2019) [Google Scholar]
  • U. Ahmad, D. Bermani, P. Mardison, Color distribution analysis for ripeness prediction of Golden Apollo Melon, Telecommunication Computing Electronics and Control, 16(4), 16591666 (2018) [Google Scholar]
  • H. Paris, Y. Tadmor, A. Schaffer, Cucurbitaceae Melons, Squash, Cucumber, Encyclopedia of Applied Plant Sciences, 3, 209–217 (2016) [Google Scholar]
  • M. Mann, B. Zion, I. Shmulevich, D. Rubinstein, Determination of robotic melon harvesting efficiency: A probabilistic approach, International Journal of Production Research, 54(11), 3216–3228 (2016) [Google Scholar]
  • M. Mann, B. Zion, I. Shmulevich, D. Rubinstein, R. Linker, Combinatorial Optimization and Performance Analysis of a Multiarm Cartesian Robotic Fruit Harvester—Extensions of Graph Coloring, Journal of Intelligent and Robotic Systems: Theory and Applications, 82(3-4), 399–411 (2016) [Google Scholar]

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