Abstract
Forest pests and diseases is very important to forest because it not only restricts the development of forest, but also causes huge economic. Chemical pesticides control the pests and diseases effectively and pollute environment seriously. How to reduce the amount of pesticide is the research hotspot in the field of plant protection. Forest plant protection machinery is the most important way to spray chemical pesticides. With the development of various modern information technologies, forest plant protection machinery has entered the electronic age in developed country. There are many modern information technologies which are applied in forest plant protection machinery, such as database, 3S technology, and sensor technology and so on. In this paper, a large number of relevant scientific literatures have been analyzed and compared in order to summarize application of modern information technology in the forest plant protection machinery. As the wide forest range, forest plant protection machinery should base mainly on large-scale spraying. 3S technologies, database technology, computer control technology and a variety of detection techniques should be effectively combined together and applied in forest plant protection machinery in order to meet environmental safety requirements and improve the efficiency.
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Cheng, G.: The Establishment of the Management Information System of Ornamental Plants Diseases and Pests in Qingdao. Journal of Shandong Forestry Science and Technology 5, 44–48 (2008) (in Chinese)
Wang, N., Zhang, Y., Wang, W.: Design and Realization of forest disease and insects Remote Consultation System based on natural language understanding. Journal of Natural Science of Heilongjiang University 6, 794–797 (2008) (in Chinese)
Sun, H.-m., Li, Y.-q., Li, X.-m.: The Design of the Inspection and Forecast System for the ForestPlant Diseases. Journal of Agricultural Mechanization Research 2, 226–227 (2004) (in Chinese)
Zhang, H., Zheng, J., Zhou, H.: Specialized database technology for intelligent plant protection machinery. Transactions of the Chinese Society of Agricultural Engineering 1, 154–157 (2009) (in Chinese)
Rockwell, A.D., Ayers, P.D.: Variable rate sprayer development and evaluation. Applied Engineering in Agriculture 10, 327–333 (1994)
Nielsen, K.M., Andersen, P., Pedersen, T.S.: Control of an autonomous vehicle for registration of weed and crop in precision agriculture. In: IEEE Conference on Control Applications, Glasgow, Scotland, vol. 2, pp. 18–20 (2002)
Seelan, S.K., Laguette, S., Casady, G.M.: Remote sensing applications for precision agriculture: A learning community approach. Remote Sensing of Environment 12, 157–169 (2003)
Shi, W., Wang, X., Wang, X.: Variable Rate Spraying Technology on the Basis of GPS and GIS. Journal of Agricultural Mechanization Research 2, 19–21 (2007) (in Chinese)
Cohen, Y., Cohen, A., Hetzroni, A.: Spatial decision support system for Medfly control in citrus. Computers and Electronics in Agriculture 32, 107–117 (2008)
Mckinion, J.M., Jenkins, J.N., Willers, J.L.: Spatially variable insecticide applications for early season control of cotton insect pests. Computers and Electronics in Agriculture 67, 71–79 (2009)
Palmer, M.C.: Calculation of distance traveled by fishing vessels using GPS positional data: a theoretical evaluation of the sources of error. Fisheries Research 89, 57–64 (2008)
Shearer, S.A., Jones, P.T.: Selective application of post-emergence herbicides using photo electrics. Transactions of the ASAE 34, 1661–1666 (1991)
Giles, D.K., Slaughter, D.C.: Precision band sprayer with machine-vision guidance and adjustable yaw nozzles. Transactions of the ASAE 40, 29–36 (1997)
Lee, W.S., Slaughter, D.C., Giles, D.K.: Robotic weed control system for tomatoes. Precision Agriculture 1, 95–113 (1999)
Tian, L., Reid, J., Hummel, J.: Development of a precision sprayer for site-specific weed management. Transactions of the ASAE 42, 893–900 (1999)
Lei, T.: Development of a sensor-based precision herbicide application system. Computers and Electronics in Agriculture 36, 133–149 (2002)
Tellaeche, A., Artizzu, B., Xavier, P.: A vision-based method for weeds identification through the Bayesian decision theory. Pattern Recognition 41, 521–530 (2008)
Zhu, W., Zhu, X.: The application of support vector machine in weed classification. In: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, vol. 4, pp. 532–536 (2009) (in Chinese)
Harper, N.L., McKerrow, P.J.: Recognition of plants with CTFM ultrasonic range data using a neural network. In: IEEE International Conference on Robotics and Automation, vol. 4, pp. 3244–3249 (1997)
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Chen, L., Wang, Q., Ji, R. (2011). Research and Application of Modern Information Technology in the Forest Plant Protection Machinery. In: Li, D., Liu, Y., Chen, Y. (eds) Computer and Computing Technologies in Agriculture IV. CCTA 2010. IFIP Advances in Information and Communication Technology, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18354-6_62
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DOI: https://doi.org/10.1007/978-3-642-18354-6_62
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