TY - GEN
T1 - QPAIS
T2 - A web-based expert system for assisted identification of quarantine stored insect pests
AU - Huang, Han
AU - Rajotte, Edwin G.
AU - Li, Zhihong
AU - Chen, Ke
AU - Zhang, Shengfang
PY - 2009
Y1 - 2009
N2 - Stored insect pests can seriously depredate stored products causing worldwide economic losses. Pests enter countries traveling with transported goods. Inspection and Quarantine activities are essential to prevent the invasion and spread of pests. Identification of quarantine stored insect pests is an important component of the China's Inspection and Quarantine procedure, and it is necessary not only to identify whether the species captured is an invasive species, but determine control procedures for stored insect pests. With the development of information technologies, many expert systems that aid in the identification of agricultural pests have been developed. Expert systems for the identification of quarantine stored insect pests are rare and are mainly developed for stand-alone PCs. This paper describes the development of a web-based expert system for identification of quarantine stored insect pests as part of the China 11th Five-Year National Scientific and Technological Support Project (115 Project). Based on user needs, textual knowledge and images were gathered from the literature and expert interviews. ASP.NET, C# and SQL language were used to program the system. Improvement of identification efficiency and flexibility was achieved using a new inference method called characteristic-select-based spatial distance method. The expert system can assist identifying 150 species of quarantine stored insect pests and provide detailed information for each species. The expert system has also been evaluated using two steps: system testing and identification testing. With a 85% rate of correct identification and high efficiency, the system evaluation shows that this expert system can be used in identification work of quarantine stored insect pests.
AB - Stored insect pests can seriously depredate stored products causing worldwide economic losses. Pests enter countries traveling with transported goods. Inspection and Quarantine activities are essential to prevent the invasion and spread of pests. Identification of quarantine stored insect pests is an important component of the China's Inspection and Quarantine procedure, and it is necessary not only to identify whether the species captured is an invasive species, but determine control procedures for stored insect pests. With the development of information technologies, many expert systems that aid in the identification of agricultural pests have been developed. Expert systems for the identification of quarantine stored insect pests are rare and are mainly developed for stand-alone PCs. This paper describes the development of a web-based expert system for identification of quarantine stored insect pests as part of the China 11th Five-Year National Scientific and Technological Support Project (115 Project). Based on user needs, textual knowledge and images were gathered from the literature and expert interviews. ASP.NET, C# and SQL language were used to program the system. Improvement of identification efficiency and flexibility was achieved using a new inference method called characteristic-select-based spatial distance method. The expert system can assist identifying 150 species of quarantine stored insect pests and provide detailed information for each species. The expert system has also been evaluated using two steps: system testing and identification testing. With a 85% rate of correct identification and high efficiency, the system evaluation shows that this expert system can be used in identification work of quarantine stored insect pests.
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U2 - 10.1007/978-1-4419-0209-2_72
DO - 10.1007/978-1-4419-0209-2_72
M3 - Conference contribution
AN - SCOPUS:85099734541
SN - 9781441902085
T3 - IFIP International Federation for Information Processing
SP - 701
EP - 714
BT - Computer and Computing Technologies In Agriculture II, Volume 1
PB - Springer Science and Business Media, LLC
ER -