| Title: | Plant Pest Detection Using an Artificial Nose System: A Review |
| Author(s): | Cui S; Ling P; Zhu H; Keener HM; |
| Address: | "Department of Food, Agricultural and Biological Engineering, The Ohio State University/Ohio Agricultural Research and Development Center, 1680 Madison Ave, Wooster, OH 44691-4096, USA. cui.411@osu.edu. Department of Food, Agricultural and Biological Engineering, The Ohio State University/Ohio Agricultural Research and Development Center, 1680 Madison Ave, Wooster, OH 44691-4096, USA. ling.23@osu.edu. United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Application Technology Research Unit, 1680 Madison Ave, Wooster, OH 44691-4096, USA. heping.zhu@ars.usda.gov. Department of Food, Agricultural and Biological Engineering, The Ohio State University/Ohio Agricultural Research and Development Center, 1680 Madison Ave, Wooster, OH 44691-4096, USA. keener.3@osu.edu" |
| ISSN/ISBN: | 1424-8220 (Electronic) 1424-8220 (Linking) |
| Abstract: | "This paper reviews artificial intelligent noses (or electronic noses) as a fast and noninvasive approach for the diagnosis of insects and diseases that attack vegetables and fruit trees. The particular focus is on bacterial, fungal, and viral infections, and insect damage. Volatile organic compounds (VOCs) emitted from plants, which provide functional information about the plant's growth, defense, and health status, allow for the possibility of using noninvasive detection to monitor plants status. Electronic noses are comprised of a sensor array, signal conditioning circuit, and pattern recognition algorithms. Compared with traditional gas chromatography-mass spectrometry (GC-MS) techniques, electronic noses are noninvasive and can be a rapid, cost-effective option for several applications. However, using electronic noses for plant pest diagnosis is still in its early stages, and there are challenges regarding sensor performance, sampling and detection in open areas, and scaling up measurements. This review paper introduces each element of electronic nose systems, especially commonly used sensors and pattern recognition methods, along with their advantages and limitations. It includes a comprehensive comparison and summary of applications, possible challenges, and potential improvements of electronic nose systems for different plant pest diagnoses" |
| Keywords: | Electronic Nose Fruit Gas Chromatography-Mass Spectrometry Humans Pest Control *Plants Volatile Organic Compounds gas sensor noninvasive detection pest management pest scouting; |
| Notes: | "MedlineCui, Shaoqing Ling, Peter Zhu, Heping Keener, Harold M eng Review Switzerland 2018/02/01 Sensors (Basel). 2018 Jan 28; 18(2):378. doi: 10.3390/s18020378" |
