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Sensors 2014, 14(10), 18114-18130; doi:10.3390/s141018114

Estimation of the Age and Amount of Brown Rice Plant Hoppers Based on Bionic Electronic Nose Use

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1
Key Laboratory of Key Technology on Agricultural Machine and Equipment, South China Agricultural University, Guangzhou 510642, China
2
College of Engineering, South China Agricultural University, Guangzhou 510642, China
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Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843, USA
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Plant Protection Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
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Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangzhou 510640, China
*
Author to whom correspondence should be addressed.
Received: 6 August 2014 / Revised: 17 September 2014 / Accepted: 23 September 2014 / Published: 29 September 2014
(This article belongs to the Special Issue Agriculture and Forestry: Sensors, Technologies and Procedures)
View Full-Text   |   Download PDF [2413 KB, uploaded 29 September 2014]   |  

Abstract

The brown rice plant hopper (BRPH), Nilaparvata lugens (Stal), is one of the most important insect pests affecting rice and causes serious damage to the yield and quality of rice plants in Asia. This study used bionic electronic nose technology to sample BRPH volatiles, which vary in age and amount. Principal component analysis (PCA), linear discrimination analysis (LDA), probabilistic neural network (PNN), BP neural network (BPNN) and loading analysis (Loadings) techniques were used to analyze the sampling data. The results indicate that the PCA and LDA classification ability is poor, but the LDA classification displays superior performance relative to PCA. When a PNN was used to evaluate the BRPH age and amount, the classification rates of the training set were 100% and 96.67%, respectively, and the classification rates of the test set were 90.67% and 64.67%, respectively. When BPNN was used for the evaluation of the BRPH age and amount, the classification accuracies of the training set were 100% and 48.93%, respectively, and the classification accuracies of the test set were 96.67% and 47.33%, respectively. Loadings for BRPH volatiles indicate that the main elements of BRPHs’ volatiles are sulfur-containing organics, aromatics, sulfur-and chlorine-containing organics and nitrogen oxides, which provide a reference for sensors chosen when exploited in specialized BRPH identification devices. This research proves the feasibility and broad application prospects of bionic electronic noses for BRPH recognition. View Full-Text
Keywords: bionic electronic nose; bionic olfaction; brown rice plant hopper; age; amount; volatile; classification bionic electronic nose; bionic olfaction; brown rice plant hopper; age; amount; volatile; classification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Xu, S.; Zhou, Z.; Lu, H.; Luo, X.; Lan, Y.; Zhang, Y.; Li, Y. Estimation of the Age and Amount of Brown Rice Plant Hoppers Based on Bionic Electronic Nose Use. Sensors 2014, 14, 18114-18130.

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