中文摘要：

2006-2015年,我国农作物病虫草鼠害总体处于严重发生状态,各类病虫害年发生面积在4.603 5亿～5.075 3亿hm^2次,年均挽回粮食损失9 684.68万t,占全国粮食总产的17.35%;年均实际损失粮食1 965.49万t,占全国粮食总产的3.53%。五大粮食作物中每年通过防治挽回损失的比例,水稻、小麦、玉米、大豆和马铃薯分别占55.18%、21.29%、18.97%、1.88%和2.68%,实际造成损失的比例分别占33.67%、23.31%、35.13%、2.11%和5.79%。影响全国粮食生产最为重要的10种（类）病虫害依次为稻飞虱、水稻纹枯病、稻纵卷叶螟、玉米螟、小麦蚜虫、二化螟、稻瘟病、小麦纹枯病、小麦赤霉病、小麦白粉病;某一个病虫暴发危害时最高可实际造成200万t以上的粮食损失,总损失可达2 200万t,占某类粮食总产的12%左右,对国家粮食安全影响巨大。最具暴发和流行危害特点的种类主要有稻飞虱、稻纵卷叶螟、稻瘟病、小麦条锈病、小麦赤霉病和黏虫等6种。本文运用大量翔实的历史数据统计分析了近10年来水稻、小麦、玉米三大粮食作物病虫害的危害损失和暴发危害情况。

英文摘要：

Canopy spectral data of Dalbergia odorifera were collected according to different disease incidences,using Spectra Vista Corporation（SVC）HR-1024 i un-imaging hyperspectral of America,then scan matching/overlap correction and white plate reflectance correction of spectral data were completed based on the disease index of D.odorifera black scurf obtained simultaneously in the field.Principal component analysis（PCA）was applied to conduct dimension-reduction of sensitive wave band which highly related to disease index.Both sensitive wave bands from53 training sets before and after processing by PCA were chosen as input variables for training BP neural network of D.odorifera black scurf.The results showed that both coefficients of determination（R^2）between the predictive values from BP neural network established by above two variables and the actual values were to99%.Further accuracy test by using 27 validation sets showed that the coefficients of determination（R^2）between the predictive value and the actual value were up to 0.951 9 and 0.706 0,and the root mean square errors（RMSE）were 5.998 0 and 12.919 3.The results indicated that both methods of training BP neural network by using sensitive wave bands directly and after treatment by PCA as variables were all effective ways,of which using sensitive wave bands directly was more accurate.