摘要
为了快速无损地检测作物生长期营养含量,设计了一套作物营养智能检测仪。该检测仪由控制器和若干光学传感器节点组成,两者之间通过ZigBee协议通信。其中,光学传感器节点可分别测量中心波长为550、650、766和850 nm的太阳光和作物冠层反射光的强度,进而计算光谱反射率和植被指数。应用该仪器检测大田冬小麦叶绿素含量,结果表明应用不同波段组合构建的归一化植被指数与冬小麦冠层叶绿素含量间相关性较比值植被指数高。基于标准白板和太阳光研究了系统的标定方法,相关性分析表明该方法可有效提高归一化植被指数与叶绿素含量之间的相关系数。其中根据550和766 nm计算所求归一化植被指数与SPAD所测叶绿素含量的相关性最高(相关系数为0.693 9),并建立了叶绿素含量线性预测模型,建模精度为0.494,检验模型精度为0.478。
In order to real-time detect crop nutrition content,a smart apparatus for detecting crop nutrition was developed based on NIR spectroscopy,electronics and ZigBee wireless communication technology.It was designed to work as a wireless sensor network with one control unit and several optical sensor nodes.The incident sunlight and reflective light from crop canopy were measured at the wavebands of 550 nm,650 nm,766 nm and 850 nm respectively,and then the canopy reflectance and some vegetative indices were calculated.The field experiments and analyses on crop growth monitoring in wheat fields were conducted.Results showed that the correlation coefficient between NDVI and chlorophyll content was higher than RVI.The chlorophyll content and the vegetation index which was calculated with the reflectance at 550 nm and 766 nm had the highest correlation coefficients(r was 0.693 9),and the prediction model of chlorophyll content was built.The r2 of the calibration model reached to 0.494,and r2 of the predicted model reached to 0.478.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2013年第S2期215-219,共5页
Transactions of the Chinese Society for Agricultural Machinery
基金
"十二五"国家科技支撑计划资助项目(2012BAH29B04)
