摘要
为探究冠层图像分析技术在冬小麦长势监测中应用,6个施氮水平的田间试验条件下,在冬小麦拔节期采集冠层图像,并同步测定冬小麦叶面积指数和叶片SPAD值。通过图像分析软件计算了冬小麦冠层覆盖度及红、绿、蓝亮度值等10种色彩指数,分析了叶面积指数及叶片SPAD值与色彩指数和冠层覆盖度的相关性,利用逐步回归方法构建了叶面积指数及叶片SPAD值的估算模型。结果表明:冬小麦拔节期叶面积指数与冠层覆盖度及几个色彩指数呈极显著相关;叶片SPAD值与红光标准化值等几个色彩指数呈极显著相关;利用叶面积指数估算模型计算的预测值与实测值的线性回归方程的决定系数为0.771,相对均方根误差为25.181%;利用叶片SPAD值估算模型计算的预测值与实测值的线性回归方程的决定系数为0.644,相对均方根误差为6.734%。相关分析和估算模型验证结果表明,基于冠层图像分析的冬小麦拔节期叶面积指数和叶片SPAD值的监测是可行的。
In order to study the feasibility to using canopy color image analysis to estimate winter wheat leaf area index（LAI）and leaf SPAD value during the elongation stage.Color digital images of winter wheat canopies grown under six levels of nitrogen application experiments were taken for four times,meanwhile LAI and leaf SPAD value were measured.Winter wheat canopy cover and ten color indices including red,green,and blue intensity of color digital images were obtained by using color image analysis program.Correlation analysis was conducted to identify the relationships between LAI,Leaf SPAD value and canopy cover,ten color indices.Stepwise multiple linear regression method was used to establish the models to determine winter wheat LAI and leaf SPAD value.The results showed that,LAI was highly correlated with canopy cover and several color indices;leaf SPAD value was highly correlated with normalized redness intensity（r）,normalized greenness intensity（g）,normalized blueness intensity（b）,and Hue.The stepwise regression models for estimating LAI and leaf SPAD value were constructed.The validation results indicate that the models for estimating LAI and Leaf SPAD value had good performance,and also showed the potential of the method of canopy image analysis to assess the growth and nitrogen nutrition status of winter wheat during the elongation stage.
出处
《青岛农业大学学报（自然科学版）》
2016年第2期91-96,共6页
Journal of Qingdao Agricultural University(Natural Science)
基金
农业部"948"项目(2012-Z5)
山东省旱地作物水分高效利用科研创新团队项目
青岛农业大学大学生创新计划项目资助
