[Inversion of winter wheat foliage vertical distribution based on canopy reflected spectrum by partial least squares regression method].

With the widespread application of remote sensing (RS) in agriculture, monitoring and prediction of crop nutrition condition attracts attention of many scientists. Foliar nitrogen content (N) is one of the most important nutrients for plant growth, and vertical leaf N gradient is an important indicator of crop nutrition situation. Investigations have been made on N vertical distribution to describe the growth status of winter wheat. Results indicate that from the canopy top to the ground surface, N shows an obvious gradient decreasing trend. The objective of this study was to discuss the inversion method of N vertical distribution with canopy reflected spectrum by the partial least squares regression (PLS) method. PLS was selected for the inversion of upper, middle and lower layers of N. To improve the accuracy of prediction, the N in the upper layer as well as in the middle and bottom layers should be taken into consideration when crop nutrition condition is appraised by RS data. The established models by the observed data in year 2001-2002 were validated by the data in year 2003-2004. The inversion precision and error were acceptable. It provided a theoretic basis for widely and non-damaged variable rate nitrogen application of winter wheat by canopy reflected spectrum.