不同施肥决策对冬小麦生长影响的高光谱监测及对比分析

摘要

为了明确不同变量施肥算法下的冬小麦冠层光谱特征,以及确定适宜我国气候条件的变量施肥算法,于2006年通过田间试验,分别测量了六种不同施肥决策下的冬小麦冠层光谱和产量,对这六种施肥算法进行了对比分析.结果表明,通过对施肥后冬小麦冠层光谱反射率、施肥前后反射率变化量以及不同时期的归一化植被指数的分析,得知不同施肥处理的冬小麦冠层光谱反射率存在差异,可以反映出冬小麦长势的强弱,其中基于光谱指数和作物生长模型相结合的算法(Z)进行施肥的冬小麦长势最佳.与均一施肥(W)和不施肥(CK)处理相比,变量施肥处理均显著提高小麦产量；除基于土壤养分变量施肥处理(T)外,产量变异系数明显降低,其中基于归一化SPAD值变量施肥处理(S)的变异系数最小.Z变量施肥算法综合效果最佳,S变量施肥算法在降低产量变异度方面效果最佳.拔节期施肥对开花期或灌浆初期小麦生长影响最大；并且这两时期的植被指数与产量的相关性也最好,尤其红边三角光谱指数(RTVI)最好(相关系数达到0.700),可见采用RTVI指数进行产量预测效果更优.%In order to clarify the characteristics of canopy spectrum of winter wheat under the condition of different fertilizations, and to select the best variable fertilization algorithm, a field experiment was conducted in the year 2006 during winter wheat growth period. The indices of winter wheat including canopy spectrum and yields under six different fertilizer treatments were studied. The results show that through the analysis of the canopy spectral reflectance after the fertilization, variations of the reflectance before and after the fertilization, and the normalized difference vegetation index in different growth stages, there are some differences of canopy reflectance in winter wheat under different fertilizer treatments. The fertilization algorithm based on the spectral index and crop growth model (Z) is the best one. Compared with the uniform fertilization (W) and no fertilization (CK) , the variable fertilizer treatments improve wheat yields significantly, the variation coefficients of yield are reduced, except the treatment based on soil nutrient (T) , and the one of fertilization treatment based on the normalized SPAD value (S) is the smallest. The Z variable rate fertilization algorithm is the best in combined effect and the S variable fertilization algorithm is better in reducing yield variability. The effect of fertilization at the jointing stage on the wheat growth at the flowering or early filling stages is the biggest. A significantly correlation is observed between the vegetation indexes at the flowering or early filling stages and yield, especially Red-edge triangular vegetation index ( RTVI) (r =0. 700) , so we can use RTVI index to predict grain yield of winter wheat.