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作物叶片氮含量的快速估算对于及时了解作物长势、病虫害监测以及产量评估具有重要意义。该文以经济作物生姜为研究对象,获取了2015年4月-9月不同品种、不同生育期和不同氮肥梯度下生姜叶片的高光谱和氮含量数据,对比分析了比值植被指数、归一化植被指数、植被指数组合形式对生姜叶片氮含量的估算效果。在此基础上,基于波段组合算法,筛选出了生姜叶片氮含量的敏感波段,并构建了两个新型光谱指数NDSI_((754,713))和RSI_((754,713))。结果表明,所选择的植被指数中,MCARI(705,750)/OSAVI(705,750)对生姜叶片氮含量估算效果最好,模型精度R~2、RMSE和RE分别为0.73、0.27、11.64%;利用波段组合算法构建的归一化光谱指数NDSI(754,713)对生姜叶片氮含量估算效果要优于MCARI(705,750)/OSAVI(705,750),模型估算精度R~2达0.83,使用的敏感波段713 nm与754 nm均位于植被的“红边”区域。对所建模型进行验证,叶片氮含量的预测值和实测值具有较好的一致性,验证样本R~2为0.78,RMSE为0.20,RE为9.81%。上述分析结果可为农业管理部门及时掌握生姜长势信息、制定施肥策略提供技术支持。
Rapid estimation of nitrogen content in crop leaves is of great importance to keep abreast of crop growth, pest and disease monitoring and yield assessment. In this paper, the economic crop Ginger was taken as the research object to obtain the data of the hyperspectral and nitrogen contents of ginger leaves from April to September in 2015 with different varieties, different growth stages and different nitrogen fertilizer gradients. The comparative vegetation index, normalized Vegetation Index and Vegetation Index for Estimating Nitrogen Content of Ginger Leaves. On this basis, the sensitive band of nitrogen content of ginger leaves was screened out based on the band combination algorithm, and two new spectral indexes NDSI _ ((754,713) and RSI_ (754,713)) were constructed. The results showed that MCARI (705,750) / OSAVI (705,750) had the best effect on estimating the nitrogen content of ginger leaves. The model accuracy R ~ 2, RMSE and RE were 0.73,0.27 and 11.64% respectively. The normalized spectral index (NDSI) (754,713) constructed by the proposed algorithm was superior to MCARI (705,750) / OSAVI (705,750) for estimation of nitrogen content in ginger leaves. The estimated accuracy of the model was 0.83 for R ~ 2 and the sensitive bands 713 nm and 754 nm All are located in the “Red Edge” area of the vegetation. The validation of the proposed model showed good agreement between the predicted and measured values of leaf nitrogen content. The validation sample R ~ 2 was 0.78, the RMSE was 0.20, and the RE was 9.81%. The results of the above analysis can provide technical support to the agricultural administrations in grasping the information about the growth of ginger and formulating fertilization strategies.