...
首页> 外文期刊>Computers and Electronics in Agriculture >Passive reflectance sensing using optimized two- and three-band spectral indices for quantifying the total nitrogen yield of maize
【24h】

Passive reflectance sensing using optimized two- and three-band spectral indices for quantifying the total nitrogen yield of maize

机译:使用优化的两频段和三带光谱索引来量化玉米总氮素产量的被动反射感测

获取原文
获取原文并翻译 | 示例

摘要

Precision nitrogen (N) management requires accurate and effective quantification of the total nitrogen yield (TNY) crops. Thus, this study aimed at establishing the robust prediction model to quantify the TNY of maize plants across growth stages, cultivars and years through optimizing two-band spectral indices, i.e. the normalized difference spectral index (NDSI) and the ratio spectral index (RSI), and three-band spectral indices, i.e. the canopy chlorophyll content index (CCCI) by re-determining the central wavelength and bandwidth. Field experiments with three maize cultivars and five N treatments were carried out in the North China Plain during 2011, 2012, and 2013. The results showed that the optimized band ranges of NDSI and RSI were mainly located within 720-760 nm (the red-edge domain) and 750-900 nm (the near-infrared domain). The central wavelengths of the NDSI were 768 and 740 nm, whereas those of the RSI were 756 and 744 nm. The most suitable band domains of the CCCI were 720-760, 500-600 and 740-800 nm, and their central wave-lengths were 766, 738 and 548 nm. Our study found that the optimized spectral indices could predict the TNY of maize accurately and robustly compared with existing spectral indices. The relationships between the optimized NDSI and RSI and maize TNY reached a high coefficient of determination (R-2 = 0.83). However, the prediction accuracy of TNY using the NDSI and RSI was gradually decreased with an increase in bandwidth, i.e., the bandwidths with central wavelengths of 740 and 768 nm of the NDSI were 13 and 21 nm, respectively. For RSI, the bandwidths with central wavelengths of 744 and 756 nm were 29 and 17 nm, respectively. The results also demonstrated that an optimized narrow and broadband CCCI was significantly linear in relation to the TNY of maize (R-2 = 0.85), suggesting an optimized CCCI may be used to quantify TNY of maize plants with higher accuracy by avoiding the saturation effect and improving sensitivity.
机译:精密氮(N)管理需要准确有效地定量氮素产量(TNY)作物。因此,本研究旨在建立鲁棒预测模型,通过优化双频谱指标,即归一化差异光谱指数(NDSI)和比率光谱索引(RSI)来量化增长阶​​段,品种和年多年的TNE跨越生长阶段,品种和多年的玉米植物。和三带光谱索引,即通过重新确定中心波长和带宽来实现冠层叶绿素内容索引(CCCI)。在2011年,2012年和2013年,在华北平原中进行了三种玉米品种和五个治疗的田间试验。结果表明,NDSI和RSI的优化频段范围主要位于720-760 nm内(红色 - 边缘域)和750-900 nm(近红外域)。 NDSI的中心波长为768和740nm,而RSI的中心波长为756和744nm。 CCCI最合适的带域为720-760,500-600和740-800nm,它们的中央波长度为766,738和548nm。我们的研究发现,优化的光谱指标可以与现有的光谱指标相比,准确且鲁棒地预测TNY玉米。优化的NDSI和RSI与玉米TNY之间的关系达到了高度的确定系数(R-2 = 0.83)。然而,使用NDSI和RSI的TNY的预测精度随着带宽的增加而逐渐降低,即,具有740和768nm的中心波长的带宽分别为13和21nm。对于RSI,具有744和756nm的中心波长的带宽分别为29和17 nm。结果还表明,优化的窄和宽带CCCI与TNY的玉米(R-2 = 0.85)有显着线性,建议通过避免饱和效应来定量高精度的玉米植物的优化CCCI提高敏感性。

著录项

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号