...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Transactions of the ASABE >Remote Sensing of Cotton Nitrogen Status Using the Canopy Chlorophyll Content Index (CCCI)
【24h】

Remote Sensing of Cotton Nitrogen Status Using the Canopy Chlorophyll Content Index (CCCI)

机译：利用冠层叶绿素含量指数（CCCI）遥感棉花氮素状况

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3 -N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.
机译：各种遥感指数已被用于推断作物氮素的水平，以进行田间规模的养分管理。但是，如果受其他因素（例如水分胁迫）影响的作物冠层密度降低，则此类指数可能表示错误的N状态。冠层叶绿素含量指数（CCCI）是已提出的用于推断棉花N状况的二维遥感指数。 CCCI使用近红外（NIR）和红色光谱区域中的反射率来解释冠层密度的季节性变化，而NIR和远红色区域中的反射率用于检测冠层叶绿素的相对变化（N含量的替代物） 。这项研究的主要目的是评估CCCI和其他几个遥感指数，以检测生长期期间棉花的N态。第二个目标是评估在水状态变化时指标适当检测N的能力。在亚利桑那州的1998年棉花季（每年[DOY] 114到310年）和1999年棉花期（DOY 106到316年）收集了遥感数据，其中对氮和水进行了优化处理。在1998年季节，直到完全覆盖之后，才在季节后期进行水处理（DOY 261）。 1998年针对最佳氮肥（DOY 154）进行了早期的氮肥施用，但对低氮肥并非如此，CCCI发现从DOY 173开始，当冠层覆盖率约为30％时，氮肥之间的作物氮素状况存在显着差异。一个常见的植被指数，即NIR与红色的比率（RVI），也检测到N种处理之间的显着分离，但是RVI的检测发生在CCCI响应后16天。在1998年对DOY 190的最佳氮处理和低氮处理均施以等量的N后，CCCI指示DOY 198的N处理的氮状况相当，RVI未发现这一趋势。在1999年的季节中，在该季节的早期和经常进行氮和水处理。当部分处理的水位不同时，CCCI和RVI在部分冠层条件下对N的状态描述不佳。但是，一旦在1999年获得了完全的树冠，无论水的状况如何，CCCI都会提供可靠的N状态信息。在全棉覆盖下，CCCI与测得的氮素状态参数显着相关，包括叶柄NO 3 -N（r = 0.74），SPAD叶绿素（r = 0.65）和总叶N含量（r = 0.86）。对于水分充足的棉花，在冠层覆盖率达到约30％之后，CCCI有望将其作为棉花N状况的有用指标。然而，需要进一步的研究以将CCCI发展为独立于水分胁迫的强大的N检测工具。

著录项

  • 来源
    《Transactions of the ASABE》 |2008年第1期|p.73-82|共10页
  • 作者

    D. M. El-Shikha E. M. Barnes T. R. Clarke D. J. Hunsaker J. A. Haberland P. J. Pinter Jr. P. M. Waller T. L. Thompson;

  • 作者单位

    The authors are Disa M. El-Shikha, Research Specialist, USDA-ARS U.S. Arid Land Agricultural Research Center, Maricopa, Arizona;

    Edward M. Barnes, ASABE Member Engineer, Director Agricultural Research, Cotton, Inc., Cary, North Carolina;

    Thomas R. Clarke, Physical Scientist, and Douglas J. Hunsaker, ASABE Member Engineer, Agricultural Engineer, USDA-ARS U.S. Arid Land Agricultural Research Center, Maricopa, Arizona;

    Julio A. Haberland, Professor, Department of Engineering and Soils, University of Chile, Santiago, Chile;

    Paul J. Pinter, Former Research Biologist, USDA-ARS U.S. Water Conservation Laboratory, Phoenix, Arizona;

    Peter M. Waller, Associate Professor, Department of Agricultural and Biosystems Engineering, University of Arizona, Tucson, Arizona;

    and Thomas L. Thompson, Chair and Professor of Soil Science, Department of Plant and Soil Science, Texas Tech University, Lubbock, Texas. Corresponding author: Douglas J. Hunsaker, USDA-ARS U.S. Arid Land Agricultural Research Center, 21881 N. Cardon Lane, Maricopa, AZ 85238;

    phone: 520-316-6372, fax: 520-316-6330;

    e-mail: doug.hunsaker@ars.usda.gov.;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Canopy reflectance, Fertility detection, Radiometers, Spectral analysis, Water stress;

    机译：冠层反射率;生育力检测;辐射计;光谱分析;水分胁迫;

相似文献

  • 外文文献
  • 中文文献
  • 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