Hyperspectral estimation of canopy chlorophyll of winter wheat by using the optimized vegetation indices

被引:25
作者
Zhang, Xuan [1 ]
Sun, Hui [1 ,2 ]
Qiao, Xingxing [1 ]
Yan, Xiaobin [1 ]
Feng, Meichen [1 ]
Xiao, Lujie [1 ]
Song, Xiaoyan [1 ]
Zhang, Meijun [1 ]
Shafiq, Fahad [3 ]
Yang, Wude [1 ]
Wang, Chao [1 ]
机构
[1] Shanxi Agr Univ, Agr Coll, Jinzhong 030600, Peoples R China
[2] Shanxi Agr Univ, Coll Resources & Environm, Jinzhong 030600, Peoples R China
[3] Univ Lahore, Inst Mol Biol & Biotechnol, Lahore, Pakistan
基金
中国国家自然科学基金;
关键词
Hyperspectral; Vegetation index; Band optimization; Canopy chlorophyll content; Winter wheat; LEAF-AREA INDEX; NITROGEN CONCENTRATION; SPECTRAL REFLECTANCE; BIOMASS ESTIMATION; AGRICULTURE; EFFICIENCY; DENSITY; MAIZE; CORN;
D O I
10.1016/j.compag.2021.106654
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The vegetation indices (VIs) derived from the different band combinations can be used for monitoring crop quality traits. We conducted field experiments over two years time to investigate critical growth stages across four varieties and by using different nitrogen (N) application rates. In order to explore and evaluate the performance of different VIs on estimation of the canopy chlorophyll content (CCC) of winter wheat, the published and modified indices were optimized by using the random band combination through original spectrum (OS) and first-order differential (FD) treatment. The results showed that the first derivative processing improved the correlation between the red edge band and winter wheat CCC. The three-band VI can break the restriction of the number of bands on the extraction of target information, relieved the saturation problem of the dual-band VI, and improved the monitoring accuracy of winter wheat CCC. The index 2 x R1-R2-R3 was found to be the best VI for assessing the CCC of winter wheat based on the original and first-order differential spectrum (calibration R2 > 0.733), R-2 and RMSE of validation set were 0.688, 0.755 and 1.515, 1.336, respectively. In addition, the index expression formula R1/(R2 x R3) was recommended as a favorable choice for monitoring the agronomic traits of crop. Moreover, the VI is suggested to use at the red edge position band to monitor crop growth indicators. In conclusion, the use of VI can better monitor winter wheat CCC which could provide a theoretical basis for precision agriculture.
引用
收藏
页数:12
相关论文
共 50 条
[21]   Estimation of Winter Wheat Canopy Chlorophyll Content Based on Canopy Spectral Transformation and Machine Learning Method [J].
Chen, Xiaokai ;
Li, Fenling ;
Shi, Botai ;
Fan, Kai ;
Li, Zhenfa ;
Chang, Qingrui .
AGRONOMY-BASEL, 2023, 13 (03)
[22]   Comparison of different hyperspectral vegetation indices for canopy leaf nitrogen concentration estimation in rice [J].
Tian, Yong-Chao ;
Gu, Kai-Jian ;
Chu, Xu ;
Yao, Xia ;
Cao, Wei-Xing ;
Zhu, Yan .
PLANT AND SOIL, 2014, 376 (1-2) :193-209
[23]   Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression [J].
Li, Fei ;
Mistele, Bodo ;
Hu, Yuncai ;
Chen, Xinping ;
Schmidhalter, Urs .
EUROPEAN JOURNAL OF AGRONOMY, 2014, 52 :198-209
[24]   Estimation of Grain Protein Content in Winter Wheat by Using Three Methods with Hyperspectral Data [J].
Xiu-liang Jin ;
Xin-gang Xu ;
Hai-kuan Feng ;
Xiao-yu Song ;
Qian Wang ;
Wang, Ji-hua ;
Guo, Wen-shan .
INTERNATIONAL JOURNAL OF AGRICULTURE AND BIOLOGY, 2014, 16 (03) :498-504
[25]   Estimation of leaf chlorophyll content in winter wheat using variable importance for projection (VIP) with hyperspectral data [J].
He, Peng ;
Xu, Xingang ;
Zhang, Baolei ;
Li, Zhenhai ;
Feng, Haikuan ;
Yang, Guijun ;
Zhang, Yongfeng .
REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XVII, 2015, 9637
[26]   Winter Wheat GPC Estimation Based on Leaf and Canopy Chlorophyll Parameters [J].
Song Xiao-yu ;
Wang Ji-hua ;
Yang Gui-jun ;
Cui Bei ;
Chang Hong .
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34 (07) :1917-1921
[27]   Inversion of winter wheat canopy chlorophyll content using angle-insensitive UAV-based spectral indices [J].
Ye, Sumeng ;
Zhang, Zhitao ;
Chen, Junying ;
Chen, Haiying ;
Zhang, Bei ;
Bai, Xuqian ;
Yang, Ning ;
Du, Ruiqi ;
Yang, Xiaofei ;
Xu, Qi ;
Qian, Long ;
Chen, Yinwen ;
Zhang, Siying .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2025, 230
[28]   Estimation of Winter Wheat Tiller Number Based on Optimization of Gradient Vegetation Characteristics [J].
Wu, Fei ;
Wang, Junchan ;
Zhou, Yuzhuang ;
Song, Xiaoxin ;
Ju, Chengxin ;
Sun, Chengming ;
Liu, Tao .
REMOTE SENSING, 2022, 14 (06)
[29]   HYPERSPECTRAL ESTIMATION OF WHEAT CHLOROPHYLL CONTENT BASED ON PRINCIPAL COMPONENT ANALYSIS [J].
Ma, C. Y. ;
Shi, J. J. ;
Wu, X. F. ;
Guo, M. ;
Li, C. C. .
APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2023, 21 (06) :5009-5037
[30]   Estimating winter wheat nitrogen content using SPAD and hyperspectral vegetation indices with machine learning [J].
Feng H. ;
Li Y. ;
Wu F. ;
Zou X. .
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2024, 40 (01) :227-237