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Ying Yong Sheng Tai Xue Bao. 2018 Apr;29(4):1225-1232. doi: 10.13287/j.1001-9332.201804.020.

[The inversion of nitrogen balance index in typical growth period of soybean based on high definition digital image and hyperspectral data on unmanned aerial vehicles].

[Article in Chinese; Abstract available in Chinese from the publisher]

Author information

1
Henan Polytechnic University, Jiaozuo 454000, Henan, China.
2
Collaborative Innovation Center of Beidou Navigation Satellite System Research Application, Zhengzhou 450001, China.
3
Zhengzhou Vocational University of Information and Technology, Zhengzhou 450008, China.

Abstract

in English, Chinese

Nitrogen balance index (NBI) is one of the important indicators for crop growth. The high and low status of nitrogen can be quickly monitored by measuring NBI, which can provide accurate information of agricultural production and management. The relationship between NBI and original spectrum and derivative spectrum of infrared and near infrared wavelength from flowering to maturity stage was analyzed based on high definition digital image and hyperspectral data on unmanned aerial vehicles. Then, the sensitive bands were selected and the vegetation indexes were calculated. The inversion models of NBI were constructed by empirical model method. The optimal inversion model was obtained by analysing the determination coefficient (R2) and the root mean square error (RMSE) of validating model. The results showed that the correlation between NBI and derivative spectral reflectance was more stronger than that between it and original spectral reflectance. All the 14 vegetation indices selected in this study, except the derivative spectral photochemical reflectance index, had significant correlation with NBI. The NBI inversion models were constructed based on those 13 vegetation indices and the accuracy was analyzed. The inversion model constructed by derivative spectral difference vegetation index had the highest accuracy, with the R2 and RMSE being 0.771 and 3.077 respectively. The soybean NBI distribution maps of the whole growing stages generated by this model could reflect the soybean growth state. Estimation of NBI using the high definition digital image and hyperspectral data obtained by unmanned aerial vehicle, as shown by our results, could be a real-time, dynamic, non-destructive and effective way to monitor the nitrogen status of soybean. It's a simple and practical method for precise management of nitrogen in soybean.

KEYWORDS:

derivative spectrum; high definition digital image; hyperspectral data; nitrogen balance index; soybean; unmanned aerial vehicle; vegetation index

PMID:
29726232
DOI:
10.13287/j.1001-9332.201804.020
[Indexed for MEDLINE]

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