Method for modeling rice and wheat leaf nitrogen content spectrum monitoring model

Abstract

The invention discloses a method for modeling a rice and wheat leaf nitrogen content spectrum monitoring model and belongs to the field of nondestructive monitoring of crop growth information in precision agriculture. The method comprises the following steps of: fusing rice and wheat canopy leaf reflectance spectrum data which is acquired by a field high-spectrum radiometer with rice and wheat canopy leaf nitrogen content data; and establishing a canopy leaf nitrogen content spectrum monitoring model orienting different growth periods of rice and wheat based on narrow band and wide band combination. The optimal vegetation index orienting a rice and wheat jointing and booting stage and a heading and grain filling period is established by utilizing multi-point rice and wheat field test data in many years; and rice and wheat canopy leaf nitrogen content common characteristic wave band and bandwidth are developed. The model covers different species and different nitrogen levels of rice and wheat, utilizes a data validation model in an independent year, and is high in universality and high in accuracy.

Description

technical field [0001] The invention discloses a modeling method for a spectral monitoring model of nitrogen content in rice and wheat leaves, relates to a spectral monitoring model of rice and wheat growth information, and belongs to the field of non-destructive monitoring of crop growth information in precision agriculture. Background technique [0002] Rice and wheat are the most important food crops in my country. Real-time monitoring of rice and wheat nitrogen nutrition status can not only ensure the yield and quality of rice and wheat, but also improve the efficiency of nitrogen fertilizer use and reduce groundwater pollution, thereby generating huge economic and ecological benefits. For a long time, the nitrogen content monitoring of rice and wheat has been obtained through destructive sampling in the field and indoor analysis and measurement. The disadvantages are: time-consuming and laborious, poor timeliness, and cannot guide the precise management of rice and wheat...

AI Technical Summary

Problems solved by technology

For a long time, the nitrogen content monitoring of rice and wheat has been obtained through destructive sampling in the field and indoor analysis and measurement. The disadvantages are: time-consuming and laborious, poor timeliness, and cannot guide the precise management of rice and wheat in real time

The traditional method is to use characteristic bands to construct a single spectral parameter according to the growth status of crops in different growth stages, and quantitatively analyze the relationship between spectral parameters and physiological parameters to establish a spectral monitoring model; however, the spectral reflectance of rice and wheat in different growth stages The difference is large, and a single spectral parameter is difficult to reflect the changing law of the physiological parameters of rice and wheat. The established spectral monitoring model has low accuracy and poor sensitivity.

[0004] At present, crop nitrogen content monitoring models based on different characteristic spectral parameters are all aimed at a single crop, the universality of characteristic bands is poor, and the mechanism of the model is not strong

Although there are currently studies on the common characteristic spectra of nitrogen content in rice and wheat leaves, they are all based on multispectral data. Solve the problem of suitable bandwidth for characteristic bands

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