Method for detecting winter wheat ear moisture content based on hyperspectral technology

Abstract

The invention discloses a method for detecting winter wheat ear moisture content based on a hyperspectral technology. The method comprises the steps of: processing collected winter wheat ear moisturedata; screening characteristic wave bands sensitive to the winter wheat ear moisture content; constructing a winter wheat ear moisture content estimation model by adopting a partial least square method; carrying out model precision detection by adopting a determination coefficient R2 and a root-mean-square error RMSE; and finally inputting sensitive spectral data of a to-be-detected target into the model in the step 3, so as to obtain winter wheat ear moisture content information. The model constructed by adopting the method can meet the requirement for detection precision of the winter wheatear moisture content, and improves the detection precision, robustness and universality of the winter wheat ear moisture content.

Description

technical field

[0001] The invention relates to the technical field of wheat moisture content detection, in particular to a method for detecting the moisture content of winter wheat ears based on hyperspectral technology. Background technique

[0002] Winter wheat is planted in slightly warmer places. It is usually sown from mid-to-late September to early October, and matures from the end of May to mid-to-late June of the following year. For example, North China and its south are winter wheat. Winter wheat is one of the main food crops in my country. With the gradual expansion of my country's economic and social development, the demand for food production is gradually expanding. Dynamically estimating the growth and development of winter wheat is conducive to timely grasping the production of winter wheat, and the growth and development of winter wheat ears is the result of production. Therefore, it is of great significance to carry out the detection of physiological paramet...

Images