Method for Predicting Wheat Grain Yield Based on Chlorophyll Fluorescence and Its Model Construction Method

Abstract

The invention discloses a method for predicting wheat grain output based on chlorophyll fluorescence and its model construction method, which solves the technical field of large climate and agricultural model parameters, poor adaptability and large influence on a remote sensing model due to test environment, and low monitoring precision. The method comprises the following steps: information acquisition; screening of sensitive fluorescence parameters, determination of proper space leaf position, establishment of fluorescence potential index; and establishment of an output prediction model. The photopic fluorescence parameters of Fm' and Fv' of two leaves at the top of the wheat are used for better indicating the plant production performance; at a flowering stage and a grouting early stage, the chlorophyll fluorescence Fm' and Fv' potential index can predict the wheat grain output status. The prediction model can effectively reduce the influences by the factors of places, types and weather, has high precision and accuracy on the wheat grain output estimation, and has important meaning and value for guidance of the agriculture production, supply and demand balance of the grains and agriculture policy making.

Description

technical field [0001] The invention relates to the technical field of non-destructive monitoring of agricultural vegetation growth information, in particular to a method for predicting wheat grain yield based on chlorophyll fluorescence and a method for constructing a model thereof. Background technique [0002] Wheat is one of the three major food crops in my country. There are a variety of foods produced from wheat, such as noodles, bread, biscuits, steamed buns, etc. The level of wheat production directly affects people's living standards and national food security. Therefore, early forecasting of yield will help field managers to take timely response measures in the field, which is of great significance for guiding the balance of grain supply and demand and the formulation of agricultural policies. [0003] The traditional yield information adopts field sampling survey, which needs to be harvested and threshed to calculate the yield when the wheat is harvested, which is...

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Problems solved by technology

[0005] In order to solve the deficiencies in the prior art, the present invention provides a method for predicting wheat grain yield based on chlorophyll fluorescence and a method for constructing a model thereof, aiming at solving the problem that the existing climate and agronomic models have many parameters, poor adaptability, and remote sensing models. The technical problems of large impact on the test environment and low monitoring accuracy

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