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Estimation Method of Characteristic Parameters of Wheat Variety Based on mcmc

A characteristic parameter and wheat technology, which is applied in special data processing applications, calculations, electrical digital data processing, etc., can solve the problems of being unable to search for global optimal variables and low inversion efficiency

Active Publication Date: 2016-12-14
NANJING AGRICULTURAL UNIVERSITY
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Problems solved by technology

However, these methods have shortcomings such as low inversion efficiency and the inability to search for global optimal variables.

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  • Estimation Method of Characteristic Parameters of Wheat Variety Based on mcmc
  • Estimation Method of Characteristic Parameters of Wheat Variety Based on mcmc
  • Estimation Method of Characteristic Parameters of Wheat Variety Based on mcmc

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Embodiment Construction

[0043] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0044] The method for estimating characteristic parameters of wheat varieties of the present invention was applied in Xuzhou area, using the growth period and yield data of Xumai 25 wheat variety from 1999 to 2003 in Xuzhou area to effectively estimate the characteristic parameters of Xumai 25. combine figure 1 process in detail.

[0045] 1) Data preparation, WheatGrow model ( figure 2 ) data acquisition, first record the daily meteorological data in the field during the wheat growing season through the automatic weather station, including daily maximum temperature, daily minimum temperature, sunshine hours, and daily rainfall. Using the five-point sampling method, the cultivated layer is divided into four layers from top to bottom for field soil sampling, and then through indoor physical and chemical analysis, the soil bulk densit...

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Abstract

The invention discloses a method for estimating characteristic parameters of wheat varieties based on MCMC. The method mainly uses the growth period and yield of wheat varieties measured in the field and the growth period and yield simulated by the wheat growth model to construct a probability density function, and uses the MCMC method to invert Get the characteristic parameters of wheat varieties. The specific process first obtains the prior probability distribution of wheat variety characteristic parameters through test operation, proposes candidate parameters according to the initial parameters and prior distribution, calculates the probability density function and relief ratio of yield and growth period, and judges whether to accept the new model according to the M-H criterion. Finally, the posterior probability density distribution of each characteristic parameter of the variety is obtained. The estimation result of the method of the invention is both accurate and efficient, and has universal applicability in the estimation of characteristic parameters of similar model wheat varieties.

Description

technical field [0001] The invention belongs to the field of quantitative evaluation of wheat variety characteristics in precision agriculture, and relates to a method for estimating characteristic parameters of wheat varieties, in particular to a method for estimating characteristic parameters of wheat varieties combined with a Markov Chain Monte Carlo method (Markov Chain Monte Carlo, MCMC). Background technique [0002] With the development and progress of agricultural technology, new wheat varieties continue to appear. Scientists have proposed many parameters that can quantify the characteristics of crop varieties through the study of the physiological and ecological characteristics of different varieties, such as plant height, thousand-grain weight, physiological vernalization days, and grain filling. These parameters are called crop variety characteristic parameters, which mainly reflect the genotype characteristics of crops. For more than half a century, many crop gro...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
Inventor 曹卫星吕尊富朱艳刘小军姚霞汤亮倪军
Owner NANJING AGRICULTURAL UNIVERSITY
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