Method for predicting camellia oleifera suitable area

A technology for Camellia oleifera and model prediction, applied in forecasting, instrumentation, data processing applications, etc., can solve the problems of low output of camellia oil, serious diseases and insect pests, lack of fine varieties, etc., and achieve the effect of accurate prediction results and high reference value.

Inactive Publication Date: 2017-06-13
NANCHANG UNIV
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  • Abstract
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Problems solved by technology

[0003] In addition, the core problems restricting the development of camellia oleifera industry are

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0016] Embodiment 1, a kind of method for predicting Camellia oleifera suitable growth zone, its method step is as follows:

[0017]Step 1. Obtain the distribution point data of Camellia oleifera: by searching the scientific name of Camellia oleifera (such as: Camellia oleifera ) to obtain the sample data. These specimen data were screened to remove duplicates of the same specimen placed in different herbaria, specimens without geographical information and collection time, and specimens repeatedly sampled at the same location and time. Assign unique numbers to the specimen data, integrate key information about the specimens (collection time, location), and establish a database in an Excel table. The samples clearly marked as cultivated in the database were removed. Then, use Google Maps to verify the latitude and longitude information of each record, and remove some data that cannot obtain accurate latitude and longitude due to unclear collection information. In order to r...

Embodiment 2

[0030] Embodiment 2, a kind of method for predicting Camellia oleifera suitable growth area, its method step is except " in MaxEnt model analysis in the MaxEnt model analysis, the maximum number of iterations is set to 1,000, and Bootstrap repeats calculation 20 times," different from embodiment 1, the method step is different from embodiment 1. same.

Embodiment 3

[0031] Embodiment 3, a kind of method of predicting Camellia oleifera suitable growth area, its method step is except " in MaxEnt model analysis in the MaxEnt model analysis, the maximum number of iterations is set to 1,500, and Bootstrap repeats calculation 15 times," different from embodiment 1, the method steps are different from embodiment 1. same.

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Abstract

The invention discloses a method for predicting a camellia oleifera suitable area. The method comprises the following steps that: S1: obtaining camellia oleifera distribution point data; S2: obtaining the environmental data of the distribution point; S3: selecting a maximum entropy model to construct an ecological niche model, and dividing a suitable level for the potential distribution area of the camellia oleifera according to a distribution probability value for ecological niche model prediction; and S4: carrying out the reliability analysis of a prediction result. By use of the method, existing camellia oleifera distribution data and environment data can be utilized, the maximum entropy model is adopted to construct the ecological niche model, the camellia oleifera suitable area is predicted, a prediction result is accurate so as to be favorable for knowing a camellia oleifera distribution rule, and the method has a high reference value for guiding camellia oleifera production and searching wild camellia oleifera resources.

Description

technical field [0001] The invention belongs to the field of agricultural production, and in particular relates to a method for predicting the suitable growth area of ​​camellia oleifera. Background technique [0002] Camellia generally refers to the genus Camellia ( Camellia ) oil species with production and application value. Camellia oleifera is the largest woody oil crop in my country, and it is the woody oil plant with the most extensive cultivation area and the highest total oil production in my country. It is the same as oil palm ( Elaeis guineensis ),coconut( Cocos nucifera ) and olive ( Olea europaea ) and known as the world's four largest woody oil plants, and walnut ( Juglans regia ), Chinese tallow tree ( Sapium sebiferum ) and tung tree ( Vernicia Fordii ) and known as my country's four major woody oil plants. my country is the world's largest consumer of vegetable oil, with an annual consumption of more than 30 million tons of vegetable oil, of w...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/02
CPCG06Q10/04G06Q50/02
Inventor 戎俊崔相艳王文娟杨小强李述秦声远
Owner NANCHANG UNIV
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