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Construction method and prediction method of a net photosynthetic rate prediction model based on phenotypic characteristics of woody plant leaves

A net photosynthetic rate, woody plant technology, applied in the field of net photosynthetic rate prediction model construction, can solve the problem of high environmental requirements, achieve the effect of accurate division and elimination of differences

Inactive Publication Date: 2019-03-26
BEIJING FORESTRY UNIVERSITY
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Problems solved by technology

It can be seen that the existing methods for measuring the net photosynthetic rate generally have higher requirements on the environment.

Method used

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  • Construction method and prediction method of a net photosynthetic rate prediction model based on phenotypic characteristics of woody plant leaves
  • Construction method and prediction method of a net photosynthetic rate prediction model based on phenotypic characteristics of woody plant leaves
  • Construction method and prediction method of a net photosynthetic rate prediction model based on phenotypic characteristics of woody plant leaves

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Embodiment 1

[0102] S101: In the geographical distribution of Populus microphylla in the whole country (Shaanxi, Qinghai, Hebei, Henan, Ningxia, Beijing, Inner Mongolia), 1233 samples of Populus microphylla were collected, and we selected 235 individuals among them as representatives. The roots of these 235 individuals were used for vegetative propagation in a clonal botanical garden in Guan County (36°23'N, 115°47'E), Shandong Province, China. In the present study, these unrelated individuals were used to study the prediction of net photosynthetic rate using leaf phenotype data.

[0103] S102: Use a portable laser leaf area meter (CI-202) to measure the six leaf phenotype data of leaf area, length, width, circumference, aspect ratio and leaf shape factor.

[0104] S103: Combining average linkage clustering and PAM clustering, based on the leaf phenotype data measured by CI-202, divide 235 representative individuals into sub-variety.

[0105] The average linkage clustering:

[0106] 1. S...

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Abstract

The invention provides a construction method and a prediction method of a net photosynthetic rate prediction model based on the phenotypic characteristics of woody plant leaves, and belongs to the field of bioinformatics. The present invention adopts the combination of average linkage clustering and PAM clustering method to divide woody plants in different geographical locations into different sub-species, so as to eliminate the differences of different sub-species so as to predict the net photosynthetic rate more reasonably. At the same time, the present invention In each sub-variety, the gradient boosting algorithm is used to construct a net photosynthetic rate prediction model based on the phenotype data of the leaf samples. The leaf phenotype data provided the residual critical value of the algorithm iteration, and the net photosynthetic rate prediction model of P. The net photosynthetic rate of the cultivars had ideal prediction results.

Description

technical field [0001] The invention belongs to the field of biological information, and in particular relates to a construction method and a prediction method of a net photosynthetic rate prediction model based on the phenotypic characteristics of woody plant leaves. Background technique [0002] Net photosynthetic rate is an important index to measure the intensity of plant photosynthesis and plays an important role in the process of plant growth and development (ShipleyB et al.2005). In the 19th century, Sachs first proposed the method of measuring photosynthetic rate by the half-leaf method, which was the earliest method applied to the measurement of photosynthetic rate. It does not require complicated instruments and equipment, and is simple and easy to implement. However, using the half-leaf method will destroy the tested material and cannot be measured continuously, and the measurement time is long, and the environmental conditions are not easy to control, resulting i...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50G06K9/62
CPCG06F30/20G06F18/231
Inventor 张晓宇吉心悦胡梦瑶宋跃朋张德强
Owner BEIJING FORESTRY UNIVERSITY