Building and predicting methods of net photosynthetic rate predicting model based on woody plant leaf phenotypic characteristics

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

Inactive Publication Date: 2018-06-29
BEIJING FORESTRY UNIVERSITY
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It can be seen that the existing methods for measuring the net photo

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  • Building and predicting methods of net photosynthetic rate predicting model based on woody plant leaf phenotypic characteristics
  • Building and predicting methods of net photosynthetic rate predicting model based on woody plant leaf phenotypic characteristics
  • Building and predicting methods of net photosynthetic rate predicting model based on woody plant leaf phenotypic characteristics

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[0101] Example 1

[0102] S101: In the geographical distribution of Populus simonii across the country (Shaanxi, Qinghai, Hebei, Henan, Ningxia, Beijing, Inner Mongolia), 1233 samples of Populus spp. were collected, and we selected 235 individuals as representatives. In the cloning botanical garden in Guanxian County (36°23'N, 115°47'E), Shandong Province, China, the roots of these 235 individuals were used for asexual reproduction. In this study, these unrelated individuals were used to study the use of leaf phenotype data to predict net photosynthetic rate.

[0103] S102: Use the 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 obtained by CI-202 measurement, divide the 235 representative individuals into sub-species.

[0105] The average linkage clustering:

[0106] 1. S...

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Abstract

The invention provides building and predicting methods of a net photosynthetic rate predicting model based on woody plant leaf phenotypic characteristics and belongs to the field of bioinformatics. The building and predicting methods have the advantages that an average linkage clustering method and a PAM clustering method are combined to divide woody plants at different geographical positions intodifferent sub-varieties, and the differences of the different sub-varieties are eliminated to reasonably predict net photosynthetic rate; meanwhile, a gradient increasing algorithm is used in each sub-variety to build the net photosynthetic rate predicting model on the basis of the phenotype data of leaf samples, the gradient increasing algorithm iterative stopping criteria is put forward for thefirst time during modeling, algorithm iteration residual critical values are provided for the woody plant leaf phenotype data of different sub-varieties, the populus simonii net photosynthetic rate predicting model is built by using the improved gradient increasing algorithm based on the iterative stopping criteria, and an ideal predicting effect on the net photosynthetic rate of different populus simonii varieties can be achieved under a condition that the leaf phenotype data is known.

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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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
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