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Bulletin of Botanical Research ›› 2019, Vol. 39 ›› Issue (6): 890-898.doi: 10.7525/j.issn.1673-5102.2019.06.012

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Effect of Sample Size on the Precision of Biomass Model of Pinus yunnanensis Seedlings

LI Ya-Qi1, XU Yu-Lan1,2, LI Wei3, SUN Ji-Wei2, WANG Meng-Ting2, CAI Nian-Hui1,2   

  1. 1. Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China(Southwest Forestry University), Ministry of Education, Kunming 650224;
    2. Key Laboratory for Forest Genetic and Tree Improvement&Propagation in Universities of Yunnan Province, Southwest Forestry University, Kunming 650224;
    3. Yunnan Jicheng Landscape Technology Co., Ltd., Mile 652300
  • Received:2019-04-29 Online:2019-11-05 Published:2019-11-16
  • Supported by:
    National Natural Science Foundation of China(31760204,31860203);Funds for the Construction of First-class Forestry Discipline in Yunnan Province;Key Laboratory For Forest Genetic and Tree Improvement & Propagation in Universities of Yunnan Province(YNGBT201702,YNGBS201704)

Abstract: A total of 615 Pinus yunnanensis seedlings from 20 families were selected to study the influence of different sample sizes on biomass model construction and modelling accuracy. Different sampling sizes of 20 families of P.yunnanensis were used to establish the allometric equation of each organ and individual biomass of P.yunnanensis seedlings, after a sampling frame was established. The goodness of fit and accuracy of the optimal models were compared by the coefficient determination(R2), standard error of estimated value(SEE), root mean square error(RMSE), total relative error(RS) and mean absolute error(MAB). The allometric equation displayed a good biomass estimate of P.yunnanensis seedlings. With the increase of the sample size, the model precision evaluation index MAB decreases gradually in the form of power function. When the sample size is less than 200, MAB is more sensitive and the modeling accuracy is poor. If the sample size reaches about 200, the accuracy reaches a stable state.

Key words: Pinus yunnanensis, sample size, allometric equation, prediction accuracy

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