云南松苗木生物量对不同指标的预估效应  

Prediction Effect of Seedling Biomass on Different Indexes of Pinus yunnanensis

作　　者：聂婷 李亚麒 石海涛 唐军荣 陈林 陈诗 蔡年辉 许玉兰 唐红燕 王德新 Nie Ting;Li Yaqi;Shi Haitao;Tang Junrong;Chen Lin;Chen Shi;Cai Nianhui;Xu Yulan;Tang Hongyan;Wang Dexin(College of Forestry,Southwest Forestry University,Kunming Yunnan 650233,China;Institute of Tropical and Subtropical Cash Crops,Yunnan Academy of Agricultural Sciences,Baoshan Yunnan 678000,China;Puer Institute of Forestry and Grassland,Puer Yunnan 665099,China)

机构地区：[1]西南林业大学林学院,云南昆明650233 [2]云南省农业科学院热带亚热带经济作物研究所,云南保山678000 [3]普洱市林业和草原科学研究所,云南普洱665099

出　　处：《西南林业大学学报（自然科学）》2023年第4期17-25,共9页Journal of Southwest Forestry University：Natural Sciences

基　　金：国家自然科学基金项目(31860203,31760204)资助;云南省万人计划青年拔尖人才项目(09901-80201441)资助;西南林业大学高值木本油料新种质创制与产业化创新团队项目(2019HC007)资助。

摘　　要：为提高云南松生物量的估测精度,以2年生云南松苗木为材料,采用回归模型估测法,以生长指标地径(D)、苗高(H)、地径与苗高的乘积(DH)、地径平方与苗高的乘积(D^(2)H)以及地上部分生物量(鲜质量)指标地上部分鲜质量(W_(Af))、茎鲜质量(W_(Sf))、叶鲜质量(W_(Lf))共7个指标为自变量,分别预估地下部分(总根、主根、侧根)及单株生物量。以决定系数(R^(2))、估计值标准误差(SEE)和回归检验显著水平作为最优模型选取标准,并对最优模型进行精度检验。结果表明:所构建的生物量最优模型均为幂函数,生长指标中D^(2)H和生物量指标中W_(Af)分别作为自变量拟合的模型最优,其中D^(2)H能较好预估地下部分总根鲜质量和主根鲜质量,W_(Af)能较好预估总根干质量、主根干质量、侧根干质量、单株干质量、侧根鲜质量和单株鲜质量,单株生物量的拟合优度明显高于地下部分,所预估的最优模型同一变量鲜质量与干质量差异不大。因此在实际生产中,对于不同的变量,要选择与变量最相适宜的预测指标去拟合,从而提高估测准确度。In order to improve the estimation accuracy of biomass of Pinus ynnanensis seedling,a regression model was used to estimate the biomass for two-year-old P.yunnanensis seedlings.Growth indexes including ground diameter(D),seedling height(H),product of ground diameter and seedling height(DH),product of ground diameter square and seedling height(D^(2)H),and aboveground biomass(fresh weight)indexes including aboveground biomass fresh weight(W_(Af)),stem fresh weight(W_(sf)),leaf fresh weight(W_(Lf))were taken as independent variables.The underground part(total root,major root,lateral root)and individual plant biomass were predicted respectively.The determination coefficient(R^(2)),the standard error of the estimated value(SEE)and the significance level of regression test were used as the selection criteria of the optimal model,and the accuracy of the optimal model was tested.The results show that the biomass optimal models constructed were all power functions.The product of ground diameter square and seedling height(D^(2)H)in growth index and the fresh biomass of aboveground part(W_(Af))in biomass index were the best models ftted with independent variables respectively.D^(2)H could better predict the total fresh root weight and major root fresh weight of underground part.W_(Af) could better predict the total root dry weight,major root dry weight,lateral root dry weight,individual plant dry weight,lateral root fresh weight and individual plant fresh weight,and the goodness of fit of lateral root biomass was significantly higher than that of underground parts.There was no significant difference between the predicted fresh weight and dry weight of the same variable in the optimal model.Therefore,in actual production,for different variables,the most appropriate prediction index should be selected to fit the variables so as to improve the accuracy of estimation.

关 键 词：云南松 生长指标 生物量指标 回归模型 

分 类 号：S791.257[农业科学—林木遗传育种]