A pine-wilt disease forecasting model for Zhejiang Province

XIANG Yi-juan; GUAN Jian-feng; LI Jian; HUANG Ji-yu; MA Liang-jin

doi:10.11833/j.issn.2095-0756.2011.05.015

Volume 28 Issue 5

Oct. 2011

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Article Navigation > Journal of Zhejiang A&F University > 2011 > 28(5): 775-778

XIANG Yi-juan, GUAN Jian-feng, LI Jian, HUANG Ji-yu, MA Liang-jin. A pine-wilt disease forecasting model for Zhejiang Province[J]. Journal of Zhejiang A&F University, 2011, 28(5): 775-778. doi: 10.11833/j.issn.2095-0756.2011.05.015

Citation:

XIANG Yi-juan, GUAN Jian-feng, LI Jian, HUANG Ji-yu, MA Liang-jin. A pine-wilt disease forecasting model for Zhejiang Province[J]. Journal of Zhejiang A&F University, 2011, 28(5): 775-778. doi: 10.11833/j.issn.2095-0756.2011.05.015

A pine-wilt disease forecasting model for Zhejiang Province

doi: 10.11833/j.issn.2095-0756.2011.05.015

1.
Institute of Forest Protection，Zhejiang A & F University，Lin’an 311300，Zhejiang，China;
2.
Forest Disease Quarantine Station of Ninghai City，Ninghai 315600，Zhejiang，China;
3.
Forest Station of Qianxiang Town，Dongyang 322100，Zhejiang，China;
4.
Forest Enterprise of Anji City，Anji 313300，Zhejiang，China

More Information

Corresponding author: MA Liang-jin
Publish Date: 2011-10-20

Abstract

To better predict pine-wilt disease in Zhejiang，one of the provinces with a serious problem in disease prevention often lagging behind occurrence and harm，the disease was monitored from 2004 - 2008 and combined with meteorological data for Ninghai，Zhejiang using the Statistical Analysis System（SAS）to determine the variables affecting the degree of pine-wilt disease the most. Then，stepwise regression was employed to produce a forecasting model. Results showed that dead trees per hectare（x3），mid-July longicorn feather number （x9），and average temperature in July （x26） were significant （P＜0.05）variables. The forecasting model with stepwise regression was: y = 0.300 67 + 1.578 97x3－0.012 22x9 + 0.001 84x26. This model will contribute to prevention countermeasures and provide technical support for sustainably controlling pine-wilt disease. ［Ch，1 fig. 3 tab. 11 ref.］
- forest protection,
- pine-wilt disease,
- Monochamus alternatus,
- predict and forecast

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

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A pine-wilt disease forecasting model for Zhejiang Province

1. Institute of Forest Protection，Zhejiang A & F University，Lin’an 311300，Zhejiang，China;

2. Forest Disease Quarantine Station of Ninghai City，Ninghai 315600，Zhejiang，China;

3. Forest Station of Qianxiang Town，Dongyang 322100，Zhejiang，China;

4. Forest Enterprise of Anji City，Anji 313300，Zhejiang，China

Corresponding author: MA Liang-jin

Publish Date: 2011-10-20

Key words:

Abstract: To better predict pine-wilt disease in Zhejiang，one of the provinces with a serious problem in disease prevention often lagging behind occurrence and harm，the disease was monitored from 2004 - 2008 and combined with meteorological data for Ninghai，Zhejiang using the Statistical Analysis System（SAS）to determine the variables affecting the degree of pine-wilt disease the most. Then，stepwise regression was employed to produce a forecasting model. Results showed that dead trees per hectare（x3），mid-July longicorn feather number （x9），and average temperature in July （x26） were significant （P＜0.05）variables. The forecasting model with stepwise regression was: y = 0.300 67 + 1.578 97x3－0.012 22x9 + 0.001 84x26. This model will contribute to prevention countermeasures and provide technical support for sustainably controlling pine-wilt disease. ［Ch，1 fig. 3 tab. 11 ref.］

A pine-wilt disease forecasting model for Zhejiang Province

doi: 10.11833/j.issn.2095-0756.2011.05.015

Abstract

References

Proportional views

通讯作者: 陈斌, bchen63@163.com

Related

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