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Scientia Silvae Sinicae ›› 2020, Vol. 56 ›› Issue (12): 83-90.doi: 10.11707/j.1001-7488.20201210

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Prediction Disease Based Index of Needle Blight Disease (Pestalotiopsis funerea) in Pinus densiflora Pure Forest in Kunyushan Mountains

Ruirui Hu1,2,Jun Liang1,3,*,Xian Xie1,Jiming Che3,Xiaowen Yuan3,Yingjun Zhang3,Xingyao Zhang1,3   

  1. 1. Key Laboratory of Forest Protection of National Forestry and Grassland Administration Institute of Forest Ecological Environment and Protection, Chinese Academy of Forestry Beijing 100091
    2. Tianjin Academy of Institute of plant Protection Tianjin 300380
    3. Kunyushan Forest Ecosystem Research Station Yantai 264100
  • Received:2019-10-21 Online:2020-12-25 Published:2021-01-22
  • Contact: Jun Liang

Abstract:

Objective: In order to avoid planting Pinus densiflora(Japanese red pine, JRP) in the woodland which is potentially seriously damaged by JRP blight(Pestalotiopsis funerea), the disease based index(DBI)-site factors evaluation system was established to quantitatively predict the degree of potential pathogen infection of JRP needle blight in the forest land to be planted. Methods: The disease based index of each sample plot was found based on the DBI curve group graph of JRP needle blight. Through correlation analysis, the key site factors were selected, the relationship equations between DBI-all site factors and DBI-key site factors of JRP needle blight were established by using the quantificative theory I. Results: 1) Correlation analysis showed that elevation, soil texture and humus depth had an extremely significant influence on disease based index(P < 0.01), slope aspect had significant influence on disease based index(P < 0.05), and the order of contribution to disease based index was slope aspect < soil texture < elevation < humus depth. 2) The multiple linear regression model of all site factors, key site factors and disease based index reached the extremely significant level statistically(P < 0.01), and the determination coefficient(R2) was 0.710 0 and 0.678 0, respectively, indicating that the model had a good fitting effect, and 4 key site factors could be used to replace all site factors as the independent variables of the equation. 3) A field test on model (2) (DBI-key site factors) showed that the average estimation error(MPE) was 8.73%, indicating that the estimation accuracy is above 91.27%. the TRE value is close to 0, thus the model is reliable. Conclusion: Disease based index-site factors evaluation system can quantitatively predict potential infection of JRP needle blight, which can provide theoretical basis for optimum planting and prevention of JRP needle blight.

Key words: Pinus densiflora, pine needle blight, disease based index, pure plantation, Kunyushan Mountains

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