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Influence of Different Precipitation Periods on Dendrolimus superans Occurrence: A Biostatistical Analysis
Author(s) -
Zhiru Li
Publication year - 2021
Publication title -
international journal of agriculture and biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.271
H-Index - 39
eISSN - 1814-9596
pISSN - 1560-8530
DOI - 10.17957/ijab/15.1638
Subject(s) - precipitation , abiotic component , pest analysis , biology , negative correlation , veterinary medicine , positive correlation , simple correlation , correlation , zoology , toxicology , mathematics , ecology , botany , medicine , meteorology , geography , geometry
Precipitation is one of the most important abiotic factors that affect Dendrolimus superans occurrence. In this study, agrey slope-correlation model was used, and a simplified grey slope-correlation model was constructed to uncover the most crucial periods of precipitation that pest occurrence. Results revealed that thetwo models were similar; however, the simplified grey slope-correlation model required less calculative steps and was easier to operate. The calculation results revealed that the most crucial period occurred during thefirst 10 days of July (γ13 = 0.67, γ`13 = 0.69). The other precipitation periods associated with pest occurrence included thefirst 10 days of August (γ16 = 0.62, γ`16 = 0.61), the third 10 days of May (γ09 = 0.59, γ`09 = 0.62), the sec10 days of May (γ08 = 0.58, γ`08 = 0.60), and the third 10 days of August (γ18 = 0.58, γ`18 = 0.60). The less associated precipitation periods included the first 10 days of March (γ01 = 0.54, γ`01 = 0.47), the sec10 days of March (γ02 = 0.50, γ`02 = 0.49), the third 10 days of April (γ06 = 0.47, γ`06 = 0.48), the sec10 days of June (γ11 = 0.51, γ`11 = 0.48), and the third 10 days of June (γ12 = 0.51, γ`12 = 0.51). Precipitation in May (γ07 + γ08 + γ09 = 1.74, γ`07 + γ`08 + γ`09 = 1.79) and July (γ13 + γ14 + γ15 = 1.74, γ`13 + γ`14 + γ`15 = 1.79) was mostly associated with D.superansoccurrence. The findings of this study provided a simple operative model for determining the most crucial precipitation periods of pest occurrence, and these analytical methods can serve as a theoretical reference for pest forecasting and early warning, which contributes to ecological protection.© 2021Friends Science Publishers

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