YUAN Xiaokang. Study on Wet Damage Index of Rape in Flowering and Pod-bearing Period in Hunan Province[J]. Guangdong Agricultural Sciences, 2021, 48(6): 1-6. DOI: 10.16768/j.issn.1004-874X.2021.06.001
    Citation: YUAN Xiaokang. Study on Wet Damage Index of Rape in Flowering and Pod-bearing Period in Hunan Province[J]. Guangdong Agricultural Sciences, 2021, 48(6): 1-6. DOI: 10.16768/j.issn.1004-874X.2021.06.001

    Study on Wet Damage Index of Rape in Flowering and Pod-bearing Period in Hunan Province

    • Objective The study was carried out to obtain the wet damage index of rape during flowering and podbearing period, and provide a scientific basis for the monitoring and early warning of rape wet water damage.
      Method Based on the yield observation data of rape from 4 agrometeorological observation stations in Nanxian, Huaihua, Yiyang and Hengyang of Hunan Province, and the meteorological data of flowering and pod-bearing period in the same year, the relationship between relative meteorological yield of rape and meteorological factors during the flowering and pod-bearing period of yield reduction year were analyzed, and the disaster-causing meteorological factors were obtained. By performing cluster analysis on the relative meteorological yield of yield reduction year and the disaster-causing meteorological factors of the same year, the wet damage index of rape was determined, and then independent observation data was used to test the wet damage index.
      Result The amount of precipitation and the number of precipitation days during the precipitation process are the main factors that cause the yield reduction of rape in Hunan Province. The index of mild wet damage for rape in Hunan Province is: 40 mm ≤ rainfall during precipitation < 75 mm, 5 d ≤ precipitation duration < 6 d, and the index for moderate or above wet damage is: rainfall during precipitation ≥ 75 mm, precipitation duration ≥ 6 d.
      Conclusion After independent data inspection, the above wet damage indexes proposed in the study are basically accurate, which can be used for agrometeorological disaster monitoring and early warning services.
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