Assessment of black rot (Xanthomonas campestris) of cabbage (Brassica oleracea) in East Khasi Hills, Meghalaya

被引:0
|
作者
Ramachandra, Sudharshan Keralapura [1 ,2 ]
Dutta, Pranab [1 ]
Parthiban, Manikannan [1 ,2 ]
Gumachanamardi, Praveen [1 ,3 ]
机构
[1] Cent Agr Univ, Coll Post Grad Studies Agr Sci, Umiam 793103, Meghalaya, India
[2] Sher E Kashmir Univ Agr Sci & Technol, Jammu, Jammu & Kashmir, India
[3] ICAR Res Complex North Eastern Hill Reg, Umiam, Meghalaya, India
来源
关键词
Black rot; Cabbage; Disease incidence; Per cent disease index; Xanthomonas campestris; PV; CAMPESTRIS; RESISTANCE;
D O I
10.56093/ijas.v94i7.142761
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Cabbage (Brassica oleracea L. var. capitata) holds significant economic importance in Meghalaya, thriving in its high altitude and cool climate. East Khasi Hills (EKH) district, where cabbage cultivation remains viable throughout the year, contributes 70% of the state's total cabbage production. A severe outbreak of cabbage black rot, caused by Xanthomonas campestris p.v. campestris, has raised concerns in this region. To comprehensively understand the outbreak and assess its economic impact, an extensive disease survey was conducted across 6 districts of Meghalaya, with a particular focus in the EKH during 2021-22 and 2022-23. The survey was on different cruciferous vegetables such as cabbage, broccoli (Brassica oleracea L. var. italica), cauliflower (Brassica oleracea L. var. botrytis), radish (Raphanus sativus L.), mustard (Brassica juncea L.), and knol khol (Brassica oleracea L. var. gongylodes). It was found that on an average, Meghalaya experiences a disease incidence (DI) of a 52.7% and per cent disease index (PDI) of 30.9% for black rot in cabbage. However, in the EKH, highest disease incidence (69.98%) and PDI (43.38%) of black rot was recorded in cabbage, that surpassed knol khol and cauliflower. Highest DI and severity were observed during monsoon season. Further analysis revealed significant correlations (r) between black rot incidence and severity in cabbage with temperature (0.91), humidity (0.87) and rainfall (0.88). Additionally, multiple regression predictive model performed using weather parameters and DI led to the prediction of PDI with accuracy of 95% in EKH.
引用
收藏
页码:750 / 755
页数:6
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