Unravelling spatial dynamics and identification of risk regions associated with grape downy mildew in Karnataka using geostatistical approaches

IF 0.9 4区 农林科学 Q4 PLANT SCIENCES
N Sagar, M M Jamadar, Sandip Shil, Balanagouda Patil, C N Lakshminarayana Reddy, C R Jahir Basha, N H Shalini
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引用次数: 0

Abstract

The research focuses on the spatial distribution of grape downy mildew in different vineyards across major districts in Karnataka, India. Covering 6 administrative districts, 14 taluks, and 130 villages, the study employs geostatistical techniques, including GIS, point pattern analysis, and interpolation, to assess the severity and spatial patterns of the disease. Utilizing a 0–9 severity scale, the investigation reveals varying degrees of downy mildew infection in surveyed areas, with potential clusters identified through spatial analysis. District-wise and taluk-specific analyses highlight variations in disease severity, with Doddaballapura exhibiting the highest index at 64.21%, and the lowest at 20.12% in Bagalkot. Agglomerative hierarchical cluster analysis identifies two main clusters among the surveyed districts, providing insights into regional disease patterns. Spatial point pattern analysis, including Local Moran’s I and Ripley’s K function, confirms the presence of clusters and offers a deeper understanding of disease dynamics. Interpolation techniques, such as IDW, reveal inconsistent disease occurrence across locations, emphasizing the need for targeted intervention. Ordinary and indicator kriging provide detailed spatial maps, showing disease severity hot spots in southern Karnataka and select areas in Bijapur district. The study underscores the urgency of addressing the growing threat of grape downy mildew, offering scientifically robust insights for disease management strategies in Karnataka’s diverse grape ecosystems.

利用地质统计学方法揭示卡纳塔克邦与葡萄霜霉病相关的空间动力学和风险区域识别
研究了印度卡纳塔克邦主要地区不同葡萄园葡萄霜霉病的空间分布。该研究覆盖了6个行政区、14个村和130个村,采用地理信息系统、点图分析和插值等地统计技术评估了该疾病的严重程度和空间格局。调查采用0-9级的严重程度量表,揭示了调查地区不同程度的霜霉病感染,并通过空间分析确定了潜在的聚类。地区分析和特定谈话分析突出了疾病严重程度的差异,Doddaballapura的指数最高,为64.21%,而Bagalkot的指数最低,为20.12%。聚集分层聚类分析确定了调查地区中的两个主要聚类,从而提供了对区域疾病模式的见解。空间点模式分析,包括Local Moran 's I和Ripley 's K函数,证实了集群的存在,并提供了对疾病动态的更深层次的理解。IDW等插值技术揭示了不同地点疾病发生的不一致,强调了有针对性干预的必要性。普通克里格和指示克里格提供了详细的空间地图,显示了卡纳塔克邦南部和比贾布尔区某些地区的疾病严重程度热点。该研究强调了解决葡萄霜霉病日益增长的威胁的紧迫性,为卡纳塔克邦多样化葡萄生态系统的疾病管理策略提供了科学可靠的见解。
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来源期刊
Australasian Plant Pathology
Australasian Plant Pathology 生物-植物科学
CiteScore
2.90
自引率
0.00%
发文量
51
审稿时长
3 months
期刊介绍: Australasian Plant Pathology presents new and significant research in all facets of the field of plant pathology. Dedicated to a worldwide readership, the journal focuses on research in the Australasian region, including Australia, New Zealand and Papua New Guinea, as well as the Indian, Pacific regions. Australasian Plant Pathology is the official journal of the Australasian Plant Pathology Society.
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