Abstract: Viral diseases present on one of the most severe threats to global agriculture, frequently results in drastic yield losses and major economic setbacks for farmers. A crucial factor enabling the persistence and rapid transmission of plant viruses is the presence of weeds, which serve as alternate hosts and reservoirs for viral pathogens. Weeds not only harbor these viruses but also support insect vectors, such as aphids, whiteflies, leafhoppers, and thrips, that facilitate the swift spread of the diseases to nearby crops. Examples of this epidemiological link include Cynodon dactylon, which carries Rice Tungro Virus, and Parthenium hysterophorus, which is linked with Tobacco Streak Virus.
This study aims in understanding the pivotal role of weeds in the epidemiology of crop viral diseases and evaluate integrated strategies designed to mitigate their impact. Effective virus management relies heavily on the framework of Integrated Weed Management (IWM), which strategically combines cultural practices, mechanical removal, biological agents, and selective chemical methods. The primary goal of IWM in this context is to reduce viral inoculum sources and effectively break the disease cycle.
It is essential that crop protection prioritize for removal of harmful, virus-hosting weeds rather than indiscriminate eradication, as some weeds contribute positively to ecological balance by supporting pollinators and soil health. Research supports these sustainable efforts through the study of plant-based extracts, like neem, which act as natural antivirals and biopesticides.
Keywords: Crop protection, Weeds, Viral diseases, Virus reservoirs, Integrated Weed Management, Plant health.
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DOI:
10.17148/IARJSET.2025.121211
[1] Roopa K Murthy, Deepthi K, Koka Mahitha, Nelbiya N, Sumashree Pulagurla, "WEED DETECTION IN CROP FIELD USING DEEP LEARNING," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2025.121211