1. Integration of deep learning and plant biosecurity toward sustainable agriculture: A SWOT analysis.
- Author
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Sharma, Abhilasha and Sharma, Parul
- Subjects
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SUSTAINABLE agriculture , *DEEP learning , *SWOT analysis , *BIOSECURITY , *FOOD security , *GREENHOUSES , *HEBBIAN memory - Abstract
Plant biosecurity holds immense significance for every nation as it plays a crucial role in protecting crops, ensuring food security, and safeguarding ecology and the livelihoods of individuals. In this regard, plant biosecurity constitutes a vital component of sustainable agriculture progress. Digitalization is the new go-to strategy to address agriculture's productivity, sustainability, and resilience challenges. Deep Learning and other digital technologies that have emerged in recent years are currently being applied in every agriculture practice. Researchers from multidisciplinary areas strive to use these technologies and propose novel solutions to expedite the in-field workflow. However, struggle to put their solutions into production, deliver tangible results and obtain favorable outcomes with limited in-field datasets. In this view, this paper reviews remarkable research integrating deep learning with plant biosecurity and provides a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to identify the strengths, weaknesses, opportunities, and threats inherent to deep learning-driven solutions as facilitators or barriers to plant biosecurity. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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