Advanced technologies for precision tree fruit disease management: A review

Yanqiu Yang, Priyanka Mali, Lawrence Arthur, Faezeh Molaei, Sena Atsyo, Jiarui Geng, Long He, Shirin Ghatrehsamani

Research output: Contribution to journalReview articlepeer-review

Abstract

Effective disease management in tree fruit cultivation is essential for ensuring crop health, improving yield, and minimizing economic losses. In recent years, the adoption of advanced technologies has revolutionized the approach to managing tree fruit diseases. This review explores the integration of precision agriculture tools, such as Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), and various sensor technologies, alongside sophisticated machine learning algorithms and predictive models. The effectiveness of these technologies in disease scouting, monitoring, detection, and prediction is evaluated, emphasizing their potential to enhance crop health, reduce economic losses, and minimize environmental impacts. Despite the promising advancements, challenges such as data quality, computational demands, and the need for robust, generalizable models persist. This review underscores the transformative potential of these technologies in promoting a resilient, efficient, and sustainable tree fruit industry, highlighting the need for continued research and development to fully realize their benefits.

Original languageEnglish (US)
Article number109704
JournalComputers and Electronics in Agriculture
Volume229
DOIs
StatePublished - Feb 2025

All Science Journal Classification (ASJC) codes

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture

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