TY - JOUR
T1 - Advanced technologies for precision tree fruit disease management
T2 - A review
AU - Yang, Yanqiu
AU - Mali, Priyanka
AU - Arthur, Lawrence
AU - Molaei, Faezeh
AU - Atsyo, Sena
AU - Geng, Jiarui
AU - He, Long
AU - Ghatrehsamani, Shirin
N1 - Publisher Copyright:
© 2024
PY - 2025/2
Y1 - 2025/2
N2 - 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.
AB - 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.
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U2 - 10.1016/j.compag.2024.109704
DO - 10.1016/j.compag.2024.109704
M3 - Review article
AN - SCOPUS:85212118966
SN - 0168-1699
VL - 229
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
M1 - 109704
ER -