@ARTICLE{Bakry_Moustafa_M.S._Monitoring_2025,
 author={Bakry, Moustafa M.S. and Fathipour, Yaghoub and Avery, Pasco B.},
 number={No 65},
 pages={209-218},
 journal={Journal of Water and Land Development},
 howpublished={online},
 year={2025},
 publisher={Polish Academy of Sciences; Institute of Technology and Life Sciences - National Research Institute},
 abstract={The red scale insect Aonidiella aurantii (Maskell) (Hemiptera: Diaspididae) is a major pest of guava trees in different parts of the world. This study aims to determine the population abundance and spatial distribution pattern of A. aurantii during the two successive growing seasons of 2022–2023 and 2023–2024. This pest was surveyed every two weeks in a private guava grove located in the Armant district of the Luxor region of Egypt. The results showed that individuals of A. aurantii were found on the leaf surfaces of guava trees at varying densities throughout the year. In the south-eastern site, where population density remained continuously high during the two years of the study, the pest favoured the upper leaf surface in the basal canopy layer. In this context, the spatial distribution pattern of A. aurantii at all sites on the guava tree was aggregated using dispersion measures over the two years. To distinguish the estimates of A. aurantii individuals in the sixteen coordinates studied, the cluster analysis method was used in conjunction with correlation analysis. Principal component analysis was performed, followed by two-dimensional analysis of sixteen coordinates to establish their correlation. Based on the findings of this study, an integrated pest management strategy can now be developed to help mitigate pest populations of A. aurantii found in guava tree orchards.},
 type={Article},
 title={Monitoring and spatial distribution of the red scale insect Aonidiella aurantii (Hemiptera: Diaspididae) infesting guava trees},
 URL={http://ochroma.man.poznan.pl/Content/135560/2025-02-JWLD-22.pdf},
 doi={10.24425/jwld.2025.154265},
 keywords={guava tree, population abundance, sampling program, scale insect pest, spatial distribution},
}