International Journal of Molecular Evolution and Biodiversity 2024, Vol.14, No.5, 208-218 http://ecoevopublisher.com/index.php/ijmeb 217 inaccessible to researchers. Engaging the public in aphid monitoring can lead to the discovery of new species and provide insights into their distribution and ecology. The integration of genomics and artificial intelligence (AI) holds significant potential for advancing aphid taxonomy. High-throughput sequencing technologies can generate extensive genomic data, which, when analyzed using AI algorithms, can uncover complex phylogenetic relationships and evolutionary histories. For example, phylogenomic studies have already identified three main clades of Aphididae subfamilies and highlighted the role of introgression in their evolution (Ortiz-Rivas and Martínez-Torres, 2010). AI can further enhance these studies by automating the identification of phylogenetically informative markers and predicting evolutionary trends. Additionally, machine learning models can be trained to recognize morphological traits from images, aiding in the rapid and accurate classification of aphid species. Acknowledgments The author sincerely thanks his colleague Kendra D.Y. Ding from the research group for the assistance provided during the literature and data collection process of this study. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Batz P., Will T., Thiel S., Ziesche T., and Joachim C., 2023, From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring, Frontiers in Plant Science, 14. https://doi.org/10.3389/fpls.2023.1150748 Brumley C., 2020, A checklist and host catalogue of the aphids (Hemiptera: Aphididae) held in the Australian National Insect Collection, Zootaxa, 4728(4): 575-600. https://doi.org/10.11646/zootaxa.4728.4.12 Byrd D., Tran M., Kenney J., Wilson-Rankin E., and Mauck K., 2023, The aphid Myzus persicae (Hemiptera: Aphididae) acquires chloroplast DNA during feeding on host plants, Environmental Entomology, 52: 900-906. https://doi.org/10.1093/ee/nvad086 Cheng Z., and Huang X., 2023, Two new species of Aphis (Toxoptera) Koch (Hemiptera, Aphididae) from China. ZooKeys, 1172: 31-46. https://doi.org/10.3897/zookeys.1172.106518 Choi H., Shin S., Jung S., Clarke D., and Lee S., 2018, Molecular phylogeny of Macrosiphini (Hemiptera: Aphididae): an evolutionary hypothesis for the Pterocomma-group habitat adaptation, Molecular Phylogenetics and Evolution, 121: 12-22. https://doi.org/10.1016/j.ympev.2017.12.021 Ciruelos S., Brown P., and Nafría J., 2018, Two new species of the genus Aphis (Hemiptera, Aphididae) from Chile on host species of Alstroemeriaceae and Ericaceae, ZooKeys, 37-45. https://doi.org/10.3897/zookeys.738.21966 D’acier A., Cruaud A., Artige E., Genson G., Clamens A., Pierre É., Hudaverdian S., Simon J., Jousselin E., and Rasplus J., 2014, DNA barcoding and the associated PhylAphidB@se website for the identification of European aphids (Insecta: Hemiptera: Aphididae), PLoS ONE, 9. https://doi.org/10.1371/journal.pone.0097620 D’acier A., Jousselin E., Martin J., and Rasplus J., 2007, Phylogeny of the genus Aphis Linnaeus, 1758 (Homoptera: Aphididae) inferred from mitochondrial DNA sequences, Molecular Phylogenetics and Evolution, 42(3): 598-611. https://doi.org/10.1016/j.ympev.2006.10.006 Dohlen C., Rowe C., and Heie O., 2006, A test of morphological hypotheses for tribal and subtribal relationships of Aphidinae (Insecta: Hemiptera: Aphididae) using DNA sequences, Molecular Phylogenetics and Evolution, 38(2): 316-329. https://doi.org/10.1016/j.ympev.2005.04.035 Dutta S., Mondal R., Das R., Ganguli S., and Dey S., 2023, Development of web based digital key from dichotomous key through computer programming: model Aphid Predator Neuroptera (INSECTA), International Journal for Research in Applied Science and Engineering Technology. https://doi.org/10.22214/ijraset.2023.50197 Foottit R., Maw H., and Pike K., 2009, DNA barcodes to explore diversity in aphids (Hemiptera: Aphididae and Adelgidae), Redia-Giornale Di Zoologia, 92: 87-91. Huang X.L., and Qiao G.X., 2014, Aphids as models for ecological and evolutionary studies, Insect Science, 21(3): 247-250. https://doi.org/10.1111/1744-7917.12130 Júnior T., and Rieder R., 2020, Automatic identification of insects from digital images: a survey, Comput. Electron. Agric., 178: 105784. https://doi.org/10.1016/j.compag.2020.105784
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