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Applying machine learning to investigate long-term insect-plant interactions preserved on digitized herbarium specimens.
Applications in Plant Sciences ( IF 2.7 ) Pub Date : 2020-07-01 , DOI: 10.1002/aps3.11369
Emily K Meineke 1 , Carlo Tomasi 2 , Song Yuan 3 , Kathleen M Pryer 4
Affiliation  

Despite the economic significance of insect damage to plants (i.e., herbivory), long‐term data documenting changes in herbivory are limited. Millions of pressed plant specimens are now available online and can be used to collect big data on plant–insect interactions during the Anthropocene.

中文翻译:


应用机器学习来研究数字化植物标本馆标本中保存的长期昆虫与植物相互作用。



尽管昆虫对植物(即食草动物)的损害具有经济意义,但记录草食动物变化的长期数据仍然有限。现在可以在线获取数以百万计的压制植物标本,可用于收集人类世期间植物与昆虫相互作用的大数据。
更新日期:2020-07-01
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