Scaling laboratory results with machine learning is no silver bullet to strengthen global (micro)plastic mitigation policy

Zhu et al. ( 1 ) estimated “annual global losses of 4.11 to 13.52% […] for main crops” due to microplastic (MP) and nan - oplastic (NP) pollution and concluded that “These findings underscore the urgency of integrating plastic mitigation into global hunger and sustainability initiatives.” These alarming results triggered substantial press echo. However, we chal - lenge the legitimacy of such statements, given the funda - mental gaps in i) process understanding of MP/NP interaction with plants in natural systems and ii) data limitations regard - ing global MP/NP contamination. Drawing on our expertise, we highlight three main points concerning the impact of MP/ NP on terrestrial photosynthesis ( Fig. 1 )