{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T15:23:54Z","timestamp":1787325834697,"version":"build-2736575974"},"reference-count":41,"publisher":"Wiley","issue":"47","license":[{"start":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T00:00:00Z","timestamp":1780531200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T00:00:00Z","timestamp":1780531200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001381","name":"National Research Foundation Singapore","doi-asserted-by":"publisher","award":["NRF\u2010NRFF15\u20102023\u20100002"],"award-info":[{"award-number":["NRF\u2010NRFF15\u20102023\u20100002"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001352","name":"National University of Singapore","doi-asserted-by":"publisher","award":["A\u20108001604\u201000\u201000"],"award-info":[{"award-number":["A\u20108001604\u201000\u201000"]}],"id":[{"id":"10.13039\/501100001352","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Materials"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Early diagnosis of fungal infections in crops is essential for mitigating yield losses, yet most detection strategies rely on destructive assays that are incompatible with in situ monitoring. Among major fungal pathogens,\n                    <jats:italic>Fusarium<\/jats:italic>\n                    species pose a significant threat to global agriculture and produce the phytotoxin fusaric acid (FA), a key biomarker of early infection. Here, we develop a non\u2010destructive, ratiometric optical nanosensor that integrates aggregation\u2010induced emissive carbon dots within a zeolitic imidazolate framework (CD@ZIF\u20108) for selective FA detection in living plants. By rationally tuning the balance between dispersed and aggregated CDs within the ZIF\u20108 framework, we generated a dual\u2010emissive nanosensor with distinct blue and red fluorescent signals that enable self\u2010referencing readouts. Upon exposure to FA, interactions with CD@ZIF\u20108 quench the blue emission while leaving the red aggregation\u2010induced emission stable, thereby affording highly selective ratiometric sensing. Integrating CD@ZIF\u20108 into plant\u2010compatible microneedle patches enables minimally invasive sampling of plant interstitial fluid, allowing FA detection in\n                    <jats:italic>Fusarium<\/jats:italic>\n                    \u2010infected crops before visible symptoms and discrimination from abiotic and bacterial stresses. This work establishes an integrated, self\u2010referenced nanosensing platform for non\u2010destructive plant diagnostics, laying the foundation for early disease surveillance in precision and climate\u2010resilient agriculture.\n                  <\/jats:p>","DOI":"10.1002\/adma.73624","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T06:41:16Z","timestamp":1780641676000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Ratiometric Mycotoxin Detection in Living Plants With Dual\u2010Emissive Nanosensors"],"prefix":"10.1002","volume":"38","author":[{"given":"Yuliang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Chemical and Biomolecular Engineering National University of Singapore  Singapore Singapore"},{"name":"State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University  Nanjing P. R. 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