Trait-based modeling of buffalograss seed yield using UAV-derived plant height and canopy nitrogen concentration.

Chu Wang, Xinyue Qu, Yuting Wang, Wouter H Maes, Maona Li, Yan Sun

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Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Chu WangCollege of Grassland Science and Technology, China Agricultural University, Beijing, China.

Xinyue QuCangzhou Academy of Agriculture and Forestry Sciences, Cangzhou, China.

Yuting WangCollege of Grassland Science and Technology, China Agricultural University, Beijing, China.

Wouter H MaesUnpiloted Aerial Vehicle (UAV) Research Centre, Department of Plants and Crops, Ghent University, Ghent, Belgium.

Maona LiCollege of Grassland Science and Technology, China Agricultural University, Beijing, China.

Yan SunCollege of Grassland Science and Technology, China Agricultural University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate seed-yield prediction is essential for optimizing nitrogen (N) management in buffalograss seed production. However, current UAV-based approaches often rely directly on vegetation indices (VIs), which provide limited physiological insight and not transfer well across growing seasons. To address this limitation, we developed a trait-based yield prediction methold that integrates UAV-derived plant height (PH) and canopy nitrogen concentration (CNC), representing crop structural and physiological status, respectively. Field experiments were conducted from 2022 to 2024 under seven N application rates. Using data from 2022 and 2023, we calibrated a quadratic PH-CNC model and then evaluated its predictive performance with an independent 2024 dataset. We also compared this framework with a conventional direct VI-based model. The trait-based model explained 89% of the variation in seed yield during calibration and showed better cross-year predictive performance than the VI-based model (R

Indexed as

buffalograssnitrogen managementseed yield predictiontrait-based modelingUAV remote sensing

Identifiers

PMID42164777

DOI10.3389/fpls.2026.1802837

PMCPMC13183847

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.