20- 67037-30671, 2022-67013-36426, and 2022-68013-36439. C O N F L I C T O F I N T E R E S T S TAT E M E N T The authors declare no conflicts of interest. DATA AVA I L I B I L I T Y S TAT E M E N T The datasets generated and analyzed for this study are avail- able in the Washington State University Research Exchange repository (https://doi.org/10.7273/000007507).O RC I D Melinda Zubrod https://orcid.org/0000-0001-7024-8421 AndrewW. Herr https://orcid.org/0000-0001-5111-2342 ArronH. Carter https://orcid.org/0000-0002-8019-6554 R E F E R E N C E S Ahmadi, Z., Mehrabadi, M., Fazli, M., Khalesro, S., Abedi, R., & Mokhtassi-Bidgoli, A. (2025). Enhancing tolerance of wheat culti- vars to me
Open resource ↗Washington State University Research Exchange · 10.7273/000007507 · pdf-raw-page:12 lines:1-81Unverified paper record
Utilizing high‐throughput phenotyping to identify metribuzin tolerance in winter wheat
The Plant Phenome Journal · 7 Jan 2026 · 10.1002/ppj2.70058
Abstract
Abstract Plant breeders and weed scientists address weed management collaboratively by selecting for herbicide tolerance in breeding programs. Metribuzin, a Group 5 PSII‐inhibiting herbicide, is labeled for use in wheat ( Triticum aestivum L.). However, application to currently available lines results in frequent, variable, and unpredictable crop injury. Breeding for enhanced metribuzin tolerance would allow growers to utilize this herbicide effectively while minimizing the risk of crop injury. Incorporating an additional herbicide mode of action in winter wheat production would enhance rotational flexibility and weed resistance management. Selection for improved herbicide tolerance in crops has traditionally relied on visual estimation, yet assessments can be variable. The objective of this study was to improve the accuracy and efficiency of selecting for herbicide tolerance in a breeding program by utilizing a drone‐mounted multispectral sensor. Multispectral data were collected on paired rows of an diversity panel and advanced generation lines grown in paired plot yield trials. Vegetation indices calculated include normalized difference vegetation index (NDVI), normalized difference red edge (NDRE), transformed chlorophyll absorption reflectance index, normalized water index, and modified triangular vegetation index. Visual assessments of injury, plant height, and grain yield were also recorded. Correlations between reflectance indices and grain yield were stronger than those between visual injury assessments and grain yield. The top 10 lines overlapped 45%–53% when selected by highest yield and highest NDVI or NDRE, respectively, in treated plots. The relationship between yield and index differences in treated and nontreated plots showed that the difference in indices (multiple R 2 = 0.0802–0.5434) explained more yield variation than visual assessments (multiple R 2 = 0.0003–0.1915). These results suggest that multispectral analysis at the plot level is a more accurate and efficient indicator of herbicide injury in winter wheat than traditional visual assessments.
Plant phenotyping relevance
ドローン搭載マルチスペクトルセンサーと植生指数を用いて、冬コムギの除草剤傷害・耐性を従来の目視評価より高精度かつ効率的に推定する方法を実証しており、表現型取得法が研究の中心である。
abstractThe objective of this study was to improve the accuracy and efficiency of selecting for herbicide tolerance in a breeding program by utilizing a drone‐mounted multispectral sensor.
abstractThese results suggest that multispectral analysis at the plot level is a more accurate and efficient indicator of herbicide injury in winter wheat than traditional visual assessments.
Code and data availability
The article's Data Availability Statement explicitly deposits the datasets generated and analyzed (phenotype/trait and vegetation index data from the metribuzin tolerance phenotyping experiments) in the Washington State University Research Exchange repository with a public DOI. No author analysis code repository is URL
This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.