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Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1.
Wang, Jiaxin; Renninger, Heidi J; Ma, Qin; Jin, Shichao.
Afiliación
  • Wang J; Department of Forestry, Mississippi State University, Mississippi State, MS 39762, USA.
  • Renninger HJ; Department of Forestry, Mississippi State University, Mississippi State, MS 39762, USA.
  • Ma Q; School of Geography, Nanjing Normal University, Nanjing 210023, China.
  • Jin S; Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Nanjing 210095, China.
Plant Physiol ; 195(1): 378-394, 2024 Apr 30.
Article en En | MEDLINE | ID: mdl-38298139
ABSTRACT
Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https//github.com/JiaxinWang123/StoManager1) and Zenodo (https//doi.org/10.5281/zenodo.7686022).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Botánica / Programas Informáticos / Biología Celular / Estomas de Plantas / Células Vegetales Tipo de estudio: Prognostic_studies Idioma: En Revista: Plant Physiol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Botánica / Programas Informáticos / Biología Celular / Estomas de Plantas / Células Vegetales Tipo de estudio: Prognostic_studies Idioma: En Revista: Plant Physiol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos