Integrating hyperspectral features and physiological parameters for quantitative estimation of fig rust severity.

Li Y, Chen X, Din Y, Liu H, Wang Y, Cao B, Fang X, Wang Y, Zhang Z

DOI: 10.3389/fpls.2026.1930419
Published: 2026
Container: Frontiers in plant science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fpls.2026.1930419,
  title = {Integrating hyperspectral features and physiological parameters for quantitative estimation of fig rust severity.},
  author = {Li Y and Chen X and Din Y and Liu H and Wang Y and Cao B and Fang X and Wang Y and Zhang Z},
  year = {2026},
  journal = {Frontiers in plant science},
  doi = {10.3389/fpls.2026.1930419},
  url = {https://doi.org/10.3389/fpls.2026.1930419}
}

RIS

TY  - JOUR
TI  - Integrating hyperspectral features and physiological parameters for quantitative estimation of fig rust severity.
AU  - Li Y
AU  - Chen X
AU  - Din Y
AU  - Liu H
AU  - Wang Y
AU  - Cao B
AU  - Fang X
AU  - Wang Y
AU  - Zhang Z
PY  - 2026
JO  - Frontiers in plant science
DO  - 10.3389/fpls.2026.1930419
UR  - https://doi.org/10.3389/fpls.2026.1930419
ER  -

APA

Y, L., X, C., Y, D., H, L., Y, W., B, C., X, F., Y, W., & Z, Z. (2026). Integrating hyperspectral features and physiological parameters for quantitative estimation of fig rust severity.. Frontiers in plant science. https://doi.org/10.3389/fpls.2026.1930419

Source records

pubmed · retrieved 2026-09-27T07:34:10.144Z