Detection of Solanum betaceum Cav fruit maturity using YOLO11-based deep learning.
- DOI
- 10.3389/fpls.2026.1880899
- Published
- 2026
- Container
- Frontiers in plant science
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.3389/fpls.2026.1880899,
title = {Detection of Solanum betaceum Cav fruit maturity using YOLO11-based deep learning.},
author = {Quiñones Huatangari L and Vásquez Pérez HV and Valqui-Valqui L and Palomino Ojeda JM and Saravia D and Bardales Escalante W and Silva G and Chavez-Jalk A and Cruz Caro O and Valqui L},
year = {2026},
journal = {Frontiers in plant science},
doi = {10.3389/fpls.2026.1880899},
url = {https://doi.org/10.3389/fpls.2026.1880899}
}RIS
TY - JOUR TI - Detection of Solanum betaceum Cav fruit maturity using YOLO11-based deep learning. AU - Quiñones Huatangari L AU - Vásquez Pérez HV AU - Valqui-Valqui L AU - Palomino Ojeda JM AU - Saravia D AU - Bardales Escalante W AU - Silva G AU - Chavez-Jalk A AU - Cruz Caro O AU - Valqui L PY - 2026 JO - Frontiers in plant science DO - 10.3389/fpls.2026.1880899 UR - https://doi.org/10.3389/fpls.2026.1880899 ER -
APA
L, Q. H., HV, V. P., L, V., JM, P. O., D, S., W, B. E., G, S., A, C., O, C. C., & L, V. (2026). Detection of Solanum betaceum Cav fruit maturity using YOLO11-based deep learning.. Frontiers in plant science. https://doi.org/10.3389/fpls.2026.1880899
Source records
- pubmed · retrieved 2026-09-27T15:31:28.596Z