{"doi":"10.64898/2026.01.06.697986","title":"Smartphone image capture system and image analysis pipelines enable accurate and efficient phenotyping of spaced plant mapping populations","abstract":"<jats:title>Plain Language Summary</jats:title>\n                <jats:p>The lack of low-cost, user-friendly and expedient methods for plant phenotyping challenges researchers’ ability to efficiently collect accurate phenotypic data in large field experiments. Here, we demonstrate the use of a novel, smartphone-based image capture system and two user-friendly image analysis pipelines (utilizing PlantCV or Biodock AI) to increase the throughput of plant phenotyping in two large, spaced plant populations. We showed that the image capture system collected images of adequate quality for downstream analysis using either the PlantCV or Biodock AI pipeline. Both image analysis pipelines produced phenotype values in line with those obtained using manual image annotation. Together, these results provide researchers with a low-cost, user-friendly image-based phenotyping method that can be widely applied to increase phenotyping throughout in field experiments.</jats:p>","journal":null,"year":null,"id":642113,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":2,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1669924,"name":"Molly Hanlon","orcid":"0000-0002-5616-8203","position":1,"is_corresponding":false},{"id":1669925,"name":"Keely Brown","orcid":"0000-0002-5371-5830","position":2,"is_corresponding":false},{"id":1669926,"name":"Haley Schuhl","orcid":"0000-0002-8825-8297","position":3,"is_corresponding":false},{"id":743783,"name":"Ivan Baxter","orcid":"0000-0001-6680-1722","position":4,"is_corresponding":false},{"id":687530,"name":"Allison Miller","orcid":"0000-0003-3043-6852","position":5,"is_corresponding":false},{"id":1669923,"name":"Stella Woeltjen","orcid":"0009-0003-8790-065X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Smartphone image capture system and image analysis pipelines enable accurate and efficient phenotyping of spaced plant mapping populations","abstract":"<jats:title>Plain Language Summary</jats:title>\n                <jats:p>The lack of low-cost, user-friendly and expedient methods for plant phenotyping challenges researchers’ ability to efficiently collect accurate phenotypic data in large field experiments. Here, we demonstrate the use of a novel, smartphone-based image capture system and two user-friendly image analysis pipelines (utilizing PlantCV or Biodock AI) to increase the throughput of plant phenotyping in two large, spaced plant populations. We showed that the image capture system collected images of adequate quality for downstream analysis using either the PlantCV or Biodock AI pipeline. Both image analysis pipelines produced phenotype values in line with those obtained using manual image annotation. Together, these results provide researchers with a low-cost, user-friendly image-based phenotyping method that can be widely applied to increase phenotyping throughout in field experiments.</jats:p>","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":2,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19767382","pmcid":null,"openalex_id":"https://openalex.org/W7118822694","authors":[],"funders":[{"funder_name":"National Science Foundation","grant_id":"2120153","title":"BII: New Roots for Restoration: integrating plant traits, communities, and the soil ecosphere to advance restoration of natural and agricultural systems"}],"total_grants":1,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2026,"count":1}],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2026/01/07/2026.01.06.697986.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2026/01/07/2026.01.06.697986.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.64898/2026.01.06.697986","host_type":"publisher"},{"url":"https://doi.org/10.64898/2026.01.06.697986","host_type":"repository"}],"fields_of_study":["Smart Agriculture and AI","Remote Sensing in Agriculture","Leaf Properties and Growth Measurement","0401 agriculture, forestry, and fisheries","04 agricultural and veterinary sciences"],"mesh_terms":[],"keywords":["Pipeline transport","Image (mathematics)","Image processing","Pipeline (software)","Field (mathematics)","Image quality","Line (geometry)","Quality (philosophy)"],"sdg_mappings":[],"linked_datasets":[{"doi":"10.5281/zenodo.21041715","title":"Smartphone image capture system and image analysis pipelines enable accurate and efficient phenotyping of spaced plant mapping populations","publisher":"Zenodo","resource_type":"Dataset"},{"doi":"10.5281/zenodo.21041714","title":"Smartphone image capture system and image analysis pipelines enable accurate and efficient phenotyping of spaced plant mapping populations","publisher":"Zenodo","resource_type":"Dataset"}],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-07T21:36:11.691798Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}