A Blueberry ( Vaccinium L.) Crop Ontology to Enable Standardized Phenotyping for Blueberry Breeding and Research

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作   者：

Hislop, Lillian M.;  Luby, Claire H.;  Loarca, Jenyne;  Humann, Jodi;  Hummer, Kim E.;  Bassil, Nahla;  Zhao, Dongyan;  Casa, Alexandra M.;  Billings, Grant T.;  Echeverria, Daniella M.;  Ashrafi, Hudson;  Babiker, Ebrahiem;  Edger, Patrick;  Hancock, Jim;  Ehlenfeldt, Mark K.;  Finn, Chad;  Iorizzo, Massimo;  Sheehan, Moira J.;  Mackey, Ted;  Munoz, Patricio R.;  Olmstead, James;  Rowland, Lisa J.;  Sandefur, Paul;  Spencer, Jessica A.;  Stringer, Stephen;  Vorsa, Nicholi;  Wagner, Adam;  Hulse-Kemp, Amanda M.; 

作者机构：

Univ Wisconsin Madison;  Driscolls Inc;  Washington State Univ;  Univ Florida;  North Carolina State Univ;  Michigan State Univ;  USDA ARS;  Rutgers State Univ;  Oregon State Univ;  Oregon Blueberry;  Cornell Univ;  Fall Creek Farm & Nursery Inc; 

关键词：

phenotype;  database;  controlled vocabulary;  VITIS-IDAEA;  MACROCARPON;  GENES;  trait ontology;  plant ontology;  INTERSECTIONAL HYBRIDS;  HIGHBUSH BLUEBERRY; 

期刊名称：

HortScience

i s s n：

0018-5345

年卷期：

2024 年 59 卷 10 期

页   码：

1433-1442

页   码：

摘   要：

Breeding programs around the world continually collect data on large numbers of individuals. To be able to combine data collected across regions, years, and experiments, research communities develop standard operating procedures for data collection and measurement. One such method is a crop ontology, or a standardized vocabulary for collecting data on commonly measured traits. The ontology is also computer readable to facilitate the use of data management systems such as databases. Blueberry breeders and researchers across the United States have come together to develop the fi rst standardized crop ontology in blueberry (Vaccinium spp.). We provide an overview and report on the construction of the fi rst blueberry crop ontology and the 178 traits and methods included within. Researchers of Vaccinium species-such - such as other blueberry species, cranberry, lingonberry, and bilberry- - can use the described crop ontology to collect phenotypic data of greater quality and consistency, interoperability, and computer readability. Crop ontologies, as a shared data language, benefit fi t the entire worldwide research community by enabling collaborative meta-analyses that can be used with genomic data for quantitative trait loci, genome-wide association studies, and genomic selection analysis.