The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http://cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (http://www.integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP.
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http://dx.doi.org/10.3389/fphys.2012.00326 | DOI Listing |
Fish Shellfish Immunol
January 2025
State Key Laboratory of Mariculture Breeding, Key Laboratory of Marine Biotechnology of Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, PR China; University Key Lab for Integrated Chinese Traditional and Western Veterinary Medicine and Animal Healthcare in Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, PR China. Electronic address:
Dietary Astragalus polysaccharides (APS) get wide application in aquaculture due to their excellent immunoregulatory effects. However, little is known about the effects of dietary APS on vaccine potency in fish. In the present study, large yellow croakers (Larimichthys crocea) were injected with formalin-inactivated Pseudomonas plecoglossicida after APS feeding for 14 d and then challenged by live P.
View Article and Find Full Text PDFNat Plants
January 2025
Boyce Thompson Institute, Ithaca, NY, USA.
Hornworts, one of the three bryophyte phyla, show some of the deepest divergences in extant land plants, with some families separated by more than 300 million years. Previous hornwort genomes represented only one genus, limiting the ability to infer evolution within hornworts and their early land plant ancestors. Here we report ten new chromosome-scale genomes representing all hornwort families and most of the genera.
View Article and Find Full Text PDFBrief Bioinform
November 2024
State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road, Beijing, 100193, China.
Nonadditive genetic effects pose significant challenges to traditional genomic selection methods for quantitative traits. Machine learning approaches, particularly kernel-based methods, offer promising solutions to overcome these limitations. In this study, we developed a novel machine learning method, KPRR, which integrated a polynomial kernel into ridge regression to effectively capture nonadditive genetic effects.
View Article and Find Full Text PDFTransl Anim Sci
December 2024
Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE.
The Targhee breed is important to range sheep production in the Western United States. The objective of this research was to integrate industry sires participating in national genetic evaluation through the National Sheep Improvement Program (NSIP) into the U.S.
View Article and Find Full Text PDFHeliyon
November 2024
Prasad V.Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, Andhra Pradesh, 520007, India.
This paper proposes Pomarine jaeger Optimization (PJO) algorithm, Tiger hunting Optimization (THO) Algorithm, Desert Reynard and Vixen Inspired Optimization (DRVIO) Algorithm, Lonchodidae optimization (LO) algorithm, Caracal optimization (CO) algorithm, Barasingha optimization (BO) algorithm, Amur leopard optimization (AO) algorithm and Empress SARANI Optimization Algorithm to solve the active power loss reduction problem. Regular actions of Pomarine jaeger have been emulated to model the PJO procedure. In THO algorithm, how the Tiger moves to capture the prey is imitated and formulated.
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