Dataset
List of chickpea lines in the Northam 2022 trials
Murdoch University
12/04/2023
DOI:
https://doi.org/10.60867/00000005
Abstract
This dataset is the output of the GRDC funded project (DAW2205-004RTX). The project involving a collaboration between Western Australia Department of Primary Industries and Regional Development (DPIRD), Murdoch University and Agriculture Victoria aims to initiate and lay the foundation of research and breeding for acid soil tolerance in chickpea. Under this one-year initiation phase, the project team will screen and genotype targeted germplasm collection and structured populations from crosses of cultivated varieties with wild relatives known to exhibit tolerance to soil acidity. The project will identify confirmed sources of inherent tolerance, bulk up seed for future research, fine tune phenotyping methodology under lab/glasshouse conditions and develop genetic (genomic) information that chickpea pre-breeders and breeders will use in developing varieties that would sustain yield potential of new chickpea varieties on acidic soils.
Details
- Title
- List of chickpea lines in the Northam 2022 trials
- Authors/Creators
- Darshan Sharma (Project Leader) - Department of Primary Industries and Regional DevelopmentChengdao Li (Project Member) - Murdoch University, Centre for Crop and Food InnovationYong Jia (Project Member) - Department of Primary Industries and Regional DevelopmentSukhjiwan Kaur (Project Member) - Agriculture VictoriaMatthew Hayden (Project Member) - La Trobe UniversityPenghao Wang (Data Manager) - Murdoch University, Centre for Crop and Food InnovationViet Dang (Data Manager) - Murdoch UniversityWestern Crop Genetics Alliance (Data Manager)
- Publisher
- Murdoch University
- Grants
- Accelerating the development of chickpea with enhanced acid soil tolerance, DAW2205-004RTX, Grains Research and Development Corporation (Australia, Canberra) - GRDC
- Identifiers
- 991005566667707891
- Copyright
- Attribution 4.0 International (CC BY 4.0)
- Murdoch Affiliation
- Centre for Crop and Food Innovation
- Language
- English
- Resource Type
- Dataset
- Locations
- Latitude: -31.653 Longitude: 116.666
Metrics
24 File views/ downloads
313 Record Views