Projects per year
Abstract
The global demand for oilseeds is increasing along with the human population. The family of Brassicaceae crops are no exception, typically harvested as a valuable source of oil, rich in beneficial molecules important for human health. The global capacity for improving Brassica yield has steadily risen over the last 50 years, with the major crop Brassica napus (rapeseed, canola) production increasing to ~72 Gt in 2020. In contrast, the production of Brassica mustard crops has fluctuated, rarely improving in farming efficiency. The drastic increase in global yield of B. napus is largely due to the demand for a stable source of cooking oil. Furthermore, with the adoption of highly efficient farming techniques, yield enhancement programs, breeding programs, the integration of high-throughput phenotyping technology and establishing the underlying genetics, B. napus yields have increased by >450 fold since 1978. Yield stability has been improved with new management strategies targeting diseases and pests, as well as by understanding the complex interaction of environment, phenotype and genotype. This review assesses the global yield and yield stability of agriculturally important oilseed Brassica species and discusses how contemporary farming and genetic techniques have driven improvements.
Original language | English |
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Article number | 2740 |
Journal | Plants |
Volume | 11 |
Issue number | 20 |
DOIs | |
Publication status | Published - Oct 2022 |
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Dive into the research topics of 'The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics'. Together they form a unique fingerprint.-
Who’s who in the plant gene world?
Edwards, D. (Investigator 01) & Batley, J. (Investigator 02)
ARC Australian Research Council
1/01/20 → 31/12/24
Project: Research
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Understanding disease resistance gene evolution across the Brassicaceae
Batley, J. (Investigator 01) & Edwards, D. (Investigator 02)
ARC Australian Research Council
1/06/21 → 30/06/24
Project: Research
Research output
- 7 Citations
- 1 Doctoral Thesis
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Application of deep learning to leverage high-throughput phenotyping for crop breeding
Furaste Danilevicz, M., 2023, (Unpublished)Research output: Thesis › Doctoral Thesis
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