|
 Curently online :
12 |
|
 Total visitors :
7453674 |
|
| Developing an integrated genomic selection approach beyond biomass for varietal protection and nutritive traits in perennial ryegrass (Lolium perenne L.) |
|
Perennial ryegrass breeding has focused on biomass yield, but expansion into a broader set of traits is needed to benefit livestock industries whilst also providing support for intellectual property protection of cultivars. Numerous breeding objectives can be targeted simultaneously with the development of sensor-based phenomics and genomic selection (GS). Of particular interest are nutritive value (NV), which has been difficult and expensive to measure using traditional phenotyping methods |
|
M. M. Malmberg, C. Smith, P. Thakur, M. C. Drayton, J. Wilson, M. Shinozuka, W. Clayton, C. Inch, G. C. Spangenberg, K. F. Smith, N. O. I. Cogan & L. W. Pembleton Theoretical and Applied Genetics March 2023; vol. 136, Article number: 44 Key messageBreeding target traits can be broadened to include nutritive value and plant breeder’s rights traits in perennial ryegrass by using in-field regression-based spectroscopy phenotyping and genomic selection. AbstractPerennial ryegrass breeding has focused on biomass yield, but expansion into a broader set of traits is needed to benefit livestock industries whilst also providing support for intellectual property protection of cultivars. Numerous breeding objectives can be targeted simultaneously with the development of sensor-based phenomics and genomic selection (GS). Of particular interest are nutritive value (NV), which has been difficult and expensive to measure using traditional phenotyping methods, resulting in limited genetic improvement to date, and traits required to obtain varietal protection, known as plant breeder’s rights (PBR) traits. In order to assess phenotyping requirements for NV improvement and potential for genetic improvement, in-field reflectance-based spectroscopy was assessed and GS evaluated in a single population for three key NV traits, captured across four timepoints. Using three prediction approaches, the possibility of targeting PBR traits using GS was evaluated for five traits recorded across three years of a breeding program. Prediction accuracy was generally low to moderate for NV traits and moderate to high for PBR traits, with heritability highly correlated with GS accuracy. NV did not show significant or consistent correlation between timepoints highlighting the need to incorporate seasonal NV into selection indexes and the value of being able to regularly monitor NV across seasons. This study has demonstrated the ability to implement GS for both NV and PBR traits in perennial ryegrass, facilitating the expansion of ryegrass breeding targets to agronomically relevant traits while ensuring necessary varietal protection is achieved.
See https://link.springer.com/article/10.1007/s00122-023-04263-8
Fig. 1: Phenotypic distribution of individuals across timepoints represented as line graphs on the left and as boxplots on the right for a CP, b WSC and c IVVDMD
|
Trở lại
In
Số lần xem: 242
|
|
[ Tin tức liên quan ]___________________________________________________
|
(229).png "Developing an integrated genomic selection approach beyond biomass for varietal protection and nutritive traits in perennial ryegrass (Lolium perenne L.)")
