Aerial High‐Throughput Traits Improve Early‐Generation Selection

CSA News ◽  
2020 ◽  
Vol 65 (12) ◽  
pp. 16-16
Keyword(s):  
High Throughput ◽  
Early Generation ◽  
Early Generation Selection

scholarly journals Single Seed-Based High-Throughput Genotyping and Rapid Generation Advancement for Accelerated Groundnut Genetics and Breeding Research

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1226
Author(s):  
Sejal Parmar ◽  
Dnyaneshwar B. Deshmukh ◽  
Rakesh Kumar ◽  
Surendra S. Manohar ◽  
Pushpesh Joshi ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Breeding Program ◽  
Selection Marker ◽  
Routine Practice ◽  
Early Generation ◽  
Early Generation Selection ◽  
Single Seed ◽  
Breeding Research ◽  
Rapid Generation

The groundnut breeding program at International Crops Research Institute for the Semi-Arid Tropics routinely performs marker-based early generation selection (MEGS) in thousands of segregating populations. The existing MEGS includes planting of segregating populations in fields or glasshouses, label tagging, and sample collection using leaf-punch from 20–25 day old plants followed by genotyping with 10 single nucleotide polymorphisms based early generation selection marker panels in a high throughput genotyping (HTPG) platform. The entire process is laborious, time consuming, and costly. Therefore, in order to save the time of the breeder and to reduce the cost during MEGS, we optimized a single seed chipping (SSC) process based MEGS protocol and deployed on large scale by genotyping >3000 samples from ongoing groundnut breeding program. In SSC-based MEGS, we used a small portion of cotyledon by slicing-off the posterior end of the single seed and transferred to the 96-deep well plate for DNA isolation and genotyping at HTPG platform. The chipped seeds were placed in 96-well seed-box in the same order of 96-well DNA sampling plate to enable tracking back to the selected individual seed. A high germination rate of 95–99% from the chipped seeds indicated that slicing of seeds from posterior end does not significantly affect germination percentage. In addition, we could successfully advance 3.5 generations in a year using a low-cost rapid generation turnover glass-house facility as compared to routine practice of two generations in field conditions. The integration of SSC based genotyping and rapid generation advancement (RGA) could significantly reduce the operational requirement of person-hours and expenses, and save a period of 6–8 months in groundnut genetics and breeding research.

Early generation selection of insect resistance in potato

1984 ◽  
Vol 61 (7) ◽  
pp. 405-418 ◽  
Author(s):  
L. L. Sanford ◽  
T. L. Ladd ◽  
S. L. Sinden ◽  
W. W. Cantelo
Keyword(s):  
Insect Resistance ◽  
Early Generation ◽  
Early Generation Selection ◽  
Selection Of

scholarly journals Blanchability of peanut (Arachis hypogaea L.) kernels: early generation selection and genotype stability over three environments

2003 ◽  
Vol 54 (9) ◽  
pp. 885 ◽  
Author(s):  
A. W. Cruickshank ◽  
J. W. Tonks ◽  
A. K. Kelly
Keyword(s):  
Genetic Variance ◽  
Error Variance ◽  
Peanut Kernel ◽  
Early Generation ◽  
Breeding Lines ◽  
Early Generation Selection ◽  
Arachis Hypogaea L ◽  
The Mean ◽  
Selection For ◽  
The Stability

Blanching is the removal of testa from peanut kernel by heating followed by abrasion. Blanchability is the capacity to recover kernels with all the testa removed. This study investigated the response to early generation selection for blanchability and the stability of 22 breeding lines over 3 environments.F2-derived families with 'good' and 'poor' blanchability were selected. BLUPs for F4:5 lines from F2 families were significantly correlated with the mean blanchability of F2:3 rows. The within-family variance was mostly in 3�of the poor blanching families. In all other families, variance among lines within families was smaller than the error variance. Early generation selection was effective.In the 22 lines × 3 site experiment, there was a high genetic correlation common to each pair of sites, suggesting that differences in blanchability are repeatable. The expression of genetic variation was much greater at Coominya, with a 5-fold greater genetic variance than at Walkamin. All 3 environments in this experiment were irrigated. Interaction may have been greater with the inclusion of rainfed environments.Parent selection could make an important contribution to breeding for improved blanchability. Environment may not substantially affect the rank of genotypes but may affect the capacity to detect differences.

scholarly journals Aerial High-Throughput Phenotyping Enabling Indirect Selection for Grain Yield at the Early-generation Seed-limited Stages in Breeding Programs

2020 ◽  
Author(s):  
Margaret R. Krause ◽  
Suchismita Mondal ◽  
José Crossa ◽  
Ravi P. Singh ◽  
Francisco Pinto ◽  
...  
Keyword(s):  
Grain Yield ◽  
High Throughput ◽  
Vegetation Indices ◽  
Early Generation ◽  
Breeding Programs ◽  
Breeding Lines ◽  
High Throughput Phenotyping ◽  
Seed Increase ◽  
Yield Trials ◽  
Selection Of

ABSTRACTBreeding programs for wheat and many other crops require one or more generations of seed increase before replicated yield trials can be sown. Extensive phenotyping at this stage of the breeding cycle is challenging due to the small plot size and large number of lines under evaluation. Therefore, breeders typically rely on visual selection of small, unreplicated seed increase plots for the promotion of breeding lines to replicated yield trials. With the development of aerial high-throughput phenotyping technologies, breeders now have the ability to rapidly phenotype thousands of breeding lines for traits that may be useful for indirect selection of grain yield. We evaluated early generation material in the irrigated bread wheat (Triticum aestivum L.) breeding program at the International Maize and Wheat Improvement Center to determine if aerial measurements of vegetation indices assessed on small, unreplicated plots were predictive of grain yield. To test this approach, two sets of 1,008 breeding lines were sown both as replicated yield trials and as small, unreplicated plots during two breeding cycles. Vegetation indices collected with an unmanned aerial vehicle in the small plots were observed to be heritable and moderately correlated with grain yield assessed in replicated yield trials. Furthermore, vegetation indices were more predictive of grain yield than univariate genomic selection, while multi-trait genomic selection approaches that combined genomic information with the aerial phenotypes were found to have the highest predictive abilities overall. A related experiment showed that selection approaches for grain yield based on vegetation indices could be more effective than visual selection; however, selection on the vegetation indices alone would have also driven a directional response in phenology due to confounding between those traits. A restricted selection index was proposed for improving grain yield without affecting the distribution of phenology in the breeding population. The results of these experiments provide a promising outlook for the use of aerial high-throughput phenotyping traits to improve selection at the early-generation seed-limited stage of wheat breeding programs.

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