An adaptation analysis of Australian and CIMMYT/ICARDA wheat germplasm in Australian production environments

2000 ◽  
Vol 51 (7) ◽  
pp. 903 ◽  
Author(s):  
S. Sivapalan ◽  
L. O'Brien ◽  
G. Ortiz-Ferrara ◽  
G. J. Hollamby ◽  
I. Barclay ◽  
...  
Keyword(s):  
Western Australia ◽  
Wheat Breeding ◽  
Yield Data ◽  
Breeding Programs ◽  
Breeding Lines ◽  
Mediterranean Environments ◽  
Supplementary Irrigation ◽  
Production Environments ◽  
Wide Adaptation ◽  
The University

An adaptation analysis was conducted in an attempt to identify adapted germplasm and potential indicator or probe varieties that could be used for more efficient germplasm introduction and evaluation. A set of 39 advanced wheat breeding lines and named varieties from Australian breeding programs and 10 from the CIMMYT/ICARDA programs were tested using 20 environments across the Australian wheatbelt during a period of 3 years. AMMI analysis and classification analysis were performed on grain yield data. Five groups of genotypes with similar patterns in performance within each group were identified, mostly reflecting their origin and pedigree. Most of the genotypes from the CIMMYT/ICARDA programs clustered together as did most of those from the University of Adelaide and Agriculture Western Australia breeding programs. Four groups of environments with similar trends in discriminating genotypes within each group were identified. There was a clear discrimination between subtropical and Mediterranean environments. Subtropical environments with supplementary irrigation showed similar patterns to Mediterranean environments. Basic differences in adaptation and phenotypic stability among genotypes from the CIMMYT/ICARDA programs in relation to genotypes from several breeding programs in Australia were identified. CIMMYT/ICARDA genotypes such as Attila, Nesser, Pfau/Seri//Bow, Genaro 81, and Maya/Nac performed well, especially in subtropical environments. The Australian varieties Hartog and Vulcan showed similar performance and could be used as indicator varieties for assessing introduced germplasm for subtropical regions. University of Adelaide developed genotypes Trident, Spear, Excalibur, and RAC 655, along with the Agriculture Western Australia genotypes Tammin and 82Y:1186, showed wide adaptation to all environments and could be used as indicator varieties for wide adaptation. Similarly, genotypes such as BT Schomburgk, Pelsart, and Sunvale could be used as indicator varieties for the other genotype groups. The results of this study can serve as a basis for identification and introduction of germplasm from the CIMMYT/ICARDA programs for various Australian production environments. It has also provided an understanding of the pattern of discrimination of genotypes across each region of the Australian wheatbelt.

A comparative study for yield performance and adaptation of some Australian and CIMMYT/ICARDA wheat genotypes grown at selected locations in Australia and the WANA region

2003 ◽  
Vol 54 (1) ◽  
pp. 91 ◽  
Author(s):  
S. Sivapalan ◽  
L. O'Brien ◽  
G. Ortiz-Ferrara ◽  
G. J. Hollamby ◽  
I. Barclay ◽  
...  
Keyword(s):  
Grain Yield ◽  
Commercial Production ◽  
Environmental Groups ◽  
Yield Data ◽  
Germplasm Exchange ◽  
Breeding Programs ◽  
Yield Performance ◽  
Breeding Lines ◽  
Wide Adaptation ◽  
Regional Adaptation

A regional adaptation analysis was conducted to provide a basis for effective and efficient wheat germplasm exchange between Australia and the WANA region. A set of 38 Australian and CIMMYT/ICARDA genotypes was tested for grain yield in 29 environments in Australia and the WANA region for 3 years commencing in 1994–95 season. Classification analysis of grain yield data identified 9 genotypic groups and 5 environmental groups with similar patterns in yield performance within each group. Genotypes with similar origin and pedigree were similar in yield performance across environments in Australia and the WANA region. Environmental conditions across both regions showed similarity in discriminating genotypes for their yield performance. Genotypes Attila, Spear, Excalibur, and 82Y:1186 were highest yielding in Australia and the WANA region. However, genotypes Nesser, Pfau/Seri//Bow, Hartog, Vulcan, and Sunland showed wide adaptation across both regions. Genotypes Cranbrook, Genaro 81, Seri 82, Kauz, SUN 190A, and Pgo/Seri 82 showed specific adaptation to favourable environments. Genotypes in each group, based on yield performance, showed differing degrees of yield stability. Pfau/Seri//Bow has the potential for release for commercial production in Australia and the WANA region. The genotypes Pfau/Seri//Bow, Hartog, Sunland, and Vulcan could be used in trials in both regions as indicator varieties to evaluate new breeding lines for mutual exchange between the 2 sets of breeding programs.

Corrigendum to: A comparative study for yield performance and adaptation of some Australian and CIMMYT/ICARDA wheat genotypes grown at selected locations in Australia and the WANA region

2003 ◽  
Vol 54 (3) ◽  
pp. 331 ◽  
Author(s):  
S. Sivapalan ◽  
L. O'Brien ◽  
G. Ortiz-Ferrara ◽  
G. J. Hollamby ◽  
I. Barclay ◽  
...  
Keyword(s):  
Grain Yield ◽  
Commercial Production ◽  
Environmental Groups ◽  
Yield Data ◽  
Germplasm Exchange ◽  
Breeding Programs ◽  
Yield Performance ◽  
Breeding Lines ◽  
Wide Adaptation ◽  
Regional Adaptation

A regional adaptation analysis was conducted to provide a basis for effective and efficient wheat germplasm exchange between Australia and the WANA region. A set of 38 Australian and CIMMYT/ICARDA genotypes was tested for grain yield in 29 environments in Australia and the WANA region for 3 years commencing in 1994–95 season. Classification analysis of grain yield data identified 9 genotypic groups and 5 environmental groups with similar patterns in yield performance within each group. Genotypes with similar origin and pedigree were similar in yield performance across environments in Australia and the WANA region. Environmental conditions across both regions showed similarity in discriminating genotypes for their yield performance. Genotypes Attila, Spear, Excalibur, and 82Y:1186 were highest yielding in Australia and the WANA region. However, genotypes Nesser, Pfau/Seri//Bow, Hartog, Vulcan, and Sunland showed wide adaptation across both regions. Genotypes Cranbrook, Genaro 81, Seri 82, Kauz, SUN 190A, and Pgo/Seri 82 showed specific adaptation to favourable environments. Genotypes in each group, based on yield performance, showed differing degrees of yield stability. Pfau/Seri//Bow has the potential for release for commercial production in Australia and the WANA region. The genotypes Pfau/Seri//Bow, Hartog, Sunland, and Vulcan could be used in trials in both regions as indicator varieties to evaluate new breeding lines for mutual exchange between the 2 sets of breeding programs.

Yield performance and adaptation of some Australian and CIMMYT/ICARDA developed wheat genotypes in the West Asia North Africa (WANA) region

2001 ◽  
Vol 52 (6) ◽  
pp. 661 ◽  
Author(s):  
S. Sivapalan ◽  
L. O'Brien ◽  
G. Ortiz-Ferrara ◽  
G. J. Hollamby ◽  
I. Barclay ◽  
...  
Keyword(s):  
North Africa ◽  
The West ◽  
Breeding Programs ◽  
Yield Performance ◽  
Breeding Lines ◽  
Wheat Improvement ◽  
Supplementary Irrigation ◽  
Wide Adaptation ◽  
Adaptation To Heat

A set of 29 advanced breeding lines and named cultivars from different breeding programs in Australia was compared with 18 genotypes developed by the CIMMYT/ICARDA breeding programs for their adaptation and yield performance using 5 locations in the WANA region for 2 years. Classification analysis identified 13 CIMMYT/ICARDA genotypes that had a pattern in yield performance similar to 2 Australian cultivars, Leichhardt and Hartog. The classification of environments effectively identified trials that experienced heat stress and received supplementary irrigation. Most of the genotypes developed by the CIMMYT/ICARDA breeding programs showed wide adaptation in the WANA region. Genotypes developed for Australian Mediterranean environments failed to show wide adaptation in the WANA region. However, many Australian genotypes showed specific adaptation to heat-stressed environments. Variation among Australian genotypes for disease resistance and heat tolerance couldbe used for wheat improvement in the WANA region.

scholarly journals Agro-morphological, yield, and genotyping-by-sequencing data of selected wheat germplasm

2020 ◽  
Author(s):  
Madiha Islam ◽  
Abdullah ◽  
Bibi Zubaida ◽  
Nosheen Shafqat ◽  
Rabia Masood ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Sequence Data ◽  
Genotyping By Sequencing ◽  
Wheat Breeding ◽  
Sequencing Data ◽  
Illumina Hiseq ◽  
Yield Data ◽  
Single Nucleotide ◽  
Breeding Programs ◽  
Short Reads

AbstractWheat (Triticum aestivum) is the most important staple food in Pakistan. Knowledge of its genetic diversity is critical for designing effective crop breeding programs. Here we report agro-morphological and yield data for 112 genotypes (including 7 duplicates) of wheat (Triticum aestivum) cultivars, advance lines, landraces and wild relatives, collected from several research institutes and breeders across Pakistan. We also report genotyping-by-sequencing (GBS) data for a selected sub-set of 52 genotypes. Sequencing was performed using Illumina HiSeq 2500 platform using the PE150 run. Data generated per sample ranged from 1.01 to 2.5 Gb; 90% of the short reads exhibited quality scores above 99.9%. TGACv1 wheat genome was used as a reference to map short reads from individual genotypes and to filter single nucleotide polymorphic loci (SNPs). On average, 364,074±54479 SNPs per genotype were recorded. The sequencing data has been submitted to the SRA database of NCBI (accession number SRP179096). The agro-morphological and yield data, along with the sequence data and SNPs will be invaluable resources for wheat breeding programs in future.

scholarly journals CANNING AND TASTING EVALUATION OF THE SOUTHERNPEA COOPERATIVE TRIAL IN ARKANSAS

HortScience ◽  
2005 ◽  
Vol 40 (3) ◽  
pp. 876e-876
Author(s):  
Danielle Williams ◽  
Teddy Morelock ◽  
Eddy Stiles
Keyword(s):  
South Carolina ◽  
The United States ◽  
University Of Arkansas ◽  
Yield Data ◽  
Breeding Lines ◽  
Industry Standards ◽  
Yield Trial ◽  
Cooperative Trial ◽  
Water Salt ◽  
The University

There are four southernpea breeding programs left in the United States: USDA-South Carolina, Louisiana, Texas and the largest at University of Arkansas. Selected breeding lines from these programs are grown in the Southernpea Cooperative Trial along with industry standards as checks. The yield trial is conducted in Alabama, Arkansas, Louisiana, Oklahoma, South Carolina, and Texas. Each location collects yield data; at the University of Arkansas-Fayetteville samples are also canned at the Department of Food Science Pilot Plant Facility. The process we use for canning southernpeas is similar to that used in the industry. Dry weights are recorded then soaked overnight in water. Imbibed weights are recorded after the peas are drained, blanched, and cooled. A weighed amount of peas are placed in each can; prepared brine (water, salt, and preservatives) is poured to the top of the can. The cans are sealed then cooked in a retort. The cans set a month before the tasting evaluation. For the tasting evaluation we use a minimum of 10 individuals for a consumer panel. Panelists rate pea color, liquor color, wholeness, texture, flavor, and the general appearance on a scale of 1–10, 10 being best. The industry standards are included, these are used as checks. This allows breeders to see how their lines look and taste as a canned product.

scholarly journals Increased Predictive Accuracy of Multi-Environment Genomic Prediction Model for Yield and Related Traits in Spring Wheat (Triticum aestivum L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Vipin Tomar ◽  
Daljit Singh ◽  
Guriqbal Singh Dhillon ◽  
Yong Suk Chung ◽  
Jesse Poland ◽  
...  
Keyword(s):  
Complex Traits ◽  
Predictive Accuracy ◽  
Model Performance ◽  
Environmental Variation ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Environmental Variance ◽  
Breeding Programs ◽  
Breeding Lines ◽  
The Impact

Genomic selection (GS) has the potential to improve the selection gain for complex traits in crop breeding programs from resource-poor countries. The GS model performance in multi-environment (ME) trials was assessed for 141 advanced breeding lines under four field environments via cross-predictions. We compared prediction accuracy (PA) of two GS models with or without accounting for the environmental variation on four quantitative traits of significant importance, i.e., grain yield (GRYLD), thousand-grain weight, days to heading, and days to maturity, under North and Central Indian conditions. For each trait, we generated PA using the following two different ME cross-validation (CV) schemes representing actual breeding scenarios: (1) predicting untested lines in tested environments through the ME model (ME_CV1) and (2) predicting tested lines in untested environments through the ME model (ME_CV2). The ME predictions were compared with the baseline single-environment (SE) GS model (SE_CV1) representing a breeding scenario, where relationships and interactions are not leveraged across environments. Our results suggested that the ME models provide a clear advantage over SE models in terms of robust trait predictions. Both ME models provided 2–3 times higher prediction accuracies for all four traits across the four tested environments, highlighting the importance of accounting environmental variance in GS models. While the improvement in PA from SE to ME models was significant, the CV1 and CV2 schemes did not show any clear differences within ME, indicating the ME model was able to predict the untested environments and lines equally well. Overall, our results provide an important insight into the impact of environmental variation on GS in smaller breeding programs where these programs can potentially increase the rate of genetic gain by leveraging the ME wheat breeding trials.

scholarly journals A New Strategy for Using Historical Imbalanced Yield Data to Conduct Genome-Wide Association Studies and Develop Genomic Prediction Models for Wheat Breeding

2021 ◽  
Author(s):  
Chenggen Chu ◽  
Shichen Wang ◽  
Jackie C. Rudd ◽  
Amir M.H. Ibrahim ◽  
Qingwu Xue ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Prediction Models ◽  
Association Studies ◽  
Wheat Breeding ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Yield Data ◽  
Breeding Lines ◽  
Genome Wide ◽  
Genomic Regions

Abstract Using imbalanced historical yield data to predict performance and select new lines is an arduous breeding task. Genome-wide association studies (GWAS) and high throughput genotyping based on sequencing techniques can increase prediction accuracy. An association mapping panel of 227 Texas elite (TXE) wheat breeding lines was used for GWAS and a training population to develop prediction models for grain yield selection. An imbalanced set of yield data collected from 102 environments (year-by-location) over ten years, through testing yield in 40–66 lines each year at 6–14 locations with 38–41 lines repeated in the test in any two consecutive years, was used. Based on correlations among data from different environments within two adjacent years and heritability estimated in each environment, yield data from 87 environments were selected and assigned to two correlation-based groups. The yield best linear unbiased estimation (BLUE) from each group, along with reaction to greenbug and Hessian fly in each line, were used for GWAS to reveal genomic regions associated with yield and insect resistance. A total of 74 genomic regions were associated with grain yield and two of them were commonly detected in both correlation-based groups. Greenbug resistance in TXE lines was mainly controlled by Gb3 on chromosome 7DL in addition to two novel regions on 3DL and 6DS, and Hessian fly resistance was conferred by the region on 1AS. Genomic prediction models developed in two correlation-based groups were validated using a set of 105 new advanced breeding lines and the model from correlation-based group G2 was more reliable for prediction. This research not only identified genomic regions associated with yield and insect resistance but also established the method of using historical imbalanced breeding data to develop a genomic prediction model for crop improvement.

scholarly journals A New Strategy for Using Historical Imbalanced Yield Data to Conduct Genome-Wide Association Studies and Develop Genomic Prediction Models for Wheat Breeding

2021 ◽  
Author(s):  
Chenggen Chu ◽  
Shichen Wang ◽  
Jackie C. Rudd ◽  
Amir M.H. Ibrahim ◽  
Qingwu Xue ◽  
...  
Keyword(s):  
Grain Yield ◽  
Insect Resistance ◽  
Genomic Prediction ◽  
Prediction Models ◽  
Hessian Fly ◽  
Wheat Breeding ◽  
Unbiased Estimation ◽  
Yield Data ◽  
Breeding Lines ◽  
Genomic Regions

Abstract Using imbalanced historical yield data to predict performance and select new lines is an arduous breeding task. An association mapping panel of 227 Texas elite (TXE) wheat breeding lines was used for GWAS and a training population to develop prediction models for grain yield selection. An imbalanced set of yield data collected from 102 environments (year-by-location) over ten years was used. Based on correlations among data from different environments within two adjacent years and broad-sense heritability estimated in each environment, yield data from 87 environments were selected and assigned to two correlation-based groups. The yield best linear unbiased estimation (BLUE) from each group, along with reaction to greenbug and Hessian fly in each line, were used for GWAS to reveal genomic regions associated with yield and insect resistance. A total of 74 genomic regions were associated with grain yield and two of them were commonly detected in both correlation-based groups. Greenbug resistance in TXE lines was mainly controlled by Gb3 on chromosome 7DL in addition to two novel regions on 3DL and 6DS, and Hessian fly resistance was conferred by the region on 1AS. Genomic prediction models developed in two correlation-based groups were validated using a set of 105 new advanced breeding lines and the model from correlation-based group G2 was more reliable for prediction. This research not only identified genomic regions associated with yield and insect resistance but also established the method of using historical imbalanced breeding data to develop a genomic prediction model for crop improvement.

Comparison of controls on development in breeding lines from Australian and CIMMYT/ICARDA winter and facultative wheat breeding programs

1996 ◽  
Vol 47 (1) ◽  
pp. 1 ◽  
Author(s):  
LDJ Penrose ◽  
M Mosaad ◽  
TS Payne ◽  
G Ortiz-Ferrara ◽  
HJ Braun
Keyword(s):  
New South ◽  
Late Summer ◽  
Wheat Breeding ◽  
Breeding Programs ◽  
Breeding Lines ◽  
South Central ◽  
South Wales ◽  
Improvement Programs ◽  
Integrated Response ◽  
Good Proportion

This study sought to compare developmental controls in breeding a within two winter wheat improvement programs, one Australian and a CIMMYT/ICARDA program based in West Asia. Developmental controls considered were intrinsic earliness, and responses to photoperiod and to vernalization. The reliability with which each control on development had been measured was tested in separate experiments using the wheats utilized in the Australian program. Measures of intrinsic earliness showed significant agreement between experiments, better agreement being found for response to photoperiod and between integrated response to vernalization and time to double ridge after late summer sowings. The wheats utilized in the CIMMYTI/CARDA programs were found to be quick in intrinsic earliness, and to possess little response to photoperiod. While these controls varied more for the wheats utilized in the Australian program, commercial Australian winter wheats were similar to the CIMMYTI/CARDA lines. Lines utilized by both programs were represented by types with spring, facultative and winter habit. The clearest differences between programs were that CIMMYTI/CARDA winter wheats appeared to have much stronger response to vernalization than the Australian winter wheats. These findings suggest breeders would find a good proportion of segregates, from crosses between the Australian and the CIMMYTI/CARDA winter wheats, to be developmentally adapted to south-central New South Wales. This suggests CIMMYTI/CARDA winter wheats provide a matching pool from which to access germplasm to introduce new characters into Australian winter wheats.

Development of robust PCR-based DNA markers for each homoeo-allele of granule-bound starch synthase and their application in wheat breeding programs

2001 ◽  
Vol 52 (12) ◽  
pp. 1409 ◽  
Author(s):  
A. McLauchlan ◽  
F. C. Ogbonnaya ◽  
B. Hollingsworth ◽  
M. Carter ◽  
K. R. Gale ◽  
...  
Keyword(s):  
Wheat Breeding ◽  
Starch Synthase ◽  
Quality Trait ◽  
Breeding Programs ◽  
Breeding Lines ◽  
Starch Quality ◽  
Specific Pcr ◽  
Marker Selection ◽  
Allele Specific ◽  
Granule Bound Starch Synthase

The absence of expression of the granule-bound starch synthase I (GBSSI) allele from chromosome 4A of wheat is associated with improved starch quality for making Udon noodles. Several PCR-based methods for the analysis of GBSS alleles have been developed for application in wheat. A widely applied approach has involved a simple PCR followed by electrophoretic separation of DNA products on agarose gels. The PCR amplifies one band from each of the loci on chromosomes 4A (Wx-B1), 7A (Wx-A1), and 7D (Wx-D1), and the band from the Wx-B1 locus is diagnostic for the occurrence of the null Wx-B1 allele that is associated with improved starch quality. The reliable detection of the null Wx-B1 allele has been important in identifying wheat breeding lines. Allele-specific PCR has also been used to successfully detect the occurrence of the null Wx-B1 allele. In the present paper the various protocols were evaluated by testing a segregating double haploid population from a cross between Cranbrook and Halberd and the tests gave good agreement in different laboratories. The application of the DNAbased tests applied in wheat breeding programs provides one of the first examples of a molecular marker selection for a grain quality trait being successfully applied in an Australian wheat breeding program.

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