Associations among International CIMMYT Bread Wheat Yield Testing Locations in High Rainfall Areas and Their Implications for Wheat Breeding

Lillemo, Morten; Ginkel, M. van; Trethowan, Richard; Hernandez, Eduardo; Rajaram, S.

doi:10.2135/cropsci2004.1163

Cited by 41 publications

(47 citation statements)

References 11 publications

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“…Considering the diversity among test locations, wide year-to-year variations were expected. This was in agreement with previous findings using spring wheat (Trethowan et al 2001(Trethowan et al , 2003Lillemo et al 2004Lillemo et al , 2005. Such year to year disparity is also supported by the variation in average national wheat yields in the different countries, where the trials were conducted (FAO 2008).…”

Section: Discussionsupporting

confidence: 92%

“…This is particularly encouraging, considering that the superior experimental genotypes differed in pedigree; and therefore probably genotype, providing further opportunities for genetic gain through recombination of superior alleles. Previous studies suggested that since the winter wheat environments in Central and West Asia vary greatly (Braun et al 1998;Trethowan et al 2001Trethowan et al , 2003Lillemo et al 2004Lillemo et al , 2005, diversity in widely adapted wheat cultivars is needed for developing high yielding stable genotypes for the region (Ö zgen 1991; Morgounov et al 2005). Besides being higher yielding and more stable than the checks, the experimental genotypes were selected for resistance to rusts and other diseases prevalent in Tables 1 and 2 for full names of the locations and genotypes, respectively) target countries in the region, as well as for improved quality traits (information available on www.iwwip.…”

Section: Discussionmentioning

confidence: 99%

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Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia

Sharma

Morgounov²,

Braun

et al. 2009

Euphytica

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Improved winter wheat (Triticum aestivum L.) cultivars are needed for the diverse environments in Central and West Asia to improve rural livelihoods. This study was conducted to determine the performance of elite winter wheat breeding lines developed by the International Winter Wheat Improvement Program (IWWIP), to analyze their stability across diverse environments, and to identify superior genotypes that could be valuable for winter wheat improvement or varietal release. One hundred and one advanced winter wheat breeding lines and four check cultivars were tested over a 5-year period (2004)(2005)(2006)(2007)(2008). Grain yield and agronomic traits were analyzed. Stability and genotypic superiority for grain yield were determined using genotype and genotype 9 environment (GGE) biplot analysis. The experimental genotypes showed high levels of grain yield in each year, with mean values ranging from 3.9 to 6.7 t ha -1 . A set of 25 experimental genotypes was identified. These were either equal or superior to the best check based on their high mean yield and stability across environments as assessed by the GGE biplot analysis. The more stable high yielding genotypes were ID800994.W/Falke, Agri/Nac//Attila, ID8009 94W/Vee//F900K/3/Pony/Opata, AU//YT542/N10B/ 3/II8260/4/JI/Hys/5/Yunnat Esskiy/6/KS82W409/Spn and F130-L-1-12/MV12. The superior genotypes also had acceptable maturity, plant height and 1,000-kernel weight. Among the superior lines, Agri/Nac//Attila and Shark/F4105W2.1 have already been proposed for release in Kyrgyzstan and Georgia, respectively. The findings provide information on wide adaptation of the internationally important winter wheat genotypes, and demonstrate that the IWWIP program is enriching the germplasm base in the region with superior winter wheat genotypes to the benefit of national and international winter wheat improvement programs.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia

Sharma

Morgounov²,

Braun

et al. 2009

Euphytica

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“…The genotype BWL 3584 was stable across environment for grain zinc concentration and well adapted for grain yield under unfavorable environment. Eberhart and Russell (1966), Koemel et al (2004), Lillimo et al (2004), Meena et al (2014) and Kumar et al (2014) also emphasized that genotypes with high mean performance and regression coefficient near to unity with non-significant deviations are desirable and gave stable performance across the environments. Based on the mean performance, regression coefficient (bi) values and deviation from regression values, some of the genotypes have been identified to suit with stability of performance under unfavorable environments in respect of grain yield and quality traits.…”

Section: Resultsmentioning

confidence: 99%

Stability analysis for grain yield and some quality traits in bread wheat (Triticum aestivum L.

Singh

Srivastava

Sharma

et al. 2018

JANS

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Abstract:The present study was conducted to assess the genetic diversity and stability for grain yield (GY), 1000-grain weight (TGW), protein content (PC), grain iron (Fe) and grain zinc (Zn) concentration under three varied environmental locations using 28 diverse wheat genotypes (including three checks i.e., WH1105, DPW621-50, and HD2967 ). The material was sown at three locations during Rabi 2015-2016. Pooled analysis of variance revealed highly significant variance due to environments for all the traits studied indicating differential response of the genotypes. The genotype BWL 3584 exhibited stable performance across the environments for grain yield and grain zinc concentration under un-favorable environment also shows potential for high grain yield and high grain zinc concentration. After further confirmation, genotype BWL 3584 could be utilized as potential donor in hybridization programme to improve grain yield and grain zinc concentration. Further, genotype SABW 225 showed consistent performance across the environments for TGW and PC content. Whereas, PBW 744 was found to be suitable for GY (6142 kg/ha), coupled with PC (12.09%) and Zn (52.18ppm) across the locations followed by PBW 725 (6094, 12.26 and 46.96) and BWL 3584 (5219, 12.63 and 50.23) GY, PC and Grain Zn, respectively)and BWL 3584 (5219, 12.63 and 50.23) could be utilized as a donor in routine breeding programme to improve grain yield and quality traits in bread wheat.

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“…Lillemo et al (2004) and Roozeboom et al (2008) used SHMM and GGE biplot, respectively, to group locations from data consisting of variable numbers of genotypes evaluated in multi-years and locations. A least square mean of genotypes over years was used in the analysis of SHMM, GGE biplot and rank correlation.…”

Section: Resultsmentioning

confidence: 99%

Comparison of shifted multiplicative model, rank correlation, and biplot analysis for clustering winter wheat production environments

et al. 2010

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Categorization of locations with similar environments helps breeders to efficiently utilize resources and effectively target germplasm. This study was conducted to determine the relationship among winter wheat (Triticum aestivum L.) yield testing locations in South Dakota. Yield trial data containing 14 locations and 38 genotypes from 8 year were analyzed for crossover genotype (G) 9 environment (E) interactions according to the AzzaliniCox test. G 9 E was significant (P \ 0.05) and contributed a small proportion of variation over the total phenotypic variation. This suggested that for efficient resource utilization, locations should be clustered. The data were further analyzed using the Shifted Multiplicative Model (SHMM), Spearman's rank correlation and GGE biplot to group testing locations based on yield. SHMM analysis revealed four major cluster groups in which the first and third had three locations, with four locations in each of the second and fourth groups. Spearman rank correlations between locations within groups were significant and positive. GGE biplot analysis revealed two major mega-environments of winter wheat testing locations in South Dakota. Oelrichs was the best testing location and XH1888 was the highest yielding genotype. SHMM, rank correlation and GGE biplot analyses showed that the locations of Martin and Winner in the second group and Highmore, Oelrichs and Wall in the third group were similar. This indicated that the number of testing locations could be reduced without much loss of grain yield information. GGE biplot provided additional information on the performance of entries and locations. SHMM clustered locations with reduced cross-over interaction of genotype 9 location. The combined methods used in this study provided valuable information on categorization of locations with similar environments for efficient resource allocation. This information should facilitate efficient targeting of breeding and testing efforts, especially in large breeding programs.

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Associations among International CIMMYT Bread Wheat Yield Testing Locations in High Rainfall Areas and Their Implications for Wheat Breeding

Cited by 41 publications

References 11 publications

Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia

Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia

Stability analysis for grain yield and some quality traits in bread wheat (Triticum aestivum L.

Comparison of shifted multiplicative model, rank correlation, and biplot analysis for clustering winter wheat production environments

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