Brazilian Spring Wheat Homogeneous Adaptation Regions can be Dissected in Major Megaenvironments

Munaro, Lucas Berger; Benin, Giovani; Marchioro, Volmir Sérgio; Franco, Francisco de Assis; Silva, Raphael Rossi; Silva, Cristiano Lemes da; Beche, Eduardo

doi:10.2135/cropsci2013.06.0365

Cited by 22 publications

(17 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Brazil, the wheat production areas were divided into four homogeneous regions that were defined based on the variables: rainfall, temperature, altitude, and description of grain yield. The southern region comprises the Region 1 (cold, humid, and high elevation); Region 2 (moderately hot, humid, and low elevation); and Region 3 (hot, moderately dry, and low elevation) (Munaro et al, ). The origins of the samples in this study were 40% from Region 1; 47% from Region 2; and 13% from Region 3.…”

Section: Methodsmentioning

confidence: 99%

Effect of debranning process on deoxynivalenol content in whole‐wheat flours

et al. 2019

View full text Add to dashboard Cite

Background and objectives Post‐harvest mitigation strategies are essential to reduce mycotoxin contamination in wheat‐based foods. The study aimed to evaluate the effect of the debranning process on the deoxynivalenol content in whole‐wheat flour naturally contaminated by Fusarium spp. Thirty commercial wheat samples were used and were obtained in Southern Brazil Region in 2015 crop season. Findings The highest DON contamination level was found in the no‐debranned samples and the outermost fraction (extraction rate >95%), which corresponds to the debranning time of 15 s. When all debranning times were included in the analysis, only the samples from Paraná State had the DON content significantly reduced after the debranning. Conclusions The debranning process reduced the DON content in whole‐wheat flour with lower to moderate levels of contamination, corresponding to DON content of 1.032 and 1.174 µg/kg, obtained in Paraná and Rio Grande do Sul States, respectively. Significance and novelty These results are important for wheat supply chain to meet the legislation requirements and to produce safer foods.

show abstract

Section: Methodsmentioning

confidence: 99%

Effect of debranning process on deoxynivalenol content in whole‐wheat flours

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The accurate identification of test sites ensures that the selected genotypes show superior performance across several environments (Blanche and Myers, 2006) and improves the efficiency of the breeding programme. A number of techniques have been used to interpret data from multi-environment trials (Eberhart and Russel, 1966), including GGE bi-plot analysis for effectively identifying mega-environments (Munaro et al, 2014). Therefore, we need to have research programme which primarily focus to develop cultivars with high yield potential and consistent performance across the environments.…”

Section: Introductionmentioning

confidence: 99%

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

Singh

Srivastava

Sharma

et al. 2018

JANS

View full text Add to dashboard Cite

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.

show abstract

“…The formation of MEs has many consequences because the analysis of each ME must be performed separately. Furthermore, these results must be repeatable across years (i.e., repeatable location groups need to be found) (Gupta et al, 2013;Munaro et al, 2014;Xu et al, 2014). The first method used to verify the occurrence of MEs is through the strategy designated as "analyze yearly and summarize across years" (Yan, 2014).…”

Section: MVmentioning

confidence: 99%

Estimation of Missing Values Affects Important Aspects of GGE Biplot Analysis

et al. 2017

Self Cite

View full text Add to dashboard Cite

RESEARCHT he presence of genotype-by-environment interaction (GEI) is common in multi-environment trials in wheat (Triticum aestivum L.) and other crops; it leads to changes in the performance of cultivars in different environments. A GEI demands that trials be conducted at multiple locations for several years to obtain reliable data for the possible release of a new cultivar.Trials conducted across several years and locations increase the possibility of obtaining datasets with unbalanced or incomplete data. This can occur because of planned or unplanned actions by the breeder. The planned actions might be the removal of genotypes that did not perform well in a given year, introducing new genotypes developed by the breeding program and the introduction of newly released cultivars. On the other hand, unplanned actions, which are unrelated to the breeder, might be attributable to human or environmental causes (Yan, 2013).There are three primary strategies for analyzing unbalanced or incomplete datasets. The first strategy consists in the removal of genotypes or environments with missing values. The second ABSTRACT Multi-environment trials often yield unbalanced datasets, thus necessitating the estimation of missing values. It is unknown whether this estimation affects the graphic characteristics of genotype plus genotype-by-environment interaction (GGE) biplots. Therefore, our objectives were to investigate the effects of different percentages of missing values on the number of significant principal components (pCs) and on mega environments, "winner" (highest-performing) genotypes, and the amount of variation explained by the pCs. Two complete sets of two-way data from wheat (Triticum aestivum L.) were used. The first set consisted of the original data (Data1, from which we created scenarios with 0, 30, and 60% missing data. For the second dataset (Data2), we removed 50% data from the original dataset, estimated missing values to make it a new complete dataset, and created scenarios like those for Data1. Missing values were estimated via expectation-maximization-GGE (EM-GGE) and EM-additive main effects and multiplicative interaction (EM-AMMI) methods. The percentage of variation explained by the pCs was affected by the percentage of missing data; a large percentage of missing values considerably increased the amount of variation explained by pC 1 and pC 2 and reduced the complexity of the genotype-by-environment interaction because two pCs accounted for more than 80% of the variation, instead of the three pCs that were required to explain the variation in the original dataset. The EM-GGE estimation method was able to maintain the original conformation of the 'which-won-where' biplot when £30% of estimated data were used. The EM-GGE was superior to the EM-AMMI method for estimating missing data. The estimation of more than 30% of the data should be avoided because it can lead to significant changes in mega environment conformation and the identification of "winner" genotypes.

show abstract

Brazilian Spring Wheat Homogeneous Adaptation Regions can be Dissected in Major Megaenvironments

Cited by 22 publications

References 34 publications

Effect of debranning process on deoxynivalenol content in whole‐wheat flours

Effect of debranning process on deoxynivalenol content in whole‐wheat flours

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

Estimation of Missing Values Affects Important Aspects of GGE Biplot Analysis

Contact Info

Product

Resources

About