An analysis of variability and genotype × environment interaction in mung bean (Vigna radiata) in south-eastern Queensland

1982 ◽  
Vol 33 (3) ◽  
pp. 523 ◽  
Author(s):  
BC Imrie ◽  
KL Butler
Keyword(s):  
Plant Height ◽  
Seed Yield ◽  
Vigna Radiata ◽  
Mung Bean ◽  
Rainfall Variability ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Sowing Dates ◽  
Photoperiod Sensitive ◽  
Main Effects

Thirty mung bean (Vigna radiata) accessions were grown in replicated hill plots at two sites in each of 2 years. Plant height, days to flower and to harvest, and seed yield were recorded for each plot. In an analysis of variance most main effects and interactions were statistically significant. Estimated variance due to environment exceeded that due to genotypes for all characters. Broad sense heritability of seed yield was 0.07. The linear regression of seed yield on plant height was statistically significant, and there was a significant quadratic effect of yield on days to flower. It was concluded that environmental effects on the duration of growth phases were likely to be mainly due to the effect of different sowing dates on photoperiod-sensitive accessions, while rainfall variability most likely contributed to yield variance. Emphasis in an evaluation program should be on sampling years rather than locations.

scholarly journals Genotype Environment Interaction in Grass Pea (Lathyrus sativusL.) Lines

2009 ◽  
Vol 2009 ◽  
pp. 1-7 ◽  
Author(s):  
G. B. Polignano ◽  
V. Bisignano ◽  
V. Tomaselli ◽  
P. Uggenti ◽  
V. Alba ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Plant Height ◽  
Seed Yield ◽  
Principal Components ◽  
Environment Interaction ◽  
Grass Pea ◽  
Genotype Environment Interaction ◽  
Marginal Areas ◽  
Different Seasons ◽  
The Stability

Eight grass pea lines grown in three different seasons were evaluated for the stability of seed yield, 100 seeds weight, flowering time, plant height, and biomass. Significant differences existed among years, lines, and lines years interaction for all traits except for 100 seeds weight. Two methods of multivariate analysis cluster and principal components were utilized to determine: firstly, whether a pattern existed among lines in their response across years and secondly to examine the relationships among them. In both analyses, each line was presented as a vector whose elements were given by the performance of lines in each year. The analyses used arranged the lines into groups that were differentiable in terms of performances and stability. Our results provide useful information to aid the choice of grass pea lines in the Mediterranean marginal areas.

scholarly journals Stability Analysis for Seed Yield over Environments in Coriander

2016 ◽  
Vol 4 (11) ◽  
pp. 1014
Author(s):  
Sangeeta Yadav ◽  
Arun Kumar Barholia
Keyword(s):  
Stability Analysis ◽  
Seed Yield ◽  
High Fertility ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Back Ground ◽  
Ammi Model ◽  
Main Effects

Thirty five genotypes of coriander (Coriandrum sativum L.) were tested in four artificially created environments to judge their stability in performance of seed yield. The differences among genotypes and environments were significant for seed yield. Stability parameters varied considerably among the tested genotypes in all the methods used. The variation in result in different methods was due to non-fulfillment of assumption of different models. However, AMMI analysis provides the information on main effects as well as interaction effects and depiction of PCA score gives better understanding of the pattern of genotype – environment interaction. The sum of squares due to PCAs was also used for the computation of AMMI stability values for better understanding of the adaptability behavior of genotypes hence, additive main effects and multiplicative interaction (AMMI) model was most appropriate for the analysis of G x E interactions for seed yield in coriander. Genotypes RVC 15, RVC 19, RVC 22, RVC 25 and Panipat local showed wider adaptability while, Simpo S 33 exhibited specific adaptability to favourable conditions of high fertility. These genotypes could be utilized in breeding programmers to transfer the adaptability genes into high yielding genetic back ground of coriander.

A study of genotype × environment interaction in three chickpea triple test crosses

1986 ◽  
Vol 107 (3) ◽  
pp. 549-554
Author(s):  
S. Singh ◽  
I. S. Pawar ◽  
I. P. Singh
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Grain Weight ◽  
Environment Interaction ◽  
Gene Effects ◽  
Genotype Environment Interaction ◽  
Triple Test ◽  
Sowing Dates ◽  
Additive Gene ◽  
Number Of Branches

SUMMARYThe analysis of Perkins & Jinks (1971) was applied to 360 progeny families of three chickpea F2 triple test crosses, namely, F 378 × ICCC 1, P 1198–1 × ICCC 1 and US 613 × BG 203, to detect and measure the interaction of additive, dominance and epistatic gene effects with sowing dates. The families were grown in completely randomized blocks in three replications with two sowing dates, and data were recorded for plant height, number of branches per plant, number of days from sowing to flowering, number of days from sowing to maturity, number of pods per plant, number of grains per plant, 100-grain weight and grain yield per plant. The i type epistasis and additive genetic component were relatively more important than j and l type epistasis and dominance component, respectively. The j and l type epistasis and additive gene effects were more sensitive to environmental differences than the i type epistasis and dominance gene effects, respectively.

scholarly journals Seed vigor level in association to fertilizer distribution

2020 ◽  
Vol 9 (10) ◽  
pp. e5999108658
Author(s):  
Simone Morgan Dellagostin ◽  
Vinícius Jardel Szareski ◽  
Gustavo Henrique Demari ◽  
Ivan Ricardo Carvalho ◽  
Michele Renata Revers Meneguzzo ◽  
...  
Keyword(s):  
Grain Yield ◽  
Seed Yield ◽  
Distribution System ◽  
Distribution Systems ◽  
Seed Vigor ◽  
Soybean Seeds ◽  
Environment Interaction ◽  
Absolute Increase ◽  
Genotype Environment Interaction ◽  
Main Effects

This work aimed at evaluating yielding responses of soybean seeds production fields in response to the association between seed vigor level and fertilizer distribution systems at the sowing line.Experimental design was randomized blocks design, with two growing environments (Passo Fundo - RS and Ernestina - RS) x three vigor levels (high = 90%, medium = 70% and low = 60%) x three fertilizer distribution systems (absence, conventional and by transhipment), arranged in four replicates, grain yield (GY). For grain yield (GY), it was applied the method genotype main effects and genotype environment interaction (GGE). Seed vigor levels and fertilizer distribution systems influence on seed yield, first pod insertion height, plant height, number of pods in the main stem and ramifications, magnitude and length of ramifications in soybean.The high vigor level in the conventional and by transshipment fertilization systems provided an absolute increase of 10.9 and 5.6% in seed yield, respectively, in Ernestina-RS. The conventional fertilizer distribution system, in Passo Fundo-RS, increased seed yield in 12.5% in plants originated from low vigor seeds.

Application of physiological understanding in soybean improvement. I. Understanding phenological constraints to adaptation and yield potential

2011 ◽  
Vol 62 (1) ◽  
pp. 1 ◽  
Author(s):  
R. J. Lawn ◽  
A. T. James
Keyword(s):  
Seed Yield ◽  
Environmental Control ◽  
Thermal Environment ◽  
Sowing Date ◽  
Companion Paper ◽  
Interaction Effects ◽  
Yield Potential ◽  
Environment Interaction ◽  
Sowing Dates ◽  
Eastern Australia

The purpose of this paper and its companion1 is to describe how, in eastern Australia, soybean improvement, in terms of both breeding and agronomy, has been informed and influenced over the past four decades by physiological understanding of the environmental control of phenology. This first paper describes how initial attempts to grow soybean in eastern Australia, using varieties and production practices from the southern USA, met with limited success due to large variety × environment interaction effects on seed yield. In particular, there were large variety × location, variety × sowing date, and variety × sowing date × density effects. These various interaction effects were ultimately explained in terms of the effects of photo-thermal environment on the phenology of different varieties, and the consequences for radiation interception, dry matter production, harvest index, and seed yield. This knowledge enabled the formulation of agronomic practices to optimise sowing date and planting arrangement to suit particular varieties, and underpinned the establishment of commercial production in south-eastern Queensland in the early 1970s. It also influenced the establishment and operation over the next three decades of several separate breeding programs, each targeting phenological adaptation to specific latitudinal regions of eastern Australia. This paper also describes how physiological developments internationally, particularly the discovery of the long juvenile trait and to a lesser extent the semi-dwarf ideotype, subsequently enabled an approach to be conceived for broadening the phenological adaptation of soybeans across latitudes and sowing dates. The application of this approach, and its outcomes in terms of varietal improvement, agronomic management, and the structure of the breeding program, are described in the companion paper.

scholarly journals Adaptive Abilities of Broad Bean (Vicia faba L.) Accession in Terms of Main Quantitative Traits

2019 ◽  
Vol 65 (4) ◽  
pp. 136-146
Author(s):  
Natalia Georgieva ◽  
Valentin Kosev
Keyword(s):  
Plant Height ◽  
Seed Weight ◽  
Quantitative Traits ◽  
Broad Bean ◽  
Environment Interaction ◽  
High Plasticity ◽  
Forage Crops ◽  
Genotype Environment Interaction ◽  
Adaptive Ability ◽  
Adaptive Abilities

Abstract The experimental activity was conducted at the Institute of Forage Crops (Pleven) during the period 2016 – 2018. The adaptive ability of 10 broad bean accessions was determined with respect to main quantitative traits based on parametric and nonparametric analysis. The environment influences to the highest degree the traits of 1st pod height, pods number and seed weight per plant. The plant height and seeds number were strongly influenced by the genotype, and the mass of 100 seeds was determined by the genotype × environment interaction. The broad bean accessions can be distributed as follows: Fb 1929 has a high value of the 1st pod height (34 cm) and is characterized by high plasticity and stability; BGE 029055 and Fb 1896 are stable and form a large number of pods per plant (11 – 15); Fb 1896 and Fb 2486 are distinguished with good adaptability and stability, increased seed weight (28.01 and 30.28 g, respectively) and 100 seeds mass (105.48 g and 91.31 g). Accessions BGE 032012 and Fb 2481 represent a selection value in terms of plant height (61.36 and 65.83 cm); Fb 1929 – in 1st pod height (32.46 cm); and BGE 029055, Fb 1896 and Fb 2486 – in pods number (10.59, 9.67 and 11.89). Fb 1896, Fb 2486 and BGE 041470 can be used to develop a new genetic diversity in breeding aimed at increasing the mass of 100 seeds and seed productivity.

Evaluation of sugarcane genotypes with respect to sucrose yield across three crop cycles using GGE biplot analysis

2021 ◽  
pp. 1-13
Author(s):  
Aliya Momotaz ◽  
Per H. McCord ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
Miguel Baltazar ◽  
...  
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Area 5 ◽  
Randomized Complete Block Design ◽  
Main Effects

Summary The experiment was carried out in three crop cycles as plant cane, first ratoon, and second ratoon at five locations on Florida muck soils (histosols) to evaluate the genotypes, test locations, and identify the superior and stable sugarcane genotypes. There were 13 sugarcane genotypes along with three commercial cultivars as checks included in this study. Five locations were considered as environments to analyze genotype-by-environment interaction (GEI) in 13 genotypes in three crop cycles. The sugarcane genotypes were planted in a randomized complete block design with six replications at each location. Performance was measured by the traits of sucrose yield tons per hectare (SY) and commercial recoverable sugar (CRS) in kilograms of sugar per ton of cane. The data were subjected to genotype main effects and genotype × environment interaction (GGE) analyses. The results showed significant effects for genotype (G), locations (E), and G × E (genotype × environment interaction) with respect to both traits. The GGE biplot analysis showed that the sugarcane genotype CP 12-1417 was high yielding and stable in terms of sucrose yield. The most discriminating and non-representative locations were Knight Farm (KN) for both SY and CRS. For sucrose yield only, the most discriminating and non-representative locations were Knight Farm (KN), Duda and Sons, Inc. USSC, Area 5 (A5), and Okeelanta (OK).

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