scholarly journals Assessing wheat performance using environmental information

Genetika ◽  
2007 ◽  
Vol 39 (3) ◽  
pp. 413-425
Author(s):  
Dejan Dodig ◽  
Miroslav Zoric ◽  
Desimir Knezevic ◽  
Bojana Dimitrijevic ◽  
Gordana Surlan-Momirovic
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Grain Yield ◽  
Water Availability ◽  
Vegetative Growth ◽  
Environmental Variables ◽  
Environment Interaction ◽  
Pls Regression ◽  
Data Set ◽  
Genotype X Environment

The partial least squares (PLS) regression model was applied to wheat data set with objective to determining the most relevant environmental variables that explained biomass per plant and grain yield genotype x environment interaction (GEI) effects. The data set had 25 wheat genotypes (20 landraces + 5 cultivars) tested for 4 years in two different water regimes: rainfed and drought. Environmental variables such as maximum soil temperature at 5 cm in April and May, soil moisture in the top 75 cm in March, and sun hours per day in May accounted for a sizeable proportion of GEI for biomass per plant. Similar results were obtained for grain yield: maximum soil temperature at 5 cm in April, May and June, and sun hours per day in May were related to the factor that explained the largest portion (>38%) of the GEI. Generally, wheat landraces are able to better exploit environments with higher temperatures and lower water availability during vegetative growth (March-June) than cultivars.

scholarly journals Genotype X Environment Interaction of Food Barley

2015 ◽  
Vol 21 ◽  
pp. 41-48
Author(s):  
Gebremedhin Welu
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Genotype Effect ◽  
Environment Effects ◽  
Randomized Complete Block Design ◽  
Barley Genotypes

The objective of this experiment was to estimate the magnitude of genotype X environment interaction on grain yield and yield related traits. Twelve varieties of food barley were included in the study planted in randomized complete block design with three replications. The ANOVA of combined and individual location revealed significant differences among the food barley genotypes for grain yield and other traits. The results of ANOVA for grain yield showed highly significant (p≤0.01) differences among genotypes evaluated for grain yield at Maychew and significant (p≤0.05) differences in Korem, Alage and Mugulat. The ANOVA over locations showed a highly significant (p≤0.01) variation for the genotype effect, environment effects, genotype X environment interaction (GEI) effect and significant (p≤0.05) variation for GEI effect of yield and for most of the yield related traits of food barley genotypes. Haftysene, Yidogit, Estayish and Basso were the genotypes with relatively high mean grain yield across all locations and they are highly performing genotypes to the area. Among locations, the highest mean grain yield was recorded at Korem and it was a suited environment to all the genotypes whereas Mugulat is unfavoured one. ECOPRINT 21: 41-48, 2014DOI: http://dx.doi.org/10.3126/eco.v21i0.11903

scholarly journals Effect of weather variability on growth and yield of wheat crop under semi-arid region of India

2021 ◽  
Vol 22 (2) ◽  
pp. 124-131
Author(s):  
ANANTA VASHISTH ◽  
AVINASH GOYAL ◽  
P. KRISHANAN
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Grain Yield ◽  
Water Content ◽  
Relative Water Content ◽  
Significant Positive Correlation ◽  
Weather Conditions ◽  
Grain Filling ◽  
Phenological Stages ◽  
Relative Water

For generating different weather conditions during various phenological stages, experiments were conducted on two varieties of wheat (HD-2967 and HD-3086) sown on three different dates at the research farm of IARI, New Delhi during rabi 2015-16 and 2016-17. Soil temperature, soil moisture, leaf area index, biomass, chlorophyll content, radiation interceptions were measured during different crop growth stages. Number of days taken for each phenological stage was observed and thermal time for different phenological stages were calculated. Results showed that first sown crop had higher value of crop growth parameters and yield as compared to second and third sown crop.HD-3086 had higher value of LAI, biomass and yield than HD-2967. Grain yield had significant positive correlation with growing degree days during grain filling stage. Soil temperature measured at 2.21 PMat 5, 10, 15, 20 cm depth had 1-5°C lower value than the air temperature. Soil moisture measured at 0-15, 15-30, 30-45 and 45-60 cm depths had slightly higher soil moisture for HD-3086 as compared to corresponding value in HD-2967 during emergence, flowering and grain filling stages. Percentage relative water content in HD-2967 was found to be higher in first sown crop followed by second and third sown crop. However, in HD-3086, percentage relative water content was found to be higher in first sown crop followed by third and second sown crop. Grain yield had significant positive correlation with relative water content during different phenological stages. HD-3086hadhigherradiation use efficiency as compared to HD-2967 in all weather conditions.

scholarly journals Genotype x environment interaction of wheat genotypes under salinity environments

2017 ◽  
Vol 3 (1) ◽  
pp. 38-43
Author(s):  
Md Saleh Uddin ◽  
Md Sultan Alam ◽  
Nasrin Jahan ◽  
Kazi Md Wayaz Hossain ◽  
Md Ali Newaz
Keyword(s):  
Grain Yield ◽  
Grain Weight ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Wheat Genotypes ◽  
Genotype X Environment ◽  
Genotype Environment Interaction ◽  
Days To Heading ◽  
Salinity Levels ◽  
1000 Grain Weight

Genotypes x environment interaction as well as stability of performance were determined for grain yield and yield contributes of 12 wheat genotypes under four salinity levels of environments (control, 8, 12, 16 dS/m). Significant genotype-environment interaction (linear) for days to heading, plant height, number of spikes per plant and grains per spikes, 1000-grain weight and grain yield per plant at 1% level of probability when tested against pooled deviation. Both the environment (linear) and genotype x environment (linear) components of variation for stability were also significant indicating that prediction of the genotypes on the environment appeared feasible for all the characters. The variance due to pooled deviation was significant for only days to heading. Considering all the three stability parameter, genotype G11 was found most stable among all the genotypes for grain weight of wheat. Among the genotypes G11, G22, G24, G33 and G40 were most desirable for yield per plant. The genotype G32 showed more responsiveness to changing environment and was suited only for highly favorable environments. Based on three stability parameters, G11, G22 and G37 were the most stable and desirable genotypes with reasonable good yield among the all.Asian J. Med. Biol. Res. March 2017, 3(1): 38-43

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