scholarly journals Evaluation of Yield and its Components in Bread Wheat (Triticum aestivum L.) Genotypes

2021 ◽  
Vol 2 (1) ◽  
pp. 76-82
Author(s):  
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Triticum Aestivum L ◽  
Morphological Characters ◽  
Considerable Variability ◽  
Thousand Grain Weight ◽  
Important Food ◽  
Wheat Genotypes ◽  
Wheat Improvement ◽  
Plot Yield

Bread wheat is an important food crop of world and Pakistan. An experiment was conducted in winter wheat growing season to assess yield and yield related traits of newly evolved wheat genotypes. The 16 wheat genotypes includes 14 advanced lines viz., CIM-04-5, CIM-04-21, CIM-04-3, C7-98-11, 5-02, V2-10-12, CIM-03-2, C2-98- 6, 6-12, V3-10-9, C6-98-5, V3-10-32, C2-98-8, V2-10-21 and 2 local checks NIA Sunhari and Kiran 95 were tested. Experimental design was laid out in RCBD with 3 replicates. Mean square for genotypes showed high significantly differences for most of agro-morphological characters. Mean and range of all wheat genotypes for all the traits indicated a considerable variability between genotypes. Mean performance for the trait grain yield showed that newly developed genotypes C2-98-8, CIM-04-21, V3-10-32 and CIM-04-3 produced higher grain yield (3 to 3.25 kg plot-1) than both the contesting check varieties. High significantly and positively correlation of the plot yield to thousand grain weight (0.41**), biomass (0.41**) and harvest index (0.86***) with grain yield were found. It indicated that by improving these three traits, we can significantly improve grain yield. Selected genotypes and traits can be used in breeding program for wheat improvement.

scholarly journals Variability Study of Biofortified Bread Wheat Genotypes for Grain Zinc and Iron Concentration, Yield and Yield Associated Traits at Khumaltar, Lalitpur, Nepal

2019 ◽  
Vol 7 (2) ◽  
pp. 184-194 ◽  
Author(s):  
Sapana Ghimire ◽  
D.B. Thapa ◽  
A. Paudel ◽  
N.R. Adhikari
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Iron Concentration ◽  
Field Research ◽  
Food Habit ◽  
Triticum Aestivum L ◽  
Yield Attributes ◽  
Wheat Genotypes ◽  
Lattice Design ◽  
Grain Zinc

Bread wheat ( Triticum aestivum L.) is third major cereal crop of Nepal where cereal based foods represent the largest proportion of the daily diet. Lack of diverse food habit in the country is resulting micronutrient deficiency. This could be addressed by introducing biofortified bread wheat genotypes. This field research was conducted at Agriculture Botany Division, Khumaltar, Lalitpur to study the variability of biofortified bread wheat genotypes for grain zinc, iron, yield, yield attributes and identify high yielding genotypes with high grain zinc and iron concentration. 50 wheat genotypes (47 biofortified, 3 checks) were tested in alpha lattice design with two replications. Data on grain zinc, iron, yield and yield attributes were recorded and analyzed (α=5%). Genotypes differed significantly for the studied traits which provide an opportunity to improve the existing germplasms for targeted traits and environment. Grain yield was correlated positively with effective tiller, plant height, days to maturity, grains per spike and negatively with thousand grain weight. Grain zinc and iron concentration were significantly positively correlated but had positive non-significant relation with grain yield suggesting simultaneous improvement of both micronutrients without compromising grain yield is possible.  Effective tiller and peduncle length can be used as selection criteria for high grain yield and micronutrient concentration respectively. Superior genotypes containing higher grain iron, zinc and yield can be used as parent in breeding for developing zinc and iron enriched varieties.  

scholarly journals Additive Main effect and Multiplicative Interaction Analysis of Grain Yield of advanced Bread Wheat (Triticum aestivum L) Genotype in Ethiopia

2019 ◽  
Vol 2 (1) ◽  
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Interaction Analysis ◽  
Triticum Aestivum L ◽  
Yield Response ◽  
Similar Response ◽  
Wheat Genotypes ◽  
Main Effect ◽  
Ammi Analysis ◽  
Similar Yield

The present study was conducted to interpret Genotype main effect and GEI obtained by AMMI analysis and group the genotype having similar response pattern over all environments. Fifteen bread wheat genotypes were evaluated by RCBD using four replications at six locations in Ethiopia. The main effect differences among genotypes, environments, and the interaction effects were highly significant (P ≤ 0.001) of the total variance of grain yield. Results of AMMI analysis of mean grain yield for the six locations showed significant differences (P<0.001) among the genotypes, the environments and GEI. The environment had the greatest effect of the environmental sum of squares (35.28%) than the genotypes (33.46%) and GEI(31.45%) effect. The AMMI analysis for the IPCA1 captured 46.1% and the IPCA2 explained 28.6% the two IPC cumulatively captured 74.7% of the sum of square the GEI of bread wheat genotypes, when the IPCA1 was plotted against IPCA2. The genotype ETBW8075, ETBW8070 and ETBW9470 were unstable as they are located far apart from the other genotypes in the biplot when plotted on the IPCA1 and IPCA2 scores. The ETBW8078, ETBW8459, Hidase and ETBW8311 were genotype located near to the origin of the biplot which implying that it was stable bread wheat genotypes across environments. There is closer association between Lemu and ETBW8065 which indicate similar response of the genotypes to the environment. The best genotype with respect to location Kulumsa was ETBW9470, ETBW8075 was the best genotype for Dhera, ETBW8070 was the best genotype for Holeta while ETBW9466 was the best genotype for Arsi Robe. Arsi Robe and Kulumsa is the most favorable environment for all genotypes with nearly similar yield response for grain yield.

scholarly journals Path analysis of grain yield associated characters in Brazilians wheat genotypes (Triticum aestivum L.)

2017 ◽  
Vol 11 (11) ◽  
pp. 1406-1410 ◽  
Author(s):  
Ivan Ricardo Carvalho ◽  
◽  
Maicon Nardino ◽  
Diego Nicolau Follmann ◽  
Gustavo Henrique Demari ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Grain Yield ◽  
Path Analysis ◽  
Triticum Aestivum L ◽  
Wheat Genotypes
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