

Articles
by
F. Muhammad 
Total Records (
3 ) for
F. Muhammad 





I.A. Arshad
,
F. Muhammad
and
A. Ghafoor


Different mash plant traits contributes to the mash grain yield but the major contributors are plant height (X_{1}), days to flowering (X_{2}), days to first pod maturity (X_{3}), days to 90% maturity (X_{4}), branches per plant (X_{5}), pods per plant (X_{6}), pod length (X_{7}), seeds per pod (X_{8}), 100seed weight (X_{9}), biological yield per plant (X_{10}) and mash grain yield (Y). This study was initiated to find the important regressors on which the yield of mash depends. In this regard principal component analysis and path analysis were used to find correlation structure between mash plant traits and regressors effect on mash grain yield, respectively. Principal component analysis reduced the dimensionality in the system of eleven mash plant traits to four principal components, which contributes about 88% of the total variability present in the mash plant data. On the basis of correlation between principal components and original mash plant traits, a classification structure was made to observe the relation between different traits. It was observed that for the first principal component, plant height (X_{1}), days to flowering days to first pod maturity (X_{3}), days to 90% maturity (X_{4}) and 100 seeds weight (X_{9}) have positive correlation between themselves i.e. varies in the same direction. Path analysis was also described to explain correlation structure, directindirect effects between different mash plant traits. This analysis suggested that pod per plant has maximum positive direct effect on mash grain yield i.e. more pod per plant, greater will be the yield. But days to 90% maturity has maximum negative direct effect on mash grain yield i.e. more maturity lesser will be the grain yield. Similarly branches per plant and biological yield per plant have positive indirect effect on mash grain yield via pods per plant. It was observed that the direct and indirect effects of remaining predictors are negligible. 




A. Ghafoor
,
F. Muhammad
and
I.A. Arshad


To increase the precision of estimated effect of a yield character "pod length" on mashbean grains yield, Bayesian regression technique with sample and prior nonsample information about pod length was applied on simple linear relation between mash grain yield and pod length. With the use of prior inequality information about regression coefficient on pod length, a reduction was observed in the estimated value of regression coefficient and its standard error. It was observed that prior inequality information about regression parameter is helpful to increase the precision of the regression estimates. Simulation procedure was developed to generate random residuals from Exponential (1) and Uniform (0, 1) distributions, to test the results. The results were compared with those based on original data set. 




A. Ghafoor
,
I.A. Arshad
and
F. Muhammad


Stability of fifteen selected sunflower genotypes across eight environments (locations) in Pakistan with respect to oil yield was tested. On the basis of six different stability measures, genotypes such as SF187, SMH269, SC110 and PSH21 were found as stable genotypes with respect to oil yield (kg ha^{1}). Further to group the genotypes having similar response pattern over all environments and to group similar environments over all sunflower genotypes, Ward`s fusion strategy of hierarchical clustering technique was used on sunflower genotypes x environments (G x E) data. It was observed that genotypes SMH32 and SMH112 are different from remaining genotypes over all environments, but in the largest group7 genotypes, Hysun33, SF270 and SMH269 have similar response pattern (w.r.t. oil yield) over all environments. Similarly, it was observed that among eight environments, NARC and Sariab were similar, Kot. Diji and Dunya Pur were similar, Tando Jam and Faisalabad were similar and D.I.K. and Tarnab were found similar with respect to oil yield in sunflower over all genotypes. Performance plots used to illustrate each genotype group`s performance (w.r.t. oil yield) in a series of environment groups. The results showed that genotypes group1 (Hysun341 and NK265) and genotypes group2 (SF187 and NK277) consistently performed well over Kot Diji, Dunya Pur, Tando Jam and Faisalabad environments. Genotype SMH32 was found to be better in performance at NARC and Sariab. 





