تقييم أداء تراكيب وراثية من الذرة الصفراء تحت تأثير مستويات من النتروجين وحامض الهيومك

Evaluation of the Performance of Maize Genotypes Under the Influence of Nitrogen and Humic Acid Levels

The field experiment was carried out in the experimental field of Ibn Al-Bitar Preparatory Vocational School in Al-Hussainiya District-Holy Karbala governorate during the spring season 2021, with the aim of evaluating the performance of six genotypes of maize (Buhoth 5018, Buhoth 106, Al-Maha, Fajr 1, Al-Furat and Sarah) and estimating some genetic parameters by the effect of four levels of fertilization (160 kg N ha-1, 160 kg N ha-1 with humic acid, 320 kg N ha-1, 320 kg N ha-1 with humic acid) using the split plot arrangement according to the Randomized Complete Block Design (RCBD) with three replications, where the genotypes of maize represented the sub plots and fertilization as the main plots.
Several characteristics of growth, quality, yield and some of its components were studied, in addition to studying some characteristics of the tassel and the vitality of pollen grains. The genotypic and phenotypic correlations were studied and a prediction equation was found by conducting a stepwise regression analysis. The fifteen traits were reduced to two main components by conducting the base-component analysis and Bi-plot analysis was explained by a graph that showed the eigenvectors and explained the correlation between the traits by means of angles between vectors and dendrogram, which explained the intensity of the correlation between the traits.
The results of the study showed the following traits:
The analysis of variance of fertilization levels showed highly significant differences for number of days to 75% tasseling, plant height, leaf area, nitrogen and protein percentage in grains, percentage of oil in grains, number of grains in the ear, weight of 500 grains, and grain yield, and showed significant differences for pollen vitality. As for the genotypes, they were highly significant for all the studied traits, while the interaction between the experimental factors was highly significant for each of the leaf area, weight of 500 grains, yield efficiency, grain yield and significant with the number of days up to 75% tasseling, nitrogen and protein percentage in grains.
The results showed that the interaction between Al-Furat genotype and fertilizer level of 320 kg N.ha-1 with humic acid was significantly superior, achieving the highest leaf area (6850.00 cm2), weight of 500 grain 194.33gm, yield efficiency 297.00 and grain yield amounted to (10848 kg.ha-1).
It was found from the analysis of phenotypic and genotypic correlations that the values of genotypic correlations are higher than the values of phenotypic correlations for most traits. The highest significant positive phenotypic correlations was achieved between grain yield and each of leaf area, weight of 500 grains, yield efficiency, and genetically positive and highly significant correlated with weight of 500 grains and yield efficiency, and genetically positive and significant correlated, with leaf area, nitrogen and protein percentage in grains.
It was clear from the stepwise regression analysis that the independent traits that are closely related to the dependent variable (the yield) were, according to the formula predictive of the yield, the weight of 500 grains, the efficiency of the yield and the leaf area, as these traits were responsible for 95% the variance of yield.
Biplot analysis reduced the variables to two main components, which amounted to 83.02% of the total variance, according to the analysis of the main components, where the first main component PC1 was associated with grain yield, weight of 500 grains, yield efficiency, oil and protein ratio and nitrogen percentage in grains, while the second component was associated with pollen vitality and number of parts per plant. Also, the cluster diagram confirmed the strength of the relationship between the grain yield and the weight of 500 grains, so that the characteristic of the weight of 500 grains could be considered as selected criterion for improving grain yield. Also, the confirmation of the regression equation of the stepwise, the analysis of the principal components and the analysis of the biplot. This result indicates the possibility of using these methods to get the same goal.