پديد آورندگان :
ميرمحمدي ميبدي سيدعلي محمد 1341 نويسنده كشاورزي و دامپزشكي MIRMOHAMMADI MEIBODi ali mohammad , ارزانی احمد نويسنده گروه زراعت و اصلاح نباتات، دانشكده كشاورزی، دانشگاه صنعتی اصفهان Arzani A , گلكار پوراندخت نويسنده پژوهشكده زیست فناوری و مهندسی زیستی، دانشگاه صنعتی اصفهان Golkar P
كليدواژه :
پروتئين , تنوع , چند متغيره , عملكرد دانه
چكيده لاتين :
<strong >Introduction </strong >
Genetic variation is essential for the success of breeding programs and is vital to helping the genetic improvement of Triticale. Understanding patterns of genetic diversity in the Triticale and use of its genetic resources on a practical basis may help to establish appropriate procedures for breeding genetic materials. It can be used as a benchmark for classifying parenting lines and favorable heterotic groups in triticale. Triticale (X Triticosecale wittmack) has considerable potential either as a grain crop or forage crop, but has received little attention from breeding programs in Iran.
<strong >Materials and Methods </strong >
This research was conducted to study the genetic diversity and the performance of triticale cultivars imported from Poland and International Maize and Wheat Improvement Center (CIMMYT) using some agro-morphological traits. Forty one triticale genotypes were evaluated using a randomized complete block design with three replications at Research Farm of College of Agriculture, Isfahan University of Technology. Agronomic characteristics comprising plant height (cm), length of the last node (cm), flag leaf length (cm), spike length (cm), thousand seed weight (g), the number of spike per m2, seed yield (tha-1), grain number per spike, number of spikelets per spike, harvest index, test weight (kg hectoliter), biological yield (ton ha-1), wet and dry gluten content (%) were measured. All statistical analyses were performed using SAS statistical software. The multivariate analysis procedures used to analyze the collected data and to investigate relationships among variables. Mean comparison was conducted using LSD range test (at 5% level). The unweighted neighbour joining (UNJ) cluster analysis was carried out using NT-SYS software.
<strong >Results and Discussion </strong >
Analysis of variance showed that genotypes were significantly different in all characters. The measured traits varied in coefficient of genotypic and phenotypic variation. The highest coefficients of genotypic (41.7%) and phenotypic (44.9%) coefficient of variation were belonged to wet gluten content. The least coefficient of genotypic (4.5%) and phenotypic (7%) variation was denoted to test weight. Simple mean comparisons for seed yield of Triticale showed that the highest seed yield (11.84 ton ha-1) was denoted to Sorento genotype from Poland and the least seed yield (5.5 ton ha-1) to Beaglel and EMA genotypes (from CYMMYT). Using stepwise regression analysis, 98.8% of seed yield variation was attributed to two traits, including harvest index, and biological yield. Correlation analysis showed the significant relation of number of spikelets per spike, and spike length with grain yield. The results of the factor analysis revealed that five factors namely, plant height, grain yield and their components, biological yield, harvest index gluten content explained 80% of total variances of the grain yield. Cluster analysis of genotypes based on agronomic and protein content traits grouped the genotypes into four separate clusters. In categorization based on collected data, the fourth group included genotype from Poland origin (Prego, Lamberto, Moreno, Lasko, Dagro, Sorento, Fidelio, LAD1900, RH116, Tewo, Disco, Vero, DAD601, Pinokio and Magnat) with the highest value for biological yield, seed yield, number of spikelet per spike, plant height, spike length and the length of the last internode. These clusters have beneficial characteristics and are useful for plant breeding purposes.
<strong >Conclusions </strong >
Based on the data reported here, the scientific use of multivariate statistical analysis including stepwise regression analysis, principle component and cluster analysis of genotypes revealed subjectivity of these methods as a suitable way to exploit intraspecific variation within triticale and evaluate its genetic resources for their agronomic value and the amount of genetic variation for specific traits to allow more efficient genetic improvement. The identified superior genotypes such as Sorento could be used in hybridization programs for improvement the seed yield in triticale.
