Path analysis of barley (Hordeum vulgare L.) yield

Bu çalışma, 6 sıralı arpa çeşidinde bazı verim özellikleri arasındaki korelasyonu ve bunların path analizini belirlemek amacıyla tesadüf blokları deneme desenine göre 3 tekrarlamalı olarak 2 yıl buyunca yürütülmüştur. Tohum verimi, bayrak yaprağı uzunluğu, bayrak yaprağı genişliği, çiçek sapı boyu, bitki boyu, başaktaki tane sayısı, 1000 tohum ağırlığı,metrekaredeki başak sayısı, biyolojik verim, hasat indeksi, başaklanma gün sayısı, olgunlaşma gün sayısı, tane doldurma dönemi, saman verimi, başak uzunluğu, kılçık uzunluğu ve birincil tohum gücü gibi 17 karakter ölçülmüştür. Diğer özelliklere karşı tane verimi için stepwise regresyon analizi uygulanmıştır. Modeldeki diğer özellikler arasındaki korelasyon path analiziyle doğrudan ve dolaylı etkilere bölünmüştür. Korelason ve path analizinden elde edilen sonuçlar, verim üzerine başaktaki tane sayısının 0.489** doğrudan etki ile en önemli faktör olduğunu göstermiştir. 1000 tohum ağırlığı (0.472**) ve başak sayısı (0.358**)'nın doğrudan etkileri de pozitif yönde beirlenmiştir. Başaktaki tane sayısı, 1000 tane ağırlığı ve metrekaredeki başak sayısının tane verimi ile olan korelasyonu sırasıyla r=0.768**, r=0.737** ve r=0.633**'dir.Başaktaki tane sayısı, verime ve büyüme periyodu başlangıcındaki oluşumuna etkisindeki önemden dolayı, arpa ıslah programlarında gözönünde bulundurulmalıdır.

Arpa (Hordeum vulgare L.) veriminin path analizi

This research was carried out, to determine the correlations among some yield related attributes and their path analysis for 20 advanced lines and cultivar of six-row barleys, in a Randomized Complete Block Design (RCBD) with three replications for two years. Seventeen attributes include grain yield, flag leaf length, flag leaf width, peduncle length, plant height, grain number in spike, 1000-kernel weight, number of spikes per m2, biological yield, harvest index, days to heading, days to maturity, grain filling period, straw yield, spike length, awn length, and primary seed vigor were measured. A stepwise regression analysis was also applied for grain yield against other attributes. The correlation between the remaining attributes in model was divided into direct and indirect effects by path analysis. The result which was derived from correlation and path analysis indicated that grain number in spike with a direct effect of 0.489** on yield was the most important factor. The direct effect of 1000-kernel weight (0.472**) and number of spike (0.358**) on yield was positive also. Correlation coefficient of grain number in spike, 1000-kernel weight and spike number per m2 with grain yield was r=0.768**, r=0.737**, and r=0.633**, respectively. Because of importance of the grain number in spike effect on yield and its formation in the beginning of growth period, it must be regarded in improving and breeding programs of barley.

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