Genetic analysis of physiological traits in bread wheat under normal and terminal water-deficit stress conditions

Introduction Wheat is the main source of nutrition for about 85% people of the world. On the other hand, drought is one of the most damaging abiotic stresses leading limitation to food supply in the worldwide and decreases crops yield more than any other environmental factor especially in Iran. Study of physiological reactions and traits in wheat could be useful in identifying effective mechanisms to increase resistance to undesirable environmental conditions and to promote yield performance under drought stress condition. The purpose of the present study was to investigate the genetic inheritance and type of gene action in the control of physiological traits in bread wheat to progress breeding programs in order to increase the yield under both normal and drought stress conditions. Materials and methods Gene action could be studied using the generation means analysis (GMA). Generation mean analysis was performed using Mather and Jinks method (1982). The seeds of six populations (P1, P2, F1, F2, BC1:1 and BC1:2) for each cross (totally 11 treatments) were planted in a randomized complete block design with three replications. The parental genotypes used in this study were: “Winter B. C. of Roshan”, “Parsi”, “Sistan”. The crosses, “Parsi × Winter B. C. of Roshan” and “Sistan × Winter B. C. of Roshan” were made in 2014-2015. The experiment was conducted under two normal and water-deficit stress conditions in 2015-2016. Different traits including, grain yield, total chlorophyll content, chlorophyll a, chlorophyll b, leaf area index, leaf temperature, relative water content, stomatal conductance, persistence indicator and photosystem II maximum efficiency were measured. Broad-sense inheritability was calculated according to following formulas; h_b^2 = [V_(F_2 ) – (V_(P_1 ) × V_(P_2 ))1/2] / V_(F_2 ) h_b^2 = (V_(F_2 ) – V_(F_1 )) / V_(F_2 ) h_b^2 = [V_(F_2 ) – (V_(P_1 ) × V_(P_2 )×V_(F_1 ))1/3] / V_(F_2 ) h_b^2 = (V_(F_2 ) – VE) / V_(F_2 ) VE = [V_(P_1 )+ V_(P_2 )+ (2V_(F_1 ))] / 4 Narrow-sense inheritability was calculated according to Warner (Warner, 1952) as follows: h2n=[2 VF2- (VBC2 + VBC1)/ F2 Analysis of variance and mean comparison of the characters were performed using SAS Software. Generation mean analysis was carried out only for those traits that showed significant differences among generations. Results and discussion The results showed that grain yield decreased in both of crosses due to water-deficit stress. In general, “Parsi” showed a higher reduction in grain yield when compared to the “Winter B. C. of Roshan”. In normal condition of both crosses (“Parsi × Winter B. C. of Roshan” and “Sistan × Winter B. C. of Roshan”), the highest amount of narrow-sense heritability (h_n^2 ) belonged to chlorophyll b content (52% -53%), leaf area index (50-58%) and total chlorophyll content (45-63%), respectively. In water-deficit stress condition for the first population, the highest amount of narrow-sense heritability (h_n^2 )belonged to the content of chlorophyll b (61%), leaf area index (54%) and total chlorophyll content (68%), and in the second cross it belonged to content of chlorophyll a (78%) and leaf area (56%). The differences among generation was not significant for grain yield in both crosses in different conditions except for the cross “Sistan× Winter B. C. of Roshan” in normal condition. The genetic analysis for this trait showed that the additive component was not significant but dominant component was highly significant which indicating that conventional selection may not be effective for the improvement of the trait and therefore for the selection for this trait suggested to be postponed to the later generation. Conclusions The high amount of narrow-sense heritability for chlorophyll b content, leaf area index and total chlorophyll content illustrates that additive effects play a big role to control them. Therefore, selection method could be effective method to improve the mentioned traits in breeding programs.