Identification of effective agronomic traits on yield of local rice cultivars using multiple regression models

Plant breeders to select their breeding objectives through the physiological and morphological characteristics variation (Khazaei et al., 2016); require classification of the limitations and capabilities which exists in plants (Soltani et al., 2000); this issue for plant characteristics associated for yield increasing is important in crop breeding programs (Rotter et al., 2015). Therefore, the aim of this research was determine to indentify the effective agronomic traits on yield of local rice cultivars using multiple regression models in Sari region. For experiment implementation based on randomized complete blocks design with three replications and 12 local rice cultivars, requirement data for using in regression modeling were collected. Using multiple regressions applied in order to determine the important traits and to show the contribution of each trait in formation of yield. The method identified the relation between yield and all variables. Also, according to the positive or negative correlation between the number of filled spikelet per panicle and harvest index, for indentifying yield variation of these traits, three hypotheses put forward and various aspects of them was examined Seven important traits including days to seed germination, days to pollination, days to physiological maturity, flag leaf length, number of filled spikelet per panicle, 1000-grain weight and harvest index which affected the most role on yield increasing were recognized their optimal values with multiple regression model. These seven variables explained 50% of yield. The results indicate that if the correlation between the number of filled spikelet per panicle and harvest index would be changed, it can be used for the benefit of yield. Regarding negative correlation between the number of filled spikelet per panicle and harvest index, three hypotheses were evaluated. If the negative correlation between the number of filled spikelet per panicle and harvest index is not breakable, the yield variation would have an increasing of 1722 (from 4581 to 6303) kg ha-1. If with increasing the number of filled spikelet per panicle, harvest index stay at moderate level, it would be an increasing of 1985 (from 4581 to 6566) kg ha-1, and if correlation between the number of filled spikelet per panicle and harvest index is breakable, it would be an increasing of 2747 (from 4581 to 7329) kg ha-1. The results of the method used in this study, due to the fact that the genetic differences between the cultivars are noticeable, can be a way for the breeders to move towards yield increasing in rice cultivars. Obviously, if the main goal is to determine the effective traits on yield of local rice cultivars in the Sari region, it is more appropriate to use more cultivars and years of experimentation. With selecting optimum amount of traits in model, would increase grain yield from an average of 4581 kg ha-1 to 6303-7329 kg ha-1. It was concluded that the method used in this study, because of concerning the genetic differences between varieties, can be used in determining yield increasing in conjunction with other methods and it can guide plant breeders to select important traits effective on yield.