Application of the Multi-Trait Genotype-Ideotype Distance Index in the Selection of top Barley Genotypes in the Warm and Dry Region of Darab

Barley is one of the most important crops after wheat, corn, and rice. Barley is an excellent source of food for humans and is also used to feed livestock. The purpose of this study was to evaluate and select superior genotypes with high grain yield and desirable agronomic characteristics and also to investigate the application of MGIDI in selecting superior genotypes based on morpho-phenological different traits in the warm and dry region of southern Fars.

To select the best barley genotypes in the southern regions of Fars using the MGIDI index, 108 pure lines in the non-repeating Augment design with four controls (Nowruz, Auxin, Nobahar, and WB-97-11) in the Fars Agricultural and Natural Resources Research and Education Center (Darab station) were evaluated during the cropping year 2020-2021. MGIDI index was calculated to select superior genotypes using 13 morpho-phenological traits. These traits include grain yield, number of spikes per square meter, number of grain per spike, weight of spikes, 1000-grain weight, spike density, filling period length, peduncle length, awning length and spike length, plant height, days to flowering and days until the maturity.

According to the results of variance analysis, a significant difference was observed between the studied lines for all traits (except awning length and 1000-grain weight) at the probability levels of 5 and 1%. Also, the results showed that there was a significant difference between the lines and experimental controls in all traits (except peduncle length). The results of factor analysis for the 13 studied traits identified five hidden factors that explained 80.2% of the total variance of the data. Based on the MGIDI index, L110, L99, L88, L51, L56, L108, L63, L33, L50, L112, L52, L36, L20, L69, L68, L94 and L35 genotypes, respectively, with the lowest value of this index were superior genotypes. The highest and lowest values ​​of differential selection percentage of MGIDI index were related to grain yield (11.5%) and 1000-grain weight (-3.62%), respectively. The results showed that low values ​​of the number of grain per spike and weight of spikes and high values of the number of spikes per square meter were effective factors in selecting superior genotypes using the first factor. Based on this factor, L20, L94, L110 and L88 were superior. In the second factor, high values of the number of days to maturity, grain yield, and grain filling period were the main factors in selecting genotypes, and based on this factor, L112 genotype was top. Third factor selected genotypes based on high values ​​of both trait plant height and peduncle length. L88 and L94 genotypes were ideal based on the third factor. Fourth factor selected genotypes based on high awning length and spike length (L33 genotype was superior), and fifth factor selected genotypes with low values ​​of spike emergence length and 1000-grain weight and based on this factor L50, L35 and L51 genotypes were ideal.

Overall, the results showed that none of the factors could classify the superior genotypes based on the ideal value of all their internal traits. Therefore, genotypes are selected that have the lowest MGIDI value, and also their grain yield is higher than the average grain yield of unselected genotypes. So the results showed that among the selected genotypes using the MGIDI index, L99, L88, L51, L56, L108, L63, L20, L69 and L94 genotypes ​​were the top genotypes in this study. On the other hand, proving the efficiency and development of a new index such as MGIDI requires more research in other plants.