hossein rahimsoroush

Considering the lack of food in the world, increasing the production of rice is one of the demands of the global market and one of the important goals of many countries producing this crop plant. The final performance of each organism is affected by the genotypic potential, the environmental effects and the interaction between genotype and environment. The interaction of genotype and environment causes that different genotypes do not have the same reaction under different environmental conditions. Genotypes that can produce higher yields in different regions or under different environmental conditions and maintain their performance stability are considered as successful genotypes. In this study, nine promising rice lines originating from the Hashemi variety, along with two varieties Hashemi and Gilaneh, were evaluated for grain yield in two regions during two years. The objective of this study was to evaluate the stability of the studied lines and introduce the most stable ones in order to introduce the new varieties.

The plant materials of this experiment were nine promising rice lines originating from the Hashemi variety, as a Iranian local variety with good quality, along with two varieties Hashemi and Gilaneh as control varieties. The experiment was conducted in a randomized complete block design with four replications in two regions, Rice Research Institute of Iran (Guilan province, Iran) and Chaparsar Research Station (Mazandaran province, Iran), in two years, 2017 and 2018. The studied traits included grain yield, days to 50% flowering, head rice percentage, milling efficiency, grain length, amylose content and gelatinization temperature. For data statistical analysis, simple analysis of variance was firstly performed for grain yield, and then Bartlett's test was done to check the uniformity of the experimental errors. Combined analysis of variance and comparison of means by Duncan's method was performed with SAS software. To evaluate the stability of the studied lines, Lin and Binns and GGE-biplot methods were used.

The results of combined analysis of variance showed that the effects of genotype and year as well as the interaction of year × place and year × place × genotype on grain yield were significant. Therefore, grain yied stability of the studied genotypes was evaluated using Lin and Binns and GGE-biplot methods. The results of Lin and Binns method indicated that two genotypes Gilaneh and 19603 (Hashemi/IR74720-85-1-2-1), with the lowest intra-location variance, were the most stable genotypes in this experiment. The results of GGE-biplot graphical method also showed that the genotypes 19607, Hashemi and Gilaneh, which formed the vertices of the polygon in the grain yield biplot, were the best or the weakest genotypes in some environments or in all environments. Also, the simultaneous evaluation of stability and grain yield of the studied genotypes identified the promising line 19603 as the best genotype. The graph of ideal genotype also showed that the promising line 19603 had the smallest distance from the hypothetical ideal genotype compared to other genotypes, so it was the best genotype of this experiment.

The results of stability analysis of rice genotypes using Lin and Binns and GGE-biplot methods introduced genotype 19603 as the most stable genotype of this experiment. This promising line along with the promising line 19607 produced the highest average paddy yield in all studied environments. These genotypes with the number of days to 50% flowering less than 95 days, grain length more than seven mm, and medium amylose content and gelatinization temperature, were considered as genotypes with mid-maturing, long-grain (Sadri) and good cooking quality. Therefore, two promising lines 19603 and 19607 are suggested for cultivar introduction programs.

Rice is the staple food of half of the world's population and one of the most important crops in Central and West Asia. To assess variation in some important agronomic traits and grouping of rice genotypes, this study was performed and 49 genotypes from Azerbaijan, Kazakhstan, Afghanistan, Turkey, Kyrgyzstan, Iraq, and Uzbekistan along with 7 genotypes from Iran were evaluated using randomized complete block design with three replications in 2019 and 2020 cropping season in experimental field of Rice Research Institute of Iran, in Rasht, Iran. Analysis of variance showed genotypes were significantly different for all studied traits. Genotype × year interaction effect was not significant for any of the studied traits. The lowest grain yield (2.2 t.ha-1) belonged to BT7 cultivar (Iraq) and the highest grain yield (7.4 t ha-1) belonged to Mishkab2 (Iraq). The shortest plant height (79.3 cm) belonged to QazNIIR-7 (Kazakhstan) and the highest plant height (149.8 cm) recorded for Avanqard (Azerbaijan). Marjan cultivar (Kazakhstan) was the earliest maturity among the studied rice genotypes with 100 days to physiological maturity (after seeding). Correlation studybetween traits indicated negative correlation between grain yield and flag leaf length. Cluster analysis grouped the studied genotypes into seven distinct groups. In general, the existence of high diversity for agronomic traits and grain yield in the studied genotypes showed that this set of germplasm has the potential for to be used in the national rice breeding programs to improve Iranian rice cultivars.

Rice grain appearance quality traits (APQ) affect consumer preference and marketing acceptance and long grain rice has many customers on the international markets.In order to identify QTLs controlling grain length, width and length to width ratio (shape) and QTL by environment interactions a study was conducted on two set of recombinant inbred lines (RILs) of two rice populations derived from crosses of Alikazemi / IR67017-180-2-1-2 (ALIR population) and Alikazemi / Saleh (ALSA) cultivars.The treatments of each RIL population with five check varieties were evaluated in augmented based on randomized complete block design with 5 replications in two regions of Rasht and Tonekabon in northern of Iran. Linkage map of the two populations using 87 polymorph microsatellite markers (SSR) covered 1356.0 cM of rice genome with an average distance of 15.58 cM between two markers. In this study, a total of 13 main QTLs (M-QTLs) and 10 pairs of epistatic QTLs (E-QTLs) were identified for three above mentioned traits, including seven M-QTLs and five pairs of E-QTLs for the ALIR population and six M-QTLs and five pairs of E-QTLs for the ALSA population. Two QTLs, qRGL4 (1.1) and qSGL5 (1.01), were increased the grain length with positive additive effect and the highest justified phenotypic variance of 25.2 and 18.4%, respectively. In this study, three QTL clusters were identified for APQ traits. Of these, two clusters were identified on chromosome 3 that was effective in controlling all APQ traits in two populations with alleles from a common Alikazemi parent. The third QTL cluster was determined on chromosome 7 consisting of qGW7 and qGSh7 for grain width and shape in the ALIR population. Therefore it could be stated that the QTLs on each cluster were either tightly linked or had pleiotropic effects with considerable influences in controlling rice APQ traits. A common marker of RM5955 was found in the ALIR population with a genetic distance of about 3.7 centimeters with QTLs of all three traits, and could be considered as a linked marker in breeding program. In this study, ten pairs of E-QTL were identified for three traits including five pairs per population. The epistatic effects in the ALIR population were mostly expressed by significant main QTLs (80%), while they were expressed in the ALSA population more by non-detected main QTLs (60%).The contribution of explained phenotypic variances of M-QTLs in controlling APQ traits were more than epistatic QTLs. QTL by environment interactions revealed that only one main QTL had significant interaction with environment, while no epistatic QTLs with additive × additive effect were found to be interacted with environment. The appropriate QTLs and linked markers in this study can be used in the breeding program to improve the appearance quality of rice grains after fine-mapping and validation.

Rice yield as a complex trait is the main target in most rice breeding programs. To map the main and epistatic QTLs controlling grain yield and yield components, an experiment was carried out using a 129 F6 recombinant inbred lines population (IRA population) originated from a cross between Alikazemi / IR67017-180-2-1-2, in 2015 growing season in two locations, Rasht and Tonekabon, Iran.  The experimental design was augmented design arrangment with five check cultivars in randomized complete block design with five replications. Analysis of variance showed that the linkage map consisted of 87 Single Sequence Repeats (SSRs) covering 1356.0 cM of rice genome in 12 linkage groups with an average distance of 15.58 cM spamming two markers. The results of combined analysis of variance for two locations, using composite interval mapping method, identified a total of 13 main QTLs on rice chromosomes for five measured traits. The qTN3 with 13.9% for tiller number per plant, the qFG4 with 11.6% for filled grain per panicle and the qGY6 with 15.6% for grain yield had significant positive additive effect. Furthermore, the qSG1 with 19.9% phenotypivc variation had a negative additive effect on the number of unfilled grain.panicle-1. These finding suggest that these QTLs can be used in rice breeding programs for improving grain yield. The interaction between additive effect (A) of QTLs and environment (E) was significant on grain yield and number of unfilled grain.panicle-1, but it was not significan on other traits. A total of 18 QTL pairs with significant additive × additive (AA) epistatic effect were identified for all traits. The highest epistasic effects were related to grain yield and number of unfilled grain.panicle-1 with six pairs of QTLs for each of these traits. Only one of the epistatic effects between qSG1-2 and qSG6 had significant AAE effect with a R2aae = of 3.4%. In addition, some QTLs were identified as three gene clusters controlling the grain yield, number of tiller.plant-1 and number of filled grain.panicle-1. Furthermore, five microsatellite markers including RM7551, RM8218-RM3417 and RM5302- RM283 0.2 to 5 cM distance from were identified as linked markers with qGY6, qFG4 and qSG1, respectively. These markers can be considered in the marker-assisted rice breeding program.

To detect main and epistatic QTLs and their environmental interactions for rice important agronomic traits, 242 recombinant inbred lines (RIL) from two F6 rice populations derived from crosses between Alikazemi / IR67017-180-2-1-2 (IRA population) and Ali Kakami / Saleh (SA) cultivars were evaluated in two locations. Results of the present experiment showed that the linkage map of the two populations using 87 polymorph microsatellite markers (SSR) covered 1356.0 cM of rice genome with an average distance of 15.58 cM between two markers. A total of 20 main QTLs (M-QTLs) and 33 epistatic QTLs (E-QTLs) were identified with positive and negative effects. Five M-QTLs and five E-QTLs had a significant interaction with the environment. Eight M-QTLs and ten E-QTLs with significant effect on agronomic traits were stable and did not have any significant interaction with the environment. These QTLs include two M-QTLs and two E-QTLs for reducing plant height, three M-QTLs and three E-QTLs for decreasing heading date, an M-QTL and an E-QTL for increasing panicle length and two M-QTLs and four E-QTLs to increase grain yield. These main QTLs explained 11.12% (qHD6) and 24.5% (qGY1) phenotypic variation, respectively. Therefore, such useful QTLs can be used for gene pyramiding programs to improve rice agronomical traits. Furthermore, six linked SSR markers (RM421, RM178, RM3441, RM5101, RM7551 and RM5302) were identified with less than 5 cM distance from important QTLs, suggesting that such SSR markers can be used in marker-assisted selection to select rice lines with desirable traits in segregation generations.