نشریه پژوهش های کاربردی زراعی
پیاپی 130 (بهار 1400)

Rice (Oryza sativa L.) is the most important cereal after wheat (Kazemi-Arbat, 1995). Suitable cropping dates will cause plants to better utilize the factors that are effective in their growth and development, thereby leading to the formation of desired yields. Thereofore, the selection of proper cropping date can play a crucial role in crop production (Rashedmohasel, 1997). Rice plant has a special place in Chaharmahal and Bakhtiari province where an area of about 3,000 hectares is dedicated to its cultivation. It seems that the introduction of high-quality cultivars will expand the rice cultivation area in the province. Therefore, six rice cultivars from the northern provinces of the country, named Domsiah, Hashemi, Tarom, Sahel, Shafagh and Kadous, along with traditional cultivar of Kouhrang as a check were evaluated (Lotfi Chamgawi, 2007). In order to investigate the possibility of early cultivation of late-maturing cultivars from northern peovinces through the nursery with plastic cover in the Lordegan region during 2010 and 2011, a study was conducted in a randomized complete block design with three replications. Cultivars were Tarom, Domsiah, Hashemi, Kadous, Shafagh and Sahel with Koohrang cultivars as check. The seeds of each cultivar were transplanted into separate trays and after the emergence under the dark conditions, they were covered with the plastic in the nursery. The yield and yield components were measured and the results were analyzed by SAS software. The mean comparison was performed by LSD at P=0.05 probability level. The results of the combined analysis of variance showed that the studied cultivars exhibited significant differences in the all meausured agronomic traits. The difference between cultivars was significant in terms of number of days to flowering and maturity stages. Among the cultivars, Shafagh and Hashemi cultivars were the latest matuity cultivars with 127.7 and 115.2 days from planting to maturity, rspectively. Shafagh cultivar with a height of 68.5 cm was recognized as the shortest cultivar. On the other hand, Tarom, Domsiah, Koohrang and Hashemi cultivars were not significantly different from each other where their heights averaged about 120 cm. Domsiah cultivar had the highest total number of seeds and the highest number of filled grains per panicle amongst the cultivars. The 1000-seed weight of the cultivars studied varied from 21.77 g for Kadous cultivar to 19.02 g for Tarom cultivar. In this study, paddy yield was affected by the main effect of year and cultivar and also their interactions. Demsiah cultivar with the average yield of 6436 kg ha-1 was recognized as the most productive cultivar and superior to the control. The Koohrang cultivar had an average yield of 5736 kg ha-1. The lowest yields of 1117 kg ha-1 and 1171 kg ha-1 were obtained from Shafagh and Kadous cultivars, respectively. The correlation coefficients among the evaluated traits showed that there was a positive and significant correlation between grain yield and number of full grains per panicle, number of fertile stems per plant, plant height and panicle length. In contrast, the correlation between grain yield and unfilled grains per panicle, the number of days to flowering, and the number of days to maturity was negative. As expected, the traits of number of filled grains in panicle and number of filled panicle in the plant as important yield components had a very strong and positive correlation with the grain yield. The yield of rice had the highest correlation with the number of filled grains in panicle (r = 0.85**). According to the combined analysis of variance, the results of two years of the experiment showed that only Domsiah cultivar was superior to the control and could be recommended for cultivation in Lordegan and other same areas. This cultivar not only had greater number of filled grains in panicle but also a greater number of fertile tillers. The Kouhrang cultivar, as a control, with a yield production of about 7.5 tons per hectare, ranked as secondcultivar after Demsiah. Generally, in the regions with the possibilty of early-season planting, both Sahel and Domsiah cultivars could be recommended, and for the regions where there are no favorable conditions for early planting, only Domsiah cultivar is recommended.

Radiation absorption and use efficiency are affected by genotype and agronomic management (Mondani et al., 2019; Tohidi et al., 2012). Kermanshah province located in an appropriate geographical location in terms of access to radiation during maize development stages (Ahmadi et al., 2018a). However, the radiation absorption by crop canopy depends on the spatial arrangement shoot of plants. The canopy structure by effect on vertical distribution of radiation plays an important role in the crops yield. On the other hand, knowledge of the agricultural management role in optimal utilization from environmental factors such as radiation in order to improve the canopy's ability to use these factors is very important. Therefore, this research was carried out in order to study the effects of water deficit stress on radiation absorption and use efficiency of some common maize cultivars and study the role of growth indices on production formation under Kermanshah climatic conditions.

This experiment was done in 2018 growing season at the experimental field of Campus of Agriculture and Natural Resources, Razi University, Kermanshah, Iran. The experiment was conducted as split plot based on randomized complete block design with three replications. Main-factor was three irrigation regimes (IR) included supplying 130% (1064 mm), 100% (802 mm), 70% (623 mm) water requirement (IR130%, IR100% and IR70% respectively) and sub-factor included three maize cultivars in three levels (KSC704, Simon and BC678) were evaluated randomly. To calculate water requirement, the Penman-Monteith-FAO equation was used. The amount of water for each treatment was calculated and available to plants every seven days. In order to calculate the growth indices, radiation absorption and use efficiency, during different development stages, leaf area and total dry weight of maize plants were measured.

The results showed the growth indices such as leaf area index and crop growth rate, and also radiation absorption, radiation use efficiency and total dry weight were relatively similar for KSC704 and Simon cultivars in response to different irrigation regimes but they were higher for BC678 cultivar. The grain yield of Simon cultivar was significantly higher than other cultivars. Regardless of the maize cultivars, in the IR130%, IR100% and IR70% treatments, average value for maximum of leaf area index were 4.8, 4.2 and 2.9 and leaf area duration were 269.5, 235.8 and 168.1 day, respectively. The negative effect of water deficit stress on leaf area index and leaf area duration eventually led to decrease radiation absorption. In the IR130%, IR100% and IR70% treatments, the amount of cumulative radiation absorption were 1318, 1241 and 1059 MJ m-2, radiation use efficiency were 1.14, 1.05 and 1.00 g MJ-1, maximum of crop growth rate were 26, 21.9 and 18.7 g m-2 day-1, respectively. The growth season period of maize (from emergence to physiological maturity) in the IR70% treatment was 4 and 6 days shorter than IR100% and IR130% treatments, respectively. Finally, the reduction of radiation absorption, and growth season caused by water deficit stress led to lower total dry weight and grain yield. In the IR130% treatment, the total dry weight and the grain yield were 16960 kg ha-1 and 7430 kg ha-1, respectively. By reducing of 30% and 60% of irrigation water compared to IR130% treatment, the total dry weight were decreased about 18% and 28% and the grain yield were decreased about 15% and 40%, respectively.

According to results, it can be concluded that by choosing the suitable irrigation regimes in the maize production systems, a canopy with a suitable structure can be obtained. This canopy structure will provide a suitable situation for improving growth indices, efficient use of environmental resources such as radiation and eventually increasing production. In general, the results showed a positive response of the evaluated characteristics to the over-irrigation treatment, which may be due to the fact that the use of the Penman-Monteith-FAO equation is not a suitable method for determining the water requirement of the plant in the study area. Therefore, it is suggested that in case of repetition of the results of this research, alternative methods be used along with the Penman-Montith FAO method to determine the water requirement of the plant.

The main goal of the mostly soybean breeding programs is selection of desirable genotypes with high yield and stability. Genotype × environment interactions for quantitative traits such as grain yield cause genotypes to have not similar relative yields in different environments. In many statistical methods that have been used to determine yield stability and adaptability of cultivars, some basic assumptions of stability analysis such as nonlinear response of genotype and environment and dependence of environmental index on mean of genotypes are not true (Basford and cooper, 1998). Using multivariate methods such as principal components and GGE biplot method, genotype x environment interactions can be analyzed and their component values estimated ( Pacheco et al., 2009). Many breeders believe that selection of genotypes based on G or GE alone is not sufficient, and it is advisable to study these two effects together done by method such as GGE biplot . The aim of this study was to evaluate the grain yield and adaptability stability of 20 soybean pure lines in three soybean cultivation region and selection the best pureline as new crop cultivar in the territory.

In order to evaluate the grain yield and stability of 20 soybean pure lines along with Williams control (20 genotypes) during two year (2014-2015) in regions : Karaj (1321m altitude, 35.5 N & 51.1 E), Moghan ((45 m altitude, 39.3 N & 47.2 E), Khorramabad (1155 m altitude, 33.3 N & 48.2 E), farming operations and necessary fertilization were carried out uniformly in all three regions. A randomized complete block design with 3 replications was used in the locations. Each block consisted of 21 plots and each plot consisted of 4 rows of 4 m with intervals of 60 cm. Simple and composite analysis of variance on grain yield was performed to estimate main effects of genotype, environment and genotype × environment interaction and to determine adaptability and stability of grain yield of the genotypes used GGE Biplot analysis methods by Genstate Ver.12 Software .

Combined analysis of variance showed significant effects of environment, genotype, genotype x environment interaction, at 1% level probeblity (p ≤ 0.01). The first and second major components (PCA1 & PCA2) of GGE biplot analysis accounted for 47% and 28% of the variance of genotype × environment and genotype (G X E + G) interaction, respectively.. Based on GGE biplot criterion G6 (L12/Williams x Katool) genotype with yield of 3514 kg/ha had shortest distance from ideal genotype and was selected as the most desirable genotype and after that G4 (L12/Williams x Katool) with 3522 kg/ha in terms of desirability was ranked second. In this study one mega environment consisting of two environments E1 (Karaj 1394) and E3 (Moghan 2015) was identified. Also E4 environment (Moghan 2016) was the nearest to ideal environment and was recognized as the most effective environment in terms of discriminating ability and representativeness and then E2 (Karaj 1395), E1 (Karaj 1394), E3 (Moghan 1394) and E5 (Khorramabad 1394) environments were favorably ranked next.

The first and second major components (PCA1 & PCA2) of GGE biplot analysis accounted for 47% and 28% of the variance of genotype × environment and genotype (G x E + G) interaction, respectively. G6 genotype (L12/Williams x Katool) with yield of 3514 kg/ha was identified as the most desirable genotype and then G4 (L12/Williams x Katool) with 3522 kg/ha in terms of desirability was ranked second. In this study one mega environment consisting of two environments E1(Karaj 1394) and E3 (Moghan 2015) was identified. Also E4 (Moghan 2016) was recognized as the most desirable environment in terms of discriminating ability and representativeness.

Wheat (Triticum aestivum L.) is widely grown across Central and West Asia. Evaluation of wheat genotypes in different environments is essentials to estimate Genotypes x Environment interactions (Fan et al., 2007). Breeding new cultivars require evaluation of yield stability and the adaptability of high yielding genotypes across different environments. Statistical approaches such as GGE Biplot analysis reveals genotypic main effects, as well as G × E interactions. GGE biplots analysis provides a graphical depiction of relationships among environments, genotypes and their interactions in an effective manner (Yan et al., 2000). This method has been used to examine the uniformity of different environments and to identify superior genotypes in multi-environment trials. This study aimed to determine the effects of genotype by environment interactions on the performance of 22 promising wheat lines along with two check cultivars and to identify the ideal genotypes for the examined environments.

Wheat promising lines including 22 elite lines along with two commercial cultivars Azar2 and Ohadi were evaluated in a randomized complete block design (RCBD) experiment with 4 replications under rainfed dryland conditions. Uniform experiments were carried out for 3 years (2013-16) at the agricultural research stations of Maragheh, Sararod, Ghamlo, Zanjan, Ardabil, Shirvan and Arak representing cold and moderate cold dryland wheat growing regions of Iran. Entries were planted in plots with 6 x 1.2 dimension (6-m long rows, 17.5 cm apart and seeding rate of 380 kernel/m2). Morphological characteristics, phenological stages and yield components were scored during growth period. Grain yield and thousands kernel weight were determined for each plot after harvest. The collected yield data were subjected to combined ANOVA considering environment as random and genotypes as fixed effects using SAS (9.1) statistical software. Yield stability parameters were estimated and GGE biplot analysis was carried out using open-source software R packages.

The ANOVA revealed significant differences among genotypes for yield performance. Significant genotype by environment interactions were also identified. The main effect for environments and genotypes by environment interactions accounted for 82.3 and 6.5 percent of total variances in the experiment. The grand total mean grain yield for the evaluated wheat genotypes was 2165 kg/ha. Genotypes G21 and G23 produced the highest (2378 kg/ha) and the lowest (1747 kg/ha) yields, respectively. Genotype G20 was found as the most stable according to the estimated stability parameters (Table.3).Based on polygonal GGE biplot, two environmental groups and five different groups for the examined genotypes were detected (Fig. 1). The first environmental group included Maragheh (M92, M93), Ghamlo (G92, G93, G94), Ardabil (A93), Zanjan (Z92, Z93), Arak (Ak92, Ak93, Ak94) and Shirvan (Sh93, Sh94), with the G21 being as the best performer in the group. The second environmental group included 8 remaining environments with the G1 (Azar2) as the highest yielding genotype in the group (Fig. 1). Simultaneous evaluation of genotypes for yield and yield stability identified genotypes G20, G13 G2 and G6 as high yielding with high yield stability (Fig. 2).An environment is considered ideal tester for evaluating a set of genotypes if it is able to effectively differentiate genotypes based on traits of interest and if it properly represents other environments (Yan & Tinker, 2006). Our findings revealed environments Z92, Sh92 and Ak92 as the most ideal environments and environments A92, S93, Ak92, M92, M94 as the highly discriminative of the examined genotypes (Fig.3). The genotype G20 with higher average yield and the least contribution into GxE interactions showed the characteristics of an ideal genotype (Fig. 4).

Analysis of yield data revealed that, the variations due to G × E interactions were largely explained by the environment effects. In this study, cold environments were grouped closely, showing a similar behavior in discriminating the examined genotypes and were easily distinguished from the moderate cold environments. Acute angles among environments M92, G92, Sh93, Ak93, Sh94, G94, Ak94, Z93, A93, Ak92 and also among environments S94, Sh92, M94, Z94, S92 indicated high correlations in discriminating the studied genotypes. We found the genotype G20 as the ideal genotypes possessing high yield performance and high yield stability.

To date, wheat counts as one of the most important cereal grains, feeding the increasing world population (Feldmann, 2001). Evaluation of the genetic diversity of wheat genotypes will provide a great opportunity to improve its yield quality and increase its grain output. The results of previous studies on wheat have shown correlations among grain yield and its components such as number of tillers, spike length, grain number per spike, thousand-kernel weight and harvest index. However, because of complex relations among different traits and their interactions with grain yield of wheat, simple correlations of these traits can not be directly and unequivocally used to clarify those relationships. Therefore, different statistical techniques can be employed in modeling the crop yield, including correlation, regression, path analysis, factor analysis, factor components, and cluster analysis (Leilah & Al-Khateeb 2005). The goal of this study was to identify variability in grain yield and some agronomic and morphological traits and their relationship among 150 doubled haploid wheat lines. Materials and Methods In this study, morphological and phenotypic traits of 150 doubled haploid wheat lines derived from three different crosses: 1) DH-26: Ghods*3/MV17, 2) DH-27: Flanders/3*Ghods, 3) DH-28: Hybrid Bersee/*3Ghods, which consisted of 75, 45 and 30 individuals, respectively, were evaluated. The experiment was conducted using an augmented design with six check cultivars including Parsi, Mihan, Bolani, Ghods, Hybrid Bersee and MV17, which were repeated over five blocks. Some agronomic traits such as days to %50 of flowering, days to maturity, spike length, number of spikelets per spike, number of grains per spike, grain weight per spike, thousand kernel weight, plant height, grain density per spike and grain yield of DH lines as well as check cultivars were evaluated. DH lines were classified with hierarchical cluster analysis using Ward method as well as using multivariate statistical methods such as factor analysis, stepwise regression and path analysis. Statistical procedures were carried out using SAS 9.0 and SPSS 16 software packages. Results and Conclusion The analysis of variance showed that there were significant differences for days to %50 of flowering, days to maturity, spike length, number of spikelets per spike, number of grains per spike, grain weight per spike, thousand kernel weight, plant height, grain density per spike and grain yield. The determination of coefficients of variations for phenotypic and physiological traits of all three DH populations indicated that most of the studied traits had a high genetic variability. Evaluation of grain yield among different population showed that DH-26 population with an average grain yield of 4.885 T/ha had higher grain yield compared to other two populations, although within each population several lines with higher yields and superior agronomic and morphological traits than their parents and control cultivars were identified. The coefficients of correlations among yield components showed that grain yield had a positive and significant correlation with grain weight per spike and thousand-kernel weight while its correlation with days to 50% of flowering, days to maturity and number of spikelets per spike was negative and significant. The results of factor analysis indicated that three major factors effective on earliness, spike and plant height explained %68.47 of the total variation. The results of stepwise regression analysis showed that thousands kernel weight had the most important effect on grain yield and explained 8.8% of the variation. The path analysis of data indicated that, number of spikelets per spike and thousand-kernel weight had the highest direct effects on grain yield. The current genetic variability of DH lines, which are derived from parents with good agronomic traits, especially yellow rust resistance (Bakhtiar et al., 2015), can be employed for the selection of the superior genotypes that possess all beneficial characteristics. 

Rice is one of the most valuable nutrients for the food security in the world. Gowing population and changes in diet habits in the world, it is necessary to increase rice production. Using hybrid rice technology to increase grain yield can be an effective step in achieving food security (Shabestari & Mojtahedi, 2008), Therefore, it is important to examine the different characteristics and indices of parents and the resulting hybrids. Yield increase in hybrid rice is due to plant growth period and high harvest index. Increasing of number of grains and panicle weight increases grain yield in hybrid rice. Limitation of suitable cultivars to restorer, low number of effective lines and their genetic basis and cooking quality have always been the main problems of hybrid rice production in the Iran. The purpose of this experiment was identify of restorer lines in crosses with the sterile cytoplasmic line of Neda A to finally identify suitable parent lines and use them for hybrid breeding programs.

This experiment was conducted in two years )2018-2019 (in the Genetics and Agricultural Biotechnology Institute of Tabarestan. Plant materials included 26 restorer lines sent by the International Rice Research Inistitute (IRRI) as the male parent, and the Cytoplasmic male sterile (CMS) lines of Neda A as the female parent with Shirodi and Neda (control varietirs). The traits such as number of days to 50% flowering, number of days to maturity, plant height (cm), number of fertile tillers, length of spikelet (cm), number of floret in spikelet, number of spikelet per panicle, pollen grain sterility percentage, spikelet fertility percentage, grain length (mm), grain width (mm), weight of 1000-grains (gr), and grain yield (gram per square meter) were measured. Finally, crosses with the desired pollen grain fertility, spikelet fertility, and good yield were selected and introduced. The analysis of data was performed using SAS9.1 software. Cluster analysis of data was done with Ward method (using PAST software) and the dendrogram cuts were performed based on the formula proposed by (Darvish Kajouri, 2009).

Among the parental lines of fertility restorer, IR68078-15-2-2-2-2-2 R and R4842-2-3-2-1R lines had the highest number of tillers and the highest percentage of spikelet fertility were observed in the line MILYANG 46. The IRi347 line had a higher yield than all the restorer lines due to its high number of fertile spikelet and low percentage of pollen grains fertility. Cluster analysis of the genotypes placed them in five separate clusters. The mean heterosis of the hybrids for the yield trait as compared to the parents, the superior parent, and the control variety showed a variation from -94.54 to 57.46% for the parent, from -94.73 to 35.45% for superior parent, and from -2.94 to 42.52% for the control.

According to the result of the current research, the hybrids with optimal yield and high percentage of pollen as well as high spikelet fertility included the crosses of Neda A with IR68078-15-2-1-2-2-R, IR 65912-90-1-6-3-2-2R, IR36, MILYANG 54, and IR 56 hybrids which produced yields of 7112, 8708.3, 6340.3, 7253.3, and 6828.8 kg.m2 with standard heterosis values of 16.40, 42.52, 3.77, 18.74 and 8.49 respectively. Among the superior hybrids, NedaA/ MILIANG 54 hybrid had the highest milling and suitable amylose content, and NedaA/IR68078-15-2-1-2-2- R hybrid had a favorable aroma. These hybrids also exhibited good heterosis and were recognized as the best hybrids in terms of agronomic traits, which can be used for yield improvement. Since the lines studied are imported, it is necessary to make attempts to adapt them and also use them in crosses, which can lead to the production and release of promising new rice hybrids (Baloch Zehi et al., 2016). 

Introduction:

 Cotton (G.hirsutum L.) is an important cash crop in Iran, which plays a vital role in the economy of the country. The yield of cotton cultivars depends on their genotypic performance and adaptability. The most significant objectives of cotton variety improvement for dry agro systems include high yield, fair stability, better fiber quality and also special importance are given on suitability of different maturity groups for early, mid and late planting dates. A variety or genotype is considered to be the most adaptive or stable one if it has a high mean yield but a low degree of fluctuation over diverse environments (Said, 2016; Mudata et al., 2017). The association among yield related traits play a significant role toward improvement and to produce promising genotypes with high yield and quality (Nawaz et al, 2019). Low economic outcome of cotton due to low yields is one of the reasons for diminishing cotton production areas. To increase cotton economic profitability, it is necessary to first determine what critical farm management factors pose limitation to cotton production and then devise suitable plans to address these limitations. Variety selection is an example of these limitations. Cotton planting in Garmsar region begins from mid-April and continues to mid-June which lasts a span of 60 days. Evidently, the responses of cultivars to climatic conditions at each planting date are different. In spite of accomplished efforts, the majority of corn cultivation areas are still limited to Varamin and Khordad cultivars. The present research was carried out to select the best adaptable cotton variety among ten promising new genotypes for yield improvement in second planting in the dry and warm region of Garmsar.

This experiment was conducted in a RCBD experimental design with three replications under Garmsar climatic condition for three years (2014, 2015 and 2016). In this study, 10 cotton genotypes including advanced hybrids and new commercial varieties were planted in May11th, 4th and 10th in the years 2014, 2015 and 2016 respectively. The studied genotypes were: GKTB-113, Kashmar, Khorshid, SKT133, SKSH249, BC244, SKN2739, NSK847, Sahel and Varamin.

The combined analysis of three years of the study showed that the genotype BC244 produced the highest number of monopodial branches. Also, the number of nodes and plant height of this genotype was higher than the others. Genotype SKT133 was superior to others in number of sympodial branches and was placed in same statistical group as Varamin in terms of vegetative traits. Seed yield, mean of boll weight and boll number in the genotype GKTB113 were the highest among the all genotypes. Plant height and height to node ratio of this genotype was similar to Varamin and Sahel, which placed it in the same statistical group. The genotypes were classified into three groups based on Ward's method of clustering for all the investigated traits. Because of climatic and management conditions, early maturing is not the priority for some farmers in the region. Therefore, the genotype GKTB113 with producing the highest yield was found to be superior and adaptable to Garmsar conditions.

Results displayed considerable differences among hopeful cotton genotypes for the studied characters. Boll number plant-1 and boll weight were found as major yield components to have positive correlation with seed cotton yield. However, plant height was noticed negatively correlated with yield. Due to the higher yield and good vegetative characteristics of GKTB113, its introduction as a new variety will expand cotton farmer’s variety choice options. For late cropping, genotypes GKTB113, Khorshid and Kashmar are recommendable (respectively) because of their proportional earliness, seed cotton yield and yield stability.