Plant Productions

Identification of superior genotypes of barley for cultivation in the south regions of Fars province using MGIDI و FAI-BLUP indices

Hassan Zali; Alireza Pour-Aboughadareh

Volume 46, Issue 3 , December 2023, , Pages 335-351

https://doi.org/10.22055/ppd.2024.45295.2134

Abstract

IntroductionBarley (Hordeum vulgare L.) has been known as one of the most adapted cereal crops to various environmental conditions. In addition, this cereal crop ranks fourth in the ... Read More IntroductionBarley (Hordeum vulgare L.) has been known as one of the most adapted cereal crops to various environmental conditions. In addition, this cereal crop ranks fourth in the world in terms of economic importance after wheat, rice, and corn. Identification of high-yielding genotypes with highly desirable growth traits is one of the most important goals in barley breeding programs. However, the present study aimed to select superior genotypes based on grain yield and some morpho-phenological traits using different selection models. Materials and methodsTo identify superior genotypes of barley for cultivation in the warm and dry conditions in the southern regions in the Fars province, 21 genotypes were investigated in a randomized complete block with three replications during the 2021-2023 cropping seasons. During the plant growth and development, several morpho-phenological traits were recorded. Agronomic traits measured were days to spike emergence (DHE), days to maturity (DMA), plant height (PLH), grain filling period (GFP), grain yield (GY), 1000-kernel weight (TKW), spike length (SL), spike density (SD), awn length (AL), spike weight (SPW), number of grains per spike (NGS), row type (RT) and number of spikes per m2 (NS). After collecting experimental data, statistical analyses were computed using SAS and R softwares Results and DiscussionResults of the analysis of variance (ANOVA) showed that there is a significant difference among the investigated genotypes in terms of all the measured traits (except for Awn length and spike length). Based on the multi-trait genotype-ideotype distance index (MGIDI), genotypes G1 (Oxin), G7, G3, and G14 with the lowest values were identified as superior genotypes. Moreover, the ideotype design via the best linear unbiased prediction (FAI-BLUP) model identified genotypes G20, G8, G2 (Golchin) and G1 (Oxin) as the desirable genotypes compared with other genotypes. The Venn diagram revealed that genotypes G1 and G7 were selected using both selection indices, simultaneously. The MGIDI index showed a positive and significant correlation with DHE (0.58**), while it negatively and significantly correlated with GFP (-0.51*) and GY (-0.74 **). The FAI-BLUP index showed a significant positive relationship with SL (0.50 *) and SPW (0.45*), while it negatively and significantly correlated with DHE (-0.47 *). To better evaluate and group the investigated genotypes, principal components analysis (PCA) was used. Results of the PCA showed that the first and second principal components explained 30.5 and 20.6 percent, respectively. Moreover, the results of the PCA showed that the selected genotypes based on MGIDI and FAI-BLUP indices are located in the 1st and 2nd regions of the PCA diagram. In total, the results showed that there is a relative compliance between the MGIDI and FAI-BLUP indices with PCA. Additionlly, there was a high agreement between the MGIDI indices and the first principal component, and on the other hand, the second principal component showed a high agreement with the FAI-BLUP index. ConclusionIn conclusion, the genotype G7 with the highest grain performance and the relative superiority in terms of MGIDI and FAI-BLUP indices was identified as a superior genotype compared to all reference genotypes. Hence, this genotype can be recommended for further comprehensive evaluation before commercial release in the southern regions in Fars province.

Genotype- environment interaction analysis and selection of sugar beet stable genotypes in terms of white sugar yield using AMMI model

Dariush Taleghani; Abazar Rajabi; Ali Saremirad; shahram khodadadi

Volume 46, Issue 2 , September 2023, , Pages 155-169

https://doi.org/10.22055/ppd.2023.43177.2089

Abstract

Introduction The methods used to analyze genotype-environment interaction and determine the stability and adaptability of genotypes are continuously evolving to improve the accuracy ... Read More Introduction The methods used to analyze genotype-environment interaction and determine the stability and adaptability of genotypes are continuously evolving to improve the accuracy of evaluating genotypes and studying environmental interaction components. Using a combination of several methods provides a more comprehensive understanding of the genotype-environment interaction from multiple dimensions. In this study, the genotype-environment interaction was investigated using the AMMI method, along with the development of appropriate statistical techniques. Materials and Methods For this purpose, 25 sugar beet genotypes, consisting of 18 new hybrids and seven controls, were cultivated in seven environments: Karaj, Mashhad, Shiraz, Miandoab, Kermanshah, Hamadan, and Khoi. The experiment followed a randomized complete block design with four replications during the year 2020. After checking the uniformity of the variance of the experimental errors using Bartlett's test, the stability of the genotypes was analyzed based on the AMMI model. In this study, 12 statistics obtained from the AMMI model, including ASTAB, ASI, ASV, AVAMGE, DA, DZ, EV, FA, MASI, MASV, SIPCi, and Za, were used to identify stable genotypes. To further investigate the stability of the experimental genotypes, the SIIG index was also estimated, taking into account the criteria provided by each index based on the AMMI model. Results and Discussion The results obtained from Bartlett's test confirmed the homogeneity of the variance of experimental errors in experiments from different regions. Therefore, a combined variance analysis was performed based on the AMMI model. The combined analysis of variance, based on the AMMI model, indicated the significance of the additive effects of the environment and genotype, as well as the multiplicative effect of genotype-environment interaction at the 1% probability level. Analyzing the interaction effects into principal components showed that the first four components were significant at the 1% probability level and explained 93.50% of the variations related to genotype-environment interaction. According to the AMMI1 biplot, hybrids 3 and 9 were recognized as the most stable genotypes due to having a sugar yield higher than the overall average and a low value of the first interaction component. According to the AMMI2 biplot, hybrid 3 and BTS 335 with the Miandoab environment, Lexia and 4 with the Mashhad environment, Lexia with the Hamedan environment, 14 and 15 with the Kermanshah environment, 13 and 17 with the Shiraz environment, 11 with the Karaj environment, and Baloo with the Khoi environment have considerable specific adaptability. Hybrid 9, followed by 6, 2, and 8, had general adaptability. The SIIG index, calculated based on AMMI model statistics, identified 2, 9, 10, and 8 as the most stable genotypes with optimal yield. Conclusion Based on the obtained results, the environment and its interaction with the genetic structure of different genotypes have played a significant role in the phenotypic expression of white sugar yield and have caused the genotypes to provide different responses in terms of white sugar yield according to the conditions of different environments. In general, based on the results of the present study, hybrid 9 and then hybrids 6, 2, 8, 7, and 10 had high white sugar yield and yield stability. Generally, real progress in sugar beet breeding will be obtained if the genetic factors controlling the sensitivity of sugar beet genotypes to a variable environment are identified.

Evaluation of phenotypic diversity of cumulative growing degree-days (GDD) and grain yield in spring wheat cultivars under optimal and zinc deficiency conditions

Nasrin Valipour; Hadi Alipour; Reza Darvishzadeh

Volume 46, Issue 1 , June 2023, , Pages 65-78

https://doi.org/10.22055/ppd.2022.39617.2003

Abstract

IntroductionBread wheat is the first grain and the most important annual crop in the world. Like other crops, wheat faces many environmental constraints such as a lack of trace elements ... Read More IntroductionBread wheat is the first grain and the most important annual crop in the world. Like other crops, wheat faces many environmental constraints such as a lack of trace elements during its growth period. Zinc deficiency is a common micronutrient disorder in wheat-growing areas of the world. The growing degree-days (GDD) index is reliable compared to the time calendar due to its stability. These indices are important for comparing genotypes whose physiological developmental stages do not match. Temperature is an important meteorological variable in the study of plant growth and development processes and therefore its study on short time scales leads to a more accurate estimate of thermal need due to the relatively wide range of temperature changes in different phenological stages, setting the planting date. Studying the effect of temperature on wheat genotypes should be based on sufficient time and temperature to complete the phenological stages in which grain yield components are formed. Materials and MethodsTo study the phenological stages, cumulative growing degree-days, and grain yield and its components in 64 spring wheat cultivars under optimal and zinc deficiency conditions, a study was conducted in the 2019-2020 cropping season based on a simple lattice design in the research field of Urmia University, Iran. Phenological stages include the number of days to germination, the number of days to booting, the number of days to pollination, the number of days to physiological maturity, and the grain filling period with their GDDs during the growing season in each pot based on 50% of the samples were determined to have reached the relevant vegetative stage. In addition to phenological stages along with the number of grains per spike, thousand-grain weight, and grain yield were examined. Results and DiscussionAnalysis of variance revealed that there is a statistically significant difference among all cultivars in terms of all studied traits except the number of days to pollination under optimal and zinc deficiency conditions. According to the results of descriptive statistics, grain yield, the number of grains per spike, and thousand-grain weight decreased and phenological traits increased under zinc deficiency conditions compared to optimal conditions. Among phenological traits, not only the number of days to spike showed relatively high variability but also had a significant relationship with grain yield under zinc deficiency based on the results of correlation and regression analyses. The factor analysis showed that under optimal conditions, the first four components explained 87.81 percent of the total variation, so that the contribution of the first to fourth components were 38.38, 21.52, 15.88, and 12.3 percent. Under zinc deficiency stress conditions, the first five components explained 95.68 percent of the total variation, so that the first to fifth components explained 34.62, 18.48, 17.51, 14.66, and 10.40 percent, respectively. Cluster analysis classified all spring wheat cultivars into three and four clusters under optimal and zinc deficiency stress conditions. ConclusionBased on the results of cluster analysis under optimal and zinc deficiency stress conditions, Neishabour, Golestan, and Gahar cultivars were identified as desirable and tolerant cultivars that can be used in future breeding programs. The results of cluster analysis were confirmed by results of canonical discriminant function results

Evaluation of yield stability of flue cured tobaccos using some univariate and multivariate stability statistics

Naghi Hosseinzadeh Fashalami; Roghayeh Aminian; Habibollah Samizadeh

Volume 45, Issue 3 , December 2022, , Pages 311-321

https://doi.org/10.22055/ppd.2022.40945.2037

Abstract

IntroductionThe genotype × environment interaction is one of the most important factors in limiting breeding programs. The compatibility of a given genotype determines its ability ... Read More IntroductionThe genotype × environment interaction is one of the most important factors in limiting breeding programs. The compatibility of a given genotype determines its ability and genetic capacity to produce high production and yield stability in different environments. Therefore, it is necessary to study the genotype × environment interaction in order to introduce stable genotypes in different environments. The current research was carried out to determine the compatibility and stability of yield for 10 tobacco genotypes and estimate the most stable genotype for tobacco growing areas in Iran (i.e. Guilan, Mazandaran and Golestan provinces). Materials and MethodsIn this study, 10 male sterile flue cured tobacco genotypes, which they completely tested in terms of quality and taste, including 7 internal modified hybrids named RVH5, RVH6, RVH8, RVH27, RVH30, RVH48, RVH70 along with 3 imported genotype DVH2101, PVH19 and NC100 in 6 tobacco growing regions of Guilan, Mazandaran and Golestan in two years of experiment (2018-2019). In total, 12 environments were studied in a randomized complete block design with 3 replications. Combined analysis was performed by considering the environments as a random factor and genotypes as a fixed factor. Then the stability analysis of genotypes was done by 10 stability statistics and the first 3 components of AMMI (Additive Main effects and Multiplication Interaction) analysis including IPCA1, IPCA2 and IPCA3. Analysis of variance was done using SAS.9 software, AMMI analysis and related graphs were performed using IRRISTAT software. Results and DiscussionThe results of combined analysis of variance showed that the effect of location and year × location interaction, the effect of genotype and genotype × year × location interaction were significant at the 1% probability level for yield. Genotype × environment interaction analysis using the first three main components of the AMMI analysis justified 69.47% of the total variance. The lowest coefficient of variation was related to DVH2101 and RVH27 genotypes. RVH30, RVH27 and RVH8 genotypes were selected as the most stable genotypes. According to Rick equivalence and Shoklaʹs stability variance parameters. The least squares deviation from the regression line were related to RVH27, RVH30 and RVH8 genotypes. In terms of regression coefficient, RVH27, RVH30 and DVH2101 genotypes had a line slope close to 1. Based on the coefficient of determination and Jenkins and Perkins statistics, RVH27, RVH30 and RVH8 genotypes were in the same rank in terms of stability. RVH27 and RVH30 were the most stable genotypes with superiority index. RVH27, RVH30 and DVH2101 genotypes were selected as the most stable hybrids based on the AMMI first model due to their proximity to the plot center, low interaction and high yield. Based on the second model of AMMI analysis, RVH27 and DVH2101 genotypes were selected as stable genotypes. In the third AMMI model, the RVH27 genotype was selected as the stable genotype due to its closeness to the biplot center and high yield. ConclusionConsidering most of the stability statistics and AMMI analysis, the most stable genotype was RVH27 hybrid. RVH30 and DVH2101 hybrids were placed in the next categories of stability. In addition, genotypes RVH6 and NC100 showed high private compatibility to Tirtash tobacco growing area and genotype RVH27 to Rasht region.

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Keywords = Biplot

Identification of superior genotypes of barley for cultivation in the south regions of Fars province using MGIDI و FAI-BLUP indices

Abstract

Genotype- environment interaction analysis and selection of sugar beet stable genotypes in terms of white sugar yield using AMMI model

Abstract

Evaluation of phenotypic diversity of cumulative growing degree-days (GDD) and grain yield in spring wheat cultivars under optimal and zinc deficiency conditions

Abstract

Evaluation of yield stability of flue cured tobaccos using some univariate and multivariate stability statistics

Abstract