scholarly journals Genetic diversity reveals synergistic interaction between yield components could improve the sink size and yield in rice

2022 ◽  
Author(s):  
Khalid Anwar ◽  
Rohit Joshi ◽  
Alejandro Morales ◽  
Gourab Das ◽  
Xinyou Yin ◽  
...  
2014 ◽  
Vol 67 (1) ◽  
pp. 125-137 ◽  
Author(s):  
Akbar Marzooghian ◽  
Mohammad Moghaddam ◽  
Mostafa Valizadeh ◽  
Mohammad Hasan Kooshki

AbstractEvaluation of the genetic diversity present within species is essential for conservation, management and utilization of the genetic resources. The objective of this study was to evaluate genetic variability of 70 common bean genotypes for seed storage proteins, grain morphological characteristics and agronomic traits. Two methods of extracting soluble seed proteins in salt were used.Positive correlations were observed among both seed morphological characters and developmental characters while yield components showed negative correlations with each other. Factor analysis for agronomic and grain morphological traits resulted in three factors were named yield components, seed morphology and phenology, respectively. Most genotypes had lower or medium scores for yield components and phenology factors. Considerable diversity was observed for seed morphology factor among the common bean genotypes.Nei’s diversity coefficient (He= 0.4), effective number of alleles (Ae= 1.69) and number of polymorphic loci (N = 17) indicated larger variation in the extraction method of soluble proteins in low salt (0.2 M NaCl) than high salt (1 M NaCl) condition. Considering that the centers of diversity for common bean are different in seed size, the result of Gst statistics showed that bands with relative mobility of 30, 32, 38 and 40 differentiated two weight groups more than other bands. Furthermore, significant differences were observed between these bands for number of pods per plant and number of seeds per plant.


2019 ◽  
Vol 11 (30) ◽  
pp. 188-197
Author(s):  
Zeinab Taghizadeh ◽  
Hossein Sabouri ◽  
Hossein Hosseini Moghaddam ◽  
Hossein Ali Fallahi ◽  
Mahnaz Katouzi ◽  
...  

2020 ◽  
Vol 9 (1) ◽  
pp. 73-77
Author(s):  
Hasriadi Mat Akin ◽  
Emi Lidya Astri ◽  
Maimun Barmawi

Segregation pattern of the Soybean Stunt Virus resistant character and genetic diversity of F2:3 families derived from crosses between Orba and B3570.  Soybean stunt disease caused by SSV (Soybean Stunt Virus) is the most destructive soybean disease in Indonesia. This research was conducted from October 2005 to June 2006 at experiment station of Lampung University.  The aims of this research were to evaluate the segregation of resistant characters and total genetic diversity of eight populations of F2:3  families. Experiment was arranged in a randomized complete block design with three replications. The resistance was evaluated based on the score of disease severity.  The results showed that the resistant characters segregate 1:2:1 to susceptible, moderately resistant, and resistant, respectively based on  the segregation pattern. The resistant character was controlled by single gene and the action of the gene is noncompletely dominant gene.  Eight populations of F2:3 families have high diversities on the yield and yield components.


2019 ◽  
Vol 41 (1) ◽  
Author(s):  
Alberto Miele ◽  
Luiz Antenor Rizzon

Abstract It is known that rootstock can induce changes on grapevine yield components and on the physicochemical composition of musts and wines. However, its effect on the sensory characteristics of wines has been scarcely studied. For this reason, an experiment was conducted to determine the effect of 15 rootstocks on the sensory characteristics of Cabernet Sauvignon wine, whose grapevines were grafted on Rupestris du Lot, 101-14 Mgt, 3309 C, 420A Mgt, 5BB K, 161-49 C, SO4, Solferino, 1103 P, 99 R, 110 R, Gravesac, Fercal, Dogridge and Isabel, which feature some genetic diversity altogether. The experimental design was in randomized blocks, with 15 treatments, three replicates, 10 vines per plot. Mature grapes were harvested, and wines were made in 20-L glass recipients. When alcoholic and malolactic fermentations were finished, the wines were bottled and stored at 18°C. Sensory analysis was performed in the next year, following international procedures. The tasting panel was formed by 12 experienced enologists, who evaluated the wines in individual cells separated by opaque glass. They were served monadically and the perception of each taster was recorded in 9-cm unstructured scale sheets. Twenty-two variables were evaluated, which were related to the visual, olfactory and taste aspects. The results show that the tasting panel was not able to detect significant differences (p> 0.05) of rootstocks in any variable related to the sensory characteristics of Cabernet Sauvignon wine.


2018 ◽  
Vol 15 (2) ◽  
pp. 265-274
Author(s):  
Mehdi Mahmoudi ◽  
Habibollah Ghazvini ◽  
Ali Barati

The study of the relationships between the yield components can help to understand the physiological basis of crop yields. This research was conducted to investigate the genetic diversity of 168 Iranian wheat populations from the aspect of morpho-physiological characteristics in the Grain and Plant Improvement Institute research center in Karaj. In order to calculate the error and correct the collected data, four wheat cultivars of Sivand, Pishtaz, Pishgam, and Sirvan with three replications were used as control groups. The control group was cultivated based on augmented design and genotypes were placed in separate blocks among the control groups. The treatments and control groups were divided into three blocks and each block containing 60 plots which were planted on one-meter beds and the spacing between each plot from other plot was considered 62 cm. The necessary measurements and samples of the movement were collected systematically and by observationally method and sampling from the statistical population of each plot. Data analysis, statistical analyzes of multivariate data including cluster analysis based on multivariate analysis such as principal component analysis (PCA) and simple correlation analysis between characteristics (Pearson) are done using statistical software SPSS and SAS.


2018 ◽  
Vol 18 (2) ◽  
pp. 256
Author(s):  
Satendra Kumar Yadav ◽  
Mukesh Kumar ◽  
S.K. Singh ◽  
Vinay Kumar ◽  
Vipin Kumar ◽  
...  

2018 ◽  
Vol 12 (12) ◽  
pp. 1820-1828
Author(s):  
Élcio Friske ◽  
◽  
Adilson Ricken Schuelter ◽  
Ivan Schuster ◽  
Jonatas Marcolin ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document