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Research Detail

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K. Nahar
Biotechnology Division, BARI, Joydebpur, Gazipur

F. Ahmed
Biotechnology Division, BARI, Joydebpur, Gazipur

M. R. Ahmad
Biotechnology Division, BARI, Joydebpur, Gazipur

M.A.Y. Akhond
Biotechnology Division, BARI, Joydebpur, Gazipur

Salinity is a major constraint for agricultural productivity. The current study was designed to explore the variations and determine the performance of target traits to identify salt-tolerant sorghum genotypes under saline conditions. Leaf number, shoot length, fresh shoot and root weight, dry shoot and root weight of 12 sorghum genotypes were evaluated under control and saline conditions. Two-factor factorial analysis of variance revealed that genotypic and treatment effects were highly significant for all the studied traits. Genotype into treatment interaction (G×T) was highly significant for shoot length, fresh shoot weight, fresh root weight and dry root weight. Principal component analysis was conducted for both treatments separately. PCA converted the six traits into six different factors or components and only two (PC1 and PC2) factors had eigenvalue greater than 1, in the Control treatment and only one (PC1) factor had an eigenvalue greater than 1, in salt stress treatment. First, one factor (PC1) contributed 65.85% and 77.61% cumulative variability in control and salt stress treatment respectively. Based on mean performance, principal component analysis and biplot graphs G2, G4, G7 and G12 were better performers and G3, G5, G6, G10 were poor performers under salt stress conditions. Better performing genotypes would be a good source of salt-tolerant genes for the development of salt-tolerant crop variety.

  Greenhouse, salt tolerance, Drought tolerance, Wild species
  
  00-00-2020
  00-00-2020
  Variety and Species
  Soil salinity, Drought

The objective of this study was to screen sorghum genotypes for salt tolerance during the pre-anthesis stage.

This study was carried out in the greenhouse of the Biotechnology Division, BARI from March-May 2020. A total of 12 sorghum genotypes were collected and planted in a plastic pot (20x14 cm). Pots were arranged using a complete randomized design with three replicates and pots were filled with 4 kg sandy loam soil. Two salinity treatments were applied 1) T0=control: irrigated with normal water and 2) T1=saline: irrigated with the salt solution with EC 5 ds/m. The amount of water added to bring the soil to field capacity was determined on a soil weight basis (w/w). Salinity was imposed at a three-leaf stage of the plant. Irrigation was provided on alternate days up to 66 days after sowing (DAS) and every day at later stages of growth to replace evapotranspirational losses and bring soil moisture levels to field capacity. The water needed for these subsequent irrigations was determined by daily weighing of ten representative pots, to avoid waterlogging or deficit in the pots. Ten seeds of each genotype were sown in each pot in three equally spaced hills. A maximum of three plants per pot was retained after thinning at 10 DAS. Three plants per pot were sampled at 68 DAS when the salinity reached twelve ds/m. The harvested plants were separated into the root (extractable) and shoot, dried in a hot air draught oven at 600C for 3 days and the dry weights were recorded. The experiment was terminated at 68 days after planting when the stover of the plant was harvested. To minimize breakage during data collection, soil in the pots was softened by watering and roots were carefully removed and washed gently under a flowing tap. Data were recorded on a number of leaves, fresh shoot weight (g), fresh root weight (g), shoot length (cm), shoot dry weight (g), root dry weight (g). The EC of the salt solutions and soil was measured directly using a conductivity meter. Two-factor factorial analysis of variance was computed to estimate the significance of genotypic differences for each studied trait (Steel and Torrie, 1984; Steel et al, 1997). Data recorded for different morphological traits were statistically analyzed by using principal component analysis (Sneath and Sokal, 1973). The principal component analysis is defined as “a method of data reduction to clarify the relationship between two or more characters and to divide the total variance of the original characters into a limited number of uncontrolled new variables”. Biplot graph on the basis of principal component analysis was used for estimation of association among different salt tolerance indices. Correlation between variables is described as angle between vectors; acute angle (<90°) showed positive correlation, acute angle (<45°) showed strong positive correlation, right angle (=90°) showed independence or no correlation, obtuse angle (>90°) showed negative correlation and obtuse angle of >135° & <180° showed a strong negative correlation.

  Annual Research Report 2019-2020, Biotechnology Division, BARI, Joydebpur, Gazipur
  
Funding Source:
1.   Budget:  
  

A two-factor factorial analysis of variance was conducted for data of studied traits. Genotypic and treatment effects were found highly significant for all the studied traits. Genotype into treatment interaction (G×T) was highly significant for shoot length, fresh shoot weight, fresh root weight and dry root weight. Principal component analysis was conducted for both treatments separately. PCA converted the six traits into six different factors or components and only two (PC1 and PC2) factors had eigenvalue greater than 1, in the Control treatment and only one (PC1) factor had an eigenvalue greater than 1, in salt stress treatment. First, one factor (PC1) contributed 65.85% and 77.61% cumulative variability in control and salt stress treatment respectively. All studied traits contributed negatively for PC1 under both treatments except shoot length which had a positive contribution under control treatment. Fresh root weight had a positive contribution for PC1 under both treatments and dry root weight had a positive contribution for PC2 under salt stress. Shoot length and fresh shoot weight positively contributed to PC2 under control treatments. Biplot graphs were made by using PC1 and PC2 of principal component analysis for both treatments separately. Length of vector and cosine of angle was used for grouping of traits into different groups. These groups showed similar performance for discrimination of genotypes. Biplot categorized the traits into two groups under control and salt stress treatment. In control treatment Group-3 had shoot length, fresh shoot weight, fresh root weight and Group-4 had dry shoot weight, dry root weight and leaf number. Within the group, traits had a strong positive correlation with each other but among groups, traits had very weak positive and negative correlation. In salt stress treatment Group-3 had fresh root weight, dry root weight Group-4 had fresh shoot weight, dry shoot weight, shoot length and leaf number. Within the group and among the groups traits had a very positive correlation under salt stress treatment. Length of vector showed the discrimination power of trait for differentiation of genotypes. Traits with longer vector and shorter cosine of the angle with other traits showed the strength of correlation between traits. Under both treatments, all the traits had longer vector and shorter cosine of angle which showed the high discrimination power of these traits which showed that these traits should be used for evaluation of sorghum genotypes in this study. The eigenvalue is a very important criterion for the selection of principal factors and 1 is used as the cut-off value for the selection of principle factors. Eigenvalue >1 showed that the factor accounts for more variance than one of the original variables. In the current study, one factor (PC1) has an eigenvalue greater than one and only this factor is duly important under salt treatment. Shoot length, fresh root and shoot weight, dry root and shoot weight were extensively used by scientists for the evaluation of Sorghum. These traits were having significant variation among sorghum genotypes under salt stress.

Genotypes that were present away from the origin in the positive direction of discrimination traits showed their better performance whereas, genotypes that were farther away from the origin in the negative direction of traits showed their poor performance. G2, G4, G7 and G12 were better performers and G3, G5, G6, G10 were poor performers under salt stress treatment. Better performing genotypes could be used as a source of stress-tolerant genes for the development of stress-tolerant transgenic crop variety.

  Report/Proceedings
  


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