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Genetic Variability, Heritability and Genetic Advance of Yield and Yield Related Traits of Food Barley (Hordeum vulgare L.) Genotypes in Mid Rift Valley of Ethiopia

Temesgen Dinsa1*, Firew Mekbib2 and Tesfaye Letta3
1Adami Tulu Agricultural Research Center, PO Box 35, Ziway, Ethiopia
2Haramaya University College of Agriculture and Environmental Science, PO Box 138, Dire Dawa, Ethiopia
3Oromia Agricultural Research Institute, PO Box 81262, Addis Ababa, Ethiopia
*Corresponding Author: Temesgen Dinsa, Adami Tulu Agricultural Research Center, PO Box 35, Ziway, Ethiopia, Tel: +251917096403, Email: temesgendinsa@gmail.com

Received: 06-Sep-2018 / Accepted Date: 22-Oct-2018 / Published Date: 30-Oct-2018 DOI: 10.4172/2329-8863.1000401

Keywords: Genetic advance; Food barley; Genotypes; Grain yield; Heritability

Introduction

Barley (Hordeum vulgare L.) is the most ancient food crops in the world and it is an important cereal crop since the early stages of agricultural innovations 8,000-10,000 years ago [1]. In Ethiopia, it is produced mainly for human consumption as one of the most important staple food crops. Its grain is used for preparing a diversity of recipes and is deeply rooted in the culture and tradition of people's diets. The recipes are prepared in different forms of indigenous food and homemade beverages [2]. Food barley production is 20, 249, 21.68 and 146, 46.502 tons in Ethiopia and East Shewa zone, respectively [3]. More than 85% of the total production comes from the major barley growing regions, which include Wello, Shewa, Arsi, Gojam, Bale, Gondar and Tigray. Earlier studies on the diversity of Ethiopian barley shows, that most of the variation was due to differences among characters and only a relatively small fraction was due to differences between regions. And almost all characters are considerably influenced by altitude within the regions. There was shortage of improved barley varieties adapted to low-moisture stress areas of Ethiopia. Hence farmers are forced to grow low yielding genotypes.

Variability is occurrence of differences among individuals due to differences in their genetic composition or environment in which they are raised [4]. Phenotypic variability is the observable variation present in a character in a population; it includes both genotypic and environmental variation. Genotypic variability, on the other hand, is the component of variation, which is due to the genetic differences among individuals within a population [5]. Identification of superior genotype by selection is dependent on existence of reliable genetic variability. Heritability is a measure of the value of selection for particular characters and an index of their transmissibility [6]. It plays a predictive role in breeding, expressing the reliability of phenotype as a guide to its breeding value. The expected response to selection is also called genetic advance (GA). High genetic advance coupled with high heritability estimates offers the most effective condition for selection.

Genetic improvement of crop is largely depending on the scale of genetic variability and the degree to which desired traits are inherited [7]. The presence of genetic diversity and the relationship among various yield and yield related traits and their heritability is essential in identifying possible genotypes for forthcoming crop variety development [8]. Apart from simple screening of these introduced barely germplasm, detail study of their variability and genetic advance are important to enhance gain in barely breeding program. However, this kind of study was not yet conducted in the Mid Rift Valley of Ethiopia. Hence, the present study was designed with the objectives of: To estimate the level of genotypic and phenotypic variability of food barley genotypes.

Materials and Methods

The experiment was conducted at Adami Tulu Agricultural Research Center of Oromia Agricultural Research Institute (OARI) under rain-fed condition during the 2017/18 cropping season. It located at a latitude of 7°9'N and longitude of 38°7'E. It has an altitude of 1650 m.a.s.l, and it receives a bimodal unevenly distributed average annual rainfall of 760.9 mm per annum [9]. The long-term mean minimum and maximum temperatures are 12.6°C and 27°C, respectively. The soil is fine sandy loam in texture with the soil type of sand, clay and silt in proportion of 34%, 48% and 18% respectively and a pH of 7.88 [9].

Experimental materials

In the present study, a total of 22 food barley genotypes were used along with three standard checks. Twenty-two of them were advanced genotypes and screened by Sinana Agricultural Research Center.

Experimental design and management

The experiment conducted in 5 × 5 Triple Lattice Design with three replications.

The treatments were planted on a plot size of 1.2 m × 2.5 m. The space between plant, plots and blocks were 0.2 m, 0.5 m and 1 m respectively. DAP 150 kg/ha fertilizer was applied during planting and the seed rate used was 125 kg/ha and sown by hand drilling. For data collection, the middle four rows were used. All management practices including weeding were performed uniformly to the entire plot according on the local recommendation (Table 1).

S No Genotypes/Code Origin Pedigree
1 G1 Ethiopia Acc#244906
2 G2 Ethiopia Acc#244919
3 G3 ICARDA SHEMIAL NO.3/MSEL
4 G4 ICARDA VMORALES
5 G5 ICARDA LIMON/BICHY2000/4/ALELI/3/ARUPO/K8755//MORA/5/MSEL
6 G6 ICARDA CHAMICOO/M111
7 G7 ICARDA FNCI/3/LEGACY//PENCO/CHEVRON-BAR
8 G8 ICARDA P.STO/3/LBIRAN/UNA80//LIGNEE640/4/BLLU/5/PETUNIA1/6/LEGACY// PENCO/CHEVRON-BAR
9 G9 ICARDA P.STO/3/LBIRAN/UNA80//LIGNEE640/4/BLLU/5/PETUNIA1/6/LEGACY//PENCO/CHEVRON-BAR
10 G10 ICARDA CABUYA/M111/7/TRADITION/6/P.STO/3/LBIRAN/UNA80//LIGNEE40/4/BLLU/5/PETUNIA
11 G11 ICARDA SHYRI/GRIT//FNC1
12 G12 ICARDA P.STO/3/LBIRAN/UNA80//LIGNEE640/4/BLLU/5/PETUNIA1/6/CHNGADU 89//PENCO/CHEVRON-BAR/3/CHAMICO/TOCTE/CONGONA
13 G13 ICARDA CANELA/C14196
14 G14 ICARDA LIGNEE27/GARBEL/3/BOY-B*2/SURB//C12225.2D/4/GLORIA-BAR/COM
15 G15 ICARDA SVANHALS-BAR/MSEL//AZAF/GOB24DH/3/DEFERA/DESCONNCIDA-BAR
16 G16 ICARDA LIGNEE 27/ GERBEL /3/BOY-B*2/SURB //C12225.2 D/4/ GLORIA-BAR/COM
17 G17 ICARDA LIGNEE27/GARBEL/3/BOY-B*2/SURB//C12225.2D/4/GLORIA-BAR/COM
18 G18 ICARDA LIGNEE 27/ GARBEL /3/ BOY-B*2/ SURB//C 12225.2 D /4/ GLORIA-BAR/COM
19 G19 ICARDA FRES/M1004
20 G20 ICARDA FRES/LEGACY
21 G21 ICARDA SEN/5/LEGACY/4/TOCTE//GOB/HUMAI10/3/ATAH92/ALELI
22 G22 ICARDA PUEBLA/CORDO//TOCTE/3/FALCON-BAR
23 Gobe - Released Variety
24 Bentu ICARDA Released Variety
25 Robera Ethiopia Released Variety

Table 1: Lists of barely genotypes used in the study along with their origins and Pedigree. Source: Sinana Agricultural Research Center. Note: G1-G22=Genotypes used for study.

Data collection

Plant height (cm): Was measured as the height in centimeter from the soil surface to the tip of spike excluding the awn at maturity and expressed as an average of randomly taken ten plants per plot.

Peduncle length (cm): Length of the peduncle in centimeter from the node to the tip of the peduncle as the average of ten randomly taken plants from the central four rows of each plot.

Awn length (cm): Length of awn in centimeter from the end of the spike to tip of the awn.

Spike length (cm): Spike length of the main plant was measured in centimeter from base to the tip excluding the awns and expressed as the average of randomly taken ten plants in a plot.

Spikelet number per spike: Was recorded by counting the number of spikelet on each spike on the main tiller and expressed as the average of randomly taken ten plants in each plot.

Kernel number per spike: Was determined by counting the number of kernels produced on the main tiller of each plant and expressed as an average of randomly taken ten plants in each plot.

Days to first heading: Was recorded as the number of days from seedling emergence to the date on which first head was produced in the plots.

Days to heading: Was recorded as the number of days from seedling emergence to the date on which 75% of a plot has produced heads.

Days to maturity: Was recorded as the number of days from seedling emergence to the stage when 75% of a plot reached maturity.

Grain filling period: Was recorded as the number of days from days the date of heading to the date physiological maturity.

Number of effective tillers per m2: Numbers of tillers m-2 were counted in square meter frame area. Tillers was recorded by counting the number of tillers of 2.5-meter length in two central rows of each subplot and then converted to tiller m-2.

Biological yield (kg/ha): Was determined by weighing the total dried above ground biomass from the four central rows of each plot and expressed in kilogram per hectare.

Grain yield (kg/ha): Grain yield of the four central rows adjusted to 12.5% moisture content and expressed in kilogram per hectare.

Harvest index (%): Was calculated on plot bases from the four rows as the ratio of dry weight of the grain to the dry weight of the above ground biomass and expressed as a percentage.

Harvest Index=(Grain yield per plot)/(Above ground biomass per plot) × 100

Thousand kernel weights (g): Weight in gram of random samples of thousand seeds per plot adjusted to 12.5% moisture content.

Data analyses

Analysis of variance was done using Proc lattice and Proc GLM procedures of SAS version 9.0, [10] after testing the ANOVA assumptions. The difference between treatment means was compared using DMRT at 5% probability levels.

The model for lattice design is:

Yil(j)=μ+ti+rj+(b|r)l(j)+eil(j)

Where, Yil(j) is the observation of the treatment i (i=1, v=k2), in the block l (l=1, k) of the replication j (j=1, m); μ is a constant common to all observations; ti is the effect of the treatment i; rjis the effect of the replication j; (b|r)l(j) is the effect of the block l of the replication j; eil(j) is the error associated to the observation Yil(j), where eil(j)~N(0,s), independent.

Phenotypic and genotypic variability

The variability present phenotypic and genotypic variances and coefficient of variations were computed according to the methods suggested by Burton and Devane [11] as follows:

Genotypic variances2g)=(mg-me)/r

Where, σ2g=Genotypic variance, mg=genotypic mean square and σ2e=environmental variance (Error mean square).

Phenotypic variance2p)=σ2g+σ2e

Where, σ2g=genotypic variance, σ2e=Error variance, σ2p=Phenotypic variance.

Phenotypic coefficient of variation, Equation

Genotypic coefficient of variation, Equation

Where, x=population mean (Grand mean).

Estimate of heritability

Heritability (H2) in broad sense for measured characters was estimated using the formula developed by (Allard, 1960).

H2=(σ2g)/(σ2p) × 100

σ2p=σ2g+σ2e

Where, σ2g=genotypic variance, σ2p=phenotypic variance and σ2e=error variance.

Estimation of expected genetic advance

Genetic advance (GA) and genetic advance as percent of the mean (GA %) for each character were estimated using the formula developed by Johnson et al. [6] and Allard [4].

GA=(k) (σp) × (H2B)

GAM (as % of the mean)=[(GA)/X] × 100

Where, k=selection differential (k=2.06 at 5% selection intensity), σp=phenotypic standard deviation, H2=heritability (Broad sense), X=Grand mean.

Results and Discussion

The analysis of variance shown that there was highly significant (p ≤ 0.01) difference among the studied genotypes for days to first heading, days to heading, grain filling period, days to maturity, number of kernels per spike, plant height, spike length, awn length, grain yield, thousand kernel weight and harvest index. Significant (p ≤ 0.05) difference among genotypes was also observed for peduncle length. Similarly, Oettler et al. [12] reported significant differences in barley genotype for grain yield, spikes/m2, thousand kernel weight, dry matter, heading and plant height. However, the genotypes exhibited no significance difference for number of spikelet per spike, number of effective tillers and biological yield. In harmony to this result, Dawit et al. [13] reported no significant differences for biological yield and number of tillers per plant in durum wheat genotypes. Meseret [14] also reported no significant differences for biological yield, number of tillers per plant in food barley genotypes. The present findings indicated the existence of great variability among the tested genotypes for almost all characters measured, which could be exploited through selection, as variability with in populations is a basic requirement for plant breeding program on which selection depends to develop superior genotype for the studied area (Table 2).

Traits Mean Squares    
Genotypes (df=24) Replications (df=2) Error (df=36) Eff. (%) R2
Days to first flowering 33.58** 14.44* 4.11 97.45 0.88
Days to heading 52.61** 71.21** 9.22 99.84 0.85
Days to maturity 46.36** 9.45ns 7.69 106.5 0.87
Grain filling period 33.82** 29.32ns 9.99 110.35 0.78
Number of kernels per spike 168.73** 0.79ns 38.54 106.86 0.77
Number of spikelet per spike 18.52ns 50.20ns 17.53 108.25 0.51
Plant height (cm) 143.47** 37.62ns 58.35 103.98 0.73
Spike length (cm) 1.44** 0.54ns 0.58 113.98 0.68
Number of effective tiller per m2 27330.41ns 382135ns 20934 100.91 0.72
Peduncle length (cm) 24.02* 30.95ns 12.92 95.73 0.7
Awn length (cm) 2.14** 0.56ns 0.56 102.4 0.8
Grain yield (kg ha-1) 3006294.33** 932421ns 604639 116.54 0.8
Biological yield (kg ha-1) 5715842ns 11166.62ns 4814538.5 101.28 0.59
Thousand kernel weight 70.66** 12.84ns 14 100.45 0.8
Harvest index (%) 218.20** 35.10ns 50.24 114.01 0.79

Table 2: Mean square values from analysis of variance (ANOVA), coefficient of variation (CV), and coefficient of determination (R2) for 15 traits in 25 food barley genotypes grown at ATARC during the 2017/18 main cropping season. df=degrees of freedom, *,** and ns, significant at P ≤ 0.05, P ≤ 0.01 and non-significant, respectively, CV (%)=coefficient of variation, Eff.=Efficiency of Lattice design relative to RCBD.

Estimation for quantitative traits

Genotypes showed variation for days to first heading ranging from 36 to 53 and days to heading ranging from 46.67 to 64 days (Table 3). Bentu was early to mature followed by G20, G17, G18, Gobe, G16, G6, G14 and G14 while, G22, G1, G11, G12, G21 and G2, were late to mature (Table 3). The mean value of the genotypes for grain filling period was 38.88 days and ranged from 33 to 47 days. In general, the present result showed that there is a wide range of variations among the genotypes in crop phenology traits. Similarly, previous studies conducted on collection of barley landraces shown high genetic variation for days to heading [15] and days to maturity [16,17]. The mean value of thousand kernel weight of the test genotypes was 42.19 gram. Gobe, G13, G10 and Robera were the test entries that showed higher values for thousand kernel weight. In the present study, most of the genotypes had thousand kernel weight values below that of the standard check (Gobe), and hence in the target of improving this trait, the standard check (Gobe) should be used as a parent in crossing program.

Genotype DFH DH DM GFP NKPS NSPS PH SPL ET PL AL GY BY TKW HI
G-1 53.33a 64.33a 97.33ab 33h 30.67de 20.1 82.8a-d 8.4a-d 448.4 27.57a-e 11.067c-f 1296.2h 11046 33.06j 13.23g
G-2 49.67b 60.67ab 95abc 34.3fgh 41.1dc 20.7 89.1a 9.08abc 456.6 32.23a 11.58a-d 2194gh 12277 33.6ij 18.16fg
G-3 43.33cd 50.33efg 92.3bcd 42abc 56.76a 22.83 75.3a-g 7.02de 597.4 22c-g 11.28cde 5282.3a 12866 44.53b-f 41.65a-d
G-4 41.67def 50.33efg 89.67cd 39.3c-g 52.07abc 22.87 62.6g 7.22de 428.4 24.77b-g 10.65c-f 4015.7a-f 10016 44.53b-f 40.32a-d
G-5 41.67def 50efg 90.3dc 40.3b-f 52.77abc 23.4 80.1a-e 8.1b-e 630 28.6a-d 12.9a 4552.3a-e 11219 35.2hij 43.29abc
G-6 41.33defg 50efg 89d 39c-h 53.7ab 20.6 77.04a-g 6.99de 329.6 28.97a-d 11.92abc 4890.7abc 9832 40.67d-i 50.79a
G-7 43.67de 55cde 90.3cd 35.3d-h 42.2bc 22.87 67.06efg 6.94de 341.7 24.3b-g 11.03c-f 2633fgh 9550 45.6b-e 28.31edf
G-8 40.33efg 48.33fhg 90cd 41.67abc 53.3abc 23.6 85.9ab 7.8cde 598.2 29.13abc 8.85gh 5313a 12146 42.9b-g 43.27abc
G-9 45cd 51efg 89.67cd 38.67c-h 47.03abc 19.67 79.78a-e 8b-e 443.7 27.37a-e 9.7fg 4768.8a-d 11769 45.07b-f 40.35a-d
G-10 45cd 50.67efg 93.3a-d 42.67abc 53.9ab 22.07 78.4a-f 7.7cde 287 24.7b-f 10.9c-f 4595.5a-e 11762 48abc 39.48a-e
G-11 48bc 59.33abc 97ab 37.67c-h 54.03ab 21.46 83.14abc 8.1b-e 538.6 30.17ab 10.97c-f 4746a-d 13913 39.47e-j 34.05b-e
G-12 49.67b 58bcd 97ab 39c-h 49.8abc 18.5 86.19a 7.66cde 536.7 28.77a-d 11.45b-e 4509.8a-e 13343 39.73d-j 33.61b-e
G-13 44.67cd 52.33d-g 94.67abc 42.3abc 47.07abc 18.8 77.5a-g 9.3ab 578.1 25.57a-g 10.88c-f 4976.5ab 13143 49.2ab 37.74a-e
G-14 44.67cd 54c-f 89d 35e-h 48.23abc 21.2 67.92d-g 7.8cde 598.5 25.3a-g 10.68c-f 2933.8fg 11351 35.33hij 25.97ef
G-15 41.67def 50efg 91dc 41a-e 46.07abc 18.5 70.86c-g 7.89b-e 374.9 21.8d-g 10.63c-f 3419.2c-g 11419 40.93c-h 30.09c-f
G-16 41.33defg 50.33efg 88.67d 38.3c-h 56.63a 22.3 69.67c-g 7.52de 460.7 21.9d-g 10.6c-f 3810.8a-f 11644 36.67g-j 33.13b-e
G-17 44.33cd 51.33efg 88d 36.67c-h 50.3abc 20.8 65.91efg 7.66cde 383.5 22.27c-g 10.9c-f 2519.5fgh 9186 41.07c-h 27.81def
G-18 45cd 53.67c-f 88.3d 34.67fgh 47.2abc 23.9 63.8fg 7.7cde 467 19.33g 10.3def 2894.3fg 10061 44.53b-f 28.74def
G-19 45cd 56bcde 90cd 34gh 49.7abc 19.73 65.87efg 8.28a-e 392.2 20.1fg 9.9efg 3783.5a-f 9784 43.87b-g 38.54a-e
G-20 37.67gh 43.67hi 83.3e 39.67b-g 48.4abc 19.37 64.25fg 7.02de 342 20.03fg 10.62c-f 4786abc 10369 42.13b-h 46.68ab
G-21 43.67de 51.33efg 97ab 45.67ab 49.4abc 22.13 71.1b-g 9.6a 336.7 28.57a-d 10.67c-f 3248.8d-g 9832 47.07a-d 33.71b-e
G-22 42.33def 51efg 98a 47a 55.5a 20.63 77.4a-g 8.39a-e 460.3 27.07a-f 10.05efg 4955.3ab 11789 43.6b-g 45.79ab
Gobe 38.67fgh 47.33ghi 88.67d 41.3a-d 21.96e 23.13 65.16efg 7.19ed 619.8 25.37a-g 8.11h 4760.7a-d 10677 52.67a 44.64ab
Bentu 36.33h 42.67i 76.67f 34gh 47.6abc 18.9 62.57g 7.4de 259.4 21.33efg 10.26def 3132.2efg 6966 37.73f-j 45ab
Robera 43.33de 52.67defg 92bdc 39.3c-g 41.3dc 21.76 76.8a-g 6.86e 461.1 27.97a-e 12.68ab 3647.5b-g 13148 47.6abc 28.01def
DMRT(5%) ** ** ** ** ** NS ** ** NS * ** ** NS ** **
Mean 43.64 52.17 90.05 38.88 47.87 21.65 73.85 7.83 454.8 25.4 10.74 3906.63 11166 42.19 35.69
CV   4.65 5.82 3.05 8.13 12.96 19.32 10.34 9.74 27.81 14.15 7.07 19.9 19.64 8.86 19.86

Table 3: Mean performance of 12 quantitative traits for 25 food barley genotypes tested at Adami Tulu Agricultural Research Center in 2017. G1- G22=Genotypes used for study, DFH=Days to first heading, DH=Days to heading, DM=Days to maturity, GFP=Grain filling period, NKPS=Number of kernel per plant, NSPS=Number of spikelet per spike, PH=Plant height (cm), SPL=Spike length (cm), ET=Effective tiller per meter square (m2), PL=peduncle length (cm), AL=Awn length (cm), GY=Grain yield (kg), BY=Biological Yield (Kg/ha), TKW=Thousand kernel weight (g), HI=Harvest index (%).

Three genotypes G6 (50%), G20 (46.68%) and G22 (45%) showed higher harvest index values as compared to the standard checks. Consequently, it is more efficient when these three genotypes are selected as donor parent in crossing block for improving harvest index. Maximum and minimum grain yield was obtained from G8 (5313 kg ha-1) and G1 (1296.2 kg ha-1) with the range value of 4016.8 kg ha-1. This showed that there is huge variation within the test entries for grain yield. Out of the total genotypes tested, 52% of them had yielded above the grand mean (3906.6 kg ha-1).

Phenotypic and genotypic variations

The portion of genotypic variance for days to first heading, days to heading, days to maturity, number of kernel per plant, grain yield, 1000-kernel weight and harvest index were greater than 50%, which indicates that the genotypic effect on the phenotypic expression was greater than the effect of the environment by more than 50%. However, the effect of environment on the phenotypic expression for grain filling period, plant height, spike length, peduncle length and awn length were greater than the genotypic effect.

The genotypic coefficient of variation (GCV) ranged from 3.94% for days to maturity to 22.90% for grain yield, and the phenotypic coefficient of variation (PCV) ranged from 4.98% for days to maturity to 30.34% for grain yield (Table 4). According to Deshmukh et al. [18], PCV values were considered as high for grain yield (30.34%) and harvest index (28.88%), while traits with moderate PCV values were grain filling period (10.89%), number of kernel per spike (18.91%), plant height (12.61%), spike length (11.89%), peduncle length (16.05%) and 1000-kernel weight (13.59%). However, lower PCV values were observed for days to first heading (8.55%), days to heading (9.33%), days to maturity (4.98%) and awn length (9.7%). Regarding, GCV values, high GCV estimates were obtained for harvest index and grain yield whereas number of kernels per plant, and 1000-kernel weight showed moderate values, and the other traits had showed lower GCV (Table 4). The genotypic coefficient of variation for grain yield (22.9%) and harvest index (20.96) were high (Table 4). This suggested that the impact of environmental factors on the expression of these traits is relatively low and these traits are responsive to selection. Similar finding has been also reported by Jimera et al. [19] and Addisu and Shumet [20].

Traits Mean ± SE σ2g σ2p σ2e Share of % GCV (%) PCV (%) H2b% GA (5%) GAM
σ2e σ2g
DFH 43.64 ± 1.17 9.82 13.93 4.11 29.5 70.5 7.18 8.55 70.5 5.42 12.42
DH 52.17 ± 1.75 14.46 23.68 9.22 38.93 61.07 7.29 9.33 61.07 6.12 11.74
DM 91.05 ± 1.60 12.89 20.58 7.69 37.37 62.63 3.94 4.98 62.63 5.85 6.43
GFP 38.88 ± 1.83 7.94 17.94 10 55.72 44.28 7.25 10.89 44.28 3.86 9.94
NKPS 47.87 ± 3.58 43.4 81.94 38.54 47.04 52.96 13.76 18.91 52.96 9.88 20.63
PH 21.2 ± 2.42 28.37 86.72 58.35 67.28 32.72 7.21 12.61 32.72 6.28 8.5
SL 73.85 ± 4.41 0.29 0.87 0.58 66.92 33.08 6.84 11.89 33.08 0.63 8.1
PL 7.83 ± 0.44 3.7 16.62 12.92 77.74 22.26 7.57 16.05 22.26 1.87 7.36
AL 454.8 ± 83.53 0.53 1.08 0.56 51.35 48.65 6.76 9.7 48.65 1.04 9.72
GY 25.4 ± 2.08 800551.78 1405190.78 604639 43.03 56.97 22.9 30.34 56.97 1391.2 35.61
TKW 10.74 ± 0.43 18.89 32.89 14 42.57 57.43 10.3 13.59 57.43 6.78 16.08
HI 3906.6 ± 448.94 55.99 106.23 50.24 47.3 52.7 20.96 28.88 52.7 11.19 31.35

Table 4: Phenotypic and genotypic variances and coefficient of variations, heritability in broad sense, genetic advance as percent and standard error (SE) of mean for 12 traits of 25 food barley genotypes studied at ATARC during the 2017/18 main season. σ2g=genotypic variance, σ2p=phenotypic variance, σ2e=environmental variance, PCV=phenotypic coefficient of variation(%), GCV=genotypic coefficient of variation (%), H2=broad sense heritability (%), GA=Genetic advance, GAM=genetic advance as percent of mean (%). DFH=Days to first heading, DH=Days to heading, DM=Days to maturity, GFP=Grain filling period, NKPS=Number of kernel per spike, PH=Plant height (cm), SPL=Spike length (cm), PL=peduncle length (cm) AL=Awn length (cm), GY=Grain yield (kg/ha), TKW=Thousand kernel weight (g), HI=Harvest index (%).

The phenotypic coefficient of variation was relatively greater than genotypic coefficient of variation for all traits considered in this study. However, the scale of the difference was low for days to first heading, days to heading, days to maturity, grain filling period, awn length, grain yield, harvest index and 1000-kernel weight. This suggested that the marked influence of environmental factors for the phenotype expression of genotypes for these traits was low and the higher chance of improvement of these traits through selection based on the phenotype of genotypes.

Estimates of heritability and expected genetic advance

Heritability, estimates can be grouped in to the following categories: low heritability (<40%), medium heritability (40-59%), moderately high (60-79%) and very high heritability (>80%). According to this author, the present study, broad sense heritability estimate varied from 22.26% for peduncle length to 70.50% for days to first heading. Moderately high heritability (>40 and <80) values were obtained for days to first heading (70.50%), days to heading (61.07%), days to maturity (62.63%), grain filling period (44.28%), number of kernels per spike (52.96%), awn length (48.65%), grain yield (56.97%), 1000-kernel weight (57.43%) and harvest index (52.7%) (Table 4). This suggested that selection for these traits should be delayed to more advance generations. However, plant height (32.72%), spike length (33.08%) and peduncle length (22.26%) exhibited lower heritability estimates which suggest that selection for these traits would be considerably difficult or virtually impractical due to the masking effect of the environment.

Johson et al. reported that genetic advance as percent of mean was categorized as low (<10%), moderate (10-20%) and high (>20%). Among the characters measured, number of kernels per spike, grain yield and harvest index were showed moderately high heritability estimate in conjunction with higher values of genetic advance estimates as percentage of mean where these results agreed with that of Alemayehu [16], Shegaw et al. [17] and Azeb et al. [21] who reported high heritability together with relatively high genetic advance as percent of in barley. Genetic advance under selection is the advance of traits in genotypic value for the produced population compared with the original population under one cycle of selection at a given selection intensity [5]. Thus, the result suggested that selecting the top 5% of the genotypes could result in an advance of 11.74% to 35.61% over the respective population mean for the days to first heading, days to heading, number of kernel per spike, grain yield, 1000-kernel weight and harvest index.

Genetic advance under selection values were low (<10%) for days to maturity, grain filling period, plant height, spike length, peduncle length and awn length. This implies that improvement of traits in genotypic value for the produced population compared with the original population under one cycle of selection is <10% at 5% selection intensity. According to Panse [22], the effective selection is done for the characters having high heritability accompanied by high genetic advance which is due to the additive gene effect. In this study, high heritability complemented with moderate genetic advance was observed for days to first heading, days to heading and 1000-kernel weight. This provides a chance for further improvement in advanced generations through selection of these traits.

Summary and Conclusion

The analysis of variance for revealed that there were sufficient variations among food barley genotypes for grain yield and yield related traits. There were highly significant variation among genotypes for days to first heading, days to heading, grain filling periods, days to maturity, number of kernel per spike, plant height, spike length, awn length, grain yield, thousand kernel weight and harvest index. The highest mean performance for grain yield was obtained from genotypes G8 with 5313 kg ha-1 and lowest mean performance for grain yield was obtained from genotype G1 with 1296.2 kg ha-1. Among twenty-two genotypes tested seven of them had higher mean yield than the three standard checks, and this gives an opportunity for plant breeders for new variety release of the crop. The genotypic variances (δ2g) were greater than environmental variance (δ2e) for days to first heading, days to heading, days to maturity, number of kernel per plant, grain yield, 1000-kernel weight and harvest index. Thus, the variations observed between genotypes were largely the effect of inherent genetic background of the genotypes. Moderately high heritability complemented with moderate genetic advance was observed in the case of days to first heading; days to heading and 1000- kernel weight. Expressing, these traits were highly heritable and governed by additive gene action. In spite days to maturity possessing moderately high estimate of heritability but failed to show high estimate of genetic advance as percentage of mean and indicating nonadditive gene actions in its inheritance.

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Citation: Dinsa T, Mekbib F, Letta T (2018) Genetic Variability, Heritability and Genetic Advance of Yield and Yield Related Traits of Food Barley (Hordeum vulgare L.) Genotypes in Mid Rift Valley of Ethiopia. Adv Crop Sci Tech 6: 401. DOI: 10.4172/2329-8863.1000401

Copyright: © 2018 Dinsa T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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