| Livestock Research for Rural Development 27 (9) 2015 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
28 traditional barley genotypes (27 six rows and 1 two row) were compared in field trials in a sub-humid region (Mitidja - Algiers) in presence of three controls to identify the genotypes with superior agronomic traits and grain protein at maturity, forage dry matter yield and nutritive forage value at the dough stage and also to assess the genetic diversity of this germplasm using these traits. The variability among barley genotypes was estimated in the first year by agronomic traits, days to heading and days to maturity and the second year by days to heading, the dry matter yield, the crude protein content and the crude fiber content of whole-plant at the dough stage.
In the first year, a great variability within the germ-plasm was found for all the agronomic traits (P‹0.001). Much of traditional genotypes showed favorable yield components better than the controls, like that was the case for the 1000 grain weight, the number of fertile tillers per plant, the number of grains per spike. The highest value of grain protein was 12.1 % and concerned traditional barley (genotype 15). The principal component analysis showed that three components could describe 80.3% of total variance. The following traits: 1000 grain weight, awn length, days to heading, days to maturity, plant height and grain number per spike, were those contributing more to the variability among the genotypes with 47.6 % of the total variance. These parameters were all correlated between themselves.
In the second year, a variability among genotypes existed for the crude fiber (P‹0.01) and the dry matter yield (P‹0.05) but not for the crude protein (P›0.05). Many genotypes showed higher yields and better nutritional qualities (crude fiber and crude protein) than some controls. The principal component analysis showed that two components could describe 67.2 % of total variance. The most variation between genotypes was described by days to heading and the dry matter yield (38.7 % of total variance). The top rated genotypes for using as grain and straw at maturity were: 15, 8, 1, 18, 16, 7, 22 and the control 31. Those that can be used for green forage or tested for silage were: 13, 12, 6, 4, 2, 24 and also 7, 8 and the controls 21 and 31.
Keys words: local germ-plasm, ruminant, superior genotype, variability
Barley (Hordeum vulgare vulgare L.) is an ancient and important cereal grain crop (Baik and Ullrich 2008). It is the fourth important cereal crop, cultivated successfully in wide range of climates (Khajavi et al 2014). Barley is a very important feed supplement for domestic animals (Kanbar 2011).
In Algeria, barley in the past occupied a very important place, more than durum and bread wheat and formed the basis for human food. Currently, barley is used primarily for the sheep’s food. The local gerpmlasm suffered a great genetic erosion following the introduction of new performing varieties during the years 1965-1970. The new varieties of barley adopted in Algeria remain marginal because of their bigger sensibility at the climatic variations. In the country, the fodder deficit is among the major constraints hampering the development of animal production.
Conservation of the natural resources of varieties of barley in Algeria can be conceived through their integrations in the food formula of ruminants after characterization of their nutritional values (Arbouche et al 2008). According to Belaid (2014), immature cereals are an option against the summer drought in Algeria.
The assessment of genetic diversity in a crop species is fundamental to its improvement and the exploitation of genetic diversity of autochthonous barley genotypes is very important to do especially for their adaptation criteria.
Genetic diversity among and within plant species is in danger of being reduced (Eshghi and Akhundova 2010). Some studies on genetic diversity of barley have focused on phenological and agro-morphological traits (Assefa and Labuschagne 2004; Shakhatrech et al 2010; Muhe and Assefa 2011; Mekonnon et al 2015).
According to Eshghi and Akhundova (2010), many authors showed that grain yield is an ultimate product of the action and interaction of number of components such as number of tillers, number of grains per spike, 1000-grain weight, plant height, harvest index and etc.
Cereal crops such as wheat, barley, oat, triticale, rye, sorghum and rice are all used as whole-crops, but barley and wheat are probably the most common whole-crop cereals worldwide (Rustas 2009). Because of their superior combination of yield and digestibility compared to other stages of development, boot and soft dough stages are the two recommended stages at which to harvest for silage and hay (Fohner 2002).
Fiber content is an important measure of forage quality (Kennelly et al 1995). Organic matter digestibility of whole-crop barley and wheat is mainly explained by fiber concentration and digestibility (Rustas 2009). Some nutritionists define fiber as the any component in a feed that is not digested by mammalian enzymes (Mirzaei-Aghsaghali and Maheri-Sis 2011).
Crude protein is the important factor which affects the quality of forage (Khan et al 2014).
The economic value of cereal forage for feeding cattle is dependent on both its yield and feeding value (McCartney and Vaage 1993). If winter cereal crops are to be harvested for silage, management recommendations are needed to obtain the best compromise between forage yield and quality for a given farm situation or weather conditions (Geren 2014).
Review of literatures showed that on barley and other species, many studies have been done on the yield and on the nutritional traits at the immature plants (Demarquilly and Andrieu (1992); Le Gall et al (1998); Zelter et al (1971); Fohner (2002); Gill et al (2013)…).
Identification of barley varieties with the most desirable nutritional characteristics for ruminants is warranted and animal nutritionists need to work closely with plant breeders to identify appropriate selection criteria (Kennelly et al 1995).
In Algeria, few studies exist on traditional barley and even less on the nutritional quality and yield of the whole plant in the immature stage and thus the diversity of local germplasm remains unknown in many aspects.
This work was done with the objectives to conduct the phenology, the agronomic characterization and also to investigate the hectare dry matter yield and the feed quality (crude protein and crude fiber) of whole-plant at the dough stage and contribution of all these parameters to the variability among the barley genotypes.
The material used in this study included 28 traditional genotypes of barley and 3 controls. 10 traditional genotypes were recovered from ICARDA (Syria). They concerned the following regions: Biskra with four genotypes (1, 6, 8 and 14); El Bayadh (7 and 11); Ouargla (9 and 10) and Bechar (12 and 13). The remaining genotypes were collected by researchers of INRAA within the following regions: Adrar (2, 3, 18, 19, 20 and 22); Touggourt (15, 16, 17, 23, 24 and 25); Ghardaïa (4) and Tamanrasset (26, 27, 28, 29 and 30). All the genotypes were six-rowed barley except the genotype “12” from Bechar which was barley with 2 rows. Except El Bayadh which has a semiarid climate, all other regions are characterized by an arid climate.
For the two experiments, genotypes were evaluated in Mitidja (plain in Algiers with an average rainfall exceeding 500 mm and a sub-humid climate ) at the National Agronomic Research Institute of Algeria (INRAA) during 2011-2013 in presence of three controls: Pane from Spain (genotype 5) and two approved Algerian varieties Saïda (genotype 21) and Tichedrett (genotype 31). These studies were taken without fertilization, pesticides, and fungicides and without irrigation. The texture of the soil was a sandy clay loam texture. Planting of the first study occurred on 8 December in 2011. The test was done using a randomized complete block design with three replications. Rows were 4.80 m each with spacing of 40 cm between themselves. With 25 seeds by row, the distance between plants was 20 cm.
Plant height (HPL) (cm), spike length (HEP) (cm), awn length (LBA) (cm), number of fertile tillers per plant (NTE), grain number per spike (NGE), spikelet number per spike (NEE), days to heading (DEP), days to maturity (DC), 1000 grain weight (PMG) (g) and grain protein content (PRO) (%) were the quantitative traits evaluated.
A random selection of 30 plants was done on three plots (ten plants per plot chosen from the central parts of each row) of the test to study the following characters: HPL, HEP, LBA, NTE, NGE and NEE.
One-way analysis of variance (ANOVA) was made by the Gen Stat Discovery (Edition 3, Stat Soft Inc.), on six quantitative characters (HPL, NTE, HEP, LBA, NEE, NGE) (table 1). Principal Component Analysis (table 2) and correlations (table 3) were obtained by STATISTICA (Data analysis Software System, version 6, Stat Soft Inc.) and were performed based on the means values (table 4) of nine quantitative characters (HPL, NTE, HEP, LBA, NEE, NGE, PMG, DEP, DC) for the principal component analysis and on: HPL, NTE, HEP, LBA, NEE, NGE, PMG, DEP, DC and PRO for correlations.
The protein content of the grain was determined from the nitrogen content, tested by Kjeldahl method (AFNOR 1985). It is expressed in percentage by weight referred to dry matter. The value given is the average of two replications (table 4).
Planting of the second study took place on November 27 in 2012 using a randomized complete block design with two replications. In each plot, each genotype was grown in four rows of 2 m long with a spacing of 30 cm between rows. Seeding rate was 70 kg/ha. The yield was determined on two square meters chosen from the middle rows of the plots in order to avoid border effects. All yield calculations were based on dry matter content of whole plant at the dough stage by drying in a forced draught oven at 60 °C for 48 hours. The dry matter yields (DMY) obtained, were converted into t/ ha. The crude protein (CP) content was determined from the nitrogen content, tested by Kjeldahl method (AFNOR 1985). It is expressed in percentage by weight referred to dry matter. The crude fiber (CF) content (%) was determined by the Weende method (AFNOR 1985). One-way analysis of variance (ANOVA) was made by the GENSTAT software Discovery version 3, on the characters DMY, CP and CF (table 5). The principal component analysis (table 6) was based on the means of the following characters: days to heading, the crude fiber, the crude protein and the dry matter yield (table 7) and obtained by STATISTICA software version 6.
Variance analysis of the following traits HPL, NTE, HEP, LBA, NEE and NGE showed the existence of a great genetic variability (P ‹ 0.001) in the germplasm (table 1).
In six rowed barley genotypes, the highest values in 1000 grain weight, grain number per spike, number of fertile tillers per plant and grain protein were registered in traditional genotypes 8, 18, 1 and 15 with 60.9 g, 58.93, 22.73 and 12.12 % respectively. Barely with two rows (genotype 12) gave the highest number of fertile tillers (29.3).
|
Table 1. ANOVAs of agronomic traits in barley genotypes |
||||||
|
|
Minimum value |
Maximum value |
Mean |
SEM |
CV (%) |
p |
|
HPL |
87.17 |
112.63 |
101.33 |
2.36 |
9 |
‹ 0.001 |
|
NTE |
11.8 |
29.3 |
16.34 |
1.701 |
40.3 |
‹ 0.001 |
|
HEP |
4.02 |
10.4 |
6.80 |
0.241 |
13.7 |
‹ 0.001 |
|
LBA |
7.33 |
13.62 |
10.23 |
0.276 |
10.4 |
‹ 0.001 |
|
NEE |
8.53 |
12.13 |
9.99 |
0.42 |
16.3 |
‹ 0.001 |
|
NGE |
30.2 |
58.93 |
46.69 |
2.48 |
20.6 |
‹ 0.001 |
|
S.E : SEM: Standard Error of Means; CV : Coefficient of Variance ; Very highly significant at P ‹ 0.001 |
||||||
Principal component analysis indicated that three components could describe 80.29 % of the whole variance in the genotypes (table 2). The first component could justify the most amount of variance between genotypes (47.6 %). Traits that had correlation with this component were: plant height, awn length, grain number per spike, 1000 grain weight, days to maturity and days to heading.
The second component justified 18.87 % of total variance with the correlate traits: number of fertile tillers per plant and spike length. The third component explaining 13.82 % of the variance included the spikelet number per spike.
|
Table 2. Principal component analysis (PC) of 31 barley genotypes based on 9 traits |
|||
|
Parameter |
PC 1 |
PC 2 |
PC 3 |
|
Eigen values |
4.28 |
1.7 |
1.24 |
|
% of variance |
47.6 |
18.87 |
13.82 |
|
Cumulative % |
47.6 |
66.47 |
80.29 |
|
Characters |
Eigenvector |
||
|
HPL |
-0.703 |
-0.137 |
0.160 |
|
NTE |
0.079 |
-0.874 |
-0.019 |
|
HEP |
-0.637 |
-0.657 |
0.109 |
|
LBA |
-0.829 |
0.395 |
-0.143 |
|
NEE |
0.139 |
-0.439 |
-0.847 |
|
NGE |
0.677 |
0.284 |
-0.512 |
|
PMG |
-0.850 |
-0.000 |
0.027 |
|
DC |
-0.880 |
0.074 |
-0.322 |
|
DEP |
-0.844 |
0.218 |
-0.318 |
The correlation matrix (table 3) showed that all these following traits: HPL, LBA, PMG, NGE, DC and DEP were correlated between themselves. HPL, LBA, PMG, DC and DE were positively correlated but the NGE was negatively correlated with them. HEP was positively correlated with HPL and NTE but negatively correlated with NGE. No significant correlation was recorded between the grain protein content and all the other characters studied.
|
Table 3. Correlation matrix on ten traits of 31 barley genotypes |
|||||||||
|
HPL |
NTE |
HEP |
LBA |
NEE |
NGE |
PMG |
DC |
DEP |
|
|
NTE |
-0.11NS |
||||||||
|
HEP |
0.69*** |
0.38* |
|
||||||
|
LBA |
0.39* |
-0.30NS |
0.20NS |
||||||
|
NEE |
-0.16NS |
0.32NS |
0.13NS |
-0.19NS |
|||||
|
NGE |
-0.38* |
-0.20NS |
-0.60** |
-0.39NS |
0.36* |
||||
|
PMG |
0.46* |
0.00NS |
0.45* |
0.77*** |
-0.11NS |
-0.61*** |
|||
|
DC |
0.52** |
-0.08NS |
0.43* |
0.79*** |
0.08NS |
-0.44* |
0.68*** |
||
|
DEP |
0.48** |
-0.24NS |
0.38* |
0.78*** |
0.01NS |
-0.37* |
0.61** |
0.87*** |
|
|
PRO |
0.02NS |
-0.21NS |
0.08NS |
0.13NS |
0.07NS |
-0.10NS |
0.18NS |
0.03NS |
-0.01NS |
|
NS: Non-significant ; * P ‹ 0.05 ; ** P ‹ 0.01 ; *** P ‹ 0.001 |
|||||||||
|
Table 4 . Means of agronomic traits, days to heading, days to maturity and grain protein (%) in barley genotypes |
||||||||||
|
N° |
HPL |
NTE |
HEP |
LBA |
NEE |
NGE |
PMG |
DEP |
DC |
PRO |
|
1 |
87.33 |
22.73 |
5.37 |
11.17 |
9.2 |
49.13 |
48.63 |
114 |
163 |
9.3 |
|
6 |
100.77 |
15.2 |
6.7 |
9.67 |
10.07 |
46.03 |
36.8 |
121 |
173 |
9.11 |
|
8 |
105.27 |
14.87 |
7.42 |
12.41 |
9.3 |
40.06 |
60.9 |
127 |
173 |
10.54 |
|
14 |
101.77 |
15.4 |
7.74 |
12.03 |
9.73 |
42.33 |
56.2 |
127 |
173 |
9.43 |
|
2 |
93.58 |
16.43 |
6.21 |
7.73 |
9.6 |
50.53 |
34.53 |
102 |
144 |
11.5 |
|
3 |
93.17 |
13.16 |
5.33 |
7.89 |
9.76 |
48.93 |
34.7 |
102 |
144 |
8.7 |
|
18 |
87.13 |
16.1 |
4.02 |
8.58 |
12.13 |
58.93 |
35.9 |
114 |
163 |
9.62 |
|
19 |
90.93 |
14.2 |
5.34 |
7.97 |
10.2 |
52.56 |
34.13 |
102 |
144 |
11.19 |
|
20 |
94.77 |
15.23 |
6.15 |
7.66 |
8.53 |
43.5 |
35.8 |
102 |
150 |
9.9 |
|
22 |
93.5 |
13 |
5.28 |
8.09 |
10.03 |
54 |
37.7 |
102 |
144 |
10.3 |
|
5 |
96.73 |
14.5 |
5.76 |
11.63 |
10.16 |
45.53 |
52.1 |
127 |
173 |
9.3 |
|
21 |
107.73 |
16.23 |
7.07 |
12.55 |
9.26 |
39.03 |
58.73 |
127 |
173 |
10.72 |
|
31 |
87.17 |
14.7 |
4.8 |
13.62 |
10.86 |
48.2 |
45.3 |
127 |
173 |
10.7 |
|
4 |
106.13 |
13.73 |
7.55 |
9.04 |
10.43 |
49.23 |
33.6 |
129 |
163 |
9.91 |
|
7 |
103.37 |
11.8 |
7.07 |
11.98 |
8.86 |
39.1 |
54.5 |
129 |
173 |
10.67 |
|
11 |
109.27 |
20.13 |
7.48 |
11.95 |
9.13 |
41.63 |
60 |
121 |
173 |
8.51 |
|
9 |
109.4 |
12.56 |
7.07 |
11.83 |
9.3 |
46.46 |
48.63 |
132 |
173 |
9.08 |
|
10 |
100.57 |
14.3 |
7.3 |
11.69 |
9 |
44.93 |
39.53 |
129 |
173 |
10.6 |
|
12 |
100.00 |
29.3 |
10.4 |
8.32 |
12.13 |
30.2 |
57.23 |
114 |
168 |
10.43 |
|
13 |
109.13 |
15.13 |
7.77 |
12.24 |
10.03 |
41.53 |
56.83 |
129 |
173 |
9.6 |
|
15 |
107.73 |
14.43 |
8.11 |
11.91 |
10.8 |
47.73 |
59.53 |
127 |
173 |
12.12 |
|
16 |
112.63 |
14.3 |
7.68 |
12 .16 |
10.8 |
46.86 |
59.03 |
129 |
173 |
10.8 |
|
17 |
110.27 |
13.63 |
7.46 |
12.28 |
9.46 |
40.56 |
42.23 |
114 |
173 |
10.6 |
|
23 |
106.4 |
17.03 |
7.48 |
11.98 |
11.16 |
55.26 |
46.63 |
114 |
162 |
9.8 |
|
24 |
100.53 |
18.23 |
6.79 |
7.88 |
10.76 |
50.7 |
30 |
118 |
163 |
8.6 |
|
25 |
101.7 |
21.46 |
7.88 |
8.39 |
11.7 |
55.7 |
31 |
118 |
163 |
8.8 |
|
26 |
111.83 |
14.1 |
7.07 |
11.83 |
9.3 |
46.46 |
58.87 |
121 |
173 |
9.42 |
|
27 |
96.67 |
18.33 |
6.55 |
7.65 |
9.7 |
51.23 |
35.4 |
102 |
150 |
9.9 |
|
28 |
107.53 |
18.06 |
6.86 |
7.33 |
10.73 |
51.6 |
34.2 |
109 |
161 |
10.4 |
|
29 |
100.8 |
19.36 |
6.88 |
9.21 |
8.76 |
43.8 |
37.63 |
114 |
145 |
8.63 |
|
30 |
107.27 |
19 |
6.3 |
8.46 |
8.83 |
45.66 |
37.7 |
109 |
160 |
10.29 |
For the second year, the variance analysis showed variability among the genotypes for the crude fiber (P‹ 0.01) and the dry matter yield (P‹0.05) but not for the crude protein (table 5).
|
Table 5. ANOVAs of nutritional and yield components in barley genotypes |
||||||
|
|
Minimum value |
Maximum value |
Mean |
SEM |
CV (%) |
p |
|
DMY |
0.96 |
1.58 |
1.2 |
0.17 |
14.1 |
0.047* |
|
CP |
4.69 |
8.95 |
6.7 |
1.47 |
21.9 |
0.284NS |
|
CF |
10.86 |
34.46 |
26.83 |
5.04 |
18.8 |
0.006** |
|
SEM: Standard error of means; NS= no significant; *: significant at P ‹ 0.05; **: Highly Significant at P ‹ 0.01 |
||||||
|
Table 6. Principal component analysis of 31 barley genotypes based on days to heading, nutritional and yield components |
||
|
Parameter |
PC 1 |
PC 2 |
|
Eigen values |
1.55 |
1.14 |
|
% of variance |
38.7 |
28.5 |
|
Cumulative % |
38.7 |
67.2 |
|
Characters |
Eigenvector |
|
|
CP |
-0.174 |
0.801 |
|
CF |
-0.474 |
-0.663 |
|
DMY |
-0.754 |
0.244 |
|
DEP |
-0.852 |
-0.01 |
The principal component analysis showed that two components could describe 67.2 % of the whole variation (table 6). The first component explained the greatest variance (38.7 %) and included days to heading and the dry matter yield. The second component explained 28.5 % of variation and was represented by the crude protein and the crude fiber.
|
Table 7. Days to heading, means of crude protein (CP), crude fiber (CF) and dry matter yield (DMY). |
||||
|
Characters/ |
Heading |
CP |
CF |
DMY |
|
21 |
124 |
7.29 |
29.11 |
1.58 |
|
15 |
124 |
5.72 |
30 |
1.49 |
|
11 |
124 |
6.85 |
27.75 |
1.47 |
|
7 |
124 |
6.4 |
25.7 |
1.43 |
|
14 |
124 |
4.69 |
32.51 |
1.41 |
|
31 |
124 |
8.95 |
24.63 |
1.4 |
|
29 |
113 |
8.05 |
30.3 |
1.37 |
|
12 |
113 |
5.27 |
23.48 |
1.32 |
|
8 |
124 |
7.78 |
24.43 |
1.3 |
|
25 |
117 |
5.22 |
34.34 |
1.3 |
|
24 |
118 |
7.96 |
21.64 |
1.26 |
|
17 |
124 |
6.01 |
28.16 |
1.25 |
|
16 |
126 |
8.61 |
34.46 |
1.23 |
|
30 |
110 |
8.15 |
10.86 |
1.18 |
|
20 |
106 |
6.45 |
15.29 |
1.18 |
|
4 |
122 |
6.74 |
22.23 |
1.17 |
|
22 |
110 |
5.38 |
32.37 |
1.15 |
|
13 |
124 |
6.87 |
24.65 |
1.14 |
|
2 |
106 |
7.75 |
22 |
1.14 |
|
5 |
124 |
6.94 |
29.26 |
1.11 |
|
23 |
113 |
7.13 |
34.17 |
1.08 |
|
26 |
117 |
5.94 |
30.23 |
1.07 |
|
18 |
117 |
8.7 |
31.45 |
1.07 |
|
1 |
117 |
5.45 |
18.98 |
1.05 |
|
6 |
117 |
5.27 |
23.18 |
1.05 |
|
27 |
116 |
6.5 |
20.2 |
1.05 |
|
28 |
111 |
7.4 |
31.23 |
1.05 |
|
9 |
129 |
6.26 |
31.48 |
1.04 |
|
10 |
124 |
6.63 |
29.44 |
1.04 |
|
3 |
106 |
5.33 |
31.03 |
1.01 |
|
19 |
106 |
6.13 |
27.28 |
0.96 |
The study of the first year showed the existence of a high diversity in the germplasm studied for all the agronomic traits statistically analyzed (HPL, NTE, HEP, LBA, NEE and NGE). Genetic diversity is one of the fundamental requirements for plant breeding (Ramanujam et al 1974). According to Gegnaw and Hadado (2014), the barley landraces exhibit variation both between and within populations. In barley varieties, significant differences were also found for all agronomic traits studied by Mekonnon (2014). Compared with three controls much of traditional genotypes showed better yield components as was the case for the 1000 grain weight, the number of fertile tillers per plant and the grain number per spike.
The most important characters contributing to the variability were the 1000 grain weight, the awn length, days to heading, days to maturity, the plant height and the grain number per spike which explained 47.60 % of variation. The number of fertile tillers per plant and the spike length explained 18.87 % of the total variance; so the two components explained 66.47 % of the total variance. These results agree much with those found by Drikvand et al (2012) were traits contributing to the most variance among the barley genotypes concerned the first two components represented by: awn length, plant height, grain yield, grain number per spike, peduncle length, spike length and 1000 grain weight (with more than 62.46 % of variance).
The Matrix of correlation showed an association between many traits which is very promising for selection. As indicated by Lorencetti et al (2006), considerable importance has been given to studies involving correlation of traits in breeding programs. The 1000 grain weight, the plant height and days heading and maturity were positively correlated. In fact, the late genotypes have the greatest weight of 1000 grain and the highest stems. These results are consistent with those found by several authors (Bouzerzour and Monneveux 1992; Al-Tabbal and Fraihat 2012).
The 1000 grain weight is very highly correlated but negatively with the grain number per spike. The same result was found by Žáková and Benková (2004) and Babaiy et al (2011), thus the 1000 grain weight decreases with increasing the seed numbers. The spike length was positively and highly correlated to plant height. Babaiy et al (2011) found a negative and significant correlation between these traits. The awn length was very highly and positively correlated with 1000 grain weight and with days to heading and days to maturity. In fact, late genotypes have longer awns and heavier grains. Indeed, the role played by the awns in the drought resistance and in the grain filling was reported by several authors (Hadjichristodoulou 1993; Bort et al 1994). The number of fertile tillers per plant was positively correlated to the spike length. Babaiy et al (2011) showed a high positive correlation between these traits. No significant correlations existed between grain protein content and all the other characters. Twelve genotypes gave grain protein content exceeding 10 % and thus better than the control "Pane" (9.3 %). The highest values were registered in traditional genotypes surpassing all the controls and concerned the genotype 15 (from Touggourt) with 12.12 %, followed by genotypes 2 and 19 (from Adrar) with 11.5 % and 11.19 % respectively. In a study taken by Kennelly et al (1995), the crude protein in barley grain was 11.5 %. The level of protein in barley is highly variable, ranging from 7 to 25 % according to a large USDA study involving over 10 000 genotypes (Ullrich 2002).
For the second year, the variability among the genotypes was observed for the dry matter yield and the crude fiber but not for the crude protein. In a study taken on oat at 50 % of flowering stage, Khan et al (2014) found significant differences among varieties for the dry matter yield, the crude fiber and for the crude protein.
The most variation between genotypes was explained by the dry matter yield and days to heading which are correlated positively and significantly. At maturity, Mekonnon (2014) found a positive and significant correlation between the heading days and the grain yield on barley.
Generally, genotypes with long cycle and long stems in the first year were those presenting the highest dry matter yields in the second year (the control 21 and the traditional genotypes: 4, 7, 8, 11, 13, 14, 15, 16, 17, 24, 25, 29 and 30). The plant height seems positively correlated with the dry matter yield. Indeed, Gill et al (2013) found a positive and strong correlation between plant heights and dry matter yields on the barley varieties studied. It was concluded by Baron and Kibite (1987) that late-maturing and tall barley lines having high leaf content were more likely to produce high whole-plant digestible yield.
In the traditional genotypes, the crude protein content varied between a maximum of 8.7 % and a minimum of 4.69 % among which eight genotypes (28, 2, 8, 24, 29, 30, 16 and 18) gave protein content from 7.4 % and 8.7 % so more than the two controls 5 and 21 (6.94 % and 7.29 % respectively). In a study by Gill et al (2013) in barley harvested at the soft dough stage, the crude protein content varied from 8.7 % and 10.4 %. Harvested in milk stage, sole barley gave 12.77 % on crude protein in a study by Yolcu et al (2009). Harvested after maturity, barley straw had 4 % of crude protein without urea treatment and 7.6 % with urea treatment in a study taken by Mesfin and Ledin (2004). The control 21 gave the highest dry matter yield (1.58 t/ha) with 7.29 % of crude protein and 29.11 % of crude fiber. The control 31 gave the highest value of crude protein (8.95 %) with 24.63 % of crude fiber and 1.4 t/ha of dry matter yield.
The highest value of crude fiber was given by the genotype 16 (34.46 %) and the lowest values was given by the genotypes 30 and 20 (10.86 % and 15.29 % respectively). According to Ganovski and Ivanov (1982), it was established that crude fibers should range from 22 to 25 per cent of the dry matter in order to achieve best digestion effects. However, these authors mentioned that no data could be found in the literature on the most favorable percent amounts in the diet. On the basis of this reference, eight traditional genotypes (24, 2, 4, 6, 12, 8, 13 and 7) could be classified as best in terms of their crude fiber contents ranging between 21.64 % and 25.7 %. These genotypes have respectively: 7.96 %, 7.75 %, 6.74 %, 5.27 %, 5.27 %, 7.78 %, 6.87 % and 6.4 % of crude protein and they have more than 1t/ha of dry matter yield. The control “Tichedrett” with also a good content of crude fiber (24.63 %), was the best on crude protein content (8.95 %) and has a rather satisfactory dry matter yield (1.4 t/ha).
Among traditional genotypes, the maximum average of dry matter yield was 1.49 t/ha (genotype 15 which presented the highest grain protein content in the first year), so more than the controls 31 and 5 with 1.4 t/ha and 1.11 t/ha respectively. Esparza Martinez and Foster (1998) reported that in Mexico barley cultivated by farmers in good climatic conditions gave an average yield of 1.2 t/ha.
Without fertilization, all traditional genotypes gave dry matter yield averages more than 1 t/ha except the genotype 19 (0.96 t/ha). With fertilization, the yields could be better. Indeed, Ghanbari et al (2014) showed that fertilizations have a significant effect on quality and quantity barley forage.
Our sincere thanks go to Allam A. (Researcher at INRAA of Touggourt), Derradji H. (Researcher at INRAA of Baraki) and Kharsi M. (Senior technician at INRAA of Adrar) for their contribution to the acquisition of germplasm.
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Received 16 June 2015; Accepted 8 August 2015; Published 1 September 2015