الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
In Egyptian cultivated areas severe saline problems affect the majority of wheat extension regions. To address salinity issues, Egypt still lacks a wheat genotype that is salt tolerant. The lack of germplasm with a large genetic variation that allows for the selection of salt-tolerant and high-yielding genotypes is, at least in part, responsible for the low success rate in generating salt tolerance in wheat.
The mean objectives of the present investigation were:
1. Evaluation of salinity tolerance in different genetic backgrounds of wheat.
2. Relating genetic diversity estimated for double haploid lines as well as two parents and four Egyptian local wheat cultivars as check, using SSR markers with agronomic performance under stress conditions to establish the degree of association between these techniques.
3. Identification of genomic regions associated with salinity tolerance especially, those markers related to Na+ exclusion from salt tolerant genotype.
To fulfill those objectives, three experiments were carried out.
The results of each experiment could be summarized in the following:
I. Green house experiment:
Eighteen bread wheat genotypes, including 12 doubled haploid lines resulting from the cross (Sakha8 X Line25), via anther culture technique, in addition to four check cultivars (Sakha93, Sids1, Giza168 and Gemmeiza7) and the two parents (Sakha8 and Line25), were tested under four salinity levels (0, 3000, 6000, 9000 NaCl ppm).
The main important results were:
1. It causes an increase salinity level decreasing ten of studied characters (S%, PH, FLA, GFR, No. GS, GWS, GY, BY, HI% and Chll).
2. It causes an increase salinity level increasing three of studied characters (DTH, DTM and GFP).
3. Activation phenomenon by exposure to medium salinity level appeared on 3000 ppm salinity level at three studied characters (DTM, GFP and HI%).
4. Increasing salinity levels causes weight loss in GY estimated 22.38%, 36.81% and 67.32% at 3000, 6000 and 9000 ppm salinity levels compared with control.
5. Giza 168 proved the heaviest grain yield over all genotypes and salinity levels with grain yield estimated by 24.94 g/pot, this genotype had first rank at grain filling rate, second rank at kernels weight/spike and fifth rank at biological yield with no- significant different with Sids1 of the first rank holder.
6. The owner of the grain yield second rank was Gemmeiza7 with grain weight estimated by 22.40 g/pot, Gemmeiza7 had Second, fourth, second and first ranks at grain filling rate, kernels weight/spike, harvest index and chlorophyll content, respectively.
7. The grain yield showed a change estimated at -19.22% at 3000 ppm, -30.81% at 6000 ppm and -64.68% at 9000 ppm comparing with control.
8. Genotypes DHL12 and Gemmeiza7 appeared vigor at grain yield with low salinity level (3000 ppm) comparing with control except that genotypes appeared decreasing at grain weight with increasing salinity levels.
9. At high salinity level (9000 ppm) genotypes proved wide change range between - 29.19% and -79.21% with reduction mean estimated by -64.68%.
10. The sensitivity to salinity tolerance appeared at Salinity Tolerant Trait Index (STTI) of grain filling rate, kernels weight/spike, grain yield and biological yield. Wider range of STTI’s revealed in grain filling rate, harvest index, biological yield and grain yield estimated by 1.92, 1.38, 1.35 and 1.28, respectively, where it turns out that traits could execution deeply differentiate between genotypes.
11. The STTI of grain yield calculated to genotypes, the types of tolerance provide nine genotypes had tolerant to salinity effect, eight genotypes had moderate to salinity effect and one genotype had sensitive to salinity effect. The most tolerant genotypes were Gemmieza7, Giza168 and DHL11 with STTI’s 1.78, 1.76 and 1.41, respectively.
12. Salinity Tolerant Index (STI) cause the rank order of genotypes under study (Gemmeiza7, Giza168, DHL3, DHL4, Sids1, DHL11, Sakha8, Sakha93 and DHL8) had tolerant type to salinity effect and (DHL4, DHL6, DHL10, DHL1, DHL2, DHL12, DHL7 and Line25) had moderate type to salinity effect.
II. Open field experiment:
The present investigation was carried out in the fields of the experimental ARC in 2016/17 and 2017/18 winter seasons, Nubaria station (Alexandria Governorate).
Every season had 3 locations in the same station with three salinity levels (low salinity 250 ppm = 0.39 dSm-1, moderate salinity level 5125 ppm = 8.01dSm-1 and high salinity level 10215ppm = 15.96 dSm-1).
The main outcome can be defined as follows:
1. Increasing salinity levels caused increasing for six characters at 2016/17 winter growing season (days to heading, days to maturity, grain filling period, no. of kernels/spike, grain yield and harvest index), on the other hand caused decreasing for five characters at 2016/17 winter growing season (plant height, grain filling rate, kernels weight/spike, 1000 kernels weigh and biological yield) and all characters at 2017/18.
2. The revitalizing effect of the medium salinity level appeared at four characters at 2016/17 winter growing season (grain filling period, no. of kernels /spike, grain yield and harvest index).
3. Relatively the moderate salinity level had no effect in kernels weight/spike, 1000 kernels weight and biological yield at 2016/17 winter growing season, 1000 kernels weight and harvest index at 2017/18 winter growing season.
4. The high salinity level had no effect in days to heading at 2016/17 winter growing season, days to heading and biological yield at 2017/18 winter growing season.
5. At 2016/17 winter growing season Sakha8 and DHL5 appeared best performance at grain yield estimated by 7.34 t/ha and 7.22 t/ha, respectively. Sakha8 scored best
result at plant height and biological yield this reflects increase and high of the vegetative growth which translates to the dry matter of the grain this is the reason why Sakha8 obtained the tremendous result in the grain filling period,grain filling rate and the no. of kernels/spike. All of these traits, which scored highly performance were translated into the first rank of the grain yield. With reference to DHL5, the highly performance appeared at grain filling rate, no. of kernels/spike, kernels weight/spike and 1000 kernels weight causes the second rank at grain yield.
6. DHL8 scored highest grain yield followed by Sakha8 at 2017/18 winter growing season due to DHL8recordedthe top rank of biological yield, consequently pointing to high total dry matter that is likely to be converted into grains, which is evident DHL8 occupied the first rank at grain filling rate/day which positively affected on 1000 grains weight. Sakha8 had a best performance at grain filling rate, no. of kernels/spike and kernels weight/spike, the high amount of dry matter stored in grains with a relatively high average in the grain filling period of grains led to Sakha8 obtaining the best performance in the no. of kernels/spike and kernels weight/spike, thusSakha8 occupied the second rank in the total grains weight.
7. The moderate salinity stress grain yield result at 2016/17 winter growing season appeared with positive effect at all genotypes expect three genotypes DHL1, DHL8 and Line25, with total change +10.16 %, on the other hand the high salinity level showed negative effect estimated by -68.49 % change.
8. At 2017/18 winter growing season, grain yield showed change % -38.25 and -72.63 at moderate and high salinity levels, and DHL9 scored less change estimated by - 38.25% at moderate salinity level, and Sakha8 scored less change estimated by - 46.68% at high salinity level.
9. At Salinity Tolerant Trait Index (STTI) result DHL1 and Gemmeiza7 showed the best index (T) over all genotypes at moderate salinity stress, about high salinity stress DHL8 and Sakha8 showed the best index (T) over all genotypes.
10. The genotypes were divided into four groups, the first one: DHL5, DHL8, DHL9, Sakha8, Line25 and Gemmeiza7, showed tolerant performance to salinity effect at both of salinity stress (moderate and high salinity stress), and the second one: DHL1, DHL2, DHL3 and DHL6, showed tolerant performance to salinity effect at moderate salinity stress, and moderate performance to salinity effect at high salinity stress, the third one: DHL7 showed moderate performance to salinity effect at moderate salinity stress and tolerant performance to salinity effect at high salinity stress, the fourth one: DHL4, DHL10, DHL11, DHL12, Sakha93, Sids1 and Giza168 showed moderate performance to salinity effect at both of salinity stress (moderate and high salinity levels).
III. SSR markers experiment:
Genetic diversity for 18 wheat genotypes (12 DH lines + 2 parents + 4 wheat cheek cultivars) had tested with 36 SSR markers. This experiment was conducted to detect between all the genotypes and to ascertain their biodiversity-based similarities and differences.
Analysis of biodiversity based on SSR markers: A UPGMA cluster analysis of genetic similarity matrices was performed to assess the links between the 18 bread wheat genotypes
included in this study. These findings indicated that salinity-tolerant genotypes might be distinguished from sensitive genotypes using cluster analysis of SSR markers.
SSR primer’s levels of genetic information production: for their capacity to amplify the genomic DNA from 18 bread wheat genotypes, thirty-six SSR primers were tested. Depending on the primer and the DNA sample, the number of amplification bands per primer ranged from 1 for primer CFD18 to 9 for primer BARC 124. Fragments ranged in size from 100 to 850 bp.
The 36 primers generated 121 fragments in total, 103 of which were polymorphic. The polymorphism was in the range of 0.0% and 100.0%. The 18 bread wheat genotypes exhibit high levels of polymorphism (100%) according to the current study. Twenty-tow of the thirty-six SSR primers exhibited a polymorphism rate of equal 100%.
Primers were also used to investigate the discriminative power of each SSR primer by calculating the polymorphic information contents (PIC), observed heterozygosity (Ho) and marker index (MI).
The most important result can be summarized at the following points:
1. The average PIC per primer was 0.553, with a range of 0.00 to 0.879. The highest value of PIC appeared on four SSR primers (CFD49, WMC154, WMC432 and WMC503), on the other hand four SSR primers obtained the lowest value (CFD1, CFD18, GWM291 and WMC169).
2. The high MI values indicated the suitability of SSR markers in estimating genetic diversity, the results show that MI ranged from 0.00 to 7.03 with an average of 1.71 over all used markers. The highest MI value (7.03) was obtained from WMC432 marker and the lowest MI value observed in four markers (CFD1, CFD18, GWM291 and WMC169).
3. Result of Ho showed mean estimated by 0.38 over all thirty-six markers, and four markers presented highest result 0.50 (CFD46, VRN2-BMI, Cslink-Nax2 and WMC18).