بنجر نہ کبھی کشت تمنا میری ہو گی
بنجر نہ کبھی کشت تمنا میری ہو گی
اک فرد کا مرنا نہیں انسان کا مرنا
سر ہیں تو سرِ دار قلم اور بھی ہوں گے
ہم مرتے رہیں گے مگر ہم اور بھی ہوں گے
کوئی مسیحا نہ ایفائے عہد کو پہنچا
بہت تلاش پسِ قتل عام ہوتی رہی
Islamic education curriculum has central value for education process, as education vision direction. Islamic education mission is how to create religious people by leaning perfectly. Curriculum becomes one of success applications and quality in education institution most. Curriculum will develop based on global world and people life style existency. Therefore, education should view people life style increased as learning source that is becomed a value for curriculum step making. Beside that, islamic education curriculum development also becomes teacher’s choice to implement learning manner in class. In where, it’s implementation should be arranged and systematically to make maximal learning either in development vision, indicator, lesson teory, lesson model proccess, learning evaluation or teacher’s development skill. The process of islamic education curriculum development must be done good and awesome also seeing several factors as supports and obstacles of it. In other to get an education result based on such the plan made before(education planning).
Among abiotic stresses, drought is the most important environmental factor limiting wheat yield and the problem need a genetic solution by bringing diversity in the existing wheat gene pool. Further, better understanding of crop responses to drought stress is a prerequisite for any breeding program. Screening of wheat germplasm comprising 26 synthetic derived (SBW), 24 conventional (CBW) bread wheats and 5 check cultivars (CCT) for drought tolerance was carried out through morpho- physiological and biochemical traits in hydroponics where stress was induced with PEG. Mean values for genotypes and treatments differed highly for all the studied traits. Drought stress resulted in increased osmoprotectants and antioxidant enzymatic activities. The germplasm was evaluated for phenological traits in the field under well- watered and drought stress conditions imposed at pre anthesis stage for two successive growing seasons during 2010/2011 and 2011/2012 crop cycles. Genotypic variations, variation due to treatment and interactions between them were much prominent depicting the widest genetic background possessed by the studied germplasm. Overall, the performance of SBW was quite promising when compared to check cultivars. Some potential drought tolerant lines including AA19, AA24, AA28 and AA46 are recommended for further micro-yield trials by Wheat Program, WWC and its national collaborators. The germplasm was also evaluated for glutenin compositions and key quality parameters. Grain quality analyses have provided a stringent selection sieve to select the drought tolerant genotypes with desirable end-quality characteristics. Several unique D- genome encoded HMW-GS were found along with favorable alleles at A- and B- genomes. D-genome encoded subunit Dx5+Dy10 which is known to encode superior grain quality attributes was observed in 63.6% genotypes followed by 1Dx2+1Dy12 (30.9%). Apart from HMW-GS, PCR based allele specific markers were used to identify allelic variation at Glu-3 loci (LMW-GS), which had a significant effect on visco-elastic properties of wheat dough. Several combinations of favorable LMW-GS alleles were observed at Glu-A3 and Glu-B3 loci. Key quality parameters like protein, sedimentation volume and carotenoids differed significantly within genotypes. Results established significant variability in quality characteristics and glutenin composition among D-genome synthetic-hexaploid wheat derivatives as compared to conventional bread wheat germplasm suggestive of their ability to improve quality traits in bread wheat. The germplasm was genotyped with 101 SSR markers for assessing its genetic diversity. Marker-trait association analysis was employed to identify SSR markers associated with traits related to drought. The stable estimate for the sub-populations (1- 20) was carried out with Structure Software 2.2. TASSEL 2.0.1 was used to calculate Kinship Coefficients Matrix. Association mapping was performed using Q-matrix as covariates and K-matrix (relatedness relationship coefficients) by applying the general linear model and the mixed linear model. In total, 61 marker–trait associations significant in both models were detected at p<0.01. The intra-chromosomal position/location of several of these MTAs coincided with those previously reported whereas some were unique that had not been located to date. Opportunities for further wheat improvement are provided by these novel loci/MTAs based on a marker approach.