مروجہ جاگیردارانہ نظام کا تاریخی ارتقاء اور اسلامی تعلیمات کی روشنی میں تقابلی جائزہ

Islamic theory of possession is explicit. It is different from the contemporary feudal system. Islam does not believe in any tribe, nation and ancestry. Islam negates the concept of lordship and slavery. The history of Islam tells us that Muhammad (PBUH) awarded the property to the companion but it was a special gift and his purpose was not to rule. The purpose of feudal system is to land a certain class for political purpose. The Islamic concept of possession is different from feudal system. It is not correct to say that Islam allows the contemporary feudal system

Stability Analysis for Production Traits in Bread Wheat

Cross over interaction is of primary interest when developing relatively stable and high yielding crop cultivars as plant breeders are not only interested in the ranking of genotypes but also how the ranks fluctuate within test sites. Multi-environment trials were conducted to determine genotype by environment interaction (GEI) for production traits in wheat. Eighty-one wheat genotypes were field-planted in alpha lattice design with two replicates across nine environments (E-1 to E-9) in Khyber Pakhtunkhwa, Pakistan during 2013/14, 2014/15 and 2015/16. The E-1, E-2 and E-3 refer to Peshawar during 2013/14, 2014/15 and 2015/16; E-4 and E-5 to Nowshera; E- 6 and E-7 to Swabi while E-8 and E-9 to Charsadda during 2014/15 and 2015/16, respectively. Combined analysis of variance revealed significant GEI for all traits, suggesting that genotypic performance was inconsistent across environments. The GEI explained maximum proportion of total variation and thus had dominating effect in phenotypic expression. Based on mean performance across nine test environments, genotype G-79 had higher number of tillers (181 tillers m-2), grains spike-1 (71), grain yield (4862 kg ha-1) and harvest index (33.8 %) and was thus identified as a leading genotype. Similarly, G-79 produced maximum grain yield in all test environments i.e. E-1 (4537 kg ha-1), E-2 (4840 kg ha-1), E-4 (5035 kg ha-1), E-5 (4976 kg ha-1), E-6 (4797 kg ha-1), E-7 (5024 kg ha-1), E-8 (4767 kg ha-1), E-9 (4886 kg ha-1), except E-3. Similarly, E-1, E-2, E-3, E-6 and E-7 were declared as highly productive environments for grain yield. Correlation coefficients among production traits revealed significant associations of grain yield with tillers m-2 (rg = 0.72**), grains spike-1 (rg = 0.41**), 1000-grain weight (rg = 0.30**) and harvest index (rg = 0.90**). Significant GEI justified further analysis using various stability models. The AMMI analysis revealed a major role of GEI in the expression of tillers m-2 (78.6%), grains spike-1 (71.7%), 1000-grain weight (77.9%) and grain yield (72.4%), realizing inconsistent performance across environments. The GEI sum of squares for grain yield was 5 times larger than that of genotypes, suggesting the possible existence of mega environments. The AMMI analysis partitioned GEI sum of squares into eight principal components. First two principal components (PC1 and PC2) explained half of the variation due to GEI, indicating that the first two principal components were sufficient to explain the complex patterns of GE interaction. Based on AMMI1 and AMMI2 biplots, G-79 was unanimously declared as stable and high yielding genotype. Similarly, first two principal components of GGE biplot analysis cumulatively explained 36.5%, 62.6%, 56.8% and 54.8% variations due to GEI for tillers m-2, grains spike-1, 1000-grain weight and grain yield, respectively. The GGE biplot analysis confirmed the differential response of genotypes across environments, suggesting environment-based expression of genes. The GGE biplot also declared G- 79 as an ideal genotype for tillers m-2, grains spike-1 and grain yield, whereas G-36 for 1000-grain weight. The E-09 appeared to be the most discriminating and representative environment for grains spike-1 and grain yield while E-02 for tillers m-2 and E-01 for 1000-grain weight. The GGE biplot grouped Peshawar (E-01, E-02 and E-03), Nowshera (E-04 only) and Charsadda (E-08 and E-09) as one megaenvironment for yield and yield components. Stability parameters such as AMMI stability value (ASV), regression coefficient (bi), Wricke’s ecovalence (Wi), cultivar superiority measure (Pi), coefficient of variation (CV), Shukla stability measure (σi 2) and non-parametric stability measures Si (1) and Si (2) were strongly correlated with mean performance of genotype, inferring that these models can interchangeably be used. Critical comparison of various statistical models as applied to the data in this study transpired that the recommendations of AMMI and GGE analyses got refined when reviewed in conjunction with other stability models. Application of various stability models in this study identified G-79 as stable and widely adapted genotype for grain yield and its components, therefore, G-79 is recommended for commercialization after necessary procedural requirements.