Portrayal of Positive Psychological Capital in Quran

The present study aims at exploring positive psychological capital in the verses of Qur’an. Positive psychology is the latest advancement in the field of psychology which focuses on improving the well-being of society. Positive psychological capital refers to the combination of overall qualities of positive psychology that contributes to the well-being and mental health. The present study is based on the content analysis of the verses of Qur’an. Content analysis comprises of three steps including identifying the categories or themes, dividing the information into units or parts and finally rating all the themes in all units. In the first step the researchers identified 41 themes from Qur’an by using committee approach and reading the verses between the lines. All these categories were identified by keeping in view the underlying themes of positive psychology. In the second step 30 units were devised from Qur’an by considering each Part as a single unit. The categories included behavior modification, belief in divine help, brotherhood, bravery, contentment, civility, credibility, encouragement of virtue, emotional regulation, excellence, forgiveness, generosity, gratitude, honesty, hopefulness, humility, justice, knowledge, lawful spending, learning, meaningfulness, mindfulness, moderation, obedience, patience, peace, determination, positivity, prosperity, repentance, resilience, reward, self-actualization, self-awareness, self-control, sincerity, social leadership, truthfulness, trust, and wisdom. Results suggest that the most prominent category in Qur’an is the reward. Validity of the study was maintained through the selection of the themes with the help of committee approach. Reliability of the scoring system was maintained through partial inter-rater reliability. Overall the present research has many implications in the positive psychology of religion.    

Modeling the Potential Impacts of Climate Change and Adaptation Options for Rainfed Wheat

The environment of our globe is changing due to climate change (CC) which is influencing agricultural and agronomic practices. Being open to vagaries of nature, agriculture sector is highly vulnerable to climate change phenomena. Any change in climate ultimately influenced food security. Keeping in view the climate change phenomenon the current study aided with simulation modeling was carried out during wheat growing season of 2013-14 and 2014-15 at rainfed Pothwar. Experiments arranged in Randomized Complete Block Design were conducted having five wheat genotypes (Dharabi, Chakwal-50, NARC-2009, Pak-13 and AUR- 809), four sowing dates (21-30 Oct, 10-20 Nov, 01-10 Dec and 20-30 Dec of 2013- 14 and 2014- 15), and three climatically varying locations i.e. Islamabad, URFKoont and Talagang characterized by high, medium a nd low rainfall and low, medium and high temperature areas respectively. Climate data required for the study was collected from the met observatory located at NARC and for URF-Koont and Talagang it was generated by downscaling. Increase in temperature at Islamabad (1oC), URF-Koont (4.6 oC) and Talagang (4.8oC) was observed during study period than the baseline temperature. Wheat crop days to maturity and LAI reduced by 15% and 51% respectively due to higher temperature (4.8 oC). Biological yield ranged 9.7 t ha-1 to 4.72 t ha-1 from low temperature zone (Islamabad) to higher temperature zone (Talagang). Therefore, due to 1 oC increase in temperature, 7.6% reduction in biological yield was observed. Maximum grain yield observed at Islamabad (2.39 t ha-1) while minimum grain yield recorded at Talagang (2.19 t ha-1). Similarly, among genotypes, the performance of Pak-13 and AUR-809 was better than other genotypes therefore, their genetic blood should be used in future for breeding programs. Grain growth curve was also developed in relation to temperature. Grain growth curve depicted 8.2 % reduction in individual grain weight due to 1oC increased temperature. Maximum water use efficiency was recorded at URF-Koont (7.43 kg mm-1) than Talagang (7.14 kg mm-1) and Islamabad (6.23 kg mm-1) which showed higher water productivity due to less evapotranspiration. Agricultural Production Systems Simulator (APSIM), Cropping System Model (CropSyst) and Decision Support System for Agrotechnology Transfer (DSSAT) models were parameterized. Validation skill scores like d-Index, RMSE, and coefficient of determination (R2) were used to determine the performance of models which confirmed the field results with good accuracy (R2 for grain yield was 0.97, 0.96, 0.92 for APSIM, CropSyst and DSSAT respectively). Different global circulation models (GCMs) were used under varying RCPs (Representative concentration pathways). Future projections showed that under current management practices at Islamabad, URF-Koont and Talagang wheat yield will be reduced. Under RCP 4.5, GCMs showed that during early scenarios i.e. 2030, SD2 (5-10 November sowing) will be beneficial, while under later years 15-October sowing will be beneficial.Under RCP 8.5 (higher temperature and low rainfall), GCMs showed even severe results showing reduction in wheat productivity. Adaptation based upon results should include SD2 (01-10 November sowing) for early scenarios i.e. 2030, while for later scenarios i.e. 2050 and 2070, SD1 i.e. 15-25 October sowing will be beneficial in order to avoid terminal heat stress during grain filling stages of wheat. Genotypes Pak-13 and AUR-809 showed great potential to produce sustainable crop yield under higher temperature therefore, these two genotypes should be considered for temperature extremes. Crop models should be used as decision support tools to reduce agricultural environment vulnerability to climate variability.