Investigating science teachers’ technology integration in classrooms: A case study of a private higher secondary school in Karachi, Pakistan

The use of technology in all fields of education has expanded, and investigating the level of technology integration in schools becomes increasingly significant because it offers data-driven technology integration for policymakers, school administrators, and educators to make better budgeting decisions, determine educator professional development needs, and ensure effective and efficient use of technology in schools. This study investigated science teachers’ technology integration in classrooms at a private higher secondary school in Karachi. In this study, the SAMR model and TPACK framework were used to evaluate the technology integration. The SAMR model was used to see at what levels teachers are in technology integration, where substitution is the lowest and redefinition is the highest level of technology integration. The TPACK framework was used to explore the technological, pedagogical, and content knowledge of the teachers. This study employed a qualitative single embedded case study design. Multiple data were collected through document review (syllabus breakup), observations, and participant interviews. Purposive sampling was used to select six in-service science teachers. Even though this case was chosen for its well-established use of technology, the findings of the study indicated that teachers’ use of technology and knowledge about technology integration was at the basic level. The result of the study showed that most of the science teacher participants were at the substitution level and demonstrated low TPACK knowledge. The study concludes by suggesting that sustainable teacher professional development focusing on technology integration and teacher-sustained commitment to learning and use of technology can enhance teachers’ TPACK knowledge and enable them to practice transformative technology integration in classrooms

Performance of four crop model for simulations of wheat phenology, leaf growth, biomass and yield across planting dates.

Robustness of four wheat simulation model were tested with 2-year field experiments of three cultivars across a wide range of sowing dates in two different climatic regions: Faisalabad (semi-arid) and Layyah (arid), in Punjab-Pakistan. Wheat growing season temperature ranged from -0.1°C to 43°C. The wide series of sowing dates was a unique opportunity to grow the wheat in an environment which temperatures varies from -0.1°C to 43°C. The CERES-Wheat, Nwheat, CROPSIM-Wheat and APSIM-Wheat model were calibrated against the least-stressed treatment for each wheat cultivar. Overall, the four models described performance of early, optimum and late sown wheat well, but poorly described yields of very late planting dates with associated high temperatures during grain filling. The poor accuracy of simulations of yield for extreme planting dates point to the need to improve the accuracy of model simulations at the high end of the growing temperature range, especially given the expected future increases in growing season temperature. Improvement in simulation of maximum leaf area index of wheat for all models is needed. APSIM-Wheat only poorly simulated days to maturity of very and extremely late sown wheat compared to other models. Overall, there is a need of improvement in function of models to response high temperature

Influence of seed size and ecological factors on the germination and emergence of field bindweed (Convolvulus arvensis)

An understanding of seed germination ecology of weeds can assist in predicting their potential distribution and developing effective management strategies. Influence of environmental factors and seed size on germination and seedling emergence of Convolvulus arvensis (field bindweed) was studied in laboratory and greenhouse conditions. Germination occurred over a wide range of constant temperatures, between 15 and 40 ºC, with optimum germination between 20 and 25 ºC. Time to start germination, time to 50% germination and mean germination time increased while germination percentage and germination index decreased with an increase in temperature from 20 ºC, salinity and osmotic stress. However, germination was tolerant to low salt (25 mM) or osmotic stress (0.2 MPa), but as salinity and osmotic stress increased, germination percentage and germination index decreased. Seeds of C. arvensis placed at soil surface showed maximum emergence and decreased as seeding depth increased. Seeds of C. arvensis germinated over a wide range of pH (4 to 9) but optimum germination occurred at pH 6 to 8. Under highly alkaline and acidic pH, time to start germination, time to 50% germination and mean germination time increased while germination percentage and germination index decreased. Increase in field capacity caused decreased time to start germination, time to 50% germination and mean germination time but increased germination percentage and germination index. Bigger seeds had low time to start germination, time to 50% germination and mean germination time but high germination percentage and germination index. Smaller seeds were more sensitive to environmental factors as compared to larger or medium seeds. It can be concluded that except for pH, all environmental factors and seed sizes adversely affect C. arvensis as regards seed germination or emergence and germination or emergence traits, and larger seeds result in improved stand establishment and faster germination than small seeds, regardless of moisture stress or deeper seeding depth

Proceedings: 1st International Conference on Food and Agricultural Economics: MODELING THE IMPACT OF CLIMATE CHANGE ON SUNFLOWER (HELIANTHUS ANNUUS L.) PRODUCTIVITY IN PUNJAB, PAKISTAN

A field study was carried out during spring season, 2015 at research area of University College of Agriculture, Sargodha and Adaptive Research Farm Karor (Dist. Layyah) to investigate the climate change impact on growth, development and yield of sunflower hybrids planting at different times. The experiments were comprised of three sunflower hybrids (Hysun 33, S-278 and SF-0046) sown at three different dates (29th Jan, 14th Feb and 1st Mar) under randomized complete block design (RCBD) with split plot arrangement. Hybrids were randomized in main plots and sowing dates in sub-plots. Maximum achene yield (4213.2 kg ha-1) was produced by Hysun-33 followed by SF-0046 (3721.4 kg ha-1) and S-278 (3531.3 kg ha-1). In case of sowing dates (29th Jan) performed best for growth, development and yield as compared to 14th Feb and 1st Mar. The APSIM (Agricultural Production System Simulator) Model was calibrated successfully by adjusting genetic coefficients by using data on phenology, growth and yield of sunflower hybrids of 29th Jan sowing. Average error of three cultivars in calibration of achene yield and total dry matter was (17% and 7.6) at Sargodha and (22 and 5.9) at Layyah location. Evaluation of model was done against the observed data of remaining two sowing dates. The average error between achene yield and total dry matter for 14th Feb was (9% and -9%) at Sargodha and (11.7% and -8.9%) at Layyah location. For 1st March error was (23.5% and -6.6) at Sargodha while, (-9.8% and -13.4%) at Layyah location. The climate change analysis describes the strong effect on sunflower production. The factors which were changed are temperatureand CO2. So, the model was sensitized at different temperatures and CO2 levels. The achene yield was increased averagely under all three concentrations (395 ppm, 480 ppm and 560 ppm) for sowing date 29th Jan and 14th Feb and decreased for 1st March at Sargodha while, at Layyah decrease averagely at both 14th Feb and 1st March sowing. However, in case of increase in temperature (1oC, 2oC, 3oC achene yield increased averagely for 29th Jan and decreased for 14th Feb and 1st March at Sargodha. While, at Layyah for both 29th Jan and 14th Feb yield showed increased and decreased for 1st March

Development of Climate Change Adaptation Strategies for Rice-wheat Cropping System of Punjab Pakistan

Climate change is an established fact and its impacts on water, agriculture, health, biodiversity, forest and socio-economic sectors are quite visible around the globe. By virtue of its geographical location, Pakistan is highly vulnerable to the consequent climate change because of global warming. Adaptation to climate change and building resilience among ecosystems and people to respond to climate variability and hazard threats are relatively new concepts. Rice-wheat cropping system zone is the bread basket of Punjab, Pakistan and comprising more than 1 million farm families. There is an urgent need for improved climate modeling and forecasting that can provide a basis for informed decision-making and the implementation of adaptation strategies. For this study crop growth models (DSSAT and APSIM) were calibrated and evaluated on experimental field data to develop the robust genetic coefficients. Models were validated using farmers’ field data. Survey data for rice and wheat in Rice-wheat cropping zone of Punjab were collected for this study. An extensive farm survey for 155 farms from the selected five districts Sheikhupura, Nankana Sahib, HafizAbad, Gujranwala, and Sialkot was conducted. Surveyed data (initial condition, crop management, soil characteristic) were used to create the input files in both DSSAT and APSIM. The past climate of the study region, baseline (1981–2010) was analyzed by using the available weather station data and future climate projection were generated by General Circulation Models (GCMs) for mid-century (2040-2069) under RCP 8.5. Five GCMs (CCSM4, GFDLESM2M, HadGEM2-ES, MIROC5, and MPI-ESM-MR) were used for the generation of climate projections. Trade of Analysis model for Multidimensional (TOA-MD) was used for economic analysis. Results of climate change scenarios showed that there would be mean 2.8 °C rise in maximum and 2.2 31 °C in minimum temperature for mid-century (2040-2069) in Rice-wheat (RW) cropping system of Punjab, Pakistan. In Rice average yield reduction in DSSAT and APSIM was 15.2% and 17.2% while in Wheat average yield reduction by DSSAT and APSIM was 14.1% and 12% during mid-century (2040-2069). A close agreement was observed between farmer and simulated fine rice yield with good statistical indices such as Root Mean Square Error (RMSE) 409 kg ha-1 and 440 kg ha-1 with d-index (0.80 and 0.78) for DSSAT and APSIM models, respectively. Economic loss of 83% farm household, if they continue to use current production technology in changed climate. Adaptation strategies using Representative Concentration Pathways (RAP’s) were developed to achieve high productivity and meet the need of growing population, it would be required to increase the planting density, fertilizer use and reduce the irrigation amount up to 15% over current with greater potential for promising cultivars. This suggested that due to projected rise in temperature, the cropping seasons will be affected and 5 days earlier transplanting of rice nursery and two weeks earlier in wheat planting over current would be recommended. These strategies have a significant impact in reducing the vulnerabilities of the changing climate with 33% improvement in rice yield to sustain production in Rice-wheat cropping system. Significant reduction in poverty (5-6%) among farm households, if adaptation takes place in this zon

Performance of four crop model for simulations of wheat phenology, leaf growth, biomass and yield across planting dates - Fig 1

<p>Evaluation of models CERES-Wheat, APSIM-Wheat, CROPSIM-Wheat and DSSAT-Nwheat with observed data for Days to anthesis (Fig a, b, c and d), Days to Maturity (Fig e, f, g and h), Maximum LAI (Fig i, j, k and l), Above ground biomass (Fig m, n, o and p) and grain yield (Fig q, r, s and t) of three varieties (Lasani-2008, Punjab-2011 and Galaxy-2013) during 11 planting dates 15^th October to 15^th march with interval of 15 days.</p

Development of Climate Change Adaptation Strategies for Rice-wheat Cropping System of Punjab Pakistan

Climate change is an established fact and its impacts on water, agriculture, health, biodiversity, forest and socio-economic sectors are quite visible around the globe. By virtue of its geographical location, Pakistan is highly vulnerable to the consequent climate change because of global warming. Adaptation to climate change and building resilience among ecosystems and people to respond to climate variability and hazard threats are relatively new concepts. Rice-wheat cropping system zone is the bread basket of Punjab, Pakistan and comprising more than 1 million farm families. There is an urgent need for improved climate modeling and forecasting that can provide a basis for informed decision-making and the implementation of adaptation strategies. For this study crop growth models (DSSAT and APSIM) were calibrated and evaluated on experimental field data to develop the robust genetic coefficients. Models were validated using farmers’ field data. Survey data for rice and wheat in Rice-wheat cropping zone of Punjab were collected for this study. An extensive farm survey for 155 farms from the selected five districts Sheikhupura, Nankana Sahib, HafizAbad, Gujranwala, and Sialkot was conducted. Surveyed data (initial condition, crop management, soil characteristic) were used to create the input files in both DSSAT and APSIM. The past climate of the study region, baseline (1981–2010) was analyzed by using the available weather station data and future climate projection were generated by General Circulation Models (GCMs) for mid-century (2040-2069) under RCP 8.5. Five GCMs (CCSM4, GFDLESM2M, HadGEM2-ES, MIROC5, and MPI-ESM-MR) were used for the generation of climate projections. Trade of Analysis model for Multidimensional (TOA-MD) was used for economic analysis. Results of climate change scenarios showed that there would be mean 2.8 °C rise in maximum and 2.2 31 °C in minimum temperature for mid-century (2040-2069) in Rice-wheat (RW) cropping system of Punjab, Pakistan. In Rice average yield reduction in DSSAT and APSIM was 15.2% and 17.2% while in Wheat average yield reduction by DSSAT and APSIM was 14.1% and 12% during mid-century (2040-2069). A close agreement was observed between farmer and simulated fine rice yield with good statistical indices such as Root Mean Square Error (RMSE) 409 kg ha-1 and 440 kg ha-1 with d-index (0.80 and 0.78) for DSSAT and APSIM models, respectively. Economic loss of 83% farm household, if they continue to use current production technology in changed climate. Adaptation strategies using Representative Concentration Pathways (RAP’s) were developed to achieve high productivity and meet the need of growing population, it would be required to increase the planting density, fertilizer use and reduce the irrigation amount up to 15% over current with greater potential for promising cultivars. This suggested that due to projected rise in temperature, the cropping seasons will be affected and 5 days earlier transplanting of rice nursery and two weeks earlier in wheat planting over current would be recommended. These strategies have a significant impact in reducing the vulnerabilities of the changing climate with 33% improvement in rice yield to sustain production in Rice-wheat cropping system. Significant reduction in poverty (5-6%) among farm households, if adaptation takes place in this zon

Normalized root mean square error (%) of days to anthesis and maturity, grain and biological yield and leaf area index maximum of CROPSIM-Wheat, CERES-Wheat, DSSAT-Nwheat and APSIM-Wheat with observed data during 2013–14 and 2014–15 at Faisalabad.

<p>Normalized root mean square error (%) of days to anthesis and maturity, grain and biological yield and leaf area index maximum of CROPSIM-Wheat, CERES-Wheat, DSSAT-Nwheat and APSIM-Wheat with observed data during 2013–14 and 2014–15 at Faisalabad.</p

Organic Amendments and Reduced Tillage Accelerate Harvestable C Biomass and Soil C Sequestration in Rice–Wheat Rotation in a Semi-Arid Environment

Rice–wheat crop rotations have high carbon fluxes. A 2-year field study in Punjab, Pakistan quantified impacts of different nutrient management on harvestable carbon biomass, crop-derived C, soil organic C sequestration (SCS), and decomposition. Treatments included different combinations of mineral fertilizer, animal manure (20 Mg ha−1), and incorporated crop residue in a split-plot design under conventional tillage (CT) and reduced tillage (RT). Combined use of mineral fertilizer and manure resulted in (1) 12.56% to 53.31% more harvestable C biomass compared to use of fertilizer and manure alone and (2) 18.27% to 60.72% more crop-derived C inputs relative to using only fertilizer or manure across both tillage practices. Combined fertilizer/manure treatments also significantly enhanced SCS relative to using fertilizer alone. Using only manure increased SCS by 63.25% compared with fertilizer alone across both tillage practices. The relationship between SCS and C inputs indicated high humification (14.50%) and decomposition rates (0.46 Mg ha−1 year−1) under CT compared to RT at 0–15 cm soil depth. At 15–30 cm soil depth, rates of humification (10.7%) and decomposition (0.06 Mg ha−1 year−1) were lower for CT compared to RT. Combined manure/fertilizer treatments could induce high C sequestration and harvestable C biomass with reduced decomposition in rice–wheat rotations

Percentage differences (%) between observed and simulated data of four models CROPSIM-Wheat, CERES-Wheat, DSSAT-Nwheat and APSIM-Wheat for calibration of cultivars coefficients of Lasani-2008, Punjab-2011 and Galaxy-2013.

<p>Percentage differences (%) between observed and simulated data of four models CROPSIM-Wheat, CERES-Wheat, DSSAT-Nwheat and APSIM-Wheat for calibration of cultivars coefficients of Lasani-2008, Punjab-2011 and Galaxy-2013.</p