Pakistan Journal of Life and Social Sciences Estimating Growth and Yield Related Traits of Wheat Genotypes under Variable Nitrogen Application in SemiArid Conditions

The current study was conducted at Agronomic Research Area of the University of Agriculture, Faisalabad during 2008-09 and 2009-10 growing seasons, to investigate the grain yield and yield components of ten new wheat cultivars under variable nitrogen (N) levels. Each year, the crop was sown on 12 th November with four N levels (N 1 = 0 kg ha -1 , N 2 = 55 kg ha -1 , N 3 =110 kg ha -1 , N 4 = 220 kg ha -1 ) and ten cultivar

Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan

Unpredictable precipitation trends have largely influenced by climate change which prolonged droughts or floods in South Asia. Statistical analysis of monthly, seasonal, and annual precipitation trend carried out for different temporal (1996–2015 and 2041–2060) and spatial scale (39 meteorological stations) in Pakistan. Statistical downscaling model (SimCLIM) was used for future precipitation projection (2041–2060) and analyzed by statistical approach. Ensemble approach combined with representative concentration pathways (RCPs) at medium level used for future projections. The magnitude and slop of trends were derived by applying Mann-Kendal and Sen's slop statistical approaches. Geo-statistical application used to generate precipitation trend maps. Comparison of base and projected precipitation by statistical analysis represented by maps and graphical visualization which facilitate to detect trends. Results of this study projects that precipitation trend was increasing more than 70% of weather stations for February, March, April, August, and September represented as base years. Precipitation trend was decreased in February to April but increase in July to October in projected years. Highest decreasing trend was reported in January for base years which was also decreased in projected years. Greater variation in precipitation trends for projected and base years was reported in February to April. Variations in projected precipitation trend for Punjab and Baluchistan highly accredited in March and April. Seasonal analysis shows large variation in winter, which shows increasing trend for more than 30% of weather stations and this increased trend approaches 40% for projected precipitation. High risk was reported in base year pre-monsoon season where 90% of weather station shows increasing trend but in projected years this trend decreased up to 33%. Finally, the annual precipitation trend has increased for more than 90% of meteorological stations in base (1996–2015) which has decreased for projected year (2041–2060) up to 76%. These result revealed that overall precipitation trend is decreasing in future year which may prolonged the drought in 14% of weather stations under study

Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan

Land use/land cover (LULC) change has serious implications for environment as LULC is directly related to land degradation over a period of time and results in many changes in the environment. Monitoring the locations and distributions of LULC changes is important for establishing links between regulatory actions, policy decisions, and subsequent LULC activities. The normalized difference vegetation index (NDVI) has the potential ability to identify the vegetation features of various eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. Similarly, the normalized difference built-up index (NDBI) may be used for quoting built-up land. This study aims to detect the pattern of LULC, NDBI, and NDVI change in Lodhran district, Pakistan, from the Landsat images taken over 40 years, considering four major LULC types as follows: water bodies, built-up area, bare soil, and vegetation. Supervised classification was applied to detect LULC changes observed over Lodhran district as it explains the maximum likelihood algorithm in software ERDAS imagine 15. Most farmers (46.6%) perceived that there have been extreme changes of onset of temperature, planting season, and less precipitation amount in Lodhran district in the last few years. In 2017, building areas increased (4.3%) as compared to 1977. NDVI values for Lodhran district were highest in 1977 (up to + 0.86) and lowest in 1997 (up to − 0.33). Overall accuracy for classification was 86% for 1977, 85% for 1987, 86% for 1997, 88% for 2007, and 95% for 2017. LULC change with soil types, temperature, and NDVI, NDBI, and slope classes was common in the study area, and the conversions of bare soil into vegetation area and built-up area were major changes in the past 40 years in Lodhran district. Lodhran district faces rising temperatures, less irrigation water, and low rainfall. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support from government

Simulated CSM-CROPGRO-cotton yield under projected future climate by SimCLIM for southern Punjab, Pakistan

Climate change is widely affecting the agriculture sector in Pakistan with an estimated annual loss of up to 16 billion dollars by the end of 21st century (GOP, 2015). Southern Punjab is famous for producing more cotton than the entire province of Sindh in Pakistan but here the climatic variations largely affect the cotton production. The present research was carried out in Vehari, an arid area of Southern Punjab, Pakistan, to determine the intensity of the climatic impacts on the projected agricultural production of cotton in southern Punjab for 2025 and 2050 using SimCLIM(climate model) with CSM (crop simulation model)-CROPGRO-Cotton by comparing with observed data (2013 and 2014).The integrated assessment model (IAM) SimCLIM uses a statistical approach for regional downscaling. Scenarios for two general circulation models (GCMs) (BCC-CSM1-1 and MIR005) and three greenhouse gas concentration pathways (RCP-8.5, 6.0, 4.5) were developed. The three levels of phosphorous (0, 57, and 114 kg ha(-1)) were applied to find the yield output of cotton cultivars (MNH-886 and FH-142) for the prediction of development and yield with different GCMs. The model predicted that FH-142 would give a higher percentage yield than MNH-886 for 2025 and 2050; the lowest percentage yield would be for MNH-886 at maturity for three RCPs. The lowest percentage change in the yield was projected for MNH-886 by RCP-8.5 ( - 0.77) and ( - 0.85) for 2025 and 2050, respectively. Farmers might have to apply a moderate level of phosphorous (57 kg P ha(-1))to avoid the potential threat of climate change. Both the cultivars MNH-886 and FH-142 are suitable for 57 kg P ha(-1), but cultivar FH-142 performed better when compared to MNH-886 for GCM and three RCPs

Radiation efficiency and nitrogen fertilizer impacts on sunflower crop in contrasting environments of Punjab, Pakistan

Sunflower (Helianthus annuus L.) is the leading non-conventional oilseed crop in Pakistan. Nitrogen fertilizer can affect plant growth and productivity by changing canopy size which has an effect on the radiation use efficiency (RUE) of the crop. The response of sunflower hybrids in terms of phenology, fraction of intercepted radiation (F-i), and RUE to nitrogenous rates (0, 60, 120, 180, and 240 kg ha(-1)) was studied in three field experiments conducted in three various environments: Multan (arid), Faisalabad (semi-arid), and Gujranwala (sub-humid) during spring seasons 2008 and 2009. The treatments were laid out according to a randomized complete block design with split plot arrangements, keeping the sunflower hybrids in main plots and nitrogen rates in subplots, and replicated three times. The results showed Hysun-38 took a maximum number of days to anthesis (101) as compared to Pioneer-64A93 (100) and Hysun-33 (99). The mean values of F-i were 0.850, 0.903, and 0.978, and the estimated values of RUE for total aboveground dry matter were 2.14, 2.47, and 2.65 g MJ(-1) at experimental locations of Multan, Faisalabad, and Gujranwala, respectively. The values of RUE for grain yield (RUEGY) were 0.78, 0.98, and 1.26 g MJ(-1) at experimental locations of Multan, Faisalabad, and Gujranwala, respectively. The average RUEGY values over three locations were 2.61, 2.60, 2.43, and 2.36 g MJ(-2) in N-4 (180 kg ha(-1)), N-5 (240 kg ha(-1)), N-3 (120 kg ha(-1)), and N-2 (60 kg ha-1) treatments, respectively. Increasing rates of N increased RUEGY over the standard treatment N-3 (120 kg N ha(-1)); however, the averaged values over three locations were 1.22, 1.08, 0.99, and 0.92 g MJ(-2) in N-4, N-5, N-3, and N-2 treatments, respectively. Therefore, optimum water and N doses are important for attaining higher RUE, which may enhance sunflower growth and yield

Evaluation and analysis of temperature for historical (1996-2015) and projected (2030-2060) climates in Pakistan using SimCLIM climate model: ensemble application

Climate change is a global issue that's affecting food security. An increase and decrease in temperature due to climate change is expected across many regions of the world. Analysis of 39 weather stations (Pakistan) trend for maximum and minimum temperatures was done on monthly, seasonal and annual observations. Two statistical tests (Sen's slope and Mann-Kendall) were applied to find out the slopes and magnitude of climate change trend. This statistical analysis was carried out to study the possible variations for maximum and minimum temperature trend. A statistical downscaling climate projection model (SimCLIM) was used to predict magnitude of maximum and minimum temperature for 2030 and 2060. Ensemble of 40 General Circulation Models (GCMs) was used with median Representative Concentration Pathway (RCP-6.0) for future projections in SimCLIM. This study showed more number of positive trends for maximum temperature over all the weather stations. Significantly positive temperature trend was observed in February and March for maximum temperature for all sites ranges from 0.06 to 0.51 degrees C. Mostly, statistically significant negative trend (-0.06 to -0.30 degrees C) was found in Balochistan province and northern areas of Pakistan. In future, minimum temperature projected by model showed negative trends for 60% of weather sites for December where, the negative trend also increased for monthly and seasonal analysis. Minimum temperature trend reveal that December has large number of sites with negative trends with high magnitude, which further decreased for annual followed by seasonal analysis. Minimum temperature projections showed similar trends with past December results but negative trends decreased for seasonal and annual resolution. Future projections also reveal that annual maximum and minimum temperature will be increased for 2060 as compared to 2030. These results may have significant effect on agriculture of northern and high mountain areas of Pakistan, which could be managed by sustainable agricultural activities

Optimizing the phosphorus use in cotton by using CSM-CROPGRO-cotton model for semi-arid climate of Vehari-Punjab, Pakistan

Crop nutrient management is an essential component of any cropping system. With increasing concerns over environmental protection, improvement in fertilizer use efficiencies has become a prime goal in global agriculture system. Phosphorus (P) is one of the most important nutrients, and strategies are required to optimize its use in important arable crops like cotton (Gossypium hirsutum L.) that has great significance. Sustainable P use in crop production could significantly avoid environmental hazards resulting from over-P fertilization. Crop growth modeling has emerged as an effective tool to assess and predict the optimal nutrient requirements for different crops. In present study, Decision Support System for Agro-technology Transfer (DSSAT) sub-model CSM-CROPGRO-Cotton-P was evaluated to estimate the observed and simulated P use in two cotton cultivars grown at three P application rates under the semi-arid climate of southern Punjab, Pakistan. The results revealed that both the cultivars performed best at medium rate of P application (57\ua0kg\ua0ha-1) in terms of days to anthesis, days to maturity, seed cotton yield, total dry matter production, and harvest index during 2013 and 2014. Cultivar FH-142 performed better than MNH-886 in terms of different yield components. There was a good agreement between observed and simulated days to anthesis (0 to 1\ua0day), days to maturity (0 to 2\ua0days), seed cotton yield, total dry matter, and harvest index with an error of -4.4 to 15%, 12-7.5%, and 13-9.5% in MNH-886 and for FH-142, 4-16%, 19-11%, and 16-8.3% for growing years 2013 and 2014, respectively. CROPGRO-Cotton-P would be a useful tool to forecast cotton yield under different levels of P in cotton production system of the semi-arid climate of Southern Punjab