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Millets are becoming popular due to special features of high nutrition, low inputs, and climate resiliency. While major crops like wheat, rice & maize are exhaustive, resource-loving, and susceptible. There is a need for crop diversification & potential millets to be adapted for sustainability. Faisalabad is the grain belt of Punjab, Pakistan, but only one millet crop, pearl millet, is being cultivated for grain purposes. An alternate crop, foxtail millet study was designed, and 200 exotic accessions of different origins were acquired from the USDA. Germination behavior at optimal controlled temperatures (18 °C, 25°C, 32°C, and 39 °C) was tested, best germination was observed at 32 °C, and 135 out of 200 accessions germinated at ≥80%. These accessions were initially screened for germination strength (G%, G50, MGT, U, GI, Z, and CVG), seedling vigor (SL, RL, SFW, SDW), and preliminary yield tests in the greenhouse, then evaluated under three different field locations of varied soil environments. Principle component analysis (PCA) was performed, and 14 clusters of accessions were sorted out using hierarchical clustering. The high-yielding accessions were selected from each cluster and sown at three different locations/soil environments in the Faisalabad, i.e., 1-ARA, UAF (fertile, low irrigated), 2= DFP, UAF (salt-affected soil), 3= JKA, CJF (fertile, well-irrigated). Results were statistically analyzed & graphically represented using project R for statistical computing. Accessions A73-IN and A101-IN produced the highest grain yield of 3504 kg ha-1 and 2667 kg ha-1 respectively, and a biomass accumulation of 8 t ha-1 at the location JKA, CJF. Yield-related results under low irrigation & saline soil were also significant, however, overall, 69% of yield was reduced in the saline and 67% in low irrigated fields. It was concluded that accessions of Indian origin may be adapted under Faisalabad climate and an additional inquiry into abiotic stresses is required to discover suitable genotypes. [ABSTRACT FROM AUTHOR]

Mungbean is one of the important grain legume crops in Pakistan due to its vigorous growth even in adverse environment. Mungbean is part of daily cuisine in the country but its production is low mostly due to imbalance fertilization. The study was carried out to find best combination of nitrogen (N), phosphorus (P) and potassium (K) for maximum production under less fertile soils during 2017-2018. In this study, three combinations of NPK (i.e., 30:30:0, 30:60:0 and 30:60:30 kg ha-1) were compared with control (without fertilization). Maximum pods per plant (22.43), pod length (9.51 cm), seeds per pod (8.97), 1000 seed weight (44.07 g), seed yield (1163 kg ha-1), biological yield (5231 kg ha-1) and harvest index (24.63 %) were obtained from 30:60:30 kg NPK ha-1 during 2017 and similar trends were found during 2018. Maximum leaf area duration (212.64, 215.09 days), crop growth rate (3.99, 4.02 g m-2 d-1), net assimilation rate (2.46, 2.54 g m-2 d-1) and fraction of intercepted radiation (0.89, 0.88 MJ m-2) were obtained from mungbean plant under 30:60:30 kg ha-1 NPK application during 2017 and 2018, respectively. These results are suggesting that integrated application of nitrogen, phosphorous and potash is very imperative to attain higher production of mungbean under semi-arid environments. It is concluded from the findings that farmers can harvest maximum final outputs of mungbean by the application of 30:60:30 kg ha-1 NPK, respectively. [ABSTRACT FROM AUTHOR]

Agroforestry, intercropping or grass barriers have a great potential to enhance cropping system's productivity and work as a source of soil conservation on hilly terrain. These soil conservation cropping methods comprise of complex interactions between plant, soil and atmosphere. Sustainability of such cropping systems can be assessed by measuring resources use limitations, above ground biomass production (AGB) and Land Equivalent Ratio (LER). Modeling is an alternate approach to assess such cropping systems sustainability. Water, Nutrient and Light Capture in Agro-forestry System (WaNuLCAS) model was used to investigate the sustainability of various soil conservation maize-based cropping systems and to figure out some mitigation strategies to overcome the resources limitation in-case of competition. A two years field experiment (2010, 2011) with maize alone (monocropping, tillage), maize intercropping with chili and hedgerow with and without fertilization and minimum tillage were used to assess the sustainability of these studied cropping systems on uplands of Thailand. The results revealed that maize AGB was maximum 1.8 g m-2 in intercropping treatment of maize intercropping with chili and hedgerow including fertilizer application and minimum tillage. LER also showed that maize intercropping with chili and hedgerow including fertilizer application and minimum tillage used the resources judiciously to produce higher quantity of maize biomass. Model suggested that small but targeted amount of additional nitrogen and phosphorous application overcome nutrient limitation and sustain productivity of cropping systems. Such management options are easy to practice under field condition and can also be adopted by the local farmer's for sustainable crop production in future. [ABSTRACT FROM AUTHOR]

Growth, development, and economic yield of agricultural crops rely on moisture, temperature, light, and carbon dioxide concentration. However, the amount of these parameters is varying with time due to climate change. Climate change is factual and ongoing so, first principle of agronomy should be to identify climate change potential impacts and adaptation measures to manage the susceptibilities of agricultural sector. Crop models have ability to predict the crop’s yield under changing climatic conditions. We used OILCROP-SUN model to simulate the influence of elevated temperature and CO2 on crop growth duration, maximum leaf area index (LAI), total dry matter (TDM), and achene yield of sunflower under semi-arid conditions of Pakistan (Faisalabad, Punjab). The model was calibrated and validated with the experimental data of 2012 and 2013, respectively. The simulation results showed that phenological events of sunflower were not changed at higher concentration of CO2 (430 and 550 ppm). However LAI, achene yield, and TDM increased by 0.24, 2.41, and 4.67% at 430 ppm and by 0.48, 3.09, and 9.87% at 550 ppm, respectively. Increased temperature (1 and 2 °C) reduced the sunflower duration to remain green that finally led to less LAI, achene yield, and TDM as compared to present conditions. However, the drastic effects of increased temperature on sunflower were reduced to some extent at 550 ppm CO2 concentration. Evaluation of different adaptation options revealed that 21 days earlier (as compared to current sowing date) planting of sunflower crop with increased plant population (83,333 plants ha−1) could reduce the yield losses due to climate change. Flowering is the most critical stage of sunflower to water scarcity. We recommended skipping second irrigation or 10% (337.5 mm) less irrigation water application to conserve moisture under possible water scarce conditions of 2025 and 2050. [ABSTRACT FROM AUTHOR]

Unbalanced climate during the last decades has created spatially alarming and destructive situations in the world. Anomalies in temperature and precipitation enhance the risks for crop production in large agricultural region (especially the Southern Punjab) of Pakistan. Detailed analysis of historic weather data (1980-2011) record helped in creating baseline data to compare with model projection (SimCLIM) for regional level. Ensemble of 40 GCMs used for climatic projections with greenhouse gas (GHG) representative concentration pathways (RCP-4.5, 6.0, 8.5) was selected on the baseline comparison and used for 2025 and 2050 climate projection. Precipitation projected by ensemble and regional weather observatory at baseline showed highly unpredictable nature while both temperature extremes showed 95 % confidence level on a monthly projection. Percentage change in precipitation projected by model with RCP-4.5, RCP-6.0, and RCP-8.5 showed uncertainty 3.3 to 5.6 %, 2.9 to 5.2 %, and 3.6 to 7.9 % for 2025 and 2050, respectively. Percentage change of minimum temperature from base temperature showed that 5.1, 4.7, and 5.8 % for 2025 and 9.0, 8.1, and 12.0 % increase for projection year 2050 with RCP-4.5, 6.0, and 8.5 and maximum temperature 2.7, 2.5, and 3.0 % for 2025 and 4.7, 4.4, and 6.4 % for 2050 will be increased with RCP-4.5, 6.0, and 8.5, respectively. Uneven increase in precipitation and asymmetric increase in temperature extremes in future would also increase the risk associated with management of climatic uncertainties. Future climate projection will enable us for better risk management decisions. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium hirsutum L.) is an important fiber crop and is considered the back bone of Pakistan's economy. There are several yields limiting factors which create obstacles to achieve potential seed cotton yield. Among agronomic factors, planting time and cultivar selection are considered as key factors to get optimum seed cotton yield under a particular environmental condition. For this a field study was conducted to evaluate the effect of two planting dates 15th May and 15th June and three cotton cultivars (FH-114, FH-142 and MNH-886) on seed cotton yield at Sahiwal, Punjab (Pakistan) during 2014. The results indicated that sowing of cotton on 15th May significantly enhanced the seed cotton yield (3631.8 kg ha-1) by 45% over the late planting of cotton on 15th June and also improved the yield components. The cultivar FH-142 performed superior in terms of leaf area index (LAI), total dry matter (TDM) (11018 kg ha-1) and seed cotton yield (3281.0 kg ha-1) as compared to the other cultivars. The different planting dates and cultivars significantly affected the sympodial branches per plant and average boll weight of the cotton crop. In conclusion, the selection of suitable cultivar (FH-142) and early planting of cotton at 15th May increased seed cotton yield under semi-arid conditions of Sahiwal. [ABSTRACT FROM AUTHOR]

Suitable cotton variety selection is imperative to cope with temporal variations for yield enhancement and sustainability under unpredictable climatic conditions. Cotton varieties including transgenic (Bacillus thuringiensis) and non-transgenic (non Bt.) were sown from 10-March to 21-June with 20 days interval for two growing seasons (2012 and 2013) consecutively while cotton sowing after wheat harvest is normal practice at farmers' field in Cotton-Wheat cropping system of Punjab-Pakistan. Phenology, growth indices, seed cotton yield (SCY) and its heat use efficiency of varieties were estimated on daily basis by using statistical models. Seed cotton yield (SCY) was significantly correlated with crop duration exhibiting delays in planting (21-June) impact on shortening of phenophases i.e. first square, flower, boll initiation and boll opening by 8, 7, 4 and 6 days, respectively compared with 10-May planting in first season while second season advanced 0-3 days owing to deviation in frequency of cold shock <11 °C and heat stress >35 °C. Long crop cycle varieties AA-802 and IR-3701 took 6-9 days more compared to short season NIAB-112. More heat units accretion 46, 33, 20 and 13 % to switch into next phenophase (first square, flower, boll initiation and boll opening) was computed in 10-May planting than 10-March due to excessive heat stress (>40 °C) during early phenophases while reduced variations observed in later phases. Reproductive stage initiation and accumulated higher thermal time delayed in late mature varieties compared to short one with lower root mean square error (RMSE) and higher coefficient of determination (R²). Significant reduction in days after planting to attain maximum LAI, CGR, TDM and SCY-heat use efficiency (HUESCY) decreased with delay in planting with good statistical indices. Less impact of cold shock and heat stress on 21-April and 10-May plantings noted while 10-March and 21-June planting had higher incidence during early growth phases. Cotton varieties MNH-886 and NIAB-9811 (NIAB-Kiran) planted 30-March to 10-May exhibited higher resilience to variable weather conditions with fostered growth potential and yield. Variety NIAB-112 seemed heat tolerant and it can be recommend for early and especially for late plating while MNH-886 and NIAB-Kiran can be adopted at farmer's field in the region for maximizing cotton production under variable environment. [ABSTRACT FROM AUTHOR]

CSM-CROPGRO-Cotton Model under DSSAT V 4.0.2.0 has been extensively tested and validated in many studies, mainly in United States. The objective of this study was to test and validate this model in three cotton growing regions of Pakistan (Faisalabad, Multan and Sahiwal) for dynamic simulation of development, growth and seed cotton yield of four cotton cultivars (CIM-496, CIM-506, NIAB-111 and SLH-284) at varying nitrogen increments (50, 100, 150 and 200 kg ha-1) sown at different timings (20 May and 10 June). The model was first calibrated with data (phenology, biomass, LAI, and yield components) collected during 2009 at all locations against the best performing treatment May 15 sowing, cv. CIM-496 and 200 kg N ha-1 (D1V1N4) in field trials. The model was then tested with data recorded against remaining thirty-one treatments for all locations. Similarly, the data of year 2010 was used for validation. The simulated values of crop phenology (days to anthesis and maturity) by the model were reliable with the recorded data, with root mean square error (RMSE) less than 2 days during both years. Although RMSE values for LAI approached higher than 1 in many of the treatments, these values for total dry matter and seed-cotton yield were reasonably good (367 to 497 kg ha-1and 122 to 227 kg ha-1, respectively). There is a dire need to assess impact of climate variation on seed cotton yield under various climatic regions of Pakistan to ensure fiber quality and yield in future. [ABSTRACT FROM AUTHOR]

Appropriate nitrogen application and optimum plant population ensure economic crop yield. For assessing the response of sunflower hybridHysun-33 to different plant populations, i.e. 83,333, 66,666 and 55,555 plants ha-1at different N rates of 90, 120 and 150 kg ha-1, a field experiment was undertaken using RCBD in split plot arrangement with three replications at Agronomic Research Area, University of Agriculture, Faisalabad. Results demonstrated that each successive N dose increased the crop biomass, yield and its components although sunflower oil contents were negatively affected. Maximum plant growth and achene yield (3115.4 kg ha-1) were observed at 83, 333 plants ha-1. Conflictingly days to flowering (64.5), achene formation (73.73), physiological maturity (95.98), head diameter (19.16 cm), thousand achene weight (43.53 g) and number of achenes per head (1138.8) were maximum in 55,555 plants ha-1. Application of 150 kg N ha-1 in 83,333 plants ha-1 plant population was found to be best treatment to attain maximum achene yield. [ABSTRACT FROM AUTHOR]

Crop models are particularly valuable for understanding research across varying disciplines, crop system managements and policy analysis. The proposed study was carried out to evaluate the performance of CROPGRO-legume model under Chickpea in irrigated conditions of Faisalabad. The collected data against outstanding treatment in the field was used to calibrate the model and rest of data was used for model evaluation. Model simulated flowering and maturity dates well for all cultivars of chickpea. Comparison of simulated and observed data showed that model simulated TDM and grain yield with RMSE 248 and 34 kg ha-1, respectively. Punjab Masoor-2009, NIAB Masoor-2002 and NIAB Masoor-2006 were simulated accurately by model with the values of R2 96%, 95% and 94% for TDM, respectively. Agreement of statistics (d index) for TDM in all cultivars was 0.90. Generally model simulated well under non stressed condition. However error was higher in simulation at lesser level of nitrogen in all crop parameters. There is dire need to quantify growth and yield under varying climatic conditions to assess the accuracy of model simulations. [ABSTRACT FROM AUTHOR]

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 12lh November with four N levels (N1= 0 kg ha-1, N2= 55 kg ha-1, N3=110 kg ha-1, N4= 220 kg ha-1) and ten cultivars (Faisalabad-2008, Lasani-2008, Miraj-2008, Sahar-2006, Shafaq-2006, GA-2002, Bakkhar-2001, Inqlab-91, Chakwal-50 and Chakwal-97). Split Plot Design was used keeping N levels in main plots and cultivars in subplots with three replications. The results showed that increasing levels of N significantly increased plant height, total dry matter, number of productive tillers, number of grains per spike, 1000-grain weight, grain yield and harvest index. Grain yield was 2670, 3140, 3480 and 4370 kg ha-1 in the respective nitrogen treatments. The application of N @ 220 kg ha-1 in cultivar Faisalabad-2008 resulted in higher yield under irrigated semi-arid conditions of the Punjab. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate the CSM-CERES-Maize model for simulating maize growth and yield against different irrigation regimes in semi-arid conditions of Punjab (Pakistan). The data required to run the model were collected from field experiments conducted at University of Agriculture Faisalabad during 2009 and 2010. Two autumn-sown maize hybrids (Monsanto-919 and Pioneer-30Y87) were grown under variable irrigation regimes: I1 = no irrigation (control), I2 (4 irrigations, 1st at V6 i.e., 6 leaf stage, 2nd at V10, 3rd at V14, 4th at V18), I3 (6 irrigations, the first 4 as in I2 and the subsequent two at reproductive stages R1 and R2), I4 (8 irrigations, the first 6 as in I3 and the subsequent two at R3 and R4), I5 (10 irrigations, the first 8 as in I4 and the subsequent two at R5 and R6), I6: irrigation at 25 mm potential soil moisture deficit (PSMD) and I7: irrigation at 50 mm PSMD. The genetic co-efficients calibrated against the treatment I6 giving superior performance regarding yield and yield components for the two hybrids during 2009, were used to evaluate the model accuracy for irrigation treatments of 2010 season. The model performance during calibration was quite good. During evaluation, the model showed variability of 1.1 to 11.2% and -4.3 to 6.4% in total dry matter and -8.5 to 24.3% and -15.8 to 28.7% in grain yield for Monsanto-919 and Pioneer-30Y87, respectively for different irrigation regimes. Daily simulations of total dry matter were also good with d-statistics values higher than 0.970 in all treatments. The results showed that CSM-CERES-Maize can be successfully used in simulation studies of autumn-sown maize under semi-arid conditions of Punjab. [ABSTRACT FROM AUTHOR]

An experiment was laid out in the Department of Agronomy, University of Agriculture, Faisalabad, Pakistan during the year 2012 under semi-arid climate conditions. Layout system was RCBD with split arrangement to quantify the effects of different irrigation and nitrogen levels on growth and yield of sunflower. Data on achene yield, total dry matter (TDM), leaf area index (LAI), leaf area duration (LAD), fraction of intercepted radiation (Fi) and radiation use efficiency (RUE) were taken. TDM pattern showed sigmoid growth curve for both irrigation and nitrogen levels and showed strong relationship (R2 = 0.96) with LAD. Mean value of fraction of incident PAR (Fi) remained maximum (73%) at 80 days after sowing DAS due to maximum crop canopy development. Five irrigations at different crop growth stages produced 0.47 g/m of TDM for each MJ (mega joule) of accumulated PAR and nitrogen at 150 kg/ha statistically proved to be better in converting radiation into dry matter production. [ABSTRACT FROM AUTHOR]