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The present study was designed to evaluate the effects of Zinc (Zn) and Boron (B) on agro-morphological and seed quality attributes of Camelina sativa. The experiment consisted of 3 levels (2%, 4% and 6%) of each mentioned nutrients along with control (no application of micronutrients). Means were calculated and subjected to analysis of variance and LSD analysis, at 5 % level of significance. Following parameters viz., plant height (cm), number of branches per plant, number of siliquae per plant, number of seeds per siliquae, thousand seed weight (g), grain yield (kg/ha), harvest index (%), dry matter accumulation (g/m2), crop growth rate (g/m2/day), biological yield (kg/ha), and oil yield (kg/ha) were evaluated. All subjected treatments were tested for every tested parameter, and results revealed significant values comparative to control. It was observed that foliar application of both boron and zinc micronutrients yielded maximum in all parameters in comparison with control which seems promising to improve crop development, oil yield and harvest index of Camelina sativa L.

Oilseed crops play a vital role in the economy of Pakistan, yet the production of oilseeds is far less than the demand for them. White mustard (Sinapis alba L.) is an emerging crop, that belongs to the Brassicaceae family. It is considered to be an alternative to all other oilseed crops for dry temperate climates. White mustard develops rapidly, and has a large canopy and deep rooting system; hence, it can draw up nutrients from deeper layers. This study aimed to evaluate the influence of nitrogen on S. alba agro-morphological attributes and enhance nutrient use efficiencies. During the Rabi seasons of 2019-20 and 2020-21, an experiment was conducted at the University Research Farm, Chakwal Road, Rawalpindi. The study included seven treatments, i.e., T1-Control, T2-20, T3-40, T4-60, T5-80, T6-100, and T7-120 kg·ha−1. Each treatment was replicated three times, and the study utilized a randomized complete block design (RCBD). The results revealed that nitrogen at 100 kg·ha−1 was the optimal concentration and significantly increased the agro-morphological parameters, i.e., plant height (47.01%), primary branches (41.36%), secondary branches (45.33%), 1000 seed weight (54.35%), siliques/plant (41.57%), seeds/silique (52.30%) biological yield (68.38%), seed yield (54.90%), harvest index (11%), and oil yield (38.84%), as compared to the control. Moreover, protein contents and oil contents were significantly increased (5.15% and 6%, respectively), as compared to the control, while glucosinolate content was decreased (4.36%). Similarly, maximum agronomic efficiency (AE), apparent recovery efficiency (ARE) (53%), physiological efficiency (PE), and nutrient use efficiency (NUE) were also improved, as compared to the control. Hence, N application at a concentration of 100 kg·ha−1 can be recommended for S. alba under the present cropping system of Pothwar.

Dryland agricultural system is under threat due to climate extremes and unsustainable management. Understanding of climate change impact is important to design adaptation options for dry land agricultural systems. Thus, the present review was conducted with the objectives to identify gaps and suggest technology-based intervention that can support dry land farming under changing climate. Careful management of the available agricultural resources in the region is a current need, as it will play crucial role in the coming decades to ensure food security, reduce poverty, hunger, and malnutrition. Technology based regional collaborative interventions among Universities, Institutions, Growers, Companies etc. for water conservation, supplemental irrigation, foliar sprays, integrated nutrient management, resilient crops-based cropping systems, artificial intelligence, and precision agriculture (modeling and remote sensing) are needed to support agriculture of the region. Different process-based models have been used in different regions around the world to quantify the impacts of climate change at field, regional, and national scales to design management options for dryland cropping systems. Modeling include water and nutrient management, ideotype designing, modification in tillage practices, application of cover crops, insect, and disease management. However, diversification in the mixed and integrated crop and livestock farming system is needed to have profitable, sustainable business. The main focus in this work is to recommend different agro-adaptation measures to be part of policies for sustainable agricultural production systems in future.

Under the climate change scenario, high-temperature stress declines crop yields. The present study was designed with the objectives to identify the stable heat-tolerant genotypes for grain yield under normal and heat stress conditions at three locations. The 80 mung bean genotypes and 3 check varieties were sown in three agro-ecological zones of Pakistan, namely, Chakwal, Piplan, and Bhakkar. The experiments were planted in two sowing dates, i.e., the normal sowing and late sowing by using an augmented randomized block design with 6 blocks at each location. The plot size for each genotype was 2.4 m2 at all the locations. All cultural and agronomic practices were carried out as per recommendations. Ten randomly selected plants were used to record the yield-related traits. An infrared gas analyzer (IRGA) was used to measure physiological traits like photosynthesis rate and stomatal conductance. To study the nature of relationship among traits, Pearson correlation analysis was done using SPSS software (v. 16.0). The GGE biplots were constructed to graphically represent the genotype and GE interaction of multi-environment data using the software plant breeding tools. Three views of the GGE biplot were generated to display the comparative performance, rank, and stability of each genotype in the tested environments. Correlation and principal component analysis (PCA) revealed a positive interaction of grain yield with pods plant−1, seed pod−1, 100 grain weight, and harvest index, while days to flowering and maturity had a negative association under normal and heat-stressed conditions. The GGE biplot analysis efficiently explained 85.1% of the total variation and demonstrated that among 8 vertex genotypes of polygon biplot, the G14 and G38 were heat tolerant as these genotypes outclassed others in all the heat-stressed environments. In contrast, the genotypes G51 and G74 produced maximum yield under normal conditions (E3 and E5). Among all the genotypes, genetic diversity was observed for grain yield and other morpho-physiological traits. Significant G × E interaction was observed. The genotypes G14, G38, and G51 were identified as stable and heat tolerant in most of the environments. These findings will be helpful for development of heat-tolerant mung bean breeding material in the future.

Phosphate solubilizing bacteria (PSB) is renowned for its excellent potential of converting unavailable forms of phosphorus (P) to a simpler available form in the soil. This P availability not only...

The present study was designed to evaluate the effect of different concentrations of Silica gel on the growth and yield of Camelina sativa. A pot experiment was laid out in Completely Randomized Design (CRD) with three replications at Nanotechnology Laboratory, Department of Agronomy, PMAS Arid Agriculture University Rawalpindi. The experiment consisted of 4 levels (0.15 mg/g, 0.30 mg/g, 0.45 mg/g and 0.60 mg/g) of each mentioned nutrient along with control. The data were recorded and analyzed according to recommended procedure for following parameters viz., germination %, root and shoot length (cm), root and shoot biomass (g), relative water content of leaf and leaf membrane stability index. It was observed that 0.60 mg/g silica gel application increased the seed germination (80%), root length (6.67) cm, shoot length (35.33) cm, root biomass (1.7) g, shoot biomass (5.57) g, relative water content of leaf (0.69) and leaf membrane stability index (0.07). The study concluded that significant effect of silica gel application is crucial and important to improve vegetative attributes of false flax.

Sesame cultivars perform differently in various environments comprising specific locations and years. Micronutrient fertilizers increase crop yields and can enhance resistance to environmental hazards and contribute to potential yield. For assessing the effect of environment and micronutrients, field experiments were carried out at three different locations (BARI, URF and NARC) of Pothwar region, Pakistan, in two succeeding years (2014, 2015). Four sesame cultivars and three micronutrients (Zn, B and Mn) with a control treatment were used in RCB design with a split-plot procedure and four replications. The results showed significant differences in the main effects of all tested factors (cultivars, micronutrients, locations and years). Maximum mean values of plant height, capsules plant−1, biomass yield and seed yield were recorded for SG-30, while TH-6 was the lowest for these parameters. Maximum mean values of capsule length, capsule weight, seeds capsules−1 and the weight of 1000 seeds were recorded for TH-6 but vice versa for SG-30. Maximum capsule length and seeds capsule−1 were observed at NARC, while other growth and yield attributes were maximum at BARI and URF, including biomass yield and seed yield. The interactive effect of cultivar × location × year was highly significant for all growth and yield traits except capsule length. Sesame cultivars revealed a differential response for all traits at three locations during both years. Application of micronutrients significantly augmented all growth and yield features of sesame. Micronutrient fertilizers (i.e., ZnSO4 at 10 kg ha−1, borax at 10 kg ha−1 and MnSO4 at 5 kg ha−1) would increase yield and yield-attributing traits in low- or medium-precipitation areas where suitable cultivars have been designated.

Nutrients are required for plant growth and development, absence or shortage of this could limit crop productivity. However, the misappropriate application of nutrients could cause environmental challenges like greenhouse gas emission, global warming, and climate change. Nutrient dynamics also seem to be affected by climate change as all the processes in which nutrients are taken up, transferred, and cycled over time in an ecosystem are linked with climatic factors directly or indirectly. Many biogeochemical models including APSIM (Agricultural Production Systems Simulator), CropSyst, CERES-EGC, DayCent, DNDC (DeNitrification DeComposition), DSSAT (Decision Support System for Agrotechnology Transfer), EPIC (Environmental Policy Integrated Climate), PaSim, RothC (Rothamsted Carbon Model), and STICS (SimulateurmulTIdisciplinaire pour les Cultures Standard, or multidisciplinary simulator for standard crops) can be used to study the nutrients dynamics which includes uptake from the soil, assimilation, and remobilization in plants. This chapter presents the application of different biogeochemical models to simulate nutrients dynamics, mainly Carbon (C), Nitrogen (N), and Phosphorus (P). Soil organic carbon (SOC) dynamics and loss of N as nitrous oxide (N2O) emission is also discussed by using models like APSIM and DNDC. Finally, life cycle assessment (LCA) is presented as a valuable tool to study environmental impacts associated with all steps of nutrients distribution among different systems. In conclusion, process-based biogeochemical cycles are valuable tools that can be used to study and manage nutrients in soil-crop system under changing climate.

Waste production is associated with human inhabitation and its rate is increasing over time. Globally, the major proportion of waste is disposed of through landfilling and open dumping, which is en...

Recently, there is an increasing trend of using metallic nanoparticles (NPs) in agriculture due to their potential role in remediating soil pollution and improving nutrient utilization from fertilizers. However, evidence suggested that these NPs were toxic to the soil life and their associated functions, and this toxicity depended on their dose, type, and size. Here, a dose-dependent (5, 50, and 100 mg kg−1 soil) toxicity of NiO NPs on poultry manure (PM: 136 kg N ha−1) decomposition, nutrient mineralization, and herbage N uptake were studied in a standard pot experiment. The NPs doses were mixed with PM and applied in soil-filled pots where then ryegrass was sown. Results revealed that the lowest dose significantly increased microbial biomass (C and N) and respiration from PM, whereas a high dose reduced these parameters. This decrease in such parameters by the highest NPs dose resulted in 13 and 41% lower soil mineral N and plant available K from PM, respectively. Moreover, such effects resulted in 32 and 35% lower herbage shoot and root N uptakes from PM in this treatment. Both intermediate and high doses decreased herbage shoot Ni uptake from PM by 33 and 34%, respectively. However, all NPs doses did not influence soil Ni content from PM. Hence, our results indicated that high NPs dose (100 mg kg−1) was toxic to decomposition, nutrient mineralization, and herbage N uptake from PM. Therefore, such NiONPs toxicity should be considered before recommending their use in agriculture for soil remediation or optimizing nutrient use efficiency of fertilizers.

Foliar epidermal features were based on the micromorphology of trichomes types, epidermal cells and stomatal complex. Even though each feature has its own limited taxonomic value but collectively these characteristics may be systematically important especially for the discrimination and identification of complex and problematic taxa. The systematics significance of nonglandular (NGTs) and glandular trichomes (GTs), stomatal complex and epidermal cells of Lamiaceous flora were analyzed by using the light microscopy (LM) and scanning electron microscopy (SEM). Variations on the observed epidermal appendages were divided into two basic types: glandular and nonglandular. GTs can be divided into subtypes: sessile capitate, subsessile capitate, and barrel and sunken. NGTs were also divided into subtypes: dendritic, stellate, conical, falcate, simple and 1-6 cells long having granulate and smooth surface ornamentation. NGTs were the most dominant features of both adaxial and abaxial surfaces of all observed taxa. Vitex negundo, Isodon rugosus, Colebrookea oppositifolia, and Marrubium vulgare could be demarked because of their twisted like appearance of NGTs at the abaxial surface. The Lamiaceae had both hypostomatic and amphistomatic leaf. Stomata were observed as diacytic, anisocytic, and anomocytic. Epidermal cells were found to be irregular, isodiametric, and rectangular. Based on these characters a taxonomic key was developed to delimit the closely related taxa. Distribution and morphology of the foliar epidermal trichomes through SEM highlight an important taxonomic tool used by the taxonomists as an aid to the correct identification of problematic Lamiaceae taxa.

The experimental work presented in this study was carried out with the hypothesis that plant derived smoke enhanced the morphological, physiological and biochemical attributes of a cereal crop, wheat ( Triticum aestivum L.). Furthermore, this study supported the hypothesis that plant derived smoke acts as vegetative growth promoter, inexpensive, rapid and most appropriate eco-friendly bio-fertilizer for sustainable agriculture. Plant derived smoke was generated by burning of plant material (leaf, straws etc) in a specially designed furnace, and seeds were treated with this smoke for different time duration. Four level of plant derived smoke (1 h, 2 h, 3 h and 4 h) along with control were tested on four wheat cultivars in CRD repeated pot experiment. The smoke-related treatments modified number of morphological, physiological and biochemical features of wheat. Compared with the control, aerosol smoke treatment of the seeds significantly improved root length (2.6%), shoot length (7.7%), RFW (0.04%), SFW (0.7%), SDW (0.1%) and leaf area (63.9%). All the smoke-related treatments significantly promoted RWC (17.3%), water potential (1.5%), osmotic potential (1.4%) and MSI (14.6%) whereas a pronounced increase in chlorophyll a (24.9%), chlorophyll b (21.7%) and total chlorophyll contents (15.5%) were recorded in response to aerosol-smoke treatments. Plant derived smoke exposure applied for short time i.e. 1 h & 2 h induced significant results as compared to prolonged PDS exposure (3 h and 4 h). The best results were observed in Pak-13 and Glaxy-13 wheat cultivars. These findings indicated that the plant-derived smoke treatment has a great potential to improve morphological, physiological and biochemical features of wheat crop.

Grain yield stability measurements under varied environmental conditions suggests selection of suitable genotype. Safflower genotypes having different origins were tested for G x E effects on yield using univariate and multivariate statistics in six test environments (three varied climate conditions and combination of years) during 2016–17 and 2017–18. Genotypes were classified as stable or unstable based on multiple stability measures. Comparative yield results reveals different genotypic grain yield response in each environment. High yield (1618.4 kg ha−1) performance and responsiveness of PI-16308 genotype to favorable environment and lowest 1419 kg ha−1 was observed for PI-26748. In lieu of varied climatic condition Env4 showed 37% extra grain yield compared to Env3.The PCA results placed Env1, Env3 and Env5 in one group for producing similar grain yield and rest of the environments showed highest variation. Results of parametric (S2di) and non-parametric (S⁽3), S⁽⁶⁾, NP⁽1⁾, NP⁽2⁾, NP⁽3⁾ & NP⁽⁴⁾) measures indicates that PI-16308 and PI-16315 can be used to improve stability. However, Wricke's ecovalence (Wi2), Shukla's stability variance (σi2), θi, θ(i), S⁽1⁾ and S⁽2⁾ could be considered for improving grain yield of PI-26748 genotype.

Parthenium hysterophorus L. is a noxious annual weed rapidly spreading in cropped areas of the irrigated Punjab and other parts of Pakistan. It has become a major threat to grazing lands and crops in Punjab province. The main objective of this study was to explore the efficacy of different herbicides with various concentrations viz. pendimethalin, S-metolachlor + atrazine, bromoxynil + 2-methyl-4-chloorphenoxyacetic acid, and atrazine at their recommended (407, 711, 445 and 469 g a.i./ha, respectively), 50% lower and 50% higher doses against Parthenium hysterophorus L. Weeds were allowed to grow in a field for three years (2010-2013) where this spring maize experiment was conducted during the years 2013 and 2014. All herbicide treatments at their recommended and higher doses significantly reduced Parthenium dry weight. Minimum density (2.3 and 2.0/m) and dry biomass (39.74 and 43.47 g/m) of parthenium weed was observed with S-metolachlor + atrazine at 711.36 g/ha treatment during 2013 and 2014, respective...

Climate variability and extreme weather might increase in frequency due to climate change, which could have significant effect on chickpea production. Recently, a study was conducted, aided with simulation modeling approach, in different rainfed regions of Pakistan to check the potential impacts of climate variability on chickpea. Initially, varieties were screened on the basis of germination percentage. Two varieties, Balkasar and Thal 2006, performed best in the germination test and thus grown at two locations, i.e., University Research Farm (URF), Koont, Chakwal Road, Rawalpindi (medium), and Bijwal Farm, Fateh Jang (low), rainfall zones of Pothwar, for field evaluation of best-performing varieties of chickpea. During the course of study, different phenological and yield component parameters have been recorded. Collected data was analyzed statistically to see the performance of varieties under different climatic conditions of these two sites. DSSAT_CROPGRO_Chickpea model was used to simulate crop phenology and yield, i.e., above-ground mass and grain yield of chickpea under rainfed conditions. The model was calibrated and validated on the basis of experimental data. Values obtained from model runs were compared with observed values by using validation scores. Simulation outcomes from days to anthesis, days to maturity, and above-ground mass, i.e., biological yield and grain yield, showed that the location URF-Koont proved better for chickpea crop. Observed and simulated data were compared for model efficiency. At both locations, Thal 2006 performed best under water-limited conditions of Pothwar. Based upon these values, further yield was predicted for varying environmental scenarios in order to recommend best-performing varieties in this particular climate.

Biotic stress is one of the major environmental factors that affect the plant’s growth and life cycle. Plant pathogens are major constraints and severe threats to agricultural production in changing climate scenarios. The effects of climate variability on plant diseases and pathogens have been examined in various plant pathosystems. Climate change is predicted to affect the development of pathogens, their survival, vigor, sporulation, multiplicity, and host susceptibility that ultimately cause changes in the crop diseases. It also affects the inoculum dispersion and pathogenicity. These effects vary depending on pathosystems and geographic locations. Climate change not only affects optimal conditions of infection but also host specificity and infection mechanism in plants. Temperature, light, and humidity are the major factors that control the development and growth of diseases. So, climate change is an emerging challenge that is impacting and driving the plants and pathogens growth, disease development in a pathosystem. This overview is aimed to summarize the previous research, reviews, opinions, and recent trends in studying the effects of climate variability on pathogens and plants health. However, managing and predicting climate change impacts are complicated because of the interaction between the indirect effects and global climate change drivers. Similarly, uncertainty in plant disease development models in changing climate needs the diversification in management strategies. Protection of plants against diseases and pathogens is an essential direction for researchers to make the plants more resistant to pests and diseases. There is a need for further research in different areas under multiple climate-changing factors and scenarios using the disease modeling frameworks such as BIOMA and APSIM-DYMEX.

Climatic variations affect growers of dry regions, and so the agricultural management techniques require modification according to the timing and amount of precipitation for the optimization of yield and economic output for a specified season and location. Farm manager preparedness depending on past practices can be enhanced by long-range skilled forecasting of rainfall. The well-known modes of interannual fluctuations affecting the Indian subcontinent are the Indian Ocean Dipole (IOD) and El-Nino Southern Oscillation (ENSO). Dry regions of Pakistan, i.e., Pothwar, are facing a number of key challenges in the prediction of irregular rain. Modeling skewed, zero, nonlinear, and non-stationary data are a few of the main challenges. To deal with this, a probabilistic statistical model was used in three of the dry areas of Pothwar to predict monsoon and wheat-growing season. To find out the prospects of rainfall, occurring in the system, the model utilizes logistic regression through generalized additive models (GAMs). Our study exploits climatic predictors (Pacific and the Indian Ocean SSTs demonstrating the status of the IOD and the ENSO) affecting rainfall fluctuations on the Indian subcontinent for their effectiveness in predicting seasonal rainfall (three rainfall intervals and the monsoon rains throughout the wheat-growing period). The outcome demonstrated that the observed area had the amount and fluctuation of rainfall determined by SSTs, so predictions can be carried out by intellect to overpass the gaps among average and potential wheat yield with a change in management practices, i.e., appropriate time of sowing and use of suitable genotypes. In addition, the forecasting ability score, i.e., R2, RMSE (root-mean-square error), BSS (Brier skill score), S% (skill score S), LEPS (linear error in probability space), NSE (Nash-Sutcliffe model efficiency coefficient), and ROC (receiver operating characteristics, p-value), assessed validation of model for rainfall prediction to verify the effectiveness of GAM and to formulate contrast among varying validation abilities to do cross-validation of rainfall prediction. Likewise, the forecast systems present substantial benefits in enhancing general operational management when used in agriculture production across the whole value chain.

Optimizing nitrogen (N) application timings and rate can improve nutrient uptake and nutrient efficiencies in wheat, particularly under rainfed conditions. Climatic stress in the form of high temperature and drought resulted in the decreased crop physiological traits, hastened maturity and, ultimately, caused lower grain yield. The impact of N application rates as full and split dose at three diverse locations of rainfed Pothwar, Pakistan was studied through field experiments for two years (2013&ndash, 14 and 2014&ndash, 15). Treatments include T1 = control (no fertilizer applied), full dose of N applied at the time of crop sowing, i.e., T2 = 50 kg N ha&minus, 1, T3 = 100 kg N ha&minus, 1 and T4 = 150 kg N ha&minus, 1, and split application of N at different timings at different stages of the crop, called split application of N, i.e., T5: application of 50 kg N ha&minus, 1 (15 kg N ha&minus, 1 (sowing, BBCH (Biologische Bundesanstalt Bundessortenamt und Chemische Industrie) 0): 20 kg N ha&minus, 1 (tillering, BBCH20): 15 kg N ha&minus, 1 (anthesis, BBCH 60), T6: application of 100 kg N ha&minus, 1 (30 kg N ha&minus, 1 (sowing, BBCH 0): 40 kg N ha&minus, 1 (tillering, BBCH 20): 30 kg N ha&minus, 1 (anthesis, BBCH 60) and T7: application of 150 kg N ha&minus, 1 (45 kg N ha&minus, 1 (sowing, BBCH 0): 60 kg N ha&minus, 1 (tillering, BBCH 20): 45 kg N ha&minus, 1 (anthesis, BBCH 60). The three study sites were Islamabad (high rainfall with optimum temperature), University Research Farm (URF)-Chakwal Road, Koont (medium rainfall with moderate temperature), and Talagang (low rainfall with high temperature). Results revealed that the highest stomatal conductance (0.80 mole H2O m&minus, 2 s&minus, 1), net photosynthetic rate (20.07 &mu, mole CO2 m&minus, 1), transpiration rate (9.58 mmole H2O m&minus, 1), intercellular CO2 concentration (329.25 &mu, mole CO2 mol&minus, 1 air), SPAD values (58.86%) and proline contents (35.42 &mu, g g&minus, 1) were obtained from split application of N (T6 = split N100) compared to control and full dose N treatments. Among the sites, these physiological traits remained highest at Islamabad and lowest at Talagang, while between the years, the maximum values of the measured parameters were obtained during 2013&ndash, 14. A similar trend was observed for crop total N, N efficiencies, and agronomic traits of the crop. The results suggested that the optimum N application rate at appropriate timings can help to harvest the real benefits of N. The split dose resulted in the maximum performance of the crop from the physiological parameters to the agronomic traits of the crop.

Optimizing the nitrogen (N) timings and rate can improve nutrient uptake, and nutrient-efficiencies, especially of N in wheat under the changing climate scenario. Climatic stress in the form of high temperature and drought resulted in the decreased crop physiology and, ultimately, grain yield. Taking the example of rainfed wheat, we quantified the impact of N application rates as full and split-dose at three variable sites of rainfed Pothwar, Pakistan by conducting field experiments for two years (2013-14 and 201-15). Treatments include, T1 = Control (No fertilizer applied), full dose of N applied at the time of crop sowing, i.e. T2 = 50 kg N ha-1, T3 = 100 kg N ha-1 and T4 = 150 kg N ha-1 and split application of N at different timings during different stages of the crop called as split application of N, i.e. T5: Application of 50 kg N ha-1 (15 kg N ha-1 (Sowing) : 20 kg N ha-1 (Tillering) :15 kg N ha-1 (Anthesis), T6: Application of 100 kg N ha-1 (30 kg N ha-1 (Sowing): 40 kg N ha-1 (Tillering) : 30 kg N ha-1 (Anthesis) and T7: Application of 150 kg N ha-1(45 kg N ha-1 (Sowing) : 60 kg N ha-1 (Tillering) : 45 kg N ha-1 (Anthesis). Three study sites include viz. Islamabad (High rainfall with optimum temperature), University Research Farm (URF)-Koont (Medium rainfall with moderate temperature), and Talagang (low rainfall with high temperature). Results showed that the highest stomatal conductance (0.80 mole m-2 sec-1), net photosynthetic rate (20.07 μmole m-2s-1), transpiration rate (9.58 mmole m-2s-1), intercellular CO2 concentration (329.25 μmole CO2 mol-1 air), SPAD values (58.86 %) and proline contents (35.42 μg g-1) were obtained for split application of N (T6 = Split N100) compared to control and full dose of N treatments. Among sites, these physiological traits remained highest at Islamabad and lowest at Talagang, while among years, maximum values of the measured parameters were obtained in 2013-14. A similar trend was observed for crop total N, N efficiencies, and agronomic traits of the crop. Our results suggest that optimum N application rate and its suitable timings can help to harvest real benefits of N as in our findings, split dose resulted in the maximum performance of the crop from physiological parameters to the agronomic traits of the rainfed wheat crop.