Study region: The source region of the Yellow River (SRYE) is located in the eastern part of the Tibetan Plateau is a major water production and water conservation area for the Yellow River. Study focus: This study aims to investigate the correlations between streamflow and meteorological factors/ocean in the SRYE from 1960 to 2018 using wavelet analysis. The effects of meteorological factors/ocean signals on streamflow were calculated using the Partial Least Squares-Structural Equation Model (PLS-SEM). Furthermore, climate factors with strong correlation with streamflow were used as inputs to random forest (RF) and multiple linear regression (MLR) models to predict monthly streamflow. New hydrological insights: Meteorological factors showed stronger correlation with streamflow compared to ocean signals, explaining 79.3% of the streamflow variation and much higher than ocean signals (0.1%). Among the meteorological factors, precipitation had the largest direct effect on streamflow (P < 0.01), followed by potential evapotranspiration (P < 0.01), and snow depth (P > 0.05), which together explained 78% of the streamflow variability. Temperature and relative humidity are two important factors that indirectly influenced streamflow through potential evapotranspiration (P < 0.01). Finally, precipitation, relative humidity, and minimum temperature were chosen as streamflow predictors in the SRYE. The RF showed a better performance in predicting long-term monthly streamflow than the MLR under complex climate-hydrological system.

Droughts cause significant economic damage worldwide. Evaluating their impacts on crop yield and water resources can help mitigate these losses. Using single variables such as precipitation, temperature, the soil moisture condition index (SMCI) and the vegetation condition index (VCI) to estimate drought impacts does not provide sufficient information on these complex conditions. Therefore, this study uses station-based and remote-sensing-based data to develop new composite drought indexes (CDIs), including the principal component analysis drought index (PSDI) and the gradient boosting method drought index (GBMDI). The first dataset includes historical observations of the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and the self-calibrated Palmer drought severity index (SC-PDSI) at the 1-, 3-, 6-, and 12-month timescales. The second dataset consists of remote-sensing-based data including the VCI, SMCI, temperature condition index (TCI), and precipitation condition index (PCI). We validated the results of PSDI and GBMDI by comparing them with historical drought events, in-situ drought indices, and annual winter wheat crop yield data from 2003 to 2022 using a regression model. Our temporal analysis revealed extreme to severe drought events during1990s and 2010s. GBMDI typically aligned with actual drought events and exhibited stronger correlations with in-situ drought indices than PSDI. We observed that drought intensity in winter were more severe than in summer. GBMDI was the most effective method, followed by PSDI, for assessing drought impacts on winter wheat yields. Thus, the proposed integrated monitoring framework and indexes offered a valuable and innovative approach to addressing the complexities of agricultural drought, particularly in evaluating its effects.

Cultivation of high-yield varieties and unbalanced fertilization have induced micronutrient deficiency in soils worldwide. Zinc (Zn) is an essential nutrient for plant growth and its deficiency is most common in alkaline and calcareous soils. Therefore, this study aimed to evaluate the effect of Zn applied either alone or in combination with foliar application on the quality and production of wheat grown in alkaline soils. Zn was applied in the form of zinc sulfate (ZnSo4) to the soil and as a foliar spray during the sowing and tillering stages, respectively. Results showed that Zn fertilization of wheat, irrespective of modes of application, significantly increased grain and biological yield, grain per spike, and 1,000 grains weight over control; however, its effect was more noticeable when applied as 7.5 kg ha−1 of soil Zn combined with foliar Zn at 2.5 kg ha−1. Zn application significantly increased the grain protein content from 9.40% in the control to a maximum of 11.83% at soil Zn of 10 kg ha−1. Similarly, Zn application improved Zn, phosphorus (P), and potassium (K) concentrations in wheat grains. Moreover, correlation analysis showed that the grain Zn concentration was positively correlated with the grain P concentration. The correlation between P concentration in wheat grains and 1,000 grain weight was not significant. A total of 1,000 grains weight was positively correlated with tillers per plant, grain yield, and biological yield. There were positive correlations between protein content, biological yield, grain yield, and tillers per plant. Therefore, soil-applied Zn + foliar application in alkaline soils with limited Zn availability is crucial for improving wheat yield and grain quality.

As a multi-beneficial amendment, biochar is very useful to be applied for improving soil health and crop productivity. Therefore, this study was carried out to assess the influence of wood biochar and mineral nitrogen (N), phosphorus (P) and potassium (K) fertilisers viz, [(control; 100% NPK (120:90:60 kg ha−1); 75% NPK + 5 tonne biochar; 50% NPK + 10 tonne biochar; 25% NPK + 15 tonne biochar and 20 tonne biochar ha−1)] on wheat yield and soil properties under different management practices [(raised bed (more than 30 cm above the ground) and flat-bed)]. Split plot two factors randomised completed block (RCB) design with three replications were used where management practices were placed to main plot, while treatments were assigned to subplots. Maximum spike length, grain per spike, 1000 grain weight, grain and biological yield were obtained with application of 75% NPK + 5 tonne biochar ha−1 under both raised and flat-bed, which were statistically at par to 50% NPK + 10 tonne biochar ha−1. The grain and biological yield observed at 75% NPK + 5 tonne biochar and 50% NPK + 10 tonne biochar ha−1 were significantly higher than that of 20 tonne biochar ha−1. However, maximum soil organic matter, extractable P and K contents with slight increases in soil pH and EC was observed at 20 tonne biochar ha−1. Moreover, almost all agronomic parameters were significantly better in raised bed compared to flat-bed sowing. Hence, the present study suggested that 75% NPK + 5 tonne biochar ha−1 is suitable for improving wheat yield and soil properties.

The global hydrological cycle is susceptible to climate change (CC), particularly in underdeveloped countries like Pakistan that lack appropriate management of precious freshwater resources. The study aims to evaluate CC impact on stream flow in the Soan River Basin (SRB). The study explores two general circulation models (GCMs), which involve Access 1.0 and CNRM-CM5 using three metrological stations (Rawalpindi, Islamabad, and Murree) data under two emission scenarios of representative concentration pathways (RCPs), such as RCP-4.5 and RCP-8.5. The CNRM-CM5 was selected as an appropriate model due to the higher coefficient of determination (R2) value for future the prediction of early century (2021–2045), mid-century (2046–2070), and late century (2071–2095) with baseline period of 1991–2017. After that, the soil and water assessment tool (SWAT) was utilized to simulate the stream flow of watersheds at the SRB for selected time periods. For both calibration and validation periods, the SWAT model’s performance was estimated based on the coefficient of determination (R2), percent bias (PBIAS), and Nash Sutcliffe Efficiency (NSE). The results showed that the average annual precipitation for Rawalpindi, Islamabad, and Murree will be decrease by 43.86 mm, 60.85 mm, and 86.86 mm, respectively, while average annual maximum temperature will be increased by 3.73 °C, 4.12 °C, and 1.33 °C, respectively, and average annual minimum temperature will be increased by 3.59 °C, 3.89 °C, and 2.33 °C, respectively, in early to late century under RCP-4.5 and RCP-8.5. Consequently, the average annual stream flow will be decreased in the future. According to the results, we found that it is possible to assess how CC will affect small water regions in the RCPs using small scale climate projections.

A research study was established at the research farm of the University of Agriculture, Peshawar during winter 2018–2019. Commercial biochars were given to the experimental site from 2014 to summer 2018 and received 0.95, 130 and 60 tons ha−1 of biochar by various treatments viz., (Biochar1) BC1, (Biochar2) BC2, (Biochar3) BC3 and (Biochar4) BC4, respectively. This piece of work was conducted within the same study to find the long-term influence of biochar on the fertility of the soil, fixation of N2, as well as the yie1d of chickpea under a mung–chickpea cropping system. A split plot arrangement was carried out by RCBD (Randomized Complete Block Design) to evaluate the study. Twenty-five kilograms of N ha−1 were given as a starter dosage to every plot. Phosphorous and potassium were applied at two levels (half (45:30 kg ha−1) and full (90:60 kg ha−1) recommended doses) to each of the four biochar treatments. The chickpea crop parameters measured were the numbers and masses of the nodules, N2 fixation and grain yield. Soil parameters recorded were Soil Organic Matter (SOM), total N and mineral N. The aforementioned soil parameters were recorded after harvesting. The results showed that nodulation in chickpea, grain yield and nutrient uptake were significantly enhanced by phosphorous and potassium mineral fertilizers. The application of biochar 95 tons ha−1 significantly enhanced number of nodules i-e (122), however statistically similar response in terms of nodules number was also noted with treatment of 130 tons ha−1. The results further revealed a significant difference in terms of organic matter (OM) (%) between the half and full mineral fertilizer treatments. With the application of 130 tons ha−1 of biochar, the OM enhanced from 1.67% in the control treatment, to 2.59%. However, total and mineral nitrogen were not statistically enhanced by the mineral fertilizer treatment. With regard to biochar treatments, total and mineral N enhanced when compared with the control treatment. The highest total N of 0.082% and mineral nitrogen of 73 mg kg−1 in the soil were recorded at 130 tons ha−1 of biochar, while the lowest total N (0.049%) and mineral nitrogen (54 mg kg−1) in the soil were recorded in the control treatment. The collaborative influence of mineral fertilizers and biochars was found to be generally non-significant for most of the soil and plant parameters. It could be concluded that the aforementioned parameters were greater for treatments receiving biochar at 95 tons or more per hectare over the last several years, and that the combination of lower doses of mineral fertilizers further improved the performance of biochar.

A field experiment was performed at Research Farm of the University of Agriculture Peshawar, Pakistan to evaluate the effect of biochar on soil and plant nitrogen and yielding parameters of mung bean.The experiment was performed in randomize complete block design with split plot arrangement with four replications.Area of each experimental unit was 10.5 m 2 and was applied with biochar at the rate of 0, 20, and 40 t ha -1 along with full and half levels of P and K i-e., (90 kg P, 60 kg K ha -1 and 45 kg P, 30 kg K ha -1 ).Nitrogen was applied to all the experimental units uniformly @ 25 kg N ha -1 .The data showed that all of the analyzed parameters were significantly influenced with various biochar levels except fresh and dry weight of nodules.With full and half dose of P and K application, soil total N and soil organic matter were found significant with an increase of 16% and 7% as compared to half dose.With application of various levels of biochar, a significant increase was recorded in most of the parameters.Data regarding Soil N and soil O.M were found significantly enhanced at 40 t ha -1 with values of 0.15% and 2.64% which were 200% and 94% higher as compared to 0 t ha -1 biochar applications.Other parameters like 1000 grain weight, biological yield (fresh and dry), plant N and number of nodules were significantly affected with 20 t ha -1 biochar application which were increased by 20 %, 33%, 21% and 21% as compared to control.Combined application of P&K and biochar significantly affected soil total nitrogen i-e., 0.16% at (full×40 t ha -1 ) and nodulation number i-e., 36 at (half×20 t ha -1 ).It was concluded that biochar application @ 20 t ha -1 along with half levels of P and K, proved the best treatments combination for most of the plant parameters and hence they are recommended .

Purpose: To develop a bioanalytical high performance liquid chromatography (HPLC) method for the quantification of doxorubicin in biological fluids and polymeric nano-formulations. Methods: Analysis of doxorubicin in polymeric nanoparticles and biological samples was carried out at 252 nm using Purospher (R) RP-18 end-capped column (250mmx4.6mm,5 mu m) secured with a guard column cartridge RP18 (30mmx4.6mm,10 mu m). The mobile phase used was 0.025M phosphate buffer and acetonitrile (ACN) (65:35, v:v) in isocratic mode at a flow rate of 0.9 ml/min, run time of 10 min, column oven temperature of 30 degrees C, and injection volume of 40 mu L. Results: The standard curve for doxorubicin was linear (0.999) in the concentration range of 0.022 1.00 mu g/mL in human and albino mice plasma. Nominal retention times of doxorubicin and IS were 3.5 and 5.5 min, respectively. Mean recovery was within acceptable limits (100 +/- 2 %). The limit of detection (LOD) and limit of quantification (LOQ) were 0.012 and 0.022 mu g/mL, respectively. Conclusion: A reliable HPLC method has been successfully developed, validated and applied for the in vitro analysis of doxorubicin released from polymeric nanoparticles and in vivo pharmacokinetic studies in albino mice. The method may also be applicable to the analysis of doxorubicin in human fluids.

The goal of this study was to observe the impact of different nutrients and their combinations on growth and yield of tomato (Solanum lycopersicum L.) cultivar named Nagina was used at Horticultural Research Area, University of Agriculture, Faisalabad. Parameters like plant height, number of leaves per plant, number of flowers per plant, number of clusters per plant, number of flowers per cluster, number of fruits per plant, average fruit weight (g), yield per plant (kg), number of infected fruits per plant, total soluble solids%, Vitamin C at Fruit Ripening, fruit color were studied. Different combinations and concentrations of boron, calcium and nitrogen were used as treatments in earlier experiments to study their performance and the best one selected for tomato crop. The combinations used were T0 (Control), T1 (Boron=0.1% solution), T2 (Boron=0.2% solution), T3 (Calcium=0.2% solution), T4 (Calcium=0.3% solution), T5 (Nitrogen=2% solution), T6 (Nitrogen=2% solution), T7 (Boron=0.1%+Calcium=0.2% solution), T8 (Boron=0.1%+Calcium=0.3% solution), T9 (Boron=0.2%+Calcium=0.2% solution), T10 (Boron=0.2%+Calcium=0.3% solution), T11 (Boron=0.1%+Calcium=0.2%+nitrogen=2% solution) and T12 (Boron=0.2%+Calcium=0.3% +nitrogen=3% solution).