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| 1 | Morphometry of leaf and shoot variables to assess aboveground biomass structure and carbon sequestration by different varieties of white mulberry(Morus alba L.)显示文摘Mulberry is economically important and can also play a pivotal role in mitigating greenhouse gases.Leaf and shoot traits were measured for Morus alba var.Kanmasi,M.alba var.Karyansuban,M.alba var.Latifolia,and M.alba var.PFI-1 to assess aboveground biomass(AGB)and carbon sequestration.Variety-specific and multivariety allometric AGB models were developed using the equivalent diameter at breast height(EDBH)and plant height(H).The completeharvest method was used to measure leaf and shoot traits and biomass,and the ash method was used to measure organic carbon content.The results showed significant(p<0.01)varietal differences in leaf and shoot traits,AGB and carbon sequestration.PFI-1 variety had the greatest leaf density(mean±SE:1828.3±0.3 leaves tree^(-1)),Karyansuban had the largest mean leaf area(185.94±8.95 cm^(2)).A diminishing return was found between leaf area and leaf density.Latifolia had the highest shoot density per tree(46.6±1.83 shoots tree^(-1)),total shoot length(264.1±2.32 m),dry biomass(16.69±0.58 kg tree^(-1)),carbon sequestration(9.99±0.32 kg tree^(-1))and CO_(2) mitigation(36.67±1.16 kg).The variety-specific AGB models b(EDBH)and b(EDBH)2 showed good fit and reasonable accuracy with a coefficient of determination(R^(2))=0.98-0.99,standard error of estimates(SEE)=0.1125-0.3130 and root mean square error(RMSE)=0.1084-0.3017.The multivariety models bln(EDBH)and(EDBH)0.756 showed good-fitness and accuracy with R^(2)=0.85-0.86,SEE=1.6231-1.6445 and RMSE=1.609-1.630.On the basis of these findings,variety Latifolia has good potential for biomass production,and allometric equations based on EDBH can be used to estimate AGB with a reasonable accuracy. | Ghulam Ali Bajwa Muhammad Umair Yasir Nawab Zahid Rizwan | 2021 | Journal of Forestry Research2021，32，6： | 2 |
| 2 | Darcy-Forchheimer relation in Casson type MHD nanofluid flow over non-linear stretching surface显示文摘Present article aims to discuss the characteristics of Casson type nanofluid maintained to flow through porous medium over non-linear stretching surface in the perspective of heat and mass transfer developments.A Casson type incompressible viscous nanofluid passes through the given porous medium via Darcy-Forchheimer relation.Slip boundary conditions are used for velocity,temperature and concentration of the nanoparticles.Brownian diffusion and thermophoresis is attended.An induced magnetic field effect is involved to accentuate the thermo-physical characteristics of the nanofluid.The model incorporates boundary layer formulations and small magnetic Reynolds for practical validity.A fourth order Runge-Kutta(RK)scheme is enforced to solve the system numerically.Graphs are prepared for various progressive values of non-dimensionalized parameters whereas;variation in wall drag factor,heat and mass transfer rates is analyzed through numerical data.Results indicate that momentum boundary layer reduces for stronger inertial impact and the resistance offered by the porous media to the fluid flow.Temperature is found as a progressive function for the Brownianmotion factor and thermophoresis.The magnitude of wall drag factor,heat transfer and masstransfer rates shows reduction for progressive values of slip parameters. | Ghulam Rasool Ali J.Chamkha Taseer Muhammad Anum Shafiq Ilyas Khan | 2020 | Propulsion and Power Research2020，9，2： | 2 |
| 3 | Proteomic anal- ysis of rice leaf sheath during drought stress显示文摘 | Ghulam Muhammad Ali Setsuko Komatsu | 2006 | Journal of Proteome Research2006，5，2： | 1 |
| 4 | Merits and Demerits of Boundary Element Methods for Incompressible Fluid Flow Problems 显示文摘 | Ghulam Muhammad Nawazish Ali Shah Muhammad Mushtaq | 2009 | Journal of American Science2009，5，6： | 1 |
| 5 | 3D Head Pose Estimation through Facial Features and Deep Convolutional Neural Networks显示文摘Face image analysis is one among several important cues in computer vision.Over the last five decades,methods for face analysis have received immense attention due to large scale applications in various face analysis tasks.Face parsing strongly benefits various human face image analysis tasks inducing face pose estimation.In this paper we propose a 3D head pose estimation framework developed through a prior end to end deep face parsing model.We have developed an end to end face parts segmentation framework through deep convolutional neural networks(DCNNs).For training a deep face parts parsing model,we label face images for seven different classes,including eyes,brows,nose,hair,mouth,skin,and back.We extract features from gray scale images by using DCNNs.We train a classifier using the extracted features.We use the probabilistic classification method to produce gray scale images in the form of probability maps for each dense semantic class.We use a next stage of DCNNs and extract features from grayscale images created as probability maps during the segmentation phase.We assess the performance of our newly proposed model on four standard head pose datasets,including Pointing’04,Annotated Facial Landmarks in the Wild(AFLW),Boston University(BU),and ICT-3DHP,obtaining superior results as compared to previous results. | Khalil Khan Jehad Ali Kashif Ahmad Asma Gul Ghulam Sarwar Sahib Khan Qui Thanh Hoai Ta Tae-Sun Chung Muhammad Attique | 2021 | Computers, Materials & Continua2021，，2： | 1 |
| 6 | TOL6BL突变导致减数分裂程序性DNA双链断裂无法产生和人类不孕显示文摘我们找到一个近亲婚配后代不育家系,该家系有3位非梗阻性无精子症患者和1位原因不明的女性不孕患者.全外显子组测序结合Sanger测序分析发现TOP6BL的c.483dup T突变在该家系中与不孕呈隐性共分离.正常的TOP6BL可与SPO11β结合进而导致减数分裂程序性DNA双链断裂(DSBs)产生,而该突变破坏了二者的结合.对家系中一位男患者的精母细胞进行分析,发现其同源染色体联会异常,减数分裂不能到达粗线期,且染色体轴上缺少减数分裂重组蛋白RPA和DMC1信号,表明其减数分裂程序性DSBs未能产生.我们制备了携带类似患者突变的小鼠,发现突变雄鼠具有与男患者相同的减数分裂异常,突变雌鼠不孕,其卵母细胞中程序性DSBs和减数分裂重组也不能发生,卵母细胞不能成熟.这些发现表明TOP6BL突变可导致人类不孕,为相关不孕不育患者的病因诊断和人工辅助生殖胚胎的遗传检查提供了分子标靶. | 焦玉莹 樊岁兴 Nazish Jabeen 张欢 Ranjha Khan Ghulam Murtaza 蒋涵玮 Asim Ali 李阳 鲍坚强 张贝贝 徐建泽 许波 Hafiz Muhammad Jafar Hussain Qumar Zaman Ihsan Khan Ihtisham Bukhari Furhan Iqbal Ayesha Yousaf Sobia Dil Manan Khan Niaz Ahmad 马慧 江小华 张远伟 史庆华 | 2020 | Science Bulletin2020，65，24： | 1 |
| 7 | Deep Learning Method to Detect the Road Cracks and Potholes for Smart Cities显示文摘The increasing global population at a rapid pace makes road trafficdense;managing such massive traffic is challenging. In developing countrieslike Pakistan, road traffic accidents (RTA) have the highest mortality percentageamong other Asian countries. The main reasons for RTAs are roadcracks and potholes. Understanding the need for an automated system forthe detection of cracks and potholes, this study proposes a decision supportsystem (DSS) for an autonomous road information system for smart citydevelopment with the use of deep learning. The proposed DSS works in layerswhere initially the image of roads is captured and coordinates attached to theimage with the help of global positioning system (GPS), communicated tothe decision layer to find about the cracks and potholes in the roads, andeventually, that information is passed to the road management informationsystem, which gives information to drivers and the maintenance department.For the decision layer, we projected a CNN-based model for pothole crackdetection (PCD). Aimed at training, a K-fold cross-validation strategy wasused where the value of K was set to 10. The training of PCD was completedwith a self-collected dataset consisting of 6000 images from Pakistani roads.The proposed PCD achieved 98% of precision, 97% recall, and accuracy whiletesting on unseen images. The results produced by our model are higher thanthe existing model in terms of performance and computational cost, whichproves its significance. | Hong-Hu Chu Muhammad Rizwan Saeed Javed Rashid Muhammad Tahir Mehmood Israr Ahmad Rao Sohail Iqbal Ghulam Ali | 2023 | Computers, Materials & Continua2023，，4： | 1 |
| 8 | A Novel Auto-Annotation Technique for Aspect Level Sentiment Analysis显示文摘In machine learning,sentiment analysis is a technique to find and analyze the sentiments hidden in the text.For sentiment analysis,annotated data is a basic requirement.Generally,this data is manually annotated.Manual annotation is time consuming,costly and laborious process.To overcome these resource constraints this research has proposed a fully automated annotation technique for aspect level sentiment analysis.Dataset is created from the reviews of ten most popular songs on YouTube.Reviews of five aspects—voice,video,music,lyrics and song,are extracted.An N-Gram based technique is proposed.Complete dataset consists of 369436 reviews that took 173.53 s to annotate using the proposed technique while this dataset might have taken approximately 2.07 million seconds(575 h)if it was annotated manually.For the validation of the proposed technique,a sub-dataset—Voice,is annotated manually as well as with the proposed technique.Cohen’s Kappa statistics is used to evaluate the degree of agreement between the two annotations.The high Kappa value(i.e.,0.9571%)shows the high level of agreement between the two.This validates that the quality of annotation of the proposed technique is as good as manual annotation even with far less computational cost.This research also contributes in consolidating the guidelines for the manual annotation process. | Muhammad Aasim Qureshi Muhammad Asif Mohd Fadzil Hassan Ghulam Mustafa Muhammad Khurram Ehsan Aasim Ali Unaza Sajid | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 9 | Climate Change Perceptions , Impacts and Adaptation Strategies of F arm Households in Potohar Region of Punjab, Pakistan显示文摘Climate change has become a global phenomenon and is adversely affecting agricultural development across the globe.Developing countries like Pakistan where 18.9%of the GDP(gross domestic product)came from the agriculture sector and also 42%of the labor force involved in agriculture.They are directly and indirectly affected by climate change due to an increase in the frequency and intensity of climatic extreme events such as floods,droughts and extreme weather events.In this paper,we have focused on the impact of climate change on farm households and their adaptation strategies to cope up the climatic extremes.For this purpose,we have selected farm households by using multistage stratified random sampling from four districts of the Potohar region i.e.Attock,Rawalpindi,Jhelum and Chakwal.These districts were selected by dividing the Potohar region into rain-fed areas.We have employed logistic regression to assess the determinants of adaptation to climate change and its impact.We have also calculated the marginal effect of each independent variable of the logistic regression to measure the immediate rate of change in the model.In order to check the significance of our suggested model,we have used hypothesis testing. | Sohaib Aqib Syed Mohsin Ali Kazmi Muhammad Amjad Ahmed Ali Soomro Ghulam Farooque Khoso | 2023 | Journal of Energy and Power Engineering2023，17，4： | 0 |
| 10 | Effects of Convolvulus arvensis Water Extract on Germination of Okra Under Different Seed Sizes显示文摘Convolvulus arvensis is a toxic allelopathic weed that suppresses germination and growth of crops.The prime object of present study was to investigate effect of Convolvulus arvensis water extract on germination and performance of okra with different seed sizes.The seeds of okra variety pusa green were separated into three different sizes,viz large size(4.00-5.00 mm),medium size(3.00-3.50 mm)and small size(2.00-3.50 mm),and then soaked in allelopathic plant bindweed water extract and kept in patrisdishes for germination into the germinator at 15℃.The experiment was laid out using Complete Randomized Design(CRD)with three replications.The results showed that after sowing of 12 days the highest germination was observed in non-treated seeds as compared to seeds treated in Convolvulus arvensis water extract for 1 h,further non-treated large seeds produced maximum plants as compared to treated small seeds after sowing of 24 days.Meanwhile,root length,shoot length,root fresh and dry weight,shoot fresh and dry weight were recorded higher in non-treated large seeds as compared to small seeds soaked for 1 h in Convolvulus arvensis allelopthic water extract.It could be found that Convolvulus arvensis affected germination,seed growth and overall performance of okra,further presence Convolvulus arvensis in crops could cause negative impact on germination and integrity of okra crops. | Abid Hussain Khoso Ghulam Mustafa Laghari Aziz Ahmed Laghari Ali Muhammad Bozdar Asif Ali Kaleri Nasir Ali | 2017 | Journal of Northeast Agricultural University(English Edition)2017，24，1： | 0 |
| 11 | Investigation of the sodium storage mechanism of iron fluoride hydrate cathodes using X-ray absorption spectroscopy and mossbauer spectroscopy显示文摘Elucidation of a reaction mechanism is the most critical aspect for designing electrodes for highperformance secondary batteries.Herein,we investigate the sodium insertion/extraction into an iron fluoride hydrate(FeF_(3)·0.5H_(2)O)electrode for sodium-ion batteries(SIBs).The electrode material is prepared by employing an ionic liquid 1-butyl-3-methylimidazolium-tetrafluoroborate,which serves as a reaction medium and precursor for F^(-)ions.The crystal structure of FeF_(3)·0.5H_(2)O is observed as pyrochlore type with large open 3-D tunnels and a unit cell volume of 1129A^(3).The morphology of FeF_(3)·0.5H_(2)O is spherical shape with a mesoporous structure.The microstructure analysis reveals primary particle size of around 10 nm.The FeF_(3)·0.5H_(2)O cathode exhibits stable discharge capacities of 158,210,and 284 mA h g^(-1) in three different potential ranges of 1.5-4.5,1.2-4.5,and 1.0-4.5 V,respectively at 0.05 C rate.The specific capacities remained stable in over 50 cycles in all three potential ranges,while the rate capability was best in the potential range of 1.5-4.5 V.The electrochemical sodium storage mechanism is studied using X-ray absorption spectroscopy,indicating higher conversion at a more discharged state.Ex-situ M?ssbauer spectroscopy strengthens the results for reversible reduction/oxidation of Fe.These results will be favorable to establish high-performance cathode materials with selective voltage window for SIBs. | Ghulam Ali Muhammad Akbar Faiza Jan Iftikhar Qamar Wali Beata Kalska Szostko Dariusz Satuła Kyung Yoon Chung | 2023 | Journal of Energy Chemistry2023，，2： | 0 |
| 12 | In vitro-in vivo correlation study on nimesulide loaded hydroxypropylmethylcellulose microparticles显示文摘This study involves mathematical simulation model such as in vitro-in vivo correlation(IVIVC) development for various extended release formulations of nimesulide loaded hydroxypropylmethylcellulose(HPMC) microparticles(M1,M2 and M3 containing 1,2,and 3 g HPMC,respectively and 1 g drug in each) having variable release characteristics.In vitro dissolution data of these formulations were correlated to their relevant in vivo absorption profiles followed by predictability worth analysis of these Level A IVIVC.Nimaran was used as control formulation to validate developed formulations and their respective models.The regression coefficients of IVIVC plots for M1,M2,M3 and Nimaran were 0.834 9,0.831 2,0.927 2 and 0.898 1,respectively.The internal prediction error for all formulations was within limits,i.e.,<10%.A good IVIVC was found for controlled release nimesulide loaded HPMC floating M3 microparticles.In other words,this mathematical simulation model is best fit for biowaiver studies which involves study parameters as those adopted for M3 because the value of its IVIVC regression coefficient is the closest to 1 as compared to M1 and M2. | Shujaat Ali KHAN Mahmood AHMAD Ghulam MURTAZA Muhammad Naeem AAMIR Rozina KOUSAR Fatima RASOOL Shahiq-u-ZAMAN | 2010 | 药学学报2010，45，6： | 0 |
| 13 | Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset显示文摘Electroencephalogram(EEG)is a method of capturing the electrophy-siological signal of the brain.An EEG headset is a wearable device that records electrophysiological data from the brain.This paper presents the design and fab-rication of a customized low-cost Electroencephalogram(EEG)headset based on the open-source OpenBCI Ultracortex Mark IV system.The electrode placement locations are modified under a 10–20 standard system.The fabricated headset is then compared to commercially available headsets based on the following para-meters:affordability,accessibility,noise,signal quality,and cost.First,the data is recorded from 20 subjects who used the EEG Headset,and signals were recorded.Secondly,the participants marked the accuracy,set up time,participant comfort,and participant perceived ease of set-up on a scale of 1 to 7(7 being excellent).Thirdly,the self-designed EEG headband is used by 5 participants for slide changing.The raw EEG signal is decomposed into a series of band sig-nals using discrete wavelet transform(DWT).Lastly,thesefindings have been compared to previously reported studies.We concluded that when used for slide-changing control,our self-designed EEG headband had an accuracy of 82.0 percent.We also concluded from the results that our headset performed well on the cost-effectiveness scale,had a reduced setup time of 2±0.5 min(the short-est among all being compared),and demonstrated greater ease of use. | Riaz Muhammad Ahmed Ali M.Abid Anwar Toufique Ahmed Soomro Omar AlShorman Adel Alshahrani Mahmoud Masadeh Ghulam Md Ashraf Naif H.Ali Muhammad Irfan Athanasios Alexiou | 2023 | Intelligent Automation & Soft Computing2023，，3： | 0 |
| 14 | Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing显示文摘In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption. | Zaiwar Ali Sadia Khaf Ziaul Haq Abbas Ghulam Abbas Lei Jiao Amna Irshad Kyung Sup Kwak Muhammad Bilal | 2021 | Computers, Materials & Continua2021，，2： | 0 |
| 15 | Decision Support System for Diagnosis of Irregular Fovea显示文摘Detection of abnormalities in human eye is one of the wellestablished research areas of Machine Learning.Deep Learning techniques are widely used for the diagnosis of RetinalDiseases(RD).Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels(PBV).Retinopathy Images(RI)contains sufficient information to classify structural changes incurred upon PBV but Macular Features(MF)and Fovea Features(FF)are very difficult to detect because features ofMFand FF could be found with Similar Color Movements(SCM)with minor variations.This paper presents novel method for the diagnosis of Irregular Fovea(IF)to assist the doctors in diagnosis of irregular fovea.By considering all above problems this paper proposes a three-layer decision support system to explore the hindsight knowledge of RI and to solve the classification problem of IF.The first layer involves data preparation,the second layer builds the decision model to extract the hidden patterns of fundus images by using Deep Belief Neural Network(DBN)and the third layer visualizes the results by using confusion matrix.This paper contributes a data preparation algorithm for irregular fovea and a highest estimated classification accuracy measured about 96.90%. | Ghulam Ali Mallah Jamil Ahmed Muhammad Irshad Nazeer Mazhar Ali Dootio Hidayatullah Shaikh Aadil Jameel | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 16 | Push-Based Content Dissemination and Machine Learning-Oriented Illusion Attack Detection in Vehicular Named Data Networking显示文摘Recent advancements in the Vehicular Ad-hoc Network(VANET)have tremendously addressed road-related challenges.Specifically,Named Data Networking(NDN)in VANET has emerged as a vital technology due to its outstanding features.However,the NDN communication framework fails to address two important issues.The current NDN employs a pull-based content retrieval network,which is inefficient in disseminating crucial content in Vehicular Named Data Networking(VNDN).Additionally,VNDN is vulnerable to illusion attackers due to the administrative-less network of autonomous vehicles.Although various solutions have been proposed for detecting vehicles’behavior,they inadequately addressed the challenges specific to VNDN.To deal with these two issues,we propose a novel push-based crucial content dissemination scheme that extends the scope of VNDN from pullbased content retrieval to a push-based content forwarding mechanism.In addition,we exploitMachine Learning(ML)techniques within VNDN to detect the behavior of vehicles and classify them as attackers or legitimate.We trained and tested our system on the publicly accessible dataset Vehicular Reference Misbehavior(VeReMi).We employed fiveML classification algorithms and constructed the bestmodel for illusion attack detection.Our results indicate that RandomForest(RF)achieved excellent accuracy in detecting all illusion attack types in VeReMi,with an accuracy rate of 100%for type 1 and type 2,96%for type 4 and type 16,and 95%for type 8.Thus,RF can effectively evaluate the behavior of vehicles and identify attacker vehicles with high accuracy.The ultimate goal of our research is to improve content exchange and secureVNDNfromattackers.Thus,ourML-based attack detection and preventionmechanismensures trustworthy content dissemination and prevents attacker vehicles from sharing misleading information in VNDN. | Arif Hussain Magsi Ghulam Muhammad Sajida Karim Saifullah Memon Zulfiqar Ali | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 17 | 机匣凹槽对轴流压气机性能的影响显示文摘燃气轮机压气机的稳定运行范围由于每级最大负荷而减少。最大性能与稳定运行状态密切相关,如果运行状态发生一些快速变化,则会导致流动失稳,并导致旋转失速。为避免这种情况,应保持适当的失速裕度,使轴流压气机性能更好。通过叶尖和机匣壁面处理可以提高失速裕度。为提高轴流压气机的失速裕度,机匣处理被广泛用于被动流动控制。当前的CFD研究使用NASA转子37通过有限体积技术离散3D RANS方程来研究凹槽的性能。为了验证转子37,对一个通道进行了稳态仿真。仿真结果与总压比和效率的实验测量数据非常吻合。根据收敛标准来预测失速。提出了矩形端壁凹槽模型并进行了数值验证。对矩形凹槽和光滑壁面的性能进行对比评估,发现与光滑壁面相比,矩形凹槽的失速裕度增加了6.37%。通过安装凹槽使TLV减至最小,矩形CGCT模型减少了涡流停滞区,有助于延迟失速的发生。机匣凹槽显著提高了轴流压气机的失速裕度,但导致了效率的略微下降。 | Naseem Ahmad Ghulam Ishaque Arif Aziz Zubair Ali Shah Mushayyed Muhammad Ali Khan 郑群 | 2021 | 风机技术2021，63，5： | 0 |
| 18 | Improving Quantitative and Qualitative Characteristics of Wheat (Triticum aestivum L.) through Nitrogen Application under Semiarid Conditions显示文摘Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(cv.Ujala-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for comparison.Two years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher yields.Application of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016. | Muhammad Rafiq Muhammad Saqib Husnain Jawad Talha Javed Sadam Hussain Muhammad Arif Baber Ali Muhammad Sultan Ali Bazmi Ghulam Abbas Marjan Aziz Mohammad Khalid Al-Sadoon Aneela Gulnaz Sobhi F.Lamlom Muhammad Azeem Sabir Jameel Akhtar | 2023 | Phyton-International Journal of Experimental Botany2023，92，4： | 0 |
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