ORCID Profile
0000-0002-2823-9959
Current Organisations
Muhammad Nawaz Shareef University of Agriculture
,
Rheinische Friedrich-Wilhelms-Universität Bonn
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Publisher: Springer Singapore
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 04-11-2018
DOI: 10.1007/S11356-017-0592-Z
Abstract: 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
Publisher: MDPI AG
Date: 30-09-2021
DOI: 10.3390/RS13193916
Abstract: Rapid and reliable flood information is crucial for minimizing post-event catastrophes in the complex river basins of the world. The Chenab River basin is one of the complex river basins of the world, facing adverse hydrometeorological conditions with unpredictable hydrologic response. Resultantly, many vicinities along the river undergo destructive inundation, resulting in huge life and economic losses. In this study, Hydrologic Engineering Centre–Hydrologic Modeling System (HEC-HMS) and HEC–River Analysis System (HEC-RAS) models were used for flood forecasting and inundation modeling of the Chenab River basin. The HEC-HMS model was used for peak flow simulation of 2014 flood event using Global Precipitation Mission (GMP) Integrated Multisatellite Retrievals-Final (IMERG-F), Tropical Rainfall Measuring Mission_Real Time (TRMM_3B42RT), and Global Satellite Mapping of Precipitation_Near Real Time (GSMaP_NRT) precipitation products. The calibration and validation of the HEC-RAS model were carried out for flood events of 1992 and 2014, respectively. The comparison of observed and simulated flow at the outlet indicated that IMERG-F has good peak flow simulation results. The simulated inundation extent revealed an overall accuracy of more than 90% when compared with satellite imagery. The HEC-RAS model performed well at Manning’s n of 0.06 for the river and the floodplain. From the results, it can be concluded that remote sensing integrated with HEC-HMS and HEC-RAS models could be one of the workable solutions for flood forecasting, inundation modeling, and early warning. The concept of integrated flood management (IFM) has also been translated into practical implementation for joint Indo-Pak management for flood mitigation in the transboundary Chenab River basin.
Publisher: Springer Singapore
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 17-01-2018
DOI: 10.1007/S10529-018-2510-Y
Abstract: As PCR methods have improved over the last 15 years, there has been an upsurge in the number of new DNA marker tools, which has allowed the generation of high-density molecular maps for all the key Brassica crop types. Biotechnology and molecular plant breeding have emerged as a significant tool for molecular understanding that led to a significant crop improvement in the Brassica napus species. Brassica napus possess a very complicated polyploidy-based genomics. The quantitative trait locus (QTL) is not sufficient to develop effective markers for trait introgression. In the coming years, the molecular marker techniques will be more effective to determine the whole genome impairing desired traits. Available genetic markers using the single-nucleotide sequence (SNP) technique and high-throughput sequencing are effective in determining the maps and genome polymorphisms amongst candidate genes and allele interactions. High-throughput sequencing and gene mapping techniques are involved in discovering new alleles and gene pairs, serving as a bridge between the gene map and genome evaluation. The decreasing cost for DNA sequencing will help in discovering full genome sequences with less resources and time. This review describes (1) the current use of integrated approaches, such as molecular marker technologies, to determine genome arrangements and interspecific outcomes combined with cost-effective genomes to increase the efficiency in prognostic breeding efforts. (2) It also focused on functional genomics, proteomics and field-based breeding practices to achieve insight into the genetics underlying both simple and complex traits in canola.
Publisher: Wiley
Date: 09-11-2018
DOI: 10.1002/WIDM.1292
Abstract: The Internet of Things (IoT) is the result of the convergence of sensing, computing, and networking technologies, allowing devices of varying sizes and computational capabilities (things) to intercommunicate. This communication can be achieved locally enabling what is known as edge and fog computing , or through the well‐established Internet infrastructure, exploiting the computational resources in the cloud. The IoT paradigm enables a new breed of applications in various areas including health care, energy management and smart cities. This paper starts off with reviewing these applications and their potential benefits. Challenges facing the realization of such applications are then discussed. The sheer amount of data stemmed from devices forming the IoT requires new data mining systems and techniques that are discussed and categorized later in this paper. Finally, the paper is concluded with future research directions. This article is categorized under: Fundamental Concepts of Data and Knowledge Big Data Mining Application Areas Health Care Application Areas Industry Specific Applications
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 04-2017
Publisher: Wiley
Date: 09-2019
Publisher: Elsevier BV
Date: 05-2019
Publisher: Elsevier
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 05-03-2018
DOI: 10.1007/S11356-018-1587-0
Abstract: 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 CO
Publisher: Springer Science and Business Media LLC
Date: 16-11-2021
Publisher: Elsevier BV
Date: 12-2017
Publisher: Springer Science and Business Media LLC
Date: 08-06-2017
DOI: 10.1007/S11356-017-9308-7
Abstract: The combination of nitrogen and plant population expresses the spatial distribution of crop plants. The spatial distribution influences canopy structure and development, radiation capture, accumulated intercepted radiation (Sa), radiation use efficiency (RUE), and subsequently dry matter production. We hypothesized that the sunflower crop at higher plant populations and nitrogen (N) rates would achieve early canopy cover, capture more radiant energy, utilize radiation energy more efficiently, and ultimately increase economic yield. To investigate the above hypothesis, we examined the influences of leaf area index (LAI) at different plant populations (83,333, 66,666, and 55,555 plants ha
Publisher: Elsevier BV
Date: 06-2018
Publisher: Springer Science and Business Media LLC
Date: 04-01-2017
DOI: 10.1007/S11356-016-8311-8
Abstract: 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 kg ha
Publisher: SAGE Publications
Date: 03-2016
DOI: 10.5367/OA.2015.0226
Abstract: Climate change, food security, water scarcity and environmental sustainability have all become major global challenges. As a consequence, improving resource use efficiency is an important aspect of increasing crop productivity. Crop models are increasingly being used as tools for supporting strategic and tactical decision making under varying agro-climatic and socioeconomic conditions. These tools can also support climate change assessment and the evaluation of adaptation strategies to limit the adverse impacts of climate change. In this paper, the authors report on a case study conducted to assess the potential impact of climate change on grain yield in sunflower under arid, semi-arid and subhumid conditions in the Punjab region of Pakistan. Experimental data obtained between 2008 and 2009 were used for model evaluation. The study focused on the impacts of incremental temperature change on sunflower production. The modelling suggests that grain yield could reduce by up to 15% by the 2020s with an average increase in temperature of +1°C, and by up to 25% if temperatures increased by up to 2°C for the 2050s. Adaptation strategies showed that, if the crop were sown between 14 days (for 2020) and 21 days (for 2050) earlier than the current date (last week in February), yield losses could potentially be reduced.
Publisher: MDPI AG
Date: 16-12-2021
DOI: 10.3390/LAND10121392
Abstract: The present investigation was conducted to understand the role of enriched biochar on soil nitrogen and carbon dynamics, leaching losses of nutrients, and growth attributes of wheat. Buffalo slurry (BS) was used to enrich the biochar for 24 h and 2% biochar (SB) or enriched biochar (SEB) was used. Enrichment of biochar with BS as SEB improved the C and N contents of biochar by 33–310% and 41–286% respectively. The application of biochar (SB) and enriched biochar (SEB) reduced the net nitrification by 81% and 94%, ammonification by 48% and 74%, and carbon dioxide by 50% and 92% respectively as compared to control. The leaching losses minerals i.e., C (by 30%), N (by 125%), P (by 50%), K (by 82%), Na (by 9%), Ca (by 24%), and Mg (by 12%) was decreased in SEB treatments compared to control. The soil enzyme activities, microbial biomass (MBC and MBN), wheat agronomy, soil bulk density and soil pore density, mineral uptake from the soil, and mineral contents in the plant body were improved in the SEB as compared to SB and control treatments. Our results revealed that the biochar enrichment process could improve the C and N storage in the soil reservoir and lower the environmental risks to soil and water.
Publisher: Frontiers Media SA
Date: 08-07-2021
DOI: 10.3389/FAGRO.2021.661932
Abstract: Wheat constitutes pivotal position for ensuring food and nutritional security however, rapidly rising soil and water salinity pose a serious threat to its production globally. Salinity stress negatively affects the growth and development of wheat leading to diminished grain yield and quality. Wheat plants utilize a range of physiological biochemical and molecular mechanisms to adapt under salinity stress at the cell, tissue as well as whole plant levels to optimize the growth, and yield by off-setting the adverse effects of saline environment. Recently, various adaptation and management strategies have been developed to reduce the deleterious effects of salinity stress to maximize the production and nutritional quality of wheat. This review emphasizes and synthesizes the deleterious effects of salinity stress on wheat yield and quality along with highlighting the adaptation and mitigation strategies for sustainable wheat production to ensure food security of skyrocketing population under changing climate.
Publisher: MDPI AG
Date: 04-03-2021
DOI: 10.3390/IJFS9010014
Abstract: This study investigates the role of Information and Communication Technologies (ICT) investment and diffusion on Pakistan’s economic growth by proposing the threshold level of ICT investment. At our proposed level, the ICT imports significantly enhance the intermediate inputs to capital goods, ultimately enhancing economic growth. For this empirical investigation, we use the maximum available data on technological innovation and investment, ranging from 2003 to 2018. Incorporating the structural breaks, the results of regression analysis reveal that Pakistan’s economic growth is unaffected by ICT development. However, we observe the mixed shreds of evidence on the ICT investment. Following existing literature, we use ICT goods exports and imports as a proxy for ICT investment. Interestingly, the economic growth of Pakistan is again unaffected by the ICT goods exports. However, we observe that a one percent increase in ICT goods imports enhances economic growth by 1.73 percent. Then, we extend this analysis to the threshold approach, which reveals that ICT imports affect the overall economic growth when the ICT goods imports reach the level of 4.13 percent of the total imports. At this threshold, the ICT goods import significantly enhances the intermediate input to the capital goods, leading to higher economic growth. Therefore, the policymakers should ensure that the ICT goods import must be greater than the 4.13 percent of Pakistani imports.
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 06-2018
Publisher: MDPI AG
Date: 10-02-2017
Abstract: Understanding the impact of the warming trend on phenological stages and phases of cotton (Gossypium hirsutum L.) in central and lower Punjab, Pakistan, may assist in optimizing crop management practices to enhance production. This study determined the influence of the thermal trend on cotton phenology from 1980–2015 in 15 selected locations. The results demonstrated that observed phenological stages including sowing (S), emergence (E), anthesis (A) and physiological maturity (M) occurred earlier by, on average, 5.35, 5.08, 2.87 and 1.12 days decade−1, respectively. Phenological phases, sowing anthesis (S-A), anthesis to maturity (A-M) and sowing to maturity (S-M) were reduced by, on average, 2.45, 1.76 and 4.23 days decade−1, respectively. Observed sowing, emergence, anthesis and maturity were negatively correlated with air temperature by, on average, −2.03, −1.93, −1.09 and −0.42 days °C−1, respectively. Observed sowing-anthesis, anthesis to maturity and sowing-maturity were also negatively correlated with temperature by, on average, −0.94, −0.67 and −1.61 days °C−1, respectively. Applying the cropping system model CSM-CROPGRO-Cotton model using a standard variety in all locations indicated that the model-predicted phenology accelerated more due to warming trends than field-observed phenology. However, 30.21% of the harmful influence of the thermal trend was compensated as a result of introducing new cotton cultivars with higher growing degree day (thermal time) requirements. Therefore, new cotton cultivars which have higher thermal times and are high temperature tolerant should be evolved.
Publisher: Elsevier BV
Date: 11-2018
Location: Pakistan
No related grants have been discovered for Muhammad Habib ur Rahman.