Evaluating the Impact of Different Tillage Regimes and Nitrogen Levels on Yield and Yield Components of Maize (Zea mays L.)

A field study to evaluate the impact of different tillage regimes and nitrogen levels on yield and yield components of maize (Zea mays L.), was conducted during autumn 2014 at Students Farm, Department of Agronomy, University of Agriculture, Faisalabad. The experiment was laid out in RCBD (Randomized Complete Block Design), with split plot arrangement having three replications. The experiment was comprised of three tillage regimes (Minimum, Conventional and Deep) and three nitrogen levels viz: 100, 200 and 300 kg•ha-1. Urea was used as a source of nitrogen, sulphate of potash as a source of potassium and triple super phosphate as a source of phosphorous. The amount of phosphorous and potash was constant in all the treatments i.e. 125 kg•ha-1 and 100 kg•ha-1 respectively. Results of present study are summarized as yield parameters are significantly affected by different nitrogen levels and tillage regimes. Maximum number of plants at harvest (7.93), number of grain rows per cob (17.70), number of grains per row (34.31), number of grains per cob (678.58), and cob weight (187.50 g) were observed in deep tillage at 200 kg•ha-1 nitrogen application. 1000-grain weight (275.52 g), biological yield (15.66 t•ha-1), grain yield (6.16 t•ha-1) and dried stalk yield (9.91 t•ha-1) were observed maximum in deep tillage at 200 kg•ha-1 nitrogen application. Harvest index significantly affected by tillage regimes and maximum harvest index (39.58%) were recorded in deep tillage which was statistically at par with conventional tillage (38.83%). It was concluded that higher grain yield of maize can be obtained by deep tillage with the application of 200 kg•ha-1 nitrogen application under the prevailing conditions of Faisalabad.

Quantitative Behaviour of Guar (Cymopsis tetragnolobus L.) to Various Tillage Systems and Mulches and Soil Physical Properties

A field study was conducted to evaluate the effect of organic mulches and tillage practices on growth, yield of cluster bean and soil physical properties. Experiment was comprised of two factors: A (Tillage), B (Mulches). Factor A was assigned to main plot and consisted of two treatments (Minimum tillage and Conventional tillage). Factor B was assigned to sub plot and consisted of four treatments (no mulch, wheat straw mulch, grass clipping mulch and saw dust mulch). The mulching materials were partially incorporated in the field after germination of crop. The experiment was laid out in Randomized Complete Block Design (RCBD) with split plot arrangement having three replications. Control treatment was kept for comparison. All other agronomic practices were kept standardized and consistent for all the treatments. Data regarding growth and yield components were collected and analyzed statistically by fisher analysis of variance and treatment significance was measured by significant difference test at 5% probability level. The factors, tillage and mulches significantly affected growth, yield, yield parameters and soil physical properties. Maximum plant population (31.7 m2), plant height (159 cm), branches per plant (18.9), cluster per plant (15.88), grains per pod (7.3), 1000-grain weight (34.6 g), grain yield (1.9 t•ha-1), biological yield (9.91 t•ha-1) and harvest index (19.15) was recorded in conventional tillage comparative to minimum tillage. Mulches also affected grain yield, and maximum grain yield was recorded in wheat straw mulch (1.88 t•ha-1) followed by grass clipping mulch (1.81 t•ha-1) and saw dust mulch (1.76 t•ha-1) while minimum grain yield was recorded in control without mulch application (1.67 t•ha-1). Tillage and mulches interactively affect pH, soil organic matter contents, electrical conductivity and soil bulk density. Mulches and minimum tillage improved soil physical properties. Highest BCR was obtained from conventional tillage without mulch and lowest calculated from minimum tillage with saw dust application. The conclusion is that the mulching and conventional tillage improves cluster bean yield about 1%.

Development of Gene Expression and Gene Silencing Vectors Based onCotton Leaf Curl Virus for Functional Genomics in Cotton

Cotton leaf curl virus is the first example of acotton-infecting virus where infectious clones areavailable.Plant viruses are valuable tools inunderstanding plant biology as they can beengineered for expression of foreign genes orsilencing of genes homologous to cloned genes.

Adaptive Islanding Strategy of Sustainable Distribution System for Post-restoration Failures

The power system is susceptible to failures,and further interruptions by subsequent outages which may cause extended events in the formed island.Most of the literature reviewed has focused on island formation after the disconnection of the main grid supply.However,there is still a need to analyze the post-restoration failures to improve the resilience and minimize the pro-longed disconnection of priority customers.The current research investigates the behavior of islanding schemes under secondary collapses and provides an adaptive solution to withstand such severities.A new total active critical node finding methodology is presented which eases the rearrangement of the initially formed island when affected by multiple faults or DG failures.The concept of single islanding with the coordination of multiple DGs is also discussed,in which the DG's power-sharing capacity is not confined to the boundaries of only particular islands.An economic plan is also proposed to select the controlled type DGs to reduce the overall cost of generation by reducing fuel cost.To evaluate the network's effectiveness and robustness,the proposed adaptive method is deployed on an updated IEEE 69-bus distribution system.Index Terms-Active distribution network,distributed generation,multi-objective,post-restoration,single islanding.

Optimal Islanding for Restoration of Power Distribution Systems Using Prim’s MST Algorithm

Power systems can suffer outages,causing complete or partial disconnection of their power supply to load centers within the distribution networks.Distributed Generation(DG)plays an essential role in power systems.DG can be used as a back-up power source to enhance the resiliency and reliability of a power system.Island mode operations after outages in an active distributing network(ADN)is an effective way to maintain continuity of the power supply to significant loads.It is a quite complicated task for power system operators to find the power flow path.Previous studies have primarily used pre-defined guidelines to find feasible power flow paths,and have focused on multiple islands for restoration.In these studies,possible restoration pathfinding with DG was the fundamental weakness,and furthermore,the power of DG was limited to pre-defined boundaries in the form of islands.Therefore,in this study,a new algorithm has been proposed,which uses the minimum spanning tree(MST)method to find the most feasible path.The proposed algorithm starts at any random node(in this case,DG),and progresses by selecting the next node with the least cost(weight),thus considering all the nodes through which power will flow.The proposed model is formulated as a multiobjective program considering the priority of loads and minimum power loss.The effectiveness of the proposed model is tested on a modified IEEE69-bus distribution system with the penetration of multiple distributed generation sources at different nodes.Results were compared with the strategies found in literature,and the proposed method was found to be feasible and efficient.