Effects of Bradyrhizobia Inoculation on Growth, Yield and Yield Components of Cowpea Varieties (Vignaunguiculata(L.)Walp) at Hawassa, Ethiopia

Declining of soil fertility, especially deficiency of nitrogen is one of the major factors adversely affecting crop productionin Ethiopia. Though the problem can be addressed through application of inorganic fertilizers, the unprecedented increase in the cost of fertilizer is increasingly limiting the use of this input. Increasing N-availability through Bradyrhizobium-legume symbiotic N-fixation process is a viable alternative for improving N-nutrition of crops. However, there is a need for identifying effective Bradyrhizobium strains compatible with specific varieties of leguminous crops. Therefore, this study was conducted to investigate the effect of differentBradyrhizobium strains on growth, yield and yield components of Cowpea (Viginaunguiculata(L.)Walp)varieties at Hawassa. A factorial combinations of four treatments [three Bradyrhizobium strains GN100, GN102 and MB140) and a positive control], and five Cowpea varieties (Bole, Black eye bean, TVU, Assabot and Wonder) were laid out in RCBD with three replications. The plot size was a 2.2m x 3 m and cowpea seeds were planted with inter and intra row spacing of 50cm by 20cm respectively. Data on nodule number, nodule volume, nodule dry weight and agronomic parameters like shoot dry weight, leaf area index (LAI), plant height, number of branches, pods, seeds per pod, grain yield, biomass yield, harvest index (HI), 100 seed weight, total plant N and some soil chemical parameters(OC%, P, N&pH) were collected and subjected to ANOVA.Inoculaton with Bradyrhizobiumsignificantly increased the nodulation parameters, Agronomic performance, yield and yield components. Nodule parameters yield and yield components of the five Cowpea varieties inoculated with strain GN102 were significantly superior followed by GN 100 and MB 140. On Black eye bean and Assabot varieties, Strain GN102 increased the grain yield by 14 and 9%, respectively relative to the positive control. Cowpea varieties also varied significantly in their performance with respect to nodule parameters, yield components and total nitrogen content. Accordingly, Black eye bean variety performed best relative to the other four varieties. Bradyhizobia by varieties interaction effects were also significant in terms of yield and yield components. Compared to before planting,strain GN100, GN 102 and MB140 increased soil N by 51.6, 46 and 40%, respectivelyafter planting.Despite the commonly reported non responsiveness of Cowpea for inoculation, the result presented here indicated the potential that exists to increase the yield of the crop through selecting and inoculating with effective Bradirhizobial strain. Keywords: Biological N-fixation,Bradyrhizobium strainsCowpea, inoculation, Nitrogen, nodulation and Soil fertility declin

Estimating the reproductive number, total outbreak size, and reporting rates for Zika epidemics in South and Central America

As South and Central American countries prepare for increased birth defects from Zika virus outbreaks and plan for mitigation strategies to minimize ongoing and future outbreaks, understanding important characteristics of Zika outbreaks and how they vary across regions is a challenging and important problem. We developed a mathematical model for the 2015 Zika virus outbreak dynamics in Colombia, El Salvador, and Suriname. We fit the model to publicly available data provided by the Pan American Health Organization, using Approximate Bayesian Computation to estimate parameter distributions and provide uncertainty quantification. An important model input is the at-risk susceptible population, which can vary with a number of factors including climate, elevation, population density, and socio-economic status. We informed this initial condition using the highest historically reported dengue incidence modified by the probable dengue reporting rates in the chosen countries. The model indicated that a country-level analysis was not appropriate for Colombia. We then estimated the basic reproduction number, or the expected number of new human infections arising from a single infected human, to range between 4 and 6 for El Salvador and Suriname with a median of 4.3 and 5.3, respectively. We estimated the reporting rate to be around 16% in El Salvador and 18% in Suriname with estimated total outbreak sizes of 73,395 and 21,647 people, respectively. The uncertainty in parameter estimates highlights a need for research and data collection that will better constrain parameter ranges.Comment: 35 pages, 16 figure

An Automatic Traffic Sign Recognition for Autonomous Driving Robot

This paper presents an automatic traffic sign detection system based on three stages like detection, pictogram extraction and classification. In detection stage we detect the type of symbol like triangle or circle. In pictogram extraction we localize signs from a whole image, and classification stage that classifies the detected sign into one of the reference signs. The detection stage includes segmentaion of image through RGB analysis, morphological filtering and connected component analysis. The classification modules includes the local region features extractions and KNN classification

Mapping Ice Covered Waters from Space

Under a leaden April Arctic sky, the United States Coast Guard Cutter Healy left the swell of the southern Labrador Sea and entered the Arctic ice pack for the first time, settling in as if she had finally found her home. The deck log notes that at about 4 pm on the 4th April 2000, the ship’s commanding officer, Capt. Bob Garrett, assumed both the deck and the con for the momentous occasion (Figure 1). The ship entered the ice at 51° 33.0’ N, 54° 33.33’ W. The ice trials of the newest U.S. icebreaker were underway

Nature’s Power and Native Persistence: The Influence of First Nations and the Environment is the Development of the Mattagami Hydro-Electric System During the Twentieth Century

To date, most analyses of hydro-electric development portray the environment and Aboriginal Peoples as victims unable to alter or resist its intrusion on to the landscape. However, an examination of the Mattagami river developments in northeastern Ontario illustrates that environmental conditions constantly influence the shape and development of the hydro-electric system. Also, while the ability of the northeastern Aboriginal Peoples to affect hydro-electric development is limited for much of this century, by the 1990s, their persistence and perseverance coalesces with changing court decisions and legislation, empowering them to negotiate with Ontario Hydro a moratorium on further development on the Mattagami River.A ce jour, la plupart des analyses du développement hydroélectrique présentent l'environnement et les peuples autochtones comme autant de victimes incapables d'infléchir ou de contrer ce type d"intrusion dans un pays. Pourtant, l'histoire des ouvrages de la rivière Mattagami dans la région nord-est de l'Ontario montre que les conditions environnementales exercent une influence constante sur la forme et le déploiement d'un système hydroélectrique. De plus, la faculté des autochtones du nord-est de peser sur les décisions concernant les travaux est récemment sortie des limites dans lesquelles la plus grande partie de ce siècle l'avait confinée. La combinaison de leur acharnement et des changements judiciaires et législatifs a permis aux Premières nations de négocier avec Ontario Hydro un moratoire sur les futurs projets d'exploitation de la rivière Mattagami

Maximizing object detection using sUAS

This paper examines optimal look-angles for a camera which is mounted on a small unmanned aerial system (sUAS), that provides for maximized object detection on the ground. Using a generic convolutional neural network (CNN), this research identifies the best angle for detecting a ground target from an aerial perspective. The study involves altering camera angles on an sUAS that is flown along a fixed trajectory and then determining the angle which provides the highest detection rate of predefined objects, which are emplaced at known locations on the ground. The experiment is conducted in simulation and validated on a physical quadcopter. The results of this paper directly influence the U.S. Army’s research efforts on training neural networks and developing object detection algorithms