Advantages and disadvantages on photosynthesis measurement techniques: A review

Through photosynthesis, green plants and cyanobacteria are able to transfer sunlight energy to molecular reaction centers for conversion into chemical energy with nearly 100% efficiency. Speed is the key as the transfer of the solar energy takes place almost instantaneously such that little energy is wasted as heat. How photosynthesis achieves this near instantaneous energy transfer is a longstanding mystery that may have finally been solved. Measurements of this process are useful in order to understand how it might be controlled and how the phytomonitoring of plant development to increase productivity can be carried out. Techniques in this sense have evolved and nowadays several have been used for this purpose. Thus, the aim of this paper is to present a review of the various methods and principles that have been used in measuring photosynthesis presenting the advantages and disadvantages of various existing measurement methodologies in order to recommend the most appropriate method according to the needs of specific investigations

Mathematical modeling tendencies in plant pathology

Nowadays plant diseases represent one of the major threats for crops around the world, because they carry healthy, economical, environmental and social problems. Considering this, it is necessary to have a description of the dynamics of plant disease in order to have sustainable strategies to prevent and diminish the impact of the diseases in crops. Mathematical tools have been employed to create models which give a description of epidemic dynamics; the commonly mathematical tools used are: Diseaseprogress curves, Linked Differential Equation (LDE), Area Under disease Progress Curve (AUDPC) and computer simulation. Nevertheless, there are other tools that have been employed in epidemiology of plant disease like: statistical tools, visual evaluations and pictorial assessment. Each tool has its own advantages and disadvantages. The nature of the problem and the epidemiologist necessities determine the mathematical tool to be used and the variables to be included into the model. This paperpresents review of the tools used in epidemiology of plant disease remarking their advantages and disadvantages and mathematical modeling tendencies in plant pathology

Evaluation of the Detectability of Electromechanical Faults in Induction Motors Via Transient Analysis of the Stray Flux

© 1972-2012 IEEE. The stray flux that is present in the vicinity of an induction motor is a very interesting information source to detect several types of failures in these machines. The analysis of this quantity can be employed, in some cases, as a supportive tool to complement the diagnosis provided by other quantities. In other cases, when no other motor quantities are available, stray flux analysis can become one of the few alternatives to evaluate the motor condition. Its noninvasive nature, low cost, and easy implementation makes it a very interesting option that requires further investigation. The aim of this work is to evaluate the suitability of the stray flux analysis under the starting transient as a way to detect certain faults in induction motors (broken rotor bars and misalignments), even when these types of faults coexist in the motor. To this end, advanced signal processing tools will be applied. Several positions of the flux sensors are considered in this study. Also, for the first time, a fault indicator based on the stray flux analysis under the starting is introduced and its sensitivity is compared versus other indicators relying on other quantities. It must be emphasized that, since the capture of the transient and steady-state flux signals can be carried out in the same measurement, the application of the approach presented in this work is straightforward and its derived information may become crucial for the diagnosis of some faults.Ministerio de Economía y Competitividad’ (MINECO) and FEDER program in the framework of the ‘Proyectos I+D del Subprograma de Generación de Conocimiento, Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia’ (ref: DPI2014-52842-P)