Stalked protozoa identification by image analysis and multivariable statistical techniques.
نویسندگان
چکیده
Protozoa are considered good indicators of the treatment quality in activated sludge systems as they are sensitive to physical, chemical and operational processes. Therefore, it is possible to correlate the predominance of certain species or groups and several operational parameters of the plant. This work presents a semiautomatic image analysis procedure for the recognition of the stalked protozoa species most frequently found in wastewater treatment plants by determining the geometrical, morphological and signature data and subsequent processing by discriminant analysis and neural network techniques. Geometrical descriptors were found to be responsible for the best identification ability and the identification of the crucial Opercularia and Vorticella microstoma microorganisms provided some degree of confidence to establish their presence in wastewater treatment plants.
منابع مشابه
Development of an image analysis procedure for identifying protozoa and metazoa typical of activated sludge system.
A procedure for the semi-automatic identification of the main protozoa and metazoa species present in the activated sludge of wastewater treatment plants was developed. This procedure was based on both image processing and multivariable statistical methodologies, leading to the use of the image analysis morphological descriptors by discriminant analysis and neural network techniques. The image ...
متن کاملRecognition of Protozoa and Metazoa using image analysis tools, discriminant analysis, neural networks and decision trees.
Protozoa and metazoa are considered good indicators of the treatment quality in activated sludge systems due to the fact that these organisms are fairly sensitive to physical, chemical and operational processes. Therefore, it is possible to establish close relationships between the predominance of certain species or groups of species and several operational parameters of the plant, such as the ...
متن کاملRaw data pre-processing in the protozoa and metazoa identification by image analysis and multivariate statistical techniques
Y. P. Ginoris*, A. L. Amaral, A. Nicolau, M. A. Z. Coelho and E. C. Ferreira Departamento de Engenharia Bioquı́mica, Escola de Quı́mica/UFRJ, Centro de Tecnologia, E-113, Cidade Universitária, Ilha do Fundão Rio de Janeiro, CEP 21949-900, Brazil Centro de Engenharia Biológica, Campus de Gualtar, Universidade do Minho, 4710-057 Braga, Portugal Departamento de Tecnologia Quı́mica e Biológica—ESTIG, ...
متن کاملSemi-automated Acanthamoeba polyphaga detection and computation of Salmonella typhimurium concentration in spatio-temporal images.
Interaction between bacteria and protozoa is an increasing area of interest, however there are a few systems that allow extensive observation of the interactions. A semi-automated approach is proposed to analyse a large amount of experimental data and avoid a time demanding manual object classification. We examined a surface system consisting of non nutrient agar with a uniform bacterial lawn t...
متن کاملBehavioral Analysis of Traffic Flow for an Effective Network Traffic Identification
Fast and accurate network traffic identification is becoming essential for network management, high quality of service control and early detection of network traffic abnormalities. Techniques based on statistical features of packet flows have recently become popular for network classification due to the limitations of traditional port and payload based methods. In this paper, we propose a metho...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Analytical and bioanalytical chemistry
دوره 391 4 شماره
صفحات -
تاریخ انتشار 2008