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Aplicación para smartphones que predice la proliferación nociva de algas en aguas continentales

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TODE20151209001
Publicado:
13/01/2016
Caducidad:
13/01/2017
Resumen:
Una universidad alemana ha desarrollado un sistema de estimación de algas, una aplicación para smartphones que predice la proliferación nociva de algas en aguas continentales basada en la ecuación de Verhulst modificada (Nt=N0 (k-N0)*exp(-r0*t)) a partir de parámetros fáciles de medir, como temperatura del lago, profundidad del disco de Secci, oxígeno disuelto, luz y fluorescencia de la clorofila. La universidad busca usuarios de la aplicación para adquirir y extraer datos y monitorizar de forma integral la calidad del agua en una región determinada, así como socios industriales e investigadores para establecer acuerdos de cooperación técnica y participar en proyectos de investigación.



Details

Tittle:
Smartphone app predicts harmful algal blooms in in-land waters
Summary:
A German university has developed an algae estimator, a smartphone app that predicts harmful algal blooms in in-land waters. The university is looking for interested app users to gain futher data for data mining in order to comprehensively monitor the water quality of a given region. Interested partners from industry and research are also offered technical cooperation and joint research projects.
Description:
An institute of the German has developed an android mobile application for a harmful algal blooms (HAB) prediction based on a modified Verhulst equation (Nt=N0 (k-N0)*exp(-r0*t)) from a variety of easy to measure input parameters, such as lake temperature, Secci depth, dissolved oxygen (DO), light (lux) and chlorophyll-fluorescence (Chl a).

As chlorophyll values are not normally easy to access for the user the reserchers used equations for chlorophyll a estimation using partial least square analysis (total Chl a (µg/l) = -6,4775 21,6396 * inverse Secci depth (m) 0,0006 * square (DO surface (%); r2=0.69; cyanobacterial Chl a (µg/L) = 0.409 - 0.7486 * surface temperature(°C) 17.6979 * inverse Secci depth (m)); r2=0.76) from a data set obtained from a shallow lake (Stadtgraben, Germany, 2013).

Data were collected by seasonal weekly sampling of eutrophication parameters (temperature, conductivity, DO, phosphate, ammonia, nitrite, nitrate, Chl a, Secci depth). Temperature differences within water depth layers diminished towards late summer with full circulation stage reached in August. This coincided with full development of algal bloom (defined as cyanobacterial Chl a = 40 µg/L) and a sharp drop in phosphate and ammonia levels at the bottom.

The model developed from there does show a deviation of max. 16% between estimated and real values in bioreactor experiments and is now under validation in different freshwater lakes.

The institute is open for various forms of research and technical cooperation with academia and industrial partners interested in monitoring of water quality in shallow lakes.
Advantages and Innovations:
Harmful algal blooms (HAB) mainly caused by cyanobacteria in freshwater ecosystems present a health risk to the public within eutrophied shallow lakes due to algal toxins released into the water. Thus, algal growth should be monitored during summer seasons, especially in recreational areas. Traditionally, water samples are sent to a lab to analyze for algal blooms, costing time and money. Models predicting HAB from easily measurable parameters on a smartphone could help individuals to take precautionary measures in order to prevent health risks from drinking and bathing in water and raise public awareness.
Stage of Development:
Already on the market
IPs:
Secret Know-how

Partner sought

Type and Role of Partner Sought:
- Type of partner sought:
1) App users / testers from industry, research, public bodies and private persons for data gaining.

2) Research organisations, public bodies and industrial partners from sectors related to in-land waters protection or operators of recreational areas interested in technical cooperation and further joint research projects.

Client

Type and Size of Client:
University
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English
German

Keywords

Technology Keywords:
01004002 Aplicaciones para el turismo
01004001 Applications for Health
10002006 Ecología
10004010 Hidrología
06001018 Virus, virología / antibióticos / bacteriología