Diagnostic kits for the detection of plant diseases caused by viruses, bacteria, and fungi..
SENSIO is focused on the development of biosensors based on metabolic changes in plants due to pathogen infections.
Our goal is to detect plant diseases at early stages using fast, portable test kits to avoid large production losses.
Between 20-40% of world crop production is lost due to diseases and pests. Every year, plant diseases cost the world economy around $220 billion. Generally, diseases in plants is performed by symptoms observation, which in most cases is already too late; or if early detection is attempt, complex and expensive laboratory techniques are needed.
Early diagnosis is the best strategy to reduce losses generated by diseases. It is essential then, to have a tool to detect early stages, in an inexpensive, fast, easy to use and in a portable way.
We developed a biosensor that, unlike traditional methods, does not detect the presence of the pathogen, but rather groups of metabolites expressed by the plant, associated with each disease. It is a test strip that through a colorimetric system informs when a plant is sick.
What we are proposing is a substantial change in global protocols for detecting plant diseases that will speed up analysis times, increase the number of plants evaluated, and decrease diagnostic costs.
We have validated with producers and phytosanitary inspectors the importance of having a tool like the one proposed.
The use is simpler than tradicional techniques.
No need to send samples to the laboratory.
More commercially scalable than the traditional technique.
It does not use molecular detection techniques, that require specialized personnel and instruments.
Less false negatives against the traditional techniques, since it is a systemic determination.
We develop an enzymatic nanobiosensor for the early and in-situ detection of HLB in citrus plants. This system is manufactured on a polymeric substrate with titanium nanostructures on which an enzymatic load is immobilized, which, being on a nanometric surface, is greater and, therefore, increases its level of sensitivity.
The detection method is colorimetric and is based on the identification of metabolites that increase differentially in diseased plants and in early stages of infection. So far, at least in our country, there are no field sensors that detect this disease in the place and quickly. This proposal proposes to obtain an accurate result in a period of 15 to 30 minutes, without the need to send the samples to the laboratory and without using molecular detection techniques that require trained personnel and complex instruments.
CEO
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San Miguel de Tucumán
Tucumán
Argentinasensiohlb@gmail.com