Software for the detection of individual beet cyst nematodes in the root system of in vitro-grown sugar beet plants.
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F24%3A73627093" target="_blank" >RIV/61989592:15310/24:73627093 - isvavai.cz</a>
Result on the web
<a href="https://github.com/PalackyUniversity/root-worm-detector" target="_blank" >https://github.com/PalackyUniversity/root-worm-detector</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Software for the detection of individual beet cyst nematodes in the root system of in vitro-grown sugar beet plants.
Original language description
The aim of this software is to automatically detect individuals of the parasitic nematode Heterodera schachtii in the roots of young sugar beet seedlings grown in vitro on nutrient media. The plants are regularly photographed throughout the experiment, and the acquired images are then analyzed using the proposed algorithm. This algorithm utilizes a neural network built on the TensorFlow platform, trained on user-provided training datasets. The trained model allows for accurate identification of nematode individuals in the root system of five-week-old plants, enabling the quantification of infestation levels. This technology iscrucial for assessing the sensitivity, tolerance, and resistance of various sugar beet genotypes to the beet cyst nematode.
Czech name
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Czech description
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Classification
Type
R - Software
CEP classification
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OECD FORD branch
40106 - Agronomy, plant breeding and plant protection; (Agricultural biotechnology to be 4.4)
Result continuities
Project
<a href="/en/project/TQ03000647" target="_blank" >TQ03000647: Methodology for evaluation of plant resistance to Heterodera schachtii and a pilot study of novel protective technology in agriculture.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Internal product ID
Root Worm Detector
Technical parameters
Software založený na strojovém učení, využívající uživatelem vytvořené trénovací datové sady. Software je volně dostupný v nejaktuálnější verzi na této adrese: https://github.com/PalackyUniversity/root-worm-detector
Economical parameters
Výstup má potenciál umožnit rutinní testování odrůd cukrovky v rámci ČR, které se až dosud provádělo v zahraničí, což povede k úspoře nákladů a zvýšení ziskovosti uživatelů.
Owner IČO
61989592
Owner name
Univerzita Palackého v Olomouci