Fungus is the major disease for plants and has caused a tremendous financial loss in agriculture. We aim to use databases to find effective and also harmless anti-fungal peptides, with IOT forecast system to save fungus-infected plants. We hope to solve both the fungal and environmental hazards, help our farmers, and put sustainable development into practice through setting up green agriculture.

Project:

Databases for Peptide Choosing

First we connect four databases to know the relations among the whole fungal infection process.

Then, we use sequence analysis to screen peptides in databases, grouping them by different conserved domains, followed by filtering with other conditions like peptide length and whether they are toxic to E. Coli in the hopes of choosing the final peptides.

IOT Device for Advanced Application

we use IOT device to connect the information of weather, humidity, temperature, and others, and build a model that can predict the incidence of disease.
Furthermore, we design the smartphone application to bridge users with IoT device. We aim to use IOT device to record and update all the data in each farm for each user. In the end, we hope to build an immediately updating and customized model for every single farmer in need.

Mechanism:

MiAMP1:bind to B-(1,3)-glucans in fungal cell wall. LaLTP: bind to the lipid on the cell membrane of the pathogen, causing permeabilization of the membrane. RsAFP2: interact with a kind of sphigolipid on the cell membrane of the pathogen, then induces cell death. Weatwin-1: contains a Barwin domain which was related to ROS production in fungal hyphae.

Team:NCTU Formosa/Description

2017 NCTU_Formosa

AI Green Fingers

Abstract:

Project:

Databases for Peptide Choosing

IOT Device for Advanced Application

Mechanism:

Biobrick:

Human Practice:

Team Members: