Did you know that chemical reaction data is somehow “special” and that it naturally aggregates in a beautiful network? 

Our python toolkit LinChemIn can help you navigate the marvelous world of the Linked Chemical Information by allowing you to manipulate and analyze synthetic routes and reaction networks. Click on our LinChemIn GitHub project and start exploring the wired universe of chemical reaction data!

Prepare to revolutionize your Amazon Lambdas experience with Syngenta Digital ALC (AWS Lambda Client)!

Say goodbye to tedious routing and validation processes as ALC streamlines your workflow, allowing you to embrace a small, internally routed API approach with ease. Unlock the power of Object Oriented Programming and embrace a self-evident solution that will supercharge your development journey.

Woodstock, or The Rainfall Tool, is a tool developed to support experts in crop protection risk assessments for birds and mammals.

Woodstock does this by providing percentile statistics about rain and temperature for time periods that occur in standard weather data files.

Battling malaria, a debilitating disease affecting millions, just got a powerful new tool! As mosquito resistance to pyrethroids threatens current prevention methods, the R Package 'detsims' offers a framework for simulating and comparing resistance-management strategies.

This tool could help delay the evolution of resistance to new insecticides. The package includes model definitions, simulation executions, and visualization of results, making it an essential tool for fighting malaria.

Find the perfect name for your next big project with Nomius!

This tool checks the availability of domain and package names for a list of provided names, so you can easily register a short and memorable name without the hassle of manual searches. Say goodbye to tedious checks and hello to quick results, with Nomius you can check dozens of names in just a minute!

Have a look at our ground-breaking machine learning technique that predicts the effects of chemicals on various species!  

We found that acute toxicity can be predicted with accuracy across multiple aquatic organisms. With this model, scientists will be able to estimate the potential impact of chemicals on multiple species without unnecessary animal testing, thereby supporting safe and sustainable chemical uses. Learn more on GitHub!

Bursting with colors! Color segmentation is the first step of many imaging pipelines that isolate the objects of interest from the background. 

This tool allows users to work intuitively and cherry-pick colors by their nominal name. It is tuned to work with the colors of plants, and has a powerful interface to help users achieve superior segmentation without the need for a neural network.

Imagine having the possibility to know what species occur when and how active they are?

Syngenta Group’s Biodiversity sensor project aimed to support the global agricultural community in building the foundation of an AI enabled network for reliable, autonomous, collection and sharing of biodiversity data openly with a primary focus on insects. We invite you to explore our open-sourced motion detection code, the machine-learning process for training our species identification AI model on GitHub, as well as the prototype hardware build by our partner Indian Institute of Technology Ropar (IIT Ropar) and its related firmware, and freely develop these further to bring science, technology, data together to improve our collective responsibility - biodiversity.

Are you tired of making multiple requests to the Meteoblue API service to retrieve the weather and soil data? Check out these scripts!  

The repository contains useful Python scripts that automate bulk extraction of weather and soil data from Meteoblue. In addition, the best dataset can be selected for a specific country code. Learn more on GitHub!