~Cue the Sun.~

Simulating in-situ environmental conditions for studying plant-associated microbiota and their interactions has long been a gold standard for research in biosafety[source]. Observing the behaviour of microorganisms in a controlled environment is a leap in the multistep process required before field application. Our proposed biological system is an advanced, highly detailed design of our engineered Pseudomonas Putida that will ensure the safety of Olive Trees against the pathogen Verticillium Dahlie. To ensure its safety and efficacy, we developed tools to monitor and test its behaviour under controlled conditions. This collaborative effort addresses a fundamental question in biosafety: "How safe is safe?"

“How safe is safe?”

The [hardware name] was initially conceived as an in-vivo method to remotely measure the growth of our engineered P. putida in soil and its impact on olive saplings. We later expanded on this idea to include a broader range of plants and microorganisms, including the plant pathogen Verticillium dahliae. Finally, we propose methods to further advance this concept by incorporating machine learning applications in modelling to better understand the expansion of microorganisms in soil.

The [hardware name] was initially conceived as an in-vivo method to remotely measure the growth of our engineered P. putida in soil and its impact on olive saplings. We later expanded on this idea to include a broader range of plants and microorganisms, including the plant pathogen Verticillium dahliae. Finally, we propose methods to further advance this concept by incorporating machine learning applications in modelling to better understand the expansion of microorganisms in soil.

~Hardware Description~

Plant Incubator:

The user sets the conditions inside the plant incubator through an application we developed. An Arduino Microcontroller is responsible for the operation of a thermal unit, a humidifier unit and an irrigation unit, while photoperiod is set directly by an outlet timer. The temperature inside the incubator can be set between 15-35°C and can also vary throughout the day. The irrigation unit and mistifier unit provide water, through droplets directly on the plant pots in the former and through mist in the latter. Full spectrum growing and flowering LED strips provide light to the plants and they are turned on, or off, at pre-specified times in the day.

Data Logger:

The Data Logger consists of a series of sensors. A Raspberry Pi handles the temperature, air humidity and pot humidity measurements. When running our application the Raspberry Pi logs and plots the sensor measurements.

Microorganism Growth Logger:

The Bacteria Interactions Logger consists of olfactory sensors that measure the mVOCs produced by each plant pot. This data can later be examined and inform us about the population and growth stage of the bacteria inside the pots. By constantly collecting experimental data we can build upon them and -in time- create a highly accurate prediction model for the growth of engineered bacteria such as our P. Putida.

~Do It Yourself!~