Team:Newcastle/Results
LUX LEVELS
First measurements taken from the LED's was when they had the 'rainbow' function loaded. Meaning the lights cycled through the colours of a rainbow. We applied this test so we could determine which colour gave the highest Lux. Which established that purple is the 'optimal' colour to use peaking at 1100 lux, confirming what our human practices has revealed when visiting various hydroponic facilities.
Next we loaded the Arduino with a programmed in 'purple' colour. This measurement stabilised at roughly 1300 lux. Leading us to believe we could tweak this light level even more. therefor we tried different preset colours; Blue, Green, Red, White, Blue proved to be the highest. Realising that the LED's manage colours by producing different quantities of Blue, Green and Red light we figured we may be able to create an optimum between these colours hopefully improving on the preset Blue. Which meant we couldn't use a preset library and would have to define the light levels of the primary colours manually.
Before starting we defined the brightness of each colour as an 8 bit integer (265 light levels). The most obvious place to start was to turn all the primary colours up to 265. Giving white light which performed worse than the preset Blue and white. Therefor we created purple via Blue, Red: 265. Which also proved to be less than the preset blue. Figure 1.0 show the results from these measurements.
Therefor thinking that the preset Blue was actually our maximum we attempted one more test. Holding Blue at a constant 265 but varying Red from 0-265 and plotting the results. We discovered that there is a peak Lux peak when the Red is at a light level of 129. Next we tried Blue:265, Red:129 and varied green from 0-265. Which appeared to have a detrimental effect on the light intensity. Figure 1.1 shows the relationship between these colours
UP TO
SEEDS CAN BE GROWN
IN HYDROPONICS
APPROXIMATELY
KWH OF POWER ANNUALLY
USED TO POWER SYSTEM
PROVIDES UP TO
LUX OF LIGHT
TO GROW SEEDS
CONTAINS
INDIVIDUALLY ADDRESSABLE
LOW-POWER LED'S
Stage Two
Green light experiment
In an attempt to confirm purple light is optimal wavelength for growing Rocket we ran a simple experiment. Using off cut ply wood we created a barrier which was placed inside the hydroponics effectively blocking the light, Figure 2.0 shows the dividers used. This allowed us to programme the Arduino to emit green and purple light independently, the light intensities were measure at 200, 1700 Lux respectively (code can be found here). Seeds were then placed in two 96 well racks, one green (A), one purple (B). They were then left to germinate for a week.
It was expected that there would be more germinations from rack B, and from the photos below we can see a comparison from racks A and B; 6, 22 respectively. However the shoots in A are significantly taller as they are straining for light. Whereas the Rocket in rack B is more uniform.
Exploring Bacterial Chemotaxis
As proof of concept, the project aimed to introduce a plasmid containing an operon for naringenin biosynthesis. Naringenin belongs to a group of chemicals named flavonoids which play an important role in plant-microbe interactions.
Through the introduction of said plasmid into our root-colonising Pseudomonas sp. chassis, it was hypothesised that the a microbial community could be engineered. This would be done by attracting selected free-living nitrogen fixing bacteria (FLNFB) in order to localise nitrogen fixation around the root. As a result of this, one would be able to alleviate the over usage of synthetic fertilisers which have numerous detrimental impacts on the environment, ranging from eutrophication [1] to degradation of soil health [2].
We selected Azorhizobium caulinodans (ORS571), Azospirillum brasilense (SP245), and Herbaspirillum seropedicae (Z67) as our FLNFB as they each form different interactions with plant roots. For example, A. caulinodans has been shown to fix nitrogen when free living and when in symbiosis with Sesbania rostrata, a semi-aquatic tree [3]. H. seropedicae on the other hand is a root endophyte, much like our Pseudomonas spp. and commonly colonises popular crops such as wheat and maize [4].
These bacteria provide potential to provide nitrogen nourishment in different ways. However, for the proof of concept, it was important to demonstrate that bacterial behaviour could be influenced by naringenin exposure. As such, a series of assays regarding naringenin’s ability to engineer a microbiome were a core aspect of our project.
Characterising Bacterial Behaviour in a Laboratory Environment
Prior to conducting in depth assays, we first needed to identify how our FLNFB would behave in our laboratory prior to the introduction of variables. The team approached this by identifying what areas were integral to understanding changes in bacterial behaviour. We identified that we needed to characterise growth in liquid culture and on solid agar. Growth on agar was further divided into colony morphology and average diameter after 24 or 48 hours (species dependent). We also characterised the change in growth rate in the presence of our selected chemoattractant –naringenin – relative to standard growth in LB.
As a measure of our methods, we refer to our Escherichia coli (DH5α) control. This is as E. coli has been very thoroughly studied and so we can refer how our E. coli behaves in relation to the literature.
Assessing the Impact of Naringenin on Bacterial Behaviour
To assess chemotactic behaviour in response to naringenin, our team adopted 3 approaches that were identified from established literature. These approaches included agar-based, capillary-based and microscopy-based techniques. The aim of all variants was to demonstrate a change in behaviour in the presence of different chemicals; said behaviour would then give a representation of chemotaxis in our species.
As previously mentioned, the Alternative Root proof of concept involves naringenin’s ability to influence the microbiome. Because of this, bacterial behaviour in the presence of naringenin was assessed. Observed behaviour would then be compared to a blank control (distilled water or 1.5% ethanol) and, when appropriate, a positive control (malate).
REFERENCES & Attributions
Attributions: Luke Waller, Umar Farooq, Connor Trotter