Team:Lambert GA/Software
AGROSENSE
Figure 1. Screenshots of AgroSense app and features
OVERVIEW
The AgroSENSE app is a complete guide for users to build and maintain a hydroponics system. Users are given a step-by-step video and written instructions to build their ideal system. In addition, the app also contains maintenance guides for hydroponics and healthy cooking recipes.
DESIGN
The AgroSENSE mobile app is built to help users set up their own hydroponics system with ease. Users first take a survey to generate their ideal systems by taking into account their specific parameters: plants, size, budget, and various other factors.Upon completion of the survey, users will be given written instructions and a tutorial video to start the building process. The app is split into 2 sections: Builder’s Guide and Community Guide. The Builder’s Guide includes all the information users will need to set up their own aquaponics/hydroponics system. The Community Guide will serve as the education portion; it will address certain topics such as how to maintain the system and include the AgroEats cookbook, containing a diverse array of recipes using the plants harvested from their system. AgroSENSE’s Builder’s and Community Guides serve as a perfect introduction to hydroponics for beginners.
FEATURES
CURRENT
- Hydroponics recipes
- Building guide
- Maintenance guide
- Hydroponics survey
FUTURE
- Public map functionality
- Aquaponics support
DATA FLOW
Figure 2. Data flows from the sensors to the Raspberry Pi web server, from the web server to the cloud database, and from the database to the Agro-Q mobile app.
AGRO-Q
Figure 3. Screenshots of Agro-Q app and features
OVERVIEW
The Agro-Q mobile app has a wide variety of features that allow users to maintain their hydroponics system. Users can view sensor data of pH, water temperature, CO2, atmospheric temperature, and light intensity, via the app, and analyze the plant growth. The Agro-Q app allows collaboration among the user by sharing their specific hydroponics setups.
DESIGN
The Agro-Q app is divided into 4 sections: map, sensor data, models, and monitor. Users can register their own hydroponics system on the map to show data such as system type, plant condition, general location, etc. In addition, users can locate local hydroponics farms to visit, allowing for a sense of community through the app. Within the app, the sensor data tab shows data specific to the user’s own system, including data (pH, CO2, light intensity, water/atmospheric temperature, etc.) from the various electronic sensors placed around their system. The data will be refreshed periodically and pulled from a database. Our future models section of the app, in coordination with the sensor data from the database, will generate a model to predict the growth of plants based on the different growth conditions and factors of the system. Finally, Agro-Q’s future monitor section will be used to scan pictures that are taken periodically and determine the amount of growth in the system by examining the color. The layout of the app allows remote users to keep track of the different components in the system.
FLUORO-Q
OVERVIEW
Figure 4. Animated schematic of Fluoro-Q device including excitation light, emission filter, and place for cuvette
The Fluoro-Q system is an improvement upon FluroCents, the frugal fluorometer developed by the 2019 Lambert iGEM team. The system consists of 3D-printed hardware and a software pipeline that is used to produce fluorescence values in arbitrary units. These values coupled with optical density can produce fluorescence similarly to a plate reader.
DESIGN
The first change is the mechanism of excitation source. The plastic excitation filter and UV LED light source from last year were swapped for an LED light source falling within GFP’s excitation wavelength range of 450-460 nanometers. This enables the two components to be combined into one without the need for the cost of the excitation filter, while allowing for more unfiltered excitation energy. Additionally, to improve upon the plastic emission filter from last year, we decided to upgrade to a glass emission filter. Relative to plastic, glass improves the durability of the filter by making it scratch-resistant. It is also more specific when filtering the emission energy. Perhaps the most significant improvement upon FluoroCents lies in the quantification mechanism itself. We transitioned from GFP quantification based upon a smartphone’s ambient light sensor to a smartphone’s camera because of the variability and lack of specificity of ambient light sensors across different brands of smartphones. Using the smartphone camera is important in order to be able to keep a record of results and increase the specificity of a selected region.
Figure 5. Schematic of how a fluorometer traditionally works from a conceptual standpoint
Once we decided to switch to the camera, we designed an experimental protocol for precise quantification derived from our Nature Communications-published Zin-Q quantification system. We created a smartphone-based fluorescence quantification system using the hue, saturation, and value, or HSV, analysis run on images. The user takes an image of the biological sample and the HSV color system is used to compare the relative intensity or brightness of GFP expression to a negative and positive control.
Figure 6. Real setup of Fluoro-Q for experimental testing
At a software level, the image analysis that Fluoro-Q uses relies upon average pixel brightness calculations. The center of the sample is located and then the average Hue, Saturation, and Value quantities are calculated within a 50 pixel radius. The V, or value, from HSV corresponds to brightness and this is used to report fluorescence in an arbitrary unit. This coupled with optical density readings is then used to report fluorescence similarly to a plate reader.
Figure 7. Data from two-fold serial dilution comparing optical density to level of fluorescence measured using Fluoro-Q
LUNCHBOX MICROSCOPE
OVERVIEW
The Lambert iGEM 2019 project required the quantification of GFP expression in our biosensor. To tackle this, we developed FlouroCents, a system capable of measuring the expression of fluorescence in a biological sample using a mobile phone, 3D-printed parts, modular filters, and a light source. The system utilized the basic principles of fluorescence excitation and emission to measure the level of excitation energy released by a biological sample using the ambient light sensor.
Our 2020 project requires the quantification of our Pho and Nar biosensors, which both utilize the GFPreporter. This is necessary to our project as it is the only way to precisely determine the level of phosphate and other nutrient levels within our hydroponics system. In an effort to improve upon the FluoroCents GFP quantification device built by last year’s iGEM team, we sought out approaches to use microscopy to quantify fluorescent cells. Conventional microscopes are expensive, bulky, and complex. To address these concerns, we reached out to Mr. Dan Heieren of Lake Region Optics and Dr. Saad Bhamla of the BhamlaLab at the Georgia Institute of Technology. The Lunchbox Microscope is a portable brightfield digital microscope developed by Lake Region Optics to promote STEM engagement that is capable of connecting to mobile devices and computers to capture microscopic images.
To adapt this technology to suit the needs of our project, we developed an attachment to create a fluorescent microscope using LEDs, filters, and 3D-printed components.
DESIGN
The initial design of the fluorescent attachment to the Lunchbox Microscope used 500 lumen cool white LEDs coupled with the same filters used in the FluoroCents device to create the necessary excitation energy for GFP to glow. The light source was positioned perpendicularly to the digital camera in the Lunchbox Microscope. This design was tested on C. elegans organisms expressing GFP provided by Dr. Hang Lu of the Georgia Institute of Technology. After consultation with Dr. Lu, the perceived GFP expression was actually determined to be a result of reflection of light off of the surface of C. elegans organisms. Before eliminating this design, we were also able to test this design on zebrafish provided by Mr. Dan Heieren. These did not produce successful GFP expression visualizations as compared to a control image provided with the zebrafish.
Figure 8. Comparison between lunchbox microscope and fluorescent microscope for protein sample
After communication with Mr. Heieren regarding the optics of the Lunchbox Microscope, he advised us to stray away from using white light with a plastic filter as this filtered out too much light; the remaining light from the filtration process would not provide enough excitation energy to produce interpretable levels of emission energy in the sample. The second iteration of the Lunchbox Microscope attachment thus utilized a blue light LED chip with wavelength range 450-460nm alongside a glass emission filter of wavelength 510nm. A brine shrimp slide was obtained from Mr. Dan Heieren to continue testing of this schematic of the Lunchbox Microscope. Currently, work is underway to test this schematic in an effort to produce successful results so that the Lunchbox Microscope will be capable of visualizing and quantifying fluorescent cells as part of our two-year project. Wet lab testing is currently being done using the Fluorocents device from last year with modifications from the fluorescent microscope schematic. This will enable us to determine nutrient values through the Agro-Q mobile app for semi-autonomous monitoring of conditions within the hydroponics system.
GITHUB JUDGING RELEASE
AgroSENSE GITHUB JUDGING RELEASE
Link to judging release on GitHub: https://github.com/igemsoftware2020/Lambert_GA/releases/tag/1.0.0
Agro-Q GITHUB JUDGING RELEASE
Link to judging release on GitHub: https://github.com/igemsoftware2020/Agro-Q/releases/tag/1.0.0/