CRCLR Recipes

CRCLR Recipes

Designing a feature that allows growers & plant scientist to set specific environmental conditions over time for any type of plant.

Challenge

How do we allow all types of users to manage environmental conditions within the system

How do we allow all types of users to manage environmental conditions within the system

  • Build multi stage timelines

  • Set clear light, water & air variable values

  • Save, modify and share recipes

What is the CRCLR system

The CRCLR system is a series of movable racks, a nutrient distribution system and a software that allows users to manage indoor farms. These farms operate year round controlling all possible environmental variables such as temperature, nutrients, humidity, light levels & more.

How does an environment affect plant growth

Plants respond strongly to environmental stimuli, the conditions in which a plant is raised has a tangible effect on their size, taste, longevity and growth speed. 



For example, if a strawberry plant is exposed to colder conditions during night cycles, it will respond with a higher sugar content resulting in sweeter berries when harvested.

How we impliment this

When our racks, named blades, come together, they create an zone in the space between where we can control up to 15 unique environmental variables with precision. These variables are split into 3 groups of water based, air based and light based.

Water Temp

EC

pH

ORP

Spray Rate

Leaf Temp

Air Temp

VPD

Relative Humidity

Air Speed

CO2

Green Light

Red Light

Blue Light

Far Red Light

CLI

PPFD

Incorporating time in an understandable manner

It's important to consider growth stages

Its also important to consider the life cycles of plants and how they affect growth. The needs of the plant during the sprouting stage will likely be different than the needs at a fruiting stage.

Its also important to consider day and night cycles of the plants, lighting for example has to be provided in phases, constant light will dy out the leaves.

Transferring time into the UI

On/Off screen

First design concepts were based around the idea of setting all setpoints at a single instance on a timeline. This worked well for inital R & D testing but proved clunky when building recipes made to actually grow plants

Graphed data

The preferred design included graphing the data over a repeating time frame. These cycles of either 12 or 24 hour periods let users create a day & night mode that ramps down quickly and easily.

Recipes UI design

Timeline Builder

The base level of any recipe is the timeline. This timeline is configured in the timeline tab of recipes. Here users can configure the time line steps, durations and order of their grows. The new timeline bar will be displayed visually below.

Timeline bar

The timeline bar has multiple versions each providing different info. They all show the number amount and ratio of stages but some also use a darker blue to display the current stage for active grows.

Within the setpoints tab, users can manage the variables within a cycle, all graphed visually through lines on a chart. Each lines can be manipulated to increase or decrease over time

Moving setpoints

When setpoints are dragged, the pop up only display the time and value associated until it’s let go. This pop up is translucent so the remaining line are still clearly visible.

Setpoint pop ups

The pop ups provide more detailed ability to manipulate the values and line types. Depending on the setpoint you can modify the point’s position, line style, acceptable range and if applicable frequency.

Lighting setpoints

Lighting setpoints are more complex and controlled by sliders. The ratios are connected so increasing one light spectrum will have an inverse effect on all of the others.

New opportunities: Machine learning recipe creation

As the user base grows, the plan is to incorporate machine learning into recipe builders. With enough data, we can generate recipes through simple real life inputs like size, sweetness, colour and growth speed.

How did we do?

Wins: Strong exploration

Once trained, farmers were quite excited to experiment with the new tools.

Fail: Steep learning curve

Teaching farmers to use the tool was farm more difficult than planned. More thorough tutorials will be needed in the future to address this.

200+

New recipes created in the first month

10%

Increase in yields in the first 6 months

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