aridpaella85
New Member
This interactive AI model is trained to draw a week over week probability curve denoting the likelihood that a plant will be ready for harvest on any particular week. This can be used to compare how quickly a particular grow schedule can be expected to yield mature flowers. Because the optimal harvest time depends on the grower's specific goals, the AI is trained to favor the "normal" case balancing quality, weight, and potency.
The tallest point on the line indicates when the AI predicts a plant will most likely be ready for harvest. Seen below, the peak during week 10 denotes that there's a 16% chance that the plant will be ready for harvest on that specific week.
This distribution can be viewed cumulatively, where each week's harvest probability is added to the sum of the previous weeks, drawing a smooth arc. Note how the projection approaches 100% as it nears week 20, because the majority of plants in the training sample were harvested within the 20 week time frame.
An interesting property of the cumulative visualization is that the closer the curve is to the left side of the chart, the faster the plant is expected to reach full maturity, offering a clear visual analogy.
One of the primary drivers behind flower maturation time is the light schedule used during the vegetative stage. Setting the light schedule to a 24-0 schedule (24 hours of light, 0 hours of darkness) causes the plant to mature significantly faster than the 18-6 schedule (drawn in blue for comparison).
Interestingly enough there does seem to be a point where adding more hours of light no longer improves flower maturation time. The AI projects that the 20-4 schedule generally strikes the best balance, maturing plants faster than other schedules. However the difference between the 20-4 schedule and the 24-0 schedule is small, which may explain some of the controversy surrounding whether or not plants need "rest" in order to reach their full potential.
In addition to light schedule, the plant's genetics play a significant role in flower maturation times. When controlling for an 18-6 light schedule, the difference between an autoflowering plant (drawn in gold) and a photoperiod sensitive plant (drawn in blue for comparison) is even larger than adjusting for light schedule alone.
The tallest point on the line indicates when the AI predicts a plant will most likely be ready for harvest. Seen below, the peak during week 10 denotes that there's a 16% chance that the plant will be ready for harvest on that specific week.
This distribution can be viewed cumulatively, where each week's harvest probability is added to the sum of the previous weeks, drawing a smooth arc. Note how the projection approaches 100% as it nears week 20, because the majority of plants in the training sample were harvested within the 20 week time frame.
An interesting property of the cumulative visualization is that the closer the curve is to the left side of the chart, the faster the plant is expected to reach full maturity, offering a clear visual analogy.
One of the primary drivers behind flower maturation time is the light schedule used during the vegetative stage. Setting the light schedule to a 24-0 schedule (24 hours of light, 0 hours of darkness) causes the plant to mature significantly faster than the 18-6 schedule (drawn in blue for comparison).
Interestingly enough there does seem to be a point where adding more hours of light no longer improves flower maturation time. The AI projects that the 20-4 schedule generally strikes the best balance, maturing plants faster than other schedules. However the difference between the 20-4 schedule and the 24-0 schedule is small, which may explain some of the controversy surrounding whether or not plants need "rest" in order to reach their full potential.
In addition to light schedule, the plant's genetics play a significant role in flower maturation times. When controlling for an 18-6 light schedule, the difference between an autoflowering plant (drawn in gold) and a photoperiod sensitive plant (drawn in blue for comparison) is even larger than adjusting for light schedule alone.
