A Node-RED flow that captures a photo on a schedule, sends it to PlantLab for diagnosis, and takes action based on the result. Push notifications, dashboard updates, MQTT messages to your controller, log lines into InfluxDB, or whatever combination you want. No Python. No YAML. Nodes and wires.
Setup runs about 25 minutes on a Node-RED instance that's already up. The cost is whatever camera you own plus PlantLab's free tier at 3 diagnoses a day. The output is a structured JSON result: 31 possible conditions, a growth stage, nutrient antagonism hypotheses, and confidence scores, all ready to feed into whatever comes next.
Something looks wrong. Maybe the bottom leaves are yellowing. Maybe the tips are curling. Maybe you walked into your tent and something just looked off in a way you can't articulate but your gut knows isn't right.
So you did what every grower does: you took a photo, posted it online, and got twelve different answers. Someone said CalMag. Someone said flush. Someone said “two more weeks.” None of them agreed on what the actual problem is.
This guide won't do that. It walks through a systematic process: look at where the damage is, what it looks like, and narrow it down to a specific cause. No guessing, no bro science, no “could be anything, hard to tell from the photo.”
You adjusted your cal-mag for two weeks. The yellowing got worse. Then you saw the webbing.
That's how most growers discover spider mites – not when the problem starts, but when it's already out of control. The early damage looks so much like a nutrient deficiency that your first instinct is to adjust the feed. Meanwhile, a single female mite is producing thousands of descendants in a month.
You won't smell it at first. By the time you do – that damp, musty sweetness coming off a cola that looked fine yesterday – you've already lost that bud and probably the ones touching it. You cut it open, and the inside is grey mush. A week from harvest.
Bud rot. It colonizes from the inside out, hiding in the densest parts of your canopy where airflow is worst and humidity is highest. By the time the exterior shows damage, the interior has been decomposing for days.
Something's wrong with your plant. The leaves look off. You post a photo to a growing forum and within minutes, three people reply: “CalMag.”
You could have posted a picture of your dog and someone would have said CalMag.
It's the universal answer to every cannabis problem, the “have you tried turning it off and on again” of indoor growing. Yellowing? CalMag. Spots? CalMag. Weird leaf curl? Believe it or not, CalMag. And hey – sometimes it works. But when it doesn't, most growers just add more CalMag, which can make things actively worse.
It looks like your plant is getting frosty. White powder spreading across the leaves, that pale shimmer catching the grow light. Then you touch it, and your finger comes away white.
That's not trichome development. That's powdery mildew – and if you're seeing it now, the infection has been active inside your plant for up to two weeks already.
PlantLab now runs a specialist model after detecting any nutrient issue. Instead of “nutrient deficiency,” the API returns “potassium deficiency” or “magnesium deficiency” or whichever of the seven it actually is. Tested and validated at 99.5% accuracy on 14,182 real-world images it has not seen before. Same API, same JSON shape – no changes required on your end.
PlantLab's AI doesn't ship once and stop improving. Behind every release is a cycle of automated experiments that audit the model's own predictions, find where it struggles, and fix the root causes before retraining. The latest cycle ran 47 hyperparameter experiments, analyzed 1,081 classification errors, and cleaned data across 1.34 million images. This is what continuous AI improvement actually looks like – no buzzwords, just the work.
Nutrient antagonism is when excess of one nutrient physically blocks another from being absorbed – your plant has enough of what it needs, it just can't get to it. Adding more of the blocked nutrient usually makes things worse. A 1953 agricultural chart called the Mulder's Chart maps all of these interference relationships; PlantLab's diagnosis now applies that same logic automatically, flagging the most likely excess nutrient in every analysis.
What this post covers:
– Why “add more” is sometimes the exact wrong answer
– The Mulder's Chart: what it shows and how to read it
– The four antagonism traps cannabis growers hit most often
– How to tell antagonism from a true deficiency
– What to actually do once you've identified the likely excess
You're three weeks into flower. New growth is showing interveinal chlorosis – yellowing between the veins. Classic iron deficiency. You've seen it before. You adjust your pH, add some chelated iron, wait a few days. Nothing. You add more. The leaves get worse. Two weeks of this and your runoff EC looks completely normal. What is going on?!
Here's the thing: your plant probably has plenty of iron. The problem is that something else is blocking it from getting in. You're chasing a deficiency that isn't really there.
Nitrogen deficiency in cannabis appears as yellowing of lower, older leaves that progresses upward from the bottom of the plant. Because nitrogen is a mobile nutrient, the plant moves it from old growth to support new leaves. The key diagnostic marker is that yellowing includes the veins – unlike iron or magnesium deficiency where veins stay green.
Quick checklist:
Yellowing starts on BOTTOM leaves
Yellowing includes veins (not just between veins)
New growth at top still green
Leaves may cup upward before falling off
If yellowing appears on top/new growth first, it is NOT nitrogen deficiency.
