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Question:AstroPlant RPi sensory system

Sidney_AstroPlant asked on July 03, 2017 14:13
115 | 1 answers | shortlink

​Dear community members,

I am currently involved in the development of a hydroponics prototype kit for assessing plant growth in the Netherlands. It is an open science initiative in collaboration with ESA aimed to measure optimum environmental conditions for plants. Hereby we use a Raspberry Pi to measure all kinds of environmental data with the kit. I have a couple of challenges:

  • I'm new to the field of hyperspectral imaging and found the InfraGram initiative very exciting. I use a Pi Noir camera with a blue filter, however I haven't managed to get the desired images that allow for assessing photosynthesis in plants. Is there anyone working with the Rpi Noir camera? Preferably I would like to read into some documentation if available or a contact person to discuss further details. In our case we have a controlled environment and can construct a specific background if needed for optimum pictures. Below a picture taken with the RPi Noir camera (taken outside of the kit):

image description

  • We would like to have water quality testing such as Electrical Conductivity, PH mainly. Most Raspberry Pi interface-capable sensors are very expensive, and we are looking for cost-effective solutions.

Thanks in advance!

Kind regards, Sidney (on behalf of AstroPlant)

water-sensing raspberry-pi infragram water-quality hyperspectral conductivity hydroponics open-water pi rpi initiative-area raspberry images pi-noir multispectral-imaging

question:infragram question:general question:raspberry-pi question:hydroponics


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1 Answers

I haven't used the Pi NoIR cam and have not seen your photos, so I can only respond from general principles.

  1. Camera sensors are not as sensitive to near IR as they are to visible light. So even though the sensor might be sensitive to wavelengths between 700nm and 1000nm, They capture less of that range than they do in the range of any single color (R,G,B). So the ratio of VIS:NIR (e.g., Red:NIR) you can derive from a modified consumer type camera will not be similar to the actual ratio in the light being reflected from plant leaves. This ratio might even be reversed.
  2. A modified camera (IR cut filter replaced with color bandpass filter) cannot produce both a pure visible light channel and a pure NIR channel. A red filter can produce a fairly pure NIR signal in the blue channel but the red channel will have red and NIR mixed in a mostly unknown proportion. A blue filter will produce a blue channel with blue and NIR mixed and a red channel with red and NIR mixed. With the proper filter combined with the proper sensor, the band of interest will dominate in the mixed channels and the hack will work. Otherwise, not so much.
  3. These weaknesses can be compensated for by altering the values returned by the camera for the channels of interest. This is called either calibration or fudging depending on whether the alteration is based on knowledge of the system or an attempt to make the results look right.
  4. With two cameras and the proper filters, pure NIR and VIS channels can be captured, but the issue of low sensitivity to NIR remains.
  5. If you know (quantitatively) the relative sensitivity of NIR and VIS in your cameras, you can correct for this issue.


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