Hi! Welcome to the 2nd weekly installment in our four-part vineyard-oriented science and technology series! Last week we talked briefly about the electromagnetic spectrum. This week, we’ll narrow the focus a bit and discuss the use of imaging systems in viticulture, particularly with regard to multispectral cameras.
Infrared radiation, or IR, (discussed in the last email, and in greater detail in last week’s blog post), is generally sensed by us humans as radiant heat. The photosynthetic foliage of plants reflects IR in a direct and positive relationship to plant health and vigor, i.e., more active photosynthesis = more intense infrared reflection. We cannot see infrared with our eyes, but a camera’s sensor can detect it much as you and I detect visible light.
Infrared film was invented about a hundred years ago, but it took until the early 1970s to discover that IR reflectance from plants is a dynamic phenomenon containing actionable information. In the past 20 years, traditional photographic film has largely been replaced by the photodetector - silicon-based imaging sensors ubiquitous in the modern age - you more than likely have one on your person right now, in your smartphone camera. The photodetector makes infrared capture more practical - and opens up a world of possibility for its use in viticulture.
A multispectral camera works much the same way as a regular digital camera, with a few important differences.
In general, a regular digital camera has one sensor with three stacked layers – each sensitive to only red, green, or blue (RGB). This sensor is divided into pixels (a truncation of the words picture and element) which are the elemental unit of a digital image. Each pixel, when exposed to light, records digital numbers - an expression of the intensity of light each color-sensitive detects. Thus, each pixel in an RGB image has three values, for example, (150, 34, 231), corresponding to (red, green, blue).
A multispectral camera, however, normally features four (or more) separate sensors, each receptive only to energy within a given wavelength range. Hence, instead of three values, each sensor will only report one value per pixel when an image is captured. A typical setup is as follows: one sensor only picks up light in the red wavelength range, one in the green, one in the blue, and one in the infrared - yielding four separate images. This allows much more precise color segmentation.
During analysis of vegetation health, each of the four images are stacked on top of each other in GIS or photo-processing software. Here, the ratios between reflectance of the four different radiation wavelength ranges are determined, allowing the researcher to draw conclusions.
To be usable in viticulture, multispectral imagery must be captured and processed according to rigorous standards.
Firstly, access to a database of vine foliage reflectance ratios that are typical of photosynthetic vigor, water status, and disease symptoms, is fundamental.
Information gained from any given imaging session must be referenced to a sound dataset in order to produce a reliable vine-health map.
The second thing that is needed is the ability to focus on a very small portion of the spectral range in question, by using filters for each sensor that exclude wavelength ranges not relevant to the analysis.
To effectively record an accurate picture of your vine health, the camera's filters must be adjustable. The correct settings to capture exactly the light wavelengths required must be informed by data compiled by decades of meticulous research. Without the correct filter settings, a multispectral camera is geared towards general agriculture - an “overview” scope that does not have much relevance to the particularities of grapevines.
In conclusion, multispectral cameras are an incredibly powerful tool, but are not likely to deliver actionable results without:
- rigorous cross-referencing with databases of grapevine reflectance.
- filter settings calibrated to pick up relevant wavelength ranges.
Signing off for this week! Stay tuned - next week's post will unpack the ins and outs of aerial image capture techniques.