Dear Colleagues,
I have been measuring the area of tropical fern leaves for several species, however the perimeter is a different and difficult task.
Ferns have higlhy divided and the small pinnule are often overlapping and this create a difficult situation to measure the perimeter. A simple strategy I have used is to divide each pinna/pinnula independently and later sum the area and perimeter values. As you can understand it is a tedious and time-consuming process, moreover the process itself can generate a small proportion of mistakes.
The software I have used range from ImageJ to Petiole and many more. I would like to ask, based on your experience do you have some advice on this regard?
I have attached three photos where is possible to see the leaves with the overlapping part.
Kind regard,
Daniele Cicuzza
Hello Daniele; This is a method that is very labor-intensive but it is technically simple. Many years ago I and my students were interested in temperature regulation is sphingid moths. That required knowing the mass of the moth as well as the wing area. Here is what we did to determine wing area.
1. Remove right-side wings from moth.
2. Make a photocopy of the wings. At the same time make images of pieces of paper of known area.
3. cut out the images carefully.
4. weigh the cutouts.
5. The weight of the wing cutouts is directly proportional to the area of the wings.
We were able to make a statistically robust number of measurements, but it was tedious.
Making cutouts of fern leaves will be a challenge to do accurately. Best regards, Jim Des Lauriers
In our ongoing scientific endeavors pertaining to various tree species in the Amazonian rainforest, we are on the cusp of disseminating our research findings through scholarly publication. The core of our methodological framework is grounded in mathematical topology, specifically employing the conceptualization of foliage as topological vector spaces. Utilizing robust segmentation algorithms in batch processing, we obviate the necessity for treating individual leaves as discrete entities, thereby achieving computational efficiency and analytical precision. Paramount to the success of this approach is our meticulous attention to the quality of the photographic input. This involves an exhaustive analysis of Exif (Exchangeable Image File Format) metadata, supplemented by the precise delineation of leaf silhouettes for optimal data extraction and analysis.
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