CranCam Update 2022

As a root project that will be able to feed lots of future work, Dr. Mura’s lab in 2021 piloted a CranCam project, which will be deployed at a larger scale in 2022. Developing a Raspberry Pi-based camera system that can take pictures of cranberry growth stages will improve selection of cultivars (color development, early flowering), as well as developing phenological models (GDD & more), as well as inform crop management practices (irrigation, fertilization, crop protection, and harvest planning).

**Fig. 1**: development and testing of the CranCam.

**Fig. 2**: Photos taken of 6 pilot test cultivars on the same marsh in the same week.

**Fig. 3**: A pilot study of when three cultivars hit growth stage milestones in the 2021 growing season.

Currently, Dr. Mura’s lab staff are identifying growth stages present in photos manually. But in order for the project to scale effectively, a model that identifies growth stages present in photos using machine vision. Fig. 4 shows two examples of progress being made on these models.

**Fig. 4**: two example photos showing a machine vision model’s labeling of dormant vines (with 85% confidence) and hook phase vines (86% and 85% confidence). These models will continue to improve with training.

This is a recap of Dr. Mura’s presentation at the April 21, 2022 Mini Clinic, prepared by Allison Jonjak.

This article was posted in Cranberry and tagged Cranberries, Crancam, Jyostna Devi Mura.

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CranCam Update 2022