Frame Rhythm: A new cost-effective approach for semi-automatic microalgal imaging and enumeration

Algal Research(2022)

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Abstract
Quantifying cell abundance is of paramount importance for monitoring the quality and production of microalgal growth, as well as for early detection of harmful algal blooms (HAB) events, which cause economic losses and societal impacts around the globe. Although manual quantification using counting chambers and microscopy is a well-established method to count microalgae, it is very time-consuming and requires an advanced level of expertise. In last decades, a variety of commercial instruments has emerged as an alternative to automate this process. However, their high cost and the need for specialized technical support hamper their dissemination, particularly in developing countries. This study presents a simple, fast, reliable and cost-effective method for semi-automatic microalgae quantification. The so-called Frame Rhythm (FR) method relies on a handcrafted simple counting chamber imaged with a digital camera coupled to a regular microscope. An in-house software subsequently detects and quantifies microalgal cells in an image sequence, preventing repetitive counts and static noise. The proposed approach was validated by comparison with well-established methods, while tracking different growth phases of the chlorophycean Tetraselmis gracilis, a widely cultured microalga. Results indicated a strong positive correlation (r = 0.99, R2 = 98.31%, p ≤ 0.01) and high agreement between methods, as well as low intra (1–11%) and inter-operator (2–12%) variance for the proposed technique. The FR method provided a reduction of at least 14× in sample processing time in relation to traditional microscopy, at a much lower implementation and maintenance cost compared to commercially available automatic and semi-automatic counting equipment. The new method represents an affordable alternative to acquire microalgal abundance data with a similar degree of accuracy compared to traditional counting chambers and sophisticated benchtop instrumentation.
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Key words
Counting chamber,Phytoplankton,Microalgae,Computer vision,Automated counting,Tetraselmis gracilis
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