> For the complete documentation index, see [llms.txt](https://help.sbtinstruments.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.sbtinstruments.com/mpd/cell-growth/optical-drawbacks.md).

# Optical drawbacks

Optical methods measure how much light your culture blocks. Optical density (OD) and backlight scattering are the two common ones. Both are often used as proxies for cell concentration. You run them on-line as a sensor, or diluted off-line in a cuvette.

They are fast, cheap, and already in your lab. They also share one blind spot: light scattering responds to much more than the number of cells. In this section we will focus on optical density at 600 nm (OD<sub>600</sub>) because it is the predominant light scattering proxy method for cell concentrations.

## OD depends on cell size

Cell size shows the problem most clearly. Cells shrink as nutrients run out. The same number of cells therefore scatters less light in stationary phase than in early-exponential phase.

<figure><img src="https://142487182-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FseAjVXi9YrPNSfdp1OXS%2Fuploads%2Fx8m3B2vkhHbTJYtRWNnm%2FOD_cuvette.png?alt=media&#x26;token=4c17bab8-2c9c-4d0c-86ed-602e8e55ab22" alt=""><figcaption><p>Optical methods are strongly dependent on the size of objects. The two samples scatter the same amount of light, but the bacteria in exponential stage (left) are considerably bigger than the cells in stationary stage (right). Same OD but different cell concentrations.</p></figcaption></figure>

## OD is affected by pigments and particulates

Optical methods like OD can't tell a cell from a bead. Less light reaching the detector may be due to scattering from bacteria, but it may also be due to scattering from non-bacterial objects or absorption by pigments.

<figure><img src="/files/IWMIndcYgF6otd9F1e9d" alt="" width="375"><figcaption><p>Optical methods like OD can't tell if a signal is due to cells, particulates or color absorption. Left: A bacterial culture. Right: Molasses containing black pigments and non-bacterial particulates</p></figcaption></figure>

## Four studies demonstrate optical shortcomings

We ran four studies to put numbers on this. Each one compares OD<sub>600</sub> against BactoBox®, plate counts, or both. The table sums up what we found. The four pages below hold the study designs, the data, and the implications. Click the links for to see the results in the subsections.

## BactoBox® compared to optical methods

<table><thead><tr><th width="279.99993896484375">Question</th><th width="226">Optical methods (OD600)</th><th>BactoBox®</th></tr></thead><tbody><tr><td>What is the output?</td><td><strong>absorbance units</strong> (AU)</td><td><strong>cells/mL</strong></td></tr><tr><td><i class="fa-blackberry">:blackberry:</i> <a href="/pages/Ok3xb1huA78ppKiyPyQI">Does it distinguish cells from other objects?</a></td><td><mark style="background-color:$danger;"><strong>No</strong></mark><br><mark style="color:$info;">Every object that scatters or absorbs light adds to the signal.</mark></td><td><mark style="background-color:$success;"><strong>Yes</strong></mark><br><mark style="color:$info;">It classifies each object, then reports cells/mL apart from total/mL.</mark></td></tr><tr><td><i class="fa-eye-low-vision">:eye-low-vision:</i> <a href="/pages/rrzL0Q9jC2W7fTzJUrbW">What is the lower limit of quantification (LLOQ)?</a></td><td>≈2×10⁸ cells/mL</td><td>3×10⁶ cells/mL at 1:100 dilution.<br>3×10⁵ cells/mL at 1:10 dilution.</td></tr><tr><td><i class="fa-scale-unbalanced">:scale-unbalanced:</i> <a href="/pages/oaLzOIvVi5wgosYzHte9">Is a calibration factor needed?</a></td><td><mark style="background-color:$danger;"><strong>Yes</strong></mark><br><mark style="color:$info;">One per strain, medium, and growth phase.</mark></td><td><mark style="background-color:$success;"><strong>No</strong></mark></td></tr><tr><td><i class="fa-scale-unbalanced">:scale-unbalanced:</i> <a href="/pages/oaLzOIvVi5wgosYzHte9">Is the calibration factor stable?</a></td><td><mark style="background-color:$danger;"><strong>No</strong></mark><br><mark style="color:$info;">Cells-per-OD moved 11.4× across a single growth curve.</mark></td><td><mark style="background-color:$success;"><strong>N/A</strong></mark><br><mark style="color:$info;">The ratio to plate counts held at geomean of 1.01, span 2.2×.</mark></td></tr><tr><td><i class="fa-scale-unbalanced">:scale-unbalanced:</i> <a href="/pages/oaLzOIvVi5wgosYzHte9">Does cell size skew the result?</a></td><td><mark style="background-color:$danger;"><strong>Yes</strong></mark><br><mark style="color:$info;">Cells-per-OD scales with size of the objects.</mark></td><td><mark style="background-color:$success;"><strong>No</strong></mark><br><mark style="color:$info;">It counts one object at a time, and reports</mark> <a href="https://help.sbtinstruments.com/software/access/pages/measurement-group/growth-curve-group-type#cize"><mark style="color:$info;">CIZE</mark></a> <mark style="color:$info;">separately.</mark></td></tr><tr><td><i class="fa-scale-unbalanced">:scale-unbalanced:</i> <a href="/pages/oaLzOIvVi5wgosYzHte9">Usable in lag and early-exponential phase?</a></td><td><mark style="background-color:$danger;"><strong>No</strong></mark><br><mark style="color:$info;">The first nine readings of an 11.6 h run sat at 0.00 ± 0.01 AU.</mark></td><td><mark style="background-color:$success;"><strong>Yes</strong></mark><br><mark style="color:$info;">It resolves a 1×10⁶ cells/mL seed.</mark></td></tr><tr><td><i class="fa-arrow-down-small-big">:arrow-down-small-big:</i> <a href="/pages/E9YRFzavJBHPx1DoyYBj">Does the method agree with plate counts when screening growth media?</a></td><td><mark style="background-color:$danger;"><strong>No</strong></mark> (R² = 0.12).</td><td><mark style="background-color:$success;"><strong>Yes</strong></mark> (R² = 0.83).</td></tr><tr><td><i class="fa-arrow-down-small-big">:arrow-down-small-big:</i> <a href="/pages/E9YRFzavJBHPx1DoyYBj">Does it rank growth media correctly?</a></td><td><mark style="background-color:$danger;"><strong>No</strong></mark><br><mark style="color:$info;">OD600 called one glycerol concentration uniquely best. Direct cell counts and CFUs disagreed.</mark></td><td><mark style="background-color:$success;"><strong>Yes</strong></mark><br><mark style="color:$info;">It tracked plate counts. Better precision gives higher statistical power than CFUs.</mark></td></tr><tr><td>Is it available as online method?</td><td><mark style="background-color:$success;"><strong>Yes</strong></mark></td><td><mark style="background-color:$danger;"><strong>No</strong></mark></td></tr><tr><td>Is it available for high-throughput screening</td><td><mark style="background-color:$success;"><strong>Yes</strong></mark></td><td><mark style="background-color:$danger;"><strong>No</strong></mark></td></tr></tbody></table>

{% hint style="info" %}

### Optical methods still earn their place

Use OD<sub>600</sub> or backlight scattering for on-line monitoring and high-throughput screening. Both are fast and cheap. Then refine your shortlist with direct cell counts.
{% endhint %}

For the individual studies, see the following subpages

* [OD is inflated by background](/mpd/cell-growth/optical-drawbacks/od-is-inflated-by-background.md)
* [OD misses low cell concentrations](/mpd/cell-growth/optical-drawbacks/od-misses-low-cell-concentrations.md)
* [OD calibration factors drift](/mpd/cell-growth/optical-drawbacks/od-calibration-factors-drift.md)
* [OD confounds medium optimization](/mpd/cell-growth/optical-drawbacks/od-confounds-medium-optimization.md)


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