Register for a Hamilton Webinar!

Process Specification Ranges

Dencytee Arc Sensors monitor in-line optical density (OD) in a wide range of processes. The total biomass sensor detects both live and dead cells, along with any debris or particulates which block light. The detected optical density directly correlates to the total cells in solution. Dencytee Arc is most applicable in yeast and bacterial systems. It can also be used in any non-adherent mammalian applications, alongside the Incyte Arc viable cell density sensor. Check out the Dencytee Arc page for further information on recommended ranges. The measurement of viable cell density from Incyte Arc can be used in tandem with the measurement of total cell density from Dencytee Arc to estimate viability within a process.

Measurement Modes and Units for Offline Correlation

The unique dual-mode total cell density sensor has four default offline correlation models. These default models are accessible using the ArcAir software:

Name of the default offline correlation modelUnitComment
TransmissionAU

  • Only Transmission signal is used
  • Usage of Reflection signal is suppressed
ReflectionArb. Unit
  • Only Reflection signal is used
  • Usage of Transmission signal is suppressed
CDW Yeastg/LBaker’s yeast in a stirred tank
Turbidity StdNTUFormazine equivalent standard

The transmission mode uses only the light transmitted through the cell solution to the front detector, providing a signal in AU (absorption units). This mode is a good default starting point, most applicable for low cell density processes.

The reflection mode uses only the light reflected off cells in solution to the back detector, providing a signal in Arb. Unit (arbitrary units). This mode is recommended if the other measurement modes result in a noisy signal or an insufficient fit to the offline data.

The CDW (cell dry weight) Yeast mode uses both transmitted and reflected light to determine the signal in g/L. This is the best option if you are performing the offline correlation with baker’s yeast in a stirred tank environment. This mode is a recommended default for high cell density processes.

The Turbidity Std mode also uses both transmitted and reflected light to determine the signal as NTU (Nephelometric Turbidity Units). The NTU is also known as the Formazine Turbidity Unit and is the best option when the offline correlation is performed in a Formazine equivalent standard.

There are six custom offline correlation models, which can use any of the supported units below. If other units are desired, use the “Arbitrary Unit” option.


UnitDefinitionComment
Arb. UnitArbitrary UnitRelative unit. If the desired unit is not available, it is recommended to select this unit
AUAbsorption UnitTypical unit used to describe turbidity
CFUColony Forming Units
E6 cells/mLMillion Cells per Milliliter
g/LGram per LiterTo differentiate between wet or dry weight, modify the correlation model name
NTUNephelometric Turbidity UnitCorresponding to FTU (Formazine Turbidity Unit), used as a Turbidity standard
ODOptical Density
PCVPacked Cell Volume

Choose your modeling units from the current offline analysis.

Arbitrary Units are default if the desired unit is not available. Absorption Units describe solution turbidity. Colony Forming Units apply to systems measuring cell density via colony counting on plates. Million cells per Milliliter is used for systems measuring viability through trypan blue staining and microscopy. Gram per Liter applies to systems monitored by the weight of cells (wet or dry). Nephelometric Turbidity Units are only recommended if the correlation model was established using the Formazine equivalent standard. Optical Density is a unitless measure of the light which passes through a solution, often measured off-line using cuvettes and a spectrophotometer. Packed Cell Volume is used in systems where cells are centrifuged out of solution into a packed volume, which is physically measured.

Once a model is selected, the ArcAir software will guide you through the entire offline correlation modeling process.

Related Content: