• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

Effect of Detergent on Membrane Permeability

Extracts from this document...


´╗┐The Effect of Detergent Concentration on Membrane Permeability of Cells Introduction: There is often a rule in cooking that says; do not rip off the skin of the beetroot or wash the tail of the beetroot when you cook*1, unless you want to dye the cooking water red. This red pigment that comes out of the beetroot is caused by a substance called betalaine, which is located within the tonoplast, the membrane of plant cells which usually contains liquid, of the beetroot cell. Normally, these pigments do not leak out of the cell because they are surrounded by the cell?s plasma membrane, which is a phospholipid bilayer. Since these membranes are soluble in water, not in liquid, they do not leak out, unless the cell?s plasma membrane is somehow disrupted or damaged. If a beetroot cell leaks out betacyanin, the cell is presumably dead because its membrane and vacuole are damaged. The plasma membrane of a cell is made up of a phospholipid bilayer. These layers are composed of hydrophilic heads that attract water and the hydrophobic tails repel the water. The hydrophilic heads are always on the outside of the cell and the hydrophobic tails are always on the inside. This membrane controls the transportation of particles into and out of the cell. With this arrangement of membrane in a beetroot cell, the membrane prevents the pigments from leaking off of the cell because they are not soluble. ...read more.


Quantitative - Data Collection Solution Absorbance (AU) (±0.001 AU) Solution without Beet Solutions with Beet Trial 1 Trial 2 Trial 2 Mean of all Trials Distilled Water (0% Detergent) 0.001 0.066 0.037 0.043 0.001 4% Detergent 0.775 0.682 0.627 0.560 0.775 8% Detergent 0.867 0.620 0.545 0.450 0.867 12% Detergent 0.982 1.041 0.653 1.042 0.982 16% Detergent 2.410 2.756 1.081 2.433 2.410 1. Calculations: 1. Mean Solution Mean (AU) Distilled Water (0% Detergent) 0.049 4% Detergent 0.623 8% Detergent 0.538 12% Detergent 0.912 16% Detergent 2.090 Sample Calculation: 4% Detergent Mean = Sum of a data set/Number of data Mean = (0.682 AU + 0.627 AU + 0.560 AU)/3 Mean = 0.623 AU 1. Range Solution Absorbance (AU) (±0.0001 AU) Trial 1 Trial 2 Trial 3 Range Distilled Water (0% Detergent) 0.066 0.037 0.043 0.029 4% Detergent 0.682 0.627 0.560 0.122 8% Detergent 0.620 0.545 0.450 0.170 12% Detergent 1.041 0.653 1.042 0.389 16% Detergent 2.756 1.081 2.433 1.675 Sample Calculation: 4% Detergent Range = Maximum Value - Minimum Value Range = 0.682 AU – 0.560 AU Range = 0.122 AU Since the mixture of detergent in water causes the water to be translucent instead of transparent, less photon are able to travel though the solution, therefore, the colorimeter reads the data as having less absorbance than it normally should, if it was caused alone by the color leakage from the beetroot. ...read more.


Even though we tried to eliminate the error by subtracting the absorbance of the original solution from the solution with beet, the error still persists because we do not know how much the betalaine leaked from the beet affect the translucency of the original solution without beet. Since we have only 3 trials, and the data do not necessarily agree in every circumstance, the data collected are not 100% reliable. There is even an outlier in the data (as mentioned above). Therefore, the mean is not 100% accurate. We could have made the experiment more accurate by repeating the same procedure for more than 3 trials. They experiment would give a more accurate data if it was repeated for about 8-10 times. Apart from the setup errors, we also noticed that the absorbance of the distilled water is not 0, even after the calibration. This would cause another slight systematic error in the experiment, because the data will likely be slightly above what they are supposed to be. It may even mean that the distilled water used in the experiment is not 100% transparent, which would be another slight error in the experiment. As with all electronic devices that uses electricity, the voltage that is needed to run the colorimeter would generate heat. This heat has the potential to affect and change the data that the colorimeter reads. Citation *1: http://www.sanitarium.com.au/health-and-wellbeing/superfood-beetroot *2: http://www.madsci.org/posts/archives/2000-12/976555915.Cb.r.html - Other resources http://www.piercenet.com/browse.cfm?fldID=5558F7E4-5056-8A76-4E55-4F3977738B63 http://en.wikipedia.org/wiki/Cell_disruption ...read more.

The above preview is unformatted text

This student written piece of work is one of many that can be found in our International Baccalaureate Biology section.

Found what you're looking for?

  • Start learning 29% faster today
  • 150,000+ documents available
  • Just £6.99 a month

Not the one? Search for your essay title...
  • Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

See related essaysSee related essays

Related International Baccalaureate Biology essays

  1. Beetroot Plasma Investigation. The main objective of this investigation is to focus on ...

    Group 4 Group 5 0 100,17 100,23 111,21 100,17 88,06 100,17 100,23 114,24 108,18 86,63 20 93,74 92,41 91,56 100,17 84,79 87,90 76,45 100,50 100,17 72,71 40 86,96 90,15 94,28 94,81 88,45 89,29 88,38 100,01 100,14 71,60 60 82,02 89,66 100,01 100,21 77,90 85,26 82,71 100,01 82,17 86,50 80 78,86

  2. The effect of toliet cleaning products on E-coli ...

    0 29.8 16.4 12.6 10 28.4 Standard deviation (mm) 0 3.8 3.0 3.2 2.2 5.7 2.3.1- Processed data graph (figure 3) The smallest zone of inhibition was the negative control of diluted water, the highest inhibition was observed for the positive control of bleach solution.

  1. Beet Lab. Aim: To determine the effects of temperature on the permeability of ...

    Students will be expected to incorporate the use of the spectrophotometer into their experimental design to measure the intensity of color in the surrounding environment. The intensity of color should be proportional to the amount of damage sustained by the beet cell membrane.

  2. Comparing the Sexy Sons Hypothesis and the Pathogen Avoidance Models Effects on Sexual Selection

    The second point adds on to this fact as female preference to the trait must be linked to the presence of the trait otherwise the trait would not even be viewed as ?ornamental? or ?showy? which is highly unlikely. Additionally, the third and fourth point tie together in that showier

  1. What is the effect of pH levels on the net production, given by the ...

    Controlled Variables: Tap water was used in all trials in order to allow for maximized growth ex situ[6]. Note: The tap water was from the same source. (water content can affect growth of phytoplankton) Phytoplankton were all cultured in same BOD bottles for testing procedures.

  2. How will changing the percentage of glucose concentration affect the light transmission percentage from ...

    Variable measured Method of measuring variable Independent variable Concentration of glucose (%) The 5 values I will use for the concentration would be 20%, 40%, 60%, 80% and 100%. These percentages will be calculated from the water to glucose concentration ratio where the water is used to dilute the glucose concentration.

  1. Comparing the effect of different antimicrobials on the growth of E.coli

    Materials Two petri dishes containing the Luria Bertani (LB) culture medium, prepared by our tutor; A marker for labelling the petri dishes with the name of the substance that would be tested in it and 5 or 6 dots (depending on the substance they chose) to mark the places the filter paper discs impregnated with the chemical would be

  2. The Effect of Alcohol on Biological Membranes

    0.325 0.300 0.298 0.168 0.572 0.382 0.240 0.243 0.169 0.146 0.222 0.212 0.280 0.449 0.771 0.377 0.231 0.320 0.145 0.167 0.244 0.212 0.232 0.120 0.191 0.197 0.223 0.202 0.232 0.140 0.179 0.315 0.285 0.189 0.451 0.216 0.270 0.242 0.214 0.235 0.265 0.355 0.275 0.173 0.219 0.258 0.266 0.244 0.207 0.348

  • Over 160,000 pieces
    of student written work
  • Annotated by
    experienced teachers
  • Ideas and feedback to
    improve your own work