Gena GorinBlock II Biology SL7 February ‘12

Lab: Transpiration Rate and Water pH

Research

The goal of this experiment is to ascertain quantitatively the deviation from a distilled-water control, due to increasing concentration of H+ ions, of the transpiration rate of a small ornamental plant with medium-sized leaves. It is presumed that as the concentration increases, the transpiration/metabolism rate will decrease; this assumption will be evaluated in tracking the loss of water over several days.

The above assumption is drawn from external research, namely: Wilkinson, Sally, Janet E. Corlett, et al. "Effects of Xylem pH on Transpiration from Wild-Type and flacca Tomato Leaves." Plant Physiology. 117. (1998): 703-709. Web.

The plant used will be a representative of the genus Peperomia; it is apparent that the specific type is Peperomia obtusifolia, judging by the moderately waxy quality and large white margins of the leaves. The control of leaf sizes is admittedly inexact; however, it may surely be said that one stem with two leaves of approximately the same (3-cm radius) size was used for each test tube.

The H+ ions will be provided by dilution of hydrochloric acid. Given that HCl dissociates completely and that the volumes used in dilution will be relatively large, any imprecision in concentration is judged negligible.

Water loss due to evaporation will theoretically be prevented by adding a hydrophobic oil film over the water in the graduated plastic tube.

Variables

The independent variable is the pH of the water provided to the plant, ranging in integer values from 4 to 7. As 7 is essentially the pH of distilled water, it is used as a control for the effects of an acidic environment.

The dependent variable is the rate of loss of water, analyzed holistically.

The control variables include the instruments, the environment, the graduation and calibration of the tubes, and the approximate sizes of the plants.

Materials

Stems of Peperomia obtusifolia plants, each with two 6-cm leaves, 4 1M HCl, 2 mL Graduated plastic tubes, 4 Test tube rack, 1 Marking tape Graduated cylinder, 10 mL Disposable pipets, 2 Test tubes, 7 Oil, approx. 4 mL

Procedure

Mark test tubes with integers from 1 to 7 Mark graduated tubes with integers from 4 to 7 Transfer 2 mL 1M HCl to graduated cylinder, add 8 mL dH2O Mix, transfer to test tube “1” Add 10 mL H2O to graduated cylinder, transfer to test tube “1” Add 2 mL of liquid in test tube “1” to graduated cylinder, add 8 mL dH2O, transfer to test

tube “2,” add 10 mL H2O to graduated cylinder, transfer to test tube “2” Repeat above step serially until all test tubes except “7” have 18 (or, in case of “6,” 20)

mL of dilute HCl Add 20 mL dH2O to test tube “7” Cut four plant stems to specifications in Materials section Add 10 mL fluid from test tube “4” to graduated tube “4,” repeat for all graduated tubes Insert plant stems into graduated tubes Use second disposable pipet to transfer enough oil into each test tube to cover the surface

of the water Take readings of initial water level Clean up test tubes/graduated cylinder/misc. equipment; place graduated tubes into test

tube rack and take measurements over a period of time

Data

All quantitative data consists of a marginally notable visibly higher rate of transpiration in the plant in the 7 pH water. It must be noted that over the period tested, the changes in metabolism did not correspond to any immediately visible changes in plant makeup, structure, or function. Presumably, those would become more evident over larger periods of time relative to the plant’s

All data concerning the water level contains an inherent uncertainty of ±.1 mL, non-negligible.

The water level data includes the thickness of the oil layer; n.b. that only the change is meaningfully interpretable, so the oil layer is insignificant to the final result.

All uncertainties concerning the times are negligible, given that the scale of presentation is in kilominutes.

Table a: Water level measurements, 4-7 pH, 26 January-3 FebruaryTime (minutes) Water level (mL)

Date Time ∆Minutes

∑Minutes Kmin pH 4 pH 5 pH 6 pH 7

26-Jan 1201 0 0 0 10.4 10.9 10.7 10.51623 262 262 0.262 10.2 10.8 10.6 10.3

31-Jan 0855 6752 7014 7.014 9.8 10.1 10.1 9.91-Feb 0847 1432 8446 8.446 9.6 9.9 9.8 9.4

1041 114 8560 8.56 9.5 9.8 9.8 9.42-Feb 0852 1331 9891 9.891 9.2 9.7 9.5 9

1612 440 10331 10.331 9.1 9.6 9.5 8.93-Feb 1041 1109 11440 11.44 9 9.5 9.1 8.5

1624 343 11783 11.783 8.9 9.4 9.1 8.4

0 2 4 6 8 10 12 148

8.5

9

9.5

10

10.5

11

Graph a: Water level v. time, incl. uncertainty

pH 4pH 5pH 6pH 7

Time / Kmin

Wat

er le

vel /

mL

0 2 4 6 8 10 12 148

8.5

9

9.5

10

10.5

11

11.5

Graph b: Water level v. time, incl. regression

pH 4Linear (pH 4)pH 5Linear (pH 5)pH 6Linear (pH 6)pH 7Linear (pH 7)

Time / Kmin

Wat

er le

vel /

mL

The following chart, Table b, outlines the three key functions for each of the trials:

The “Regression” column is taken directly from the linear regressions shown in Graph b. The “FunctionMax” column is the steepest possible linear function, equal to the line

between the initial point plus the uncertainty and the final point minus the uncertainty (i.e. the uncertainty extreme resulting in most negative slope).

The “FunctionMin” column is the least steep possible linear function, equal to the line between the initial point minus the uncertainty and the final point plus the uncertainty (i.e. the uncertainty extreme resulting in the least negative slope).

Table b: Average transpiration functions, incl. uncertaintyRegression Init Max Final

MinFunctionMax Init Min Final

MaxFunctionMin

4 -0.1152x+10.389 10.5 8.8 -0.1443x+10.5 10.3 9 -0.11033+10.35 -0.1216x+10.882 11 9.3 -0.1443x+11 10.8 9.5 -0.11033+10.36 -0.1262x+10.75 10.8 9 -0.1528+10.8 10.6 9.2 -0.11882+10.67 -0.159x+10.563 10.6 8.3 -0.1952+10.6 10.4 8.5 -0.16125+10.4

The following table, Table c, outlines the conclusions drawn from Table b, i.e. the average transpiration rates along with the maxima and minima feasible due to measurement uncertainty. All rate units in Table c are mL∙Kmin-1, that is, milliliters of water processed per thousand minutes.

Table c: Average transpiration rates, incl. uncertainty

RateMin RateAvg

RateMax

4 0.11033 0.1152 0.14435 0.11033 0.1215 0.14436 0.11882 0.1262 0.15287 0.16126 0.159 0.1952

4 5 6 70.1

0.110.120.130.140.150.160.170.180.19

0.2

Graph c: Transpiration rate v. pH

pH 4pH 5pH 6pH 7TrendlinePolynomial (Trendline)

Water acidity / pH

Rate

/ m

L Km

in-1

0 0.00002 0.00004 0.00006 0.00008 0.00010.1

0.11

0.12

0.13

0.14

0.15

0.16

0.17

0.18

0.19

0.2

Graph d: Transpiration rate v. H+ ion concentra-tion

pH 4pH 5pH 6pH 7TrendlineLogarithmic (Trendline)

[H+] / Molar

Rate

/ m

L Km

in-1

Analysis

The trendline in Graph c is dV/dt = −.006ln[H+] + .0557. The trendline for Graph d is dV/dt = .0136(pH) + .0557 = −.0136log[H+] + .0557 – the two are essentially identical. They reasonably fit within the error bars of maximum and minimum rates which may be derived from the initial data sets. Within the domain established, it is, thus, a statistically significant model of the impact of direct environmental acidity on the quantitative metabolism of plants over a short-term period of time.

Conclusion

Despite several discrepancies regarding the error ranges, it may be said to a reasonable degree of certainty that the rate of transpiration decreases with an increase in acidity, with the specific quantitative relationship of a negative logarithmic correlation with a coefficient of 0.0136 and an initial constant of approximately 0.0557, if the units are taken to be milliliters per kilominute. This appears to be a realistic correlation for Peperomia obtusifolia, reflected by most of the data and corresponding with the common notion of the optimum pH for plant metabolism being, in fact, non-acidic, with damage to said metabolism caused by increasing H+ ion concentration.

Evaluation

The procedure is not as exact as one may hope. Variable control, overall, was performed effectively, but no experimentally valid method was devised to cancel the effects of leaf size or to perform analysis at more frequent or regular intervals; however, even so, a general and self-consistent trend has been derived for the initial, short-term effects of acidity on transpiration. The discrepancies imply impact of other environmental factors or non-constant transpiration rates caused by natural growth or development intended, perhaps, to mitigate the effect of cutting the stems.

Improvements

The most significant improvement in the lab would be collecting data on a more regular basis over longer overall periods of time, as well as controlling the intrinsic effects of the plants on the transpiration rates by setting an absolute upper limit on leaf area differences between stems in separate trials. The data would thus be more consistent as well as more meaningful with regard to accounting for the possibility of changes in rate over time, as seen, perhaps, at 10.5 kilominutes on Graph b.