Why is the relationship between photosynthetic rate and light intensity curvilinear

consisted of a s pulse of high-intensity light ( pmol. m-z -1) from a W tungsten evolution was observed between 20 and 30"C, with the rate approaching Figure 2 shows the relationship between QPsII and ao, in. BA and BL. Linearity . a relationship, however, is curvilinear under low-intensity light, similar to. quantitative relationship between the two-the function and the independent chlorophyll reached their maximum rate of photosynthesis at approximately with the same light intensity, he found that therate of photosynthesis in . assoeiationi was clearly curvilinear, and, speeifically, parabolic in the second. C3 photosynthesis in air under saturating light intensity is primarily .. on the chlorophyll content, and a curvilinear relationship between leaf.

This can be achieved by observing the response of the light sensor display as the dimmer control is adjusted. Measure the increase in pO2 of the chamber for 5 - 10 min.

Give your data an appropriate file name, and save it to disk or in the subdirectory allocated for it by your laboratory instructor. Be careful not to touch any hot surface of the lamp or its fitting while doing this. Remove the leaf from the chamber and give this leaf to the Bgy 32 students.

These students will now determine the weight and leaf area of this leaf. Repeat steps 12 to 19 above. The rate of a process, such as photosynthesis, is expressed as the rate of increase in a product of that process or a decrease in the substrate for the process per unit time. To measure the rate of photosynthesis in your experiment, you will need to measure the increase in pO2 within the cuvette as a function of time.

LIGHT DEPENDENCE OF PHOTOSYNTHESIS IN SUN AND

The procedure for analyzing your data is as follows: A command box will appear asking you whether or not you wish to load the calibration stored with your data file. Your data will appear on the screen exactly as it appeared when you saved it at the end of the experiment.

Investigating the effect of light intensity on the rate of photosynthesis

Select "Analyze Data A" and then release the mouse button. A vertical line will appear on your graphs that can be moved along the data points on the graphs by moving the mouse. Note that as you move the vertical line, the digital display on the bottom of the screen will change to show you the exact O2 concentration, illumination and time value at the point on each graph where the line is situated.

To do this, move the vertical line to the point on your O2 data where you wish to start the measurement, click on the mouse button and hold it down. Move the mouse over the part of the data you wish to analyze, and then release the mouse button. The selected part of the data will be highlighted during this procedure. Select "Fit" from the "Analyze" menu and release the mouse button. A command box will appear on the lower part of the screen providing you with options concerning the type of mathematical fit that you may wish to apply to your data.

If another equation is selected, re-select the linear equation by clicking with the mouse at the open circle next to the equation. A linear regression will be made of the data that you have selected and an equation will appear on the top right-hand comer of the screen. This will provide values for bO the intercept of the regression line on the y axisand b1 the gradient of the line. The command box will disappear and the screen will have your previously selected data highlighted.

Click on a point at the start of the selected data set and hold the mouse button down. The previously highlighted data will disappear. Move the line across part of the data to be analyzed, and then release the mouse button. The equation on the screen will change to reflect the new bO and b1 values for the range of data that you have selected. Select "Analyze" from the menu and then "Fit Results".

Record the new value of b1 in the tab1e in the Results and Discussion section. Calculations Each b1 value from each regression that you performed represents the rate of increase of O2 concentration in the chamber with time. However, photosynthesis is usually expressed in terms of m moles of O2 evolved per unit leaf area per unit time i.

To make this conversion the following procedure is required. Let us assume that the b1 value was X i. To obtain photosynthetic rate we must now multiply by the volume of the chamber expressed in liters. The chamber is designed so that when closed it has a fixed internal volume of 0.

Therefore, in our example, photosynthetic rate would be 0. To express this rate on a leaf area specific basis e. Record your data in the table provided in the next section. When you have calculated rates of photosynthesis at each light intensity used in your experiment, present your data as a graph with photosynthesis plotted on the y axis and light Intensity on the x axis. Please turn this graph in with the data sheets at the end of the laboratory handout.

A photosynthetic light response curve for a generalized leaf is shown below. Note that at low light intensities, photosynthesis increases linearly as light is increased.

This is because at these intensities the rate of photosynthesis is limited by the rate of the light reactions. Insufficient photons are being supplied to the leaf to produce the ATP and reductant required to sustain maximum photosynthetic rates. At higher light intensities there is less of an increase In photosynthetic rate per unit increase in light intensity, and eventually photosynthesis reaches light saturation at the highest light intensities used in the experiment. Under these conditions, the light reactions of photosynthesis are maximized, and photosynthetic rate is limited either by the Supply of CO2 to supply the photosynthetic dark reactions, or by the turnover rate of the photosynthetic enzymes.

The photosynthetic light response curve of a particular plant is influenced by many factors, and a study of the components of the curve can tell us a great deal about the physiology and ecophysiology of the plant.

Important aspects of the light response curve are listed below. Questions may be answered on the laboratory report form at the end of this laboratory handout. Extrapolate the linear portion of the light response curve to intercept the x axis at the point where photosynthetic rate is zero. The light intensity at this point is called the light compensation point, and it represents the light intensity at which O2 production in photosynthesis is balanced by O2 consumption in respiration.

Despite a decreased Rubisco activation state, the light-saturated photosynthetic rate in high-N leaves is generally higher than that in low-N leaves Reich et al.

With a higher amount of Rubisco in C3 plants, chloroplastic CO2 partial pressure may impact the photosynthetic efficiency since Rubisco activity is induced by Cc. Previous studies demonstrated that total Rubisco activity in high-N leaves is higher than that in low-N leaves Evans, ; Cheng and Fuchigami, ; however, the question which still remains open is which limiting factor for photosynthesis impacts the photosynthetic efficiency when plants are supplied with a high concentration of N.

In the present study, it is hypothesized that, under a higher supply of N, the increased photosynthetic rate is associated with a higher Cc, which, consequently, increases total Rubisco activity. To verify this hypothesis, gas-exchange parameters and chlorophyll fluorescence of rice seedlings were analysed under conditions where plants were supplied with different concentration of N, and the relationship between Cc, mesophyll conductance gmand the distance between the chloroplastic envelope and the cell wall is described further.

Materials and methods Plant material and growth conditions After germination on moist filter paper, rice seeds Oryza sativa L. Three days afterwards, rice seedlings were transplanted to 6. The composition of the other nutrients in the solutions were as follows: Ca in low N and intermediate N treatments was compensated for by addition of CaCl2. A nitrification inhibitor dicyandiamide was added to each nutrient solution to prevent oxidation of ammonium.

Nutrient solutions were changed every 2 d, and the pH was adjusted to 5. All the treatments had five replicates with a completely random design. The placement of different treatments was randomized to avoid edge effects in the greenhouse.

Gas-exchange and fluorescence measurements Four weeks after treatments started, the rate of light-saturated photosynthesis of newly expanded leaves was measured from 9: Leaf temperature during measurements was maintained at The measured leaves were labelled, and leaf areas were calculated based on the labelled area. Side shoots of the plants were removed at weekly intervals. At the stage of fruit set, the plants were tapped every 3 d to aid pollination.

Plants were irrigated on four occasions each day with a standard nutrient feed Sangral SS ; Sinclair Horticulture Ltd. Mean cumulative daily light intensity and mean daily temperature measurements. The mean daily temperature in each compartment was recorded at intervals of 15 min using a Combine data logger Delta-T Devices Ltd. In all regression analysis, data of mean daily temperature for each experiment were used. Mean daily temperature values used in the analysis were the actual mean daily temperatures rather than the set temperatures.

The photosynthesis 'light response curve'

Mean cumulative daily light intensity data from the KIPP solarimeter recorded by means of a data logger were used as PAR for different parameters used in the analysis as mean cumulative daily light intensity averaged over each planting time Table 1. Because the three planting times were repeated in the second year, a total of 36 mean daily temperatures and 36 different mean cumulative daily light intensities were obtained.

The six different growth compartments had different mean daily temperatures and different mean cumulative daily light intensities because of changing growth periods. Although mean cumulative daily light intensity values were different as a result of differing plant growth periods, they were similar to each other Table 1.

Therefore, mean cumulative daily light intensity values calculated by taking the average of mean cumulative daily light intensities from different compartments for each planting time six different mean cumulative daily light intensities for six different planting times were used in multiple regression analysis Table 1.

Therefore, 34 mean daily temperatures and 34 matching mean cumulative daily light intensity values were used in the analysis Table 1. Equation driving, experimental design, and data analysis. The experimental design was a randomized complete block with three replications and three plants in each replication Table 1.

Data obtained from all the planting dates were gathered to carry out multiregression analysis. Mean daily temperature and mean cumulative daily light intensity were related to the following plant development variables: Data were collected until all of the third cluster on the plants matured and were harvested. Ending time of the experiment was regarded as the time at which all the fruits of the third cluster on the plants matured and were harvested Table 1.

Multiple regression analysis forward selection method was performed with Excel Microsoft Corp. Curve fitting processes were continued until the least sum of squares of residuals was obtained.

All the equations were derived by plotting the data as mean values 34 mean daily temperature values for each parameter derived from a total of nine plants three replicate and three plants for each replicate against the data sets of mean daily temperature and mean cumulative daily light intensity combined for all growing periods Table 1.

To determine the most suitable equation, multiple regression analysis for all the variables used in the study was continued until the highest regression coefficient r2 with the least sum of squares for residuals were obtained. The three-dimensional graphs were drawn using Slide-Write Package Program 2. Results and Discussion Time to first flowering. As seen from Eq. This relationship incorporates both linear and curvilinear responses as well as complex interactions between mean daily temperature and mean cumulative daily light intensity.

Figure 1 shows that FT was a negative linear and curvilinear function of mean daily temperature at both high and low mean cumulative daily light intensities, respectively. Mean cumulative daily light intensity also had a sharp and slight negative curvilinear effect on FT at low and high mean daily temperatures, respectively Fig. In general, FT declined with increasing mean cumulative daily light intensity and mean daily temperature. FT was most responsive to mean cumulative daily light intensity Fig.

Therefore, FT declined much more sharply with mean cumulative daily light intensity compared with mean daily temperature Fig. There was only a slight effect of mean daily temperature. In a new window Fig. Changes in time to first flowering with mean daily temperature and mean cumulative daily light intensity in tomato.

The rate of crop development governs plant growth period, which is of considerable importance in determining crop yields Ellis et al. Moreover, studies on a number of crops have shown that low mean cumulative daily light intensity also considerably delays time to flowering Atherton and Harris, ; Cockshull et al.