It is possible to reduce these

differences by determining

It is possible to reduce these

differences by determining the light intensity dependence of the find more parameters of interest and using these data to change settings in order to obtain comparable results. Differences in wavelengths of the exciting light may be impossible to correct for. Green light for example has been shown to probe deeper in the leaves than red light; blue light is even more efficiently absorbed than red light (Terashima et al. 2009). An example of the phenomenon, described above, is a study in which the same leaves were measured with different HandyPEA instruments (Bussotti et al. 2011a) calibrated with identical settings (lamp intensity = 3,000 μmol photons m−2 s−1, time = 1 s, gain = 1). Both original and normalized transient curves were compared. Original curves differed consistently (both the extreme values of F O and F M showed a large range of variability), but the differences decreased consistently after 5-Fluoracil normalization (double normalization between F O and F M—see Question 26 for a definition). The parameter F O/F M (parameter which is sensitive to changes in heat dissipation in the PSII antenna), as well as the normalized steps of OJIP transients—J and I (fluorescence intensities at 2–3 and 30 ms, respectively)—showed very little variability when comparing the measurements of the different instruments

with a coefficient of variation (CV = SD/Mean) ranging {Selleck Anti-diabetic Compound Library|Selleck Antidiabetic Compound Library|Selleck Anti-diabetic Compound Library|Selleck Antidiabetic Compound Library|Selleckchem Anti-diabetic Compound Library|Selleckchem Antidiabetic Compound Library|Selleckchem Anti-diabetic Compound Library|Selleckchem Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|Anti-diabetic Compound Library|Antidiabetic Compound Library|buy Anti-diabetic Compound Library|Anti-diabetic Compound Library ic50|Anti-diabetic Compound Library price|Anti-diabetic Compound Library cost|Anti-diabetic Compound Library solubility dmso|Anti-diabetic Compound Library purchase|Anti-diabetic Compound Library manufacturer|Anti-diabetic Compound Library research buy|Anti-diabetic Compound Library order|Anti-diabetic Compound Library mouse|Anti-diabetic Compound Library chemical structure|Anti-diabetic Compound Library mw|Anti-diabetic Compound Library molecular weight|Anti-diabetic Compound Library datasheet|Anti-diabetic Compound Library supplier|Anti-diabetic Compound Library in vitro|Anti-diabetic Compound Library cell line|Anti-diabetic Compound Library concentration|Anti-diabetic Compound Library nmr|Anti-diabetic Compound Library in vivo|Anti-diabetic Compound Library clinical trial|Anti-diabetic Compound Library cell assay|Anti-diabetic Compound Library screening|Anti-diabetic Compound Library high throughput|buy Antidiabetic Compound Library|Antidiabetic Compound Library ic50|Antidiabetic Compound Library price|Antidiabetic Compound Library cost|Antidiabetic Compound Library solubility dmso|Antidiabetic Compound Library purchase|Antidiabetic Compound Library manufacturer|Antidiabetic Compound Library research buy|Antidiabetic Compound Library order|Antidiabetic Compound Library chemical structure|Antidiabetic Compound Library datasheet|Antidiabetic Compound Library supplier|Antidiabetic Compound Library in vitro|Antidiabetic Compound Library cell line|Antidiabetic Compound Library concentration|Antidiabetic Compound Library clinical trial|Antidiabetic Compound Library cell assay|Antidiabetic Compound Library screening|Antidiabetic Compound Library high throughput|Anti-diabetic Compound high throughput screening| from 3 to 5 %. The parameter PIabs, which consists of the product of a parameter sensitive to the effective antenna size, a parameter based on the maximum quantum yield

of PSII, and a parameter sensitive to changes in the relative position of F J (see Question 19) showed a very high variability among instruments (PIabs showed a CV = 30 %; Bussotti et al. 2011a). The high intrinsic variability of PIabs between instruments is due to the fact that this parameter is sensitive to the initial slope of the Sinomenine fluorescence rise and the relative position of the J-step, two factors that are both relatively sensitive to the light intensity of the beam. This high intrinsic variability makes the PIabs less useful for large, multi-instrument surveys. In conclusion, in the case of small-scale experiments, it is always preferable to use the same instrument for all the measurements of an experiment. Question 28. How should a sampling campaign be organized for an ecosystem? Large-scale surveys should be carried out using a robust sampling design. Criteria and examples of such designs can be found in many statistical manuals and textbooks (see Elzinga et al. 2001). Here, we discuss some specific issues related to the assessment of fluorescence parameters. Two problems widely discussed in the context of forest health monitoring (Luyssaert et al. 2002) and other ecosystems (Tuba et al. 2010) are intercalibration and harmonization.

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