In Vitro Synthesis of Chlorophyll A in the Dark Triggers Accumulation of Chlorophyll A Apoproteins in Barley Etioplasts”

An in vitro translation system using lysed etioplasts was developed to test if the accumulation of plastid-encoded chlorophyll a apoproteins is dependent on the de novo synthesis of chlorophyll a. The P700 apoproteins, CP47 and CP43, were not radiolabeled in pulsechase translation assays employing lysed etioplasts in the absence of added chlorophyll precursors. When chlorophyllide a plus phytylpyrophosphate were added to lysed etioplast translation assays in the dark, chlorophyll a was synthesized and radiolabeled P700 apoproteins, CP47 and CP43, and a protein which comigrates with D1 accumulated. Chlorophyllide a or phytylpyrophosphate added separately to the translation assay in darkness did not induce chlorophyll a formation or chlorophyll a apoprotein accumulation. Chlorophyll a formation and chlorophyll a apoprotein accumulation were also induced in the lysed etioplast translation system by the photoreduction of protochlorophyllide to chlorophyllide a in the presence of exogenous phytylpyrophosphate. Accumulation of radiolabeled CP47 was detectable when very low levels of chlorophyll a were synthesized de novo (less than 0.01 nmol/10(7) plastids), and radiolabel increased linearly with increasing de novo chlorophyll a formation. Higher levels of de novo synthesized chlorophyll a were required prior to detection of radiolabel incorporation into the P700 apoproteins and CP43 (greater than 0.01 nmol/10(7) plastids). Radiolabel incorporation into the P700 apoproteins, CP47 and CP43, saturated at a chlorophyll a concentration which corresponds to 50% of the etioplast protochlorophyllide content (0.06 nmol of chlorophyll a/10(7) plastids)

On the link between ocean biota emissions, aerosol, and maritime clouds: Airborne, ground, and satellite measurements off the coast of California

Surface, airborne, and satellite measurements over the eastern Pacific Ocean off the coast of California during the period between 2005 and 2007 are used to explore the relationship between ocean chlorophyll a, aerosol, and marine clouds. Periods of enhanced chlorophyll a and wind speed are coincident with increases in particulate diethylamine and methanesulfonate concentrations. The measurements indicate that amines are a source of secondary organic aerosol in the marine atmosphere. Subsaturated aerosol hygroscopic growth measurements indicate that the organic component during periods of high chlorophyll a and wind speed exhibit considerable water uptake ability. Increased average cloud condensation nucleus (CCN) activity during periods of increased chlorophyll a levels likely results from both size distribution and aerosol composition changes. The available data over the period of measurements indicate that the cloud microphysical response, as represented by either cloud droplet number concentration or cloud droplet effective radius, is likely influenced by a combination of atmospheric dynamics and aerosol perturbations during periods of high chlorophyll a concentrations

From chlorophyll a towards bacteriochlorophyll a: Excited-state processes of modified pigments

By means of fluorescence spectroscopy and nonlinear absorption experiments, excited-state processes of the modified pigments [3-acetyl]-chlorophyll a, [31-OH]-bacteriochlorophyll a and [3-vinyl]-bacteriochlorophyll a were investigated and compared with those of chlorophyll a and bacteriochlorophyll a

Investigating Changes in Chlorophyll a and Other Water Chemistry Variables in Response to Global Environmental Change

Changes in water quality are influenced by climate change and other anthropogenic stressors. We 1) assessed changes in water quality in lakes in the Laurentian Great Lakes region, and 2) compiled water quality data for lakes across the world to assess global patterns in chlorophyll a. We found that at the regional scale water quality (specifically chlorophyll a, total phosphorus, total nitrogen, and dissolved organic carbon) were influenced by temperature, precipitation, morphology, and the presence of dreissenids. We also compiled chlorophyll a and water chemistry data together with morphometric characteristics for 8557 lakes worldwide. This global dataset will allow researchers to associate global water quality patterns to different pressures such as changes climate or land use

Excitated state properties of 20-chloro-chlorophyll a

The excited-state and lasing properties of 20-chloro-chlorophyll a in ether solution were compared to those of chlorophyll a. Desactivation parameters and cross-sections were obtained from non-linear absorption spectroscopy in combination with a physico-mathematical methods package. The Cl substituent at C-20 (1) increases both intersystem crossing and internal conversion, (2) produces a blue-shift of the S1 absorption spectrum, and (3) leads to pronounced photochemistry

Relationship Between Physiological Characteristic and Bean Quality on Some Cocoa Clones (Theobroma Cacao L.)

Photosynthesis is one of the physiological process that influence the bean weight and this process related with the efectiveness of the stomata character and chlorophyll content in the leaves. The research was conducted at Kaliwining Research Station, Indonesian Coffee and Cocoa Research Institute. Design of experiment was randomized complete block design (RCBD) consisted of six clones as treatment were Sulawesi 1, Sulawesi 2, Sca 6, ICS 60, TSH 858, ICCRI 03, PA 300. Each treatment was replicated three times. Stomata resistance diffusion, tranpiration,the content of chlorophyll a, chlorophyll b, chlorophyll total (a+b), bean number and bean weight were observed. The resuts of experiment showed that difference in chlorophyll a, chlorophyll b, chlorophyll total (a+b), stomata resistance diffusion, bean number and bean weight existed within six clones tested. Transpiration rate did not show the significantly different between six clones tested. Sulawesi 1 showed the highest content of chlorophyll a and ICS 60 and ICCRI 03 showed higher content of chlorophyll b than the other clones. Chlorophyll a, b and total (a+b) showed positively influence on bean number and bean weight. Transpiration rate had negatively influence to bean number per pod, on the otherhand it showed positively influence to bean weight. Chlorophyll total (a+b) showed high genetic variance (σg2), high phenotypic variance (σf2) and high estimated value of heritability (H). The chlorophyll a,b had moderate genetic variance, moderate phenotypic variance and high of estimated value of heritability. Chlorophyll total (a+b) could be used a selection criteria based on the value of correlation, genetic variance, phenotypic variance and estimated value of heritability would give high opportunity in selection process

REACTIVITY OF CHLOROPHYLL a/b-PROTEINS AND MICELLAR TRITON X-100 COMPLEXES OF CHLOROPHYLLS a OR b WITH BOROHYDRIDE

The reaction of several plant chlorophyll-protein complexes with NaBH4 has been studied by absorption spectroscopy. In all the complexes studied, chlorophyll b is more reactive than Chi a, due to preferential reaction of its formyl substituent at C-7. The complexes also show large variations in reactivity towards NaBH4 and the order of reactivity is: LHCI > PSII complex > LHCII > PSI > P700 (investigated as a component of PSI). Differential pools of the same type of chlorophyll have been observed in several complexes. Parallel work was undertaken on the reactivity of micellar complexes of chlorophyll a and of chlorophyll b with NaBH4 to study the effect of aggregation state on this reactivity. In these complexes, both chlorophyll a and b show large variations in reactivity in the order monomer > oligomer > polymer with chlorophyll b generally being more reactive than chlorophyll a. It is concluded that aggregation decreases the reactivity of chlorophylls towards NaBH4 in vitro, and may similarly decrease reactivity in naturally-occurring chlorophyll-protein complexes

Ocean color algorithm for remote sensing of chlorophyll

An algorithm for the remote detection of chlorophyll a in the ocean was tested during a Nantucket Shoals experiment conducted by NASA. A set of Multichannel Ocean Color Sensor (MOCS) data selected from one flight for each of the two altitudes flown was used to calibrate the algorithm for chlorophyll a concentration. The equations were then applied to all unsaturated MOCS data collected during the 8-day experiment to generate contour maps of chlorophyll a concentration over the shoals. One additional flight was conducted away from the shoals both on and off the Continental Shelf. Although no solar elevation or environmental corrections were made to the original conversions, the equations in these tests determined chlorophyll a concentrations to an accuracy better than 1.0 micron g/L despite the fact that the solar elevation varied between 20 deg and 56 deg during the data collection periods of the experiments

Average seasonal changes in chlorophyll a in Icelandic waters

The standard algorithms used to derive sea surface chlorophyll a concentration from remotely sensed ocean colour data are based almost entirely on the measurements of surface water samples collected in open sea (case 1) waters which cover ~60% of the worlds oceans, where strong correlations between reflectance and chlorophyll concentration have been found. However, satellite chlorophyll data for waters outside the defined case 1 areas, but derived using standard calibrations, are frequently used without reference to local in situ measurements and despite well-known factors likely to lead to inaccuracy. In Icelandic waters, multiannual averages of 8-d composites of SeaWiFS chlorophyll concentration accounted for just 20% of the variance in a multiannual dataset of in situ chlorophyll a measurements. Nevertheless, applying penalized regression spline methodology to model the spatial and temporal patterns of in situ measurements, using satellite chlorophyll as one of the predictor variables, improved the correlation considerably. Day number, representing seasonal variation, accounted for substantial deviation between SeaWiFS and in situ estimates of surface chlorophyll. The final model, using bottom depth and bearing to the sampling location as well as the two variables mentioned above, explained 49% of the variance in the fitting dataset