**Appendix A**

*CT Scans and Fibre Orientations Tensors*

Orientation tensor X Orientation tensor Y Orientation tensor Z

**Figure A1.** CT2–RS = 288 mm/s, LT = 140 μm, LP = 36 W.

Orientation tensor X Orientation tensor Y Orientation tensor Z

**Figure A2.** CT3–RS = 288 mm/s, LT = 100 μm, LP = 36 W.

Orientation tensor X Orientation tensor Y Orientation tensor Z

**Figure A3.** CT4–RS = 288 mm/s, LT = 120 μm, LP = 16 W.

Orientation tensor X Orientation tensor Y Orientation tensor Z

**Figure A4.** CT5–RS = 168 mm/s, LT = 120 μm, LP = 36 W.


**5. A simple flow injection spectrophotometric determination method for iron (III) based on O-acetylsalicylhydroxamic acid complexation (Reproduced with permission from the paper of Andac Muberra et al., 2009. Copyright of Institute of Chemistry, Slovak Academy of Sciences)**

1,10-phenanthroline and salicylic acid are the most reported chelating agents applied for the determination of iron(III) and total iron after oxidation to iron(III) (Tesfaldet et al., 2004; Udnan et al., 2004). A number of other chelating agents that have been reported for the spectrophotometric and/or flow-injection spectrophotometric determination of iron(III) and total iron include 2-thiobarbituric acid (Morelli, 1983), norfloxacin (Pojanagaron et al., 2002) tiron (van Staden & Kluever, 2002) DMF (Asan et al., 2003), tetracycline (Sultan et al., 1992) and chlortetracycline (Wirat, 2008). Flow-injection spectrophotometric methods based on the above chelating agents are either not selective, or a masking agent has to be used. However, highly selective, simple and economical methods for routine determination of iron(III) in different sample matrices are still required. In the present study, a simple and rapid flowinjection spectrophotometric method for the determination of iron (III) and total iron is proposed. The method is based on the reaction between iron (III) and *O*acetylsalicylhydroxamic acid (AcSHA) in a 2 % methanol solution resulting in an intense violet complex with strong absorption at 475 nm. The reagent itself is sparingly soluble in water and did not absorb in the visible region of the spectrum, therefore, it might be well suited for flow-injection analysis of iron(III) and total iron. An addition of copper sulphate (1*×*10*−*4 mol L*−*1) into the reagent carrier solution resulted in baseline absorbance, and possible interfering ions were eliminated without a significant decrease in the sensitivity of the method. The method was successfully applied in the determination of iron (III) and total iron in water and ore samples. The method was verified by analysing a certified reference material Zn/Al/Cu 43XZ3F and also by the AAS method.

#### **5.1 Experimental**

438 Macro to Nano Spectroscopy

also given for comparison. The results obtained with the standard addition and the calibration curve methods, and the AAS measurements were in good agreement with each

 Found3 Found4 Found3 Found4 AAS *Ec* (%) Seaport (Sea water) 52.16 (0.12) 52.92 (0.21) 67.25 (0.10) 67.52 (0.12) 66.98 (0.05) 0.60 Atakum(River water) 25.41 (0.10) 26.01 (0.19) 37.41 (0.14) 38.01 (0.17) 38.15 (0.07) 1.16 Kurtun river 32.84 (0.24) 33.57 (0.28) 48.14 (0.19) 48.57 (0.27) 49.12 (0.09) 1.55 Spring water (1) 10.95 (0.15) 11.25 (0.27) 16.75 (0.32) 16.20 (0.28) 16.62 (0.18) 0.88 Spring water (2) 12.65 (0.09) 13.18 (0.12) 21.83 (0.08) 21.32 (0.24) 21.75 (0.14) 0.81 Spring water (3) 38.17 (0.11) 38.12 (0.19) 52.54(0.04) 52.73 (0.16) 52.95 (0.12) 0.60

2. Values in parantheses are the relative standard deviations for *n* =5 with confidence level of 95 %.

Accuracy of the proposed method was also tested by analyzing a certified metal alloy solution (MBH Zn/Al/Cu 43XZ3F). Three replicates of the solution using the sampling volume of 20 μL were analyzed. The certified and the obtained values were 0.085 % and (0.084 *±* 0.006) % of iron, respectively. An excellent agreement between the found and the certified values was obtained for the certified metal alloy solution. The obtained results show that the proposed method can be applied to the determination of iron(III) and total

**5. A simple flow injection spectrophotometric determination method for iron (III) based on O-acetylsalicylhydroxamic acid complexation (Reproduced with**

1,10-phenanthroline and salicylic acid are the most reported chelating agents applied for the determination of iron(III) and total iron after oxidation to iron(III) (Tesfaldet et al., 2004; Udnan et al., 2004). A number of other chelating agents that have been reported for the spectrophotometric and/or flow-injection spectrophotometric determination of iron(III) and total iron include 2-thiobarbituric acid (Morelli, 1983), norfloxacin (Pojanagaron et al., 2002) tiron (van Staden & Kluever, 2002) DMF (Asan et al., 2003), tetracycline (Sultan et al., 1992) and chlortetracycline (Wirat, 2008). Flow-injection spectrophotometric methods based on the above chelating agents are either not selective, or a masking agent has to be used. However, highly selective, simple and economical methods for routine determination of iron(III) in different sample matrices are still required. In the present study, a simple and rapid flowinjection spectrophotometric method for the determination of iron (III) and total iron is proposed. The method is based on the reaction between iron (III) and *O*acetylsalicylhydroxamic acid (AcSHA) in a 2 % methanol solution resulting in an intense violet complex with strong absorption at 475 nm. The reagent itself is sparingly soluble in

**permission from the paper of Andac Muberra et al., 2009. Copyright of**

Sample Fe(III)2 (μg L-1) Total iron 2 (μg L-1)

1. Samples were collected at Samsun, Turkey.

Table 7. Determination of total iron in water samples1

iron content in water samples without a pre-concentration process.

**Institute of Chemistry, Slovak Academy of Sciences)**

3. Calibration curve method. 4. Standard addition method.

other.

All chemicals used were of analytical reagent grade, and solutions were prepared from double deionised water. Standard iron(II) and iron(III) stock solutions were prepared by dissolving 278.02 mg of iron(II) and 489.96 mg of iron(III) sulphate (Merck; Darmstadt, Germany) in 100 mL of 0.01 mol L*−*1 hydrochloric acid to give 0.01 mol L*−*1 stock solution of iron(II) and iron(III). Iron(II) and iron(III) working standard solutions were prepared daily by suitable dilution of the stock solutions with double deionised water. Standard reference material consisting of 0.085 % Fe (Zn/Al/Cu 43XZ3F) was provided from MBH Analytical Ltd. (UK). Hydrogen peroxide solution of 30 vol. % was obtained from Merck. AcSHA was synthesised according to the procedure described previously (Asan et al., 2003). A stock solution of AcSHA (0.01 mol L*−*1) was prepared by dissolving 0.095 g of AcSHA in 100 mL of aqueous methanol (2 vol. %). For the spectrophotometric study, AcSHA complex solutions of various metals were prepared by mixing 1 mL of 1×10−4 mol L−1standard solution of each metal in double deionised water with the suitable volume of 1×10−4 mol L−1 AcSHA stock solution. Reagent carrier solution was composed of AcSHA in a 2 % methanol solution and 1×10−4 mol L−1 CuSO4 in 0.001 mol L−1 HCl 98 % (pH 2.85). UV-VIS spectra of metal-AcSHA complexes were taken with a Unicam spectrophotometer (GBC Cintra 20, Australia). A Jenway 3040 Model digital pH-meter was used for the pH measurements. In the FIA system, a peristaltic pump (ISMATEC; IPC, Switzerland) 0.50 mm i.d. PTFE tubing was used to propel the samples and reagent solutions. Samples were injected into the carrier stream by a 7125 model stainless steel high pressure Rheodyne injection valve provided with a 20 μL loop. Absorbance of the coloured complex formed was measured with a UV-VIS spectrophotometer equipped with a flowthrough micro cell (Spectra SYSTEM UV 3000 HR,Thermo Separation Products, USA), and connected to a computer incorporated with a PC1000 software programme. A UNICAM 929 model (Shimadzu AA-68006) flame atomic absorption spectrophotometer with a deuterium-lamp background correction was used for the determination of iron in reference to the FIA method. The measuring conditions were as follows: UNICAM hollow cathode lamp, 10 cm 1-slot burner, air-acetylene flame (fuel gas flow-rate 1.50 L min−1), 0.2 nm spectral bandwidth, and 7 mm burner height. The wavelength and the lamp current of iron were 248 nm and 5 mA, respectively.

The FIA system used, similar to that proposed in our previous works (Asan et al., 2003), is quite simple. The sample solution was introduced into the reagent carrier solution by the Rhodyne injection valve. A water-soluble complex (*λ*max = 475 nm) was then formed on the passage of the reagent carrier solution in the mixing coil. As a mixing coil, PTFE tubing (50 cm long) was attached before the flow-through detection cell. The absorbance of the coloured complex was selectively monitored in the cell at 475 nm. The transient signal was recorded as a peak, the height of which was proportional to the iron(III) concentration in the sample, and it was used in all measurements. Five replicate injections per sample were made.

Flow-Injection Spectrophotometric Analysis of Iron (II), Iron (III) and Total Iron 441

As can be seen from Fig. 8, only AcSHA reacted efficiently with iron to form iron-(AcSHA)*n*  complexes with the absorbance maxima at 475 nm. At this wavelength, AcSHA itself has no absorption while Ac- SHA complexes of copper(II), nickel(II), cobalt(II), and zinc(II), among all metal ions with the anions tested, show a negligible absorption. The FIA setup shown in Fig. 9. was used in order to develop an FIA method based on the above phenomenon.

Fig. 9. Flow diagram of the flow-injection analysis system used for the determination of iron (III) and total iron, R; reagent carrier solution (1x10-4 M AcSHA, 1x10-4 M CuSO4, pH: 2.85), P, Peristaltic pump, S; Rheodyne sample injection valve, MC; mixing coil (50 cm long, 0.5 mm i.d), D; spectrophotometric detector (*max* = 475 nm), W; waste, C; computer, P; printer.

Various variables closely related to iron determination were examined using a simple flowinjection analysis system with a fixed iron(III) concentration of 5 μg L*−*1. The AcSHA concentration was varied from 1*×*10*−*5 mol L*−*1 to 1*×*10*−*2 mol L*−*1. The peak height was found to increase with the AcSHA concentration increasing up to 1*×*10*−*4 mol L*−*1, no noticeable increase was found at higher concentrations. Therefore, 1*×*10*−*4 mol L*−*1 AcSHA was used as the colour developing component of the carrier solution. With the concentration of AcSHA fixed at 1*×*10*−*4 mol L*−*1, pH of the carrier solution was varied from 1.5 to 5.5. The interference effect of iron(II) was found to increase with pH increasing up to 3.5 and to remain constant at higher pH. Also, the peak heights were found to increase with pH increasing up to 3.0, to remain constant up to 4.0, and to decrease slightly above this value. pH of the reagent carrier was, however, adjusted to 2.85 to obtain the maximum peak height and minimum iron(II) interference in the analysis. To obtain a reasonable background of absorption and a smooth baseline, CuSO4 was added into the carrier solution. The CuSO4 concentration was varied from 1*×*10*−*5 mol L*−*1 to 1*×*10*−*2 mol L*−*1. When the concentration of CuSO4 was 1*×*10*−*4 mol L*−*1, the baseline was stable and the interference effects of nickel(II), cobalt(II), and zinc(II) were found minimum. Over the CuSO4 concentration of 1*×*10*−*4 mol

In order to proceed with the final system design, the effects of sample volume, mixing coil length and flow-rate were studied at the optimal pH (2.85), and fixed concentrations of AcSHA (1*×*10*−*4 mol L*−*1) and CuSO4 (1*×*10*−*4 mol L*−*1). The sample volume was varied from 5–50 μL. The peak height was decreased by decreasing the sample size, and the peaks were broadened with the increasing sample size due to the sample zone dispersion. The sample injection volume of 20 μL was selected as a compromise between the sensitivity and sample throughput rate. The mixing coil (MC) was examined using PTFE tubing (0.5 mm i.d.) of

**5.2.2 Optimisation of chemical variables and FIA manifold**

L*−*1, the sensitivity of the method decreased.

Sea and river water samples collected in Nalgene plastics were acidified by adding 1 mL of nitric acid (0.1 mol L*−*1) per 100 mL of sample solution after filtration over a 0.45 μm Millipore Filter (Millford, MA). After the filtration, water samples were injected directly into the FIA system for the determination of iron(III).

Total iron was determined by oxidising iron(II) to iron(III). Hydrogen peroxide was chosen as the oxidising agent for the determination of total iron. A 0.25 mol L*−*1 H2O2 concentration ensured total oxidation of iron(II) into iron(III) (Pons, et al., 2005). Before the determination of total iron, H2O2 (10 mass %) was added to the water sample solution for complete oxidation of iron(II) to iron(III). Then, 20 μL of this solution were injected into the system, as in the procedure described above. A 0.10 g sample of the certified metal alloy (Zn/Al/Cu 43XZ3F) was dissolved in 12 mL of concentrated HCl and HNO3 (3 : 1) in a 100 mL beaker. The mixture was heated on a hot plate nearly to dryness; 5 mL of HNO3 were added to complete the dissolution and the solution was diluted to 100 mL with deionised water. The solution was filtered and transferred quantitatively to a 1000 mL volumetric flask and filled up to volume with deionised water. 9 mL of this solution were treated with 1 mL of H2O2 (10 mass %) for iron(II) oxidation. After the oxidation step, 20 μL of this solution were used in the determination of total iron. Metal ore samples (0.10 g) were powdered (*≥* 500 mesh) and prepared as in the procedure described above. All analyses were performed with the least possible delay.

#### **5.2 Results and discussion**

#### **5.2.1 Spectrophotometric studies of AcSHA-metal complexes**

Metal ions react with AcSHA in aqueous media in the range of pH 2.0–10.0 forming coloured complexes with different stoichiometry. These complexes are fairly soluble in aqueous media (O'Brien et al., 1997). Their absorption spectra corresponding to solutions of 5 *×* 10*−*5 mol L*−*1 metal complexes measured against a reagent blank are shown in Fig. 8.

Fig. 8. Absorption spectras of 5x10-5 M AcSHA and M-(AcSHA)*n* complexes. a) Fe(III)- (AcSHA)n; b) Fe(II)-(AcSHA)n; c) Cu-(AcSHA)n; d) M-(AcSHA)n; (M: Ni, Co, Zn, Pb); e) AcSHA only.

Sea and river water samples collected in Nalgene plastics were acidified by adding 1 mL of nitric acid (0.1 mol L*−*1) per 100 mL of sample solution after filtration over a 0.45 μm Millipore Filter (Millford, MA). After the filtration, water samples were injected directly into

Total iron was determined by oxidising iron(II) to iron(III). Hydrogen peroxide was chosen as the oxidising agent for the determination of total iron. A 0.25 mol L*−*1 H2O2 concentration ensured total oxidation of iron(II) into iron(III) (Pons, et al., 2005). Before the determination of total iron, H2O2 (10 mass %) was added to the water sample solution for complete oxidation of iron(II) to iron(III). Then, 20 μL of this solution were injected into the system, as in the procedure described above. A 0.10 g sample of the certified metal alloy (Zn/Al/Cu 43XZ3F) was dissolved in 12 mL of concentrated HCl and HNO3 (3 : 1) in a 100 mL beaker. The mixture was heated on a hot plate nearly to dryness; 5 mL of HNO3 were added to complete the dissolution and the solution was diluted to 100 mL with deionised water. The solution was filtered and transferred quantitatively to a 1000 mL volumetric flask and filled up to volume with deionised water. 9 mL of this solution were treated with 1 mL of H2O2 (10 mass %) for iron(II) oxidation. After the oxidation step, 20 μL of this solution were used in the determination of total iron. Metal ore samples (0.10 g) were powdered (*≥* 500 mesh) and prepared as in the procedure described above. All analyses were performed with the least

Metal ions react with AcSHA in aqueous media in the range of pH 2.0–10.0 forming coloured complexes with different stoichiometry. These complexes are fairly soluble in aqueous media (O'Brien et al., 1997). Their absorption spectra corresponding to solutions of 5 *×* 10*−*5 mol L*−*1 metal complexes measured against a reagent blank are shown in Fig. 8.

Fig. 8. Absorption spectras of 5x10-5 M AcSHA and M-(AcSHA)*n* complexes. a) Fe(III)- (AcSHA)n; b) Fe(II)-(AcSHA)n; c) Cu-(AcSHA)n; d) M-(AcSHA)n; (M: Ni, Co, Zn, Pb); e)

the FIA system for the determination of iron(III).

possible delay.

AcSHA only.

**5.2 Results and discussion**

**5.2.1 Spectrophotometric studies of AcSHA-metal complexes**

As can be seen from Fig. 8, only AcSHA reacted efficiently with iron to form iron-(AcSHA)*n*  complexes with the absorbance maxima at 475 nm. At this wavelength, AcSHA itself has no absorption while Ac- SHA complexes of copper(II), nickel(II), cobalt(II), and zinc(II), among all metal ions with the anions tested, show a negligible absorption. The FIA setup shown in Fig. 9. was used in order to develop an FIA method based on the above phenomenon.

Fig. 9. Flow diagram of the flow-injection analysis system used for the determination of iron (III) and total iron, R; reagent carrier solution (1x10-4 M AcSHA, 1x10-4 M CuSO4, pH: 2.85), P, Peristaltic pump, S; Rheodyne sample injection valve, MC; mixing coil (50 cm long, 0.5 mm i.d), D; spectrophotometric detector (*max* = 475 nm), W; waste, C; computer, P; printer.

#### **5.2.2 Optimisation of chemical variables and FIA manifold**

Various variables closely related to iron determination were examined using a simple flowinjection analysis system with a fixed iron(III) concentration of 5 μg L*−*1. The AcSHA concentration was varied from 1*×*10*−*5 mol L*−*1 to 1*×*10*−*2 mol L*−*1. The peak height was found to increase with the AcSHA concentration increasing up to 1*×*10*−*4 mol L*−*1, no noticeable increase was found at higher concentrations. Therefore, 1*×*10*−*4 mol L*−*1 AcSHA was used as the colour developing component of the carrier solution. With the concentration of AcSHA fixed at 1*×*10*−*4 mol L*−*1, pH of the carrier solution was varied from 1.5 to 5.5. The interference effect of iron(II) was found to increase with pH increasing up to 3.5 and to remain constant at higher pH. Also, the peak heights were found to increase with pH increasing up to 3.0, to remain constant up to 4.0, and to decrease slightly above this value. pH of the reagent carrier was, however, adjusted to 2.85 to obtain the maximum peak height and minimum iron(II) interference in the analysis. To obtain a reasonable background of absorption and a smooth baseline, CuSO4 was added into the carrier solution. The CuSO4 concentration was varied from 1*×*10*−*5 mol L*−*1 to 1*×*10*−*2 mol L*−*1. When the concentration of CuSO4 was 1*×*10*−*4 mol L*−*1, the baseline was stable and the interference effects of nickel(II), cobalt(II), and zinc(II) were found minimum. Over the CuSO4 concentration of 1*×*10*−*4 mol L*−*1, the sensitivity of the method decreased.

In order to proceed with the final system design, the effects of sample volume, mixing coil length and flow-rate were studied at the optimal pH (2.85), and fixed concentrations of AcSHA (1*×*10*−*4 mol L*−*1) and CuSO4 (1*×*10*−*4 mol L*−*1). The sample volume was varied from 5–50 μL. The peak height was decreased by decreasing the sample size, and the peaks were broadened with the increasing sample size due to the sample zone dispersion. The sample injection volume of 20 μL was selected as a compromise between the sensitivity and sample throughput rate. The mixing coil (MC) was examined using PTFE tubing (0.5 mm i.d.) of

Flow-Injection Spectrophotometric Analysis of Iron (II), Iron (III) and Total Iron 443

measurements taken in water samples are also given for comparison (Table 10). The analytical value of total iron in water is in good agreement with that obtained by the AAS

(1) Values in parenthesis are the relative standard deviations for n=5 with confidence level of 95 %.

 Found(3) Found(4) Found(3) Found(4) AAS Kurtun river 38.33(0.24) 38.55(0.12) 42.33(0.02) 42.91(0.18) 43.65(0.17) Seaport 78.84(0.32) 78.65(0.24) 95.13(0.12) 95.75(0.06) 97.12(0.12) Baruthane sea water 47.51(0.18) 47.62(0.14) 57.24(0.04) 57.65(0.15) 58.97(0.24)

(2) Values in parenthesis are the relative standard deviations for n=5 with confidence level of 95 %.

The results obtained show that the proposed method can be applied in the determination of

A number of highly sensitive, selective and rapid flow-injection spectrophotometric and spectrofluorimetric analysis methods for the determination of iron (II), iron (III) and total iron in a wide concentration range, without employing any further treatment, have been described. The methods were based on the reactions of iron (II) and iron (III) with different complexing agents in different carrier solutions in FIA. In addition to the simplicity and low reagent consumption of the methods, the complexing agents used are commercially available and may not have a risk of serious toxicity, thus enhancing the potential applicability of the methods for iron analysis in real samples. Several parameters affecting to the determination of iron (II) and iron (III) were examined. The methods developed have been successfully applied to the determination of iron (II), iron (III) and total iron different types of water samples including river, sea, industry and spring water samples. The

Ahmed M. J. and Roy U. K. (2009) A simple spectrophotometric method for the

determination of iron(II) aqueous solutions. Turkish journal of chemistry. 33, 709-

Table 10. Determination of iron (III) and total iron in river and sea water samples

iron(III) and total iron content in water samples without a preconcentration process.

methods were also verified by applying certified reference materials.

Samples(1) Iron (III)(2) (g L-1) Total iron(2) (g L-1)

Sample Total Fe(1) (%) Certified Fe (%)

Table 9. Total iron content of iron alloys and standard reference material

Alloy (1) 8.23(0.24) 8.58 Alloy (2) 16.15(0.17) 16.62 Std Zn/Al/Cu 43XZ3 F 0.083(0.022) 0.085

(1) Samples were collected at Samsun, Turkey.

(3) Calibration curve method. (4) Standard addition method.

**6. Conclusions**

**7. References**

726

method.

different lengths ranging between 10 cm and 150 cm. The peak height increased with the increasing mixing coil length from 10–50 cm, decreased at lower concentrations and broadened at higher concentrations and longer coil lengths. The mixing coil length of 50 cm was chosen since it resulted in the best peak height and good reproducibility.

The flow-rate was varied from 0.2 mL min*−*1 to 2 mL min*−*1. The peak height decreased with the increasing flow-rate, probably due to the extent of the reaction decrease. The flow-rate of 0.8 mL min*−*1 was selected as a compromise between the sample throughput rate and sensitivity. A linear calibration graph for 4–150 μg L*−*1 iron(III), with the regression coefficient of 0.9914, was obtained under optimum conditions. The relative standard deviation for the determination of 5 μg L*−*1 iron(III) was 0.85 % (10 replicate injections), RSD of the data was below 3 %. The limit of detection (blank signal plus three times the standard deviation of the blank) was 0.5 μg L*−*1. The sample throughput of the proposed method was almost 60 h*−*1.

Table 8. Effect of foreign ions on the determination of 5 μg L-1 of iron (III) in solution

The interference effects of many cations and anions on the determination of 5 μg L*−*1 iron(III) were examined. The results summarised in Table 8 represent tolerable concentrations of each diverse ion taken as the highest concentration causing an error of 3 %. Most of the ions examined did not interfere with the determination of iron(III). The major interference was caused by iron(II) at the amount of 100 μg L*−*1. It is known that zinc and cobalt are the main interference metal ions in the determination of iron (Ensafi et al., 2004). In this study, the interference of these ions was completely eliminated by an addition of copper sulphate (1*×*10*−*4 mol L*−*1) to the reagent carrier solution. Background absorbance of copper(II) maintained in the reagent carrier solution eliminated possible interfering ions and improved the determination of iron(III). It is apparent from Table 1 that the proposed method tolerates all interfering species tested in satisfactory amounts, and it is therefore adequately selective for the determination of iron(III) and total iron.

#### **5.2.3 Applications**

The FIA method was applied in the determination of iron(III) and total iron in water and ore samples. In order to evaluate the accuracy of the proposed method, the determination of total iron in a standard reference material (Zn/Al/Cu 43XZ3F) and in a metal alloy sample was carried out. The analytical results obtained by the proposed method are in good agreement with the certified values as shown in Table 9.

For the application of the proposed FIA method to water samples; river and sea water samples collected from different sources were analysed using both the calibration curve and the standard addition methods. The values obtained from the calibration curve and the standard addition methods are in good agreement as shown in Table 10. Atomic absorption measurements taken in water samples are also given for comparison (Table 10). The analytical value of total iron in water is in good agreement with that obtained by the AAS method.

(1) Values in parenthesis are the relative standard deviations for n=5 with confidence level of 95 %.

(1) Samples were collected at Samsun, Turkey.

(2) Values in parenthesis are the relative standard deviations for n=5 with confidence level of 95 %.

(3) Calibration curve method.

(4) Standard addition method.

Table 10. Determination of iron (III) and total iron in river and sea water samples

The results obtained show that the proposed method can be applied in the determination of iron(III) and total iron content in water samples without a preconcentration process.


**3. Generation mechanisms and theoretical base of the electromagnetic precursors to earthquakes**

#### **3.1 Possible generation mechanisms of electromagnetic precursors**

This paper is not intended to present an exhaustive analysis of all of literature published in this field. Instead, we have tried to provide only some representative hypothetic mechanisms related to the electromagnetic precursors to earthquakes.

The theory of semiconductors launched by Freund (2000) is considered the most comprehensive one. According to this theory, the solid rocks (e.g. granites) begin to crack under the action of a stress exceeding their elasticity limit, what leads to a release of electric charges. These charges, carried by water moving through the rocks fissures, generate currents of high amperage that, in their turn, create disturbances of the magnetic field and, also, infrared signature in the bands of 8μm and 11μm, when the charges are neutralized at the surface of the Earth.

In accordance with this theory, to have seismo-electric signals it is necessary that a few compulsory conditions to be fulfilled:

The resistivity of porous rocks is changed as a function of compression and shearing (Brace et al., 1965) and may be measured by using passive experiments (magnetotelluric method), or experiments with active methods (Park et al., 1993).

Revol et al., (1977) have shown that the magnetic properties of rocks are changed depending on the applied stress and are associated to the changes of stress emphasized on fault rupture, what produces oscillations of the magnetic field of a few nT (Johnston, 1978, 1997); this mechanism is due to the piezomagnetic effect.

When a conductive fluid is forced to flow close to a surface with stationary electric charges, an electrokinetic effect appears generating currents that start to flow either through fluid, or

Sperner, B., the Collaborative Research Center [CRC] 461 Team, (2005), taking into consideration that the geometry of the subduction zone was not unequivocally defined, proposed four possible configurations for the Vrancea zone: (i) subduction beneath the suture zone; (ii) subduction beneath the fore deep area; (iii) two interacting subduction

Various types of slab detachment or delamination have been proposed to explain the present-day seismic images of the descending slab (Girbacea & Frisch, 1998; Gvirtzman,

Viscous flows due to the sinking seismogenic slab together with dehydration-induced faulting can be considered as possible triggering mechanism explaining the intermediate-

Stanica et al., (2004) show, on the base of the three-dimensional (3D) resistivity tomographic image carried out using magnetotelluric data, that the possible triggering mechanism of the intermediate-depth earthquakes in the Vrancea zone may be the rock response to the active torsion processes sustained by the descending asthenospheric currents and the irregular shape of the relic slab. In their opinion, this torque effect may generate the increase shear

**3. Generation mechanisms and theoretical base of the electromagnetic**

This paper is not intended to present an exhaustive analysis of all of literature published in this field. Instead, we have tried to provide only some representative hypothetic

The theory of semiconductors launched by Freund (2000) is considered the most comprehensive one. According to this theory, the solid rocks (e.g. granites) begin to crack under the action of a stress exceeding their elasticity limit, what leads to a release of electric charges. These charges, carried by water moving through the rocks fissures, generate currents of high amperage that, in their turn, create disturbances of the magnetic field and, also, infrared signature in the bands of 8μm and 11μm, when the charges are neutralized at

In accordance with this theory, to have seismo-electric signals it is necessary that a few

The resistivity of porous rocks is changed as a function of compression and shearing (Brace et al., 1965) and may be measured by using passive experiments (magnetotelluric method),

Revol et al., (1977) have shown that the magnetic properties of rocks are changed depending on the applied stress and are associated to the changes of stress emphasized on fault rupture, what produces oscillations of the magnetic field of a few nT (Johnston, 1978, 1997);

When a conductive fluid is forced to flow close to a surface with stationary electric charges, an electrokinetic effect appears generating currents that start to flow either through fluid, or

that lead to disturbances of the magnetic field.

or experiments with active methods (Park et al., 1993).

this mechanism is due to the piezomagnetic effect.

**3.1 Possible generation mechanisms of electromagnetic precursors**

mechanisms related to the electromagnetic precursors to earthquakes.

zones, and (iv) subduction beneath the suture, followed by delamination.

2002; Sperner et al., 2001; Wortel & Spakman, 2000).

depth seismicity in Vrancea (Ismail-Zadeh et al., 2000)

stress and drive faulting process within the rigid slab (Fig.2).

**precursors to earthquakes**

the surface of the Earth.

compulsory conditions to be fulfilled:

through the surrounding rock, what, in conditions imposed by real crustal parameters, may create surface magnetic fields of a few nT (Fenoglio et al., 1995).

Another theory supposes the generation of the magnetic signal either by conductive fluid flowing in presence of the magnetic field of the Earth, or by magnetohydrodynamic conversion of the seismic signal into an electric signal during the propagation through a conductive medium (Molchanov et al., 2001). While these mechanisms were proved in laboratory conditions, it is unclear, yet, how this process takes place in conditions rather similar to those specific to the Earth, owing to the lack of measurements in active fault zones.

#### **3.2 Theoretical base of the electromagnetic precursors**

At the Earth surface the vertical geomagnetic component (Bz) is entirely secondary field and its existence is an immediate indicator of lateral inhomogeneity. For a two-dimensional (2D) structure, the vertical geomagnetic component (Bz) is produced essentially by the horizontal geomagnetic component perpendicular (B) to geoelectric structure orientation and, consequently, the normalized Bzn function defined as:

$$\text{Bzn (f)} = \frac{\text{Bz}(\text{f})}{\text{B}\_{\perp}(\text{f})} \tag{1}$$

should be time invariant in non geodynamic conditions (Ward et al., 1970), but it becomes unstable due to the geodynamic processes and, therefore, it could be used as a precursory parameter of the intermediate depth seismic activity (Stanica and D.A. Stanica, 2010).

In order to explain cause (earthquake) - effect (anomalous Bzn) relationship, we introduce the following equations:

$$\text{pz (f)} = \frac{0.2}{\text{f}} \left| \frac{\text{E}\_{\parallel}(\text{f})}{\text{Bz}(\text{f})} \right|^2 \tag{2}$$

where: z is vertical resistivity [m = VmA-1], f is the frequency [Hz] and the E║ is the electric field parallel to strike [Vm-1], Bz is the vertical component of the magnetic induction [Tesla (T) = V s m-2].

Also, it is possible to write the relation:

$$\rho\_{\parallel\parallel}(\mathbf{f}) = \frac{0.2}{\frac{\mathbf{f}}{\mathbf{f}}} \left| \frac{\mathbf{E}\_{\parallel\parallel}(\mathbf{f})}{\mathbf{B}\_{\perp}(\mathbf{f})} \right|^{2} \quad \text{,} \tag{3}$$

where: ║ is the resistivity parallel to strike[m], B is the component of the magnetic induction perpendicular to strike

[Tesla (T) = V s m-2].

From the relations (2) and (3) we may estimate the normalized function Bzn (f), in terms of resistivities as follows:

$$\left| \text{Bzn (f)} \right| = \sqrt{\frac{\rho\_{||}(\text{f})}{\rho z \, \text{(f)}}} \tag{4}$$

This estimation of Bzn is in error for non two-dimensional geoelectrical structure.

Earthquakes Precursors 85

model (Fig.3, b.) is of interest in selecting the site (GOPS) for continuous monitoring of the geomagnetic field. The normalized frequency scale () is proportional to distance along the x-axis and inverse-proportional to penetration depth (δ1) in medium of resistivity 1. The

As we have seen in relation (1), Bzn could be used as precursory parameter of seismic event by measuring the vertical geomagnetic component (Bz) and horizontal component perpendicular to the strike (B) which have been collected at the Geodynamic Observatory Provita de Sus (GOPS), placed on the Carpathian electrical conductivity anomaly (CECA). This anomaly is delineated by the Wiese induction arrows, and it can represent a zone of partial melting or of hot highly-mineralized fluids in sedimentary layers, formed at the collisional limit between the both platforms (East European and Moesian) with Carpathian Alpine structures (Fig.4). It is also quit possible that these two varieties of fluid anomalies to co-exist and gradually flow one into another, as indicated by the fact that geoelectric parameters remain fairly constant throughout its entire length (Pinna et al., 1993,

Induction arrows are vector representations of the ratio of vertical to horizontal magnetic field components. Since vertical magnetic fields are generated by lateral conductivity gradients, induction arrows map can be used to infer the presence, or absence of lateral variation of conductivity/resistivity. In the Wiese convection (Wiese, 1962) the vectors point away from the conductivity anomaly generated by anomalous internal concentrations of current, while in the Parkinson convection (Parkinson, 1959), the vectors point towards anomalous internal concentrations of current. Thus, insulator-conductor boundaries extended through a 2D geoelectrical structure (like CECA) give rise to induction arrows that orientate perpendicular to their geoelectrical strike, and have magnitude proportional to the intensity of anomalous current concentration (Jones & Price, 1970), which are in turn

In our methodology, it was also supposed that pre-seismic conductivity changes, due to the fluid migration through faulting system, may generate changes of the normalized function Bzn, having magnitude proportional to the intensity of anomalous current concentrations

The Geodynamic Observatory Provita de Sus (Fig.1) is located at about 100 km towards south-west of seismic active Vrancea zone and the criteria of selection as monitoring site are:

In order to select the frequency range where the relation (1) is valid (i.e., existence of a 2D geoelectrical structure and its strike orientation), as a first step in our EM methodology, at the GOPS we made a magnetotelluric sounding using the magnetotelluric (MT) equipment

1 10ρ [Ωm] 1 δ [km] = 1 2π f[Hz] (6)

electromagnetic skin depth or penetration depth is given by:

**4. Electromagnetic (EM) methodology and results**

determined by the magnitude of conductivity gradient.

condition for a 2D type geoelectric structure is fulfilled (Fig. 4);

**4.1 Electromagnetic data collection**

Rokityansky & Ingerov, 1999).

through CECA.

Bucharest).

Fig. 3. Bzn distribution versus normalized frequency for sloping interface (a.) and vertical contact (b.): =a/δ1

The relation (4) demonstrates that normalized function Bzn could be linked to the resistivity/conductivity variation along the faulting systems acting as high sensitive path (represented by the Carpathian electrical conductivity anomaly) through the lithosphere and its right part lead to the normalized resistivity defined as:

$$\rho \mathbf{u}(\mathbf{f}) = \frac{\rho \mathbf{z}(\mathbf{f})}{\rho \mathbf{z}(\mathbf{f})} \tag{5}$$

Approximate field solutions were computed for two simple 2D geoelectric structures to illustrate the robustness of the relation (1). Solutions for the sloping interface and vertical contact models were obtained using finite element code (Wannamaker et al., 1986) and the results are presented in Fig. 3. These models represent two extremes in dipping angle of the interface and similarity in the properties of the normalized function Bzn obtained for the

Fig. 3. Bzn distribution versus normalized frequency for sloping interface (a.) and vertical

its right part lead to the normalized resistivity defined as:

ρ (f) ρn(f) = ρz(f)

The relation (4) demonstrates that normalized function Bzn could be linked to the resistivity/conductivity variation along the faulting systems acting as high sensitive path (represented by the Carpathian electrical conductivity anomaly) through the lithosphere and

Approximate field solutions were computed for two simple 2D geoelectric structures to illustrate the robustness of the relation (1). Solutions for the sloping interface and vertical contact models were obtained using finite element code (Wannamaker et al., 1986) and the results are presented in Fig. 3. These models represent two extremes in dipping angle of the interface and similarity in the properties of the normalized function Bzn obtained for the

(5)

contact (b.): =a/δ1

model (Fig.3, b.) is of interest in selecting the site (GOPS) for continuous monitoring of the geomagnetic field. The normalized frequency scale () is proportional to distance along the x-axis and inverse-proportional to penetration depth (δ1) in medium of resistivity 1. The electromagnetic skin depth or penetration depth is given by:

$$\left\{\delta\_{\rm I}[\rm km] = \frac{1}{2\pi} \sqrt{\frac{10\rho\_{\rm I}[\rm \Omega m]}{\rm f[\rm Hz]}}\right. \tag{6}$$


**6. Human papilloma viruses and reproductive health**

Numerous human papilloma viruses (HPV; *papovaviridae*) belong to DNA-viruses. All species of HPV induce typical changes in mitotic activity of flat epithelial cells, and lead to appearance of neoplasm in skin and mucosa. Some variants of HPV are high oncogenic, especially types 16, 18, 31, 33, some other also may induce rare malignancy. Oncogenic variants of HPV may be found in more then 50% of melanomas [Dréau et al., 2000].

Clinical consequences of HPV infection is not restricted by risk of malignancy and cosmetic problems, but by influence on gestation process. In abortions' tissues HPV can be found nearly in 60% of cases of spontaneous abortions, but in 20% of cases, if we have deal with medical abortions [Spandorfer et al., 2006]. HPV prominently decreases the successes of IVF [Spandorfer et al., 2006]. Besides, clinical problems, concerned to inborn malformations of the nervous system, described to be related with HPV. Frequency of neural defects (very different) is arisen 10-12 times in children born by HPV infected women [Poletaev, 2008].

Influence of HPV infection on embryo and fetus development is supposingly related to induction of elevated serum level of autoantibodies against S100 proteins by mechanism of molecular mimicry. Common epitopes in molecules of S100 and few viral antigens were

As well as opportunistic viruses and bacteria presented in woman organism may trigger for abnormal production of embryotropic autoantibodies, successful anti-microbial treatment of women with chronic infection will lead to normalization the immune parameters in most cases. It is interestingly to note that nearly 30% of recently infertile women had become pregnant during the first six months after anti-bacterial or anti-viral treatment if therapy was accompanied by normalization of serum content of embryotropic autoantibodies [Serova, 2000]. These observations indicate: some women with "unexplained infertility" in essence are fertile, and their pregnancy may happens often but interrupts at early stages (usually before diagnosing) because severe but reversible immune deviations. This deviations has been reflected and may be detected by quantitative measuring of changes in

Obstetricians often arise the question, which seems to be difficult: why did some women with opportunistic infection suffer from repeated miscarriages and other reproductive problems, but reproductive functions of some other women with the same herpetic or mycoplasmic infection was not disturbed? Serova [2000], and Litvak [2001] in observed patients, and Cronise and Kelly [1999] in experiments with laboratory mice show clearly: the cause of opportunistic (potentially pathogenic) microbial factor does induce systemic immune deviations, such situation is usually associated with reproductive problems. On opposite, the situation usually does not influence negatively the pregnancy course if presence of the same microbial factor has not associates with notable immune changes. These empirical data and conclusions are close to aphoristic idea of the founder of the modern microbiology Louis Pasteur: "microbe is nothing, background (that is reactivity of the host-organism) is everything" [Mayanskiy, 1999]. In this context investigation of serum level of embryotropic autoantibodies may became a useful instrument for evaluation of individual risk of pathology in pregnancy if some viruses or bacteria persist in organism of woman. Such observing is suitable for decision on necessity or its contradictions of

Numerous human papilloma viruses (HPV; *papovaviridae*) belong to DNA-viruses. All species of HPV induce typical changes in mitotic activity of flat epithelial cells, and lead to appearance of neoplasm in skin and mucosa. Some variants of HPV are high oncogenic, especially types 16, 18, 31, 33, some other also may induce rare malignancy. Oncogenic

Clinical consequences of HPV infection is not restricted by risk of malignancy and cosmetic problems, but by influence on gestation process. In abortions' tissues HPV can be found nearly in 60% of cases of spontaneous abortions, but in 20% of cases, if we have deal with medical abortions [Spandorfer et al., 2006]. HPV prominently decreases the successes of IVF [Spandorfer et al., 2006]. Besides, clinical problems, concerned to inborn malformations of the nervous system, described to be related with HPV. Frequency of neural defects (very different) is arisen 10-12 times in children born by HPV infected women [Poletaev, 2008].

Influence of HPV infection on embryo and fetus development is supposingly related to induction of elevated serum level of autoantibodies against S100 proteins by mechanism of molecular mimicry. Common epitopes in molecules of S100 and few viral antigens were

variants of HPV may be found in more then 50% of melanomas [Dréau et al., 2000].

antimicrobial treatment before planned pregnancy in each individual case.

**6. Human papilloma viruses and reproductive health**

blood serum content of embryotropic autoantibodies.

described [Poletaev, 2008]. Two dozen proteins of S100 family take part in regulation of apoptosis, and maturation of primordial nervous system (fetal) [Poletaev, 2008]. Therefore antibody-dependent disturbances of according processes may be related to some forms of malignancy, embryo death cases as well as to malformation of the nervous tube. Consequently the investigation for serum content of autoantibodies against S100 and preventive treatment in necessity should be recommended before pregnancy to each woman


**3.2. Profilin expression and characterization of the differential reactivity of birch, hazel, timothy-grass and maize profilins**

SDS-PAGE analysis of protein extracts of mature pollen from *Betula pendula*, *Corylus avellana, Phleum pratense* and *Zea mays* displayed distinctive protein profiles in the figure 3. Defined protein bands corresponding to profilin are clearly distinguishable in the interval of 14- 17kDa, which is the expected size for profilin isoforms.

Differential Immune-Reactivity and Subcellular Distribution Reveal

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 79

**Figure 4.** Immuno-reactivity analysis of crude protein extract from pollen of 5 plant species. Reactivity of proteins from 5 plant species were assayed against different maize profilin antisera, A) anti-PRA, B) anti-ZmPRO3, C) anti-ZmPRO5, D) anti-ZmPRO4, E) as well as against olive profilin antiserum anti-Ole e 2. It was appreciable up to 2 reactive bands about 13.7 and 14.2 kDa, corresponding to different isoforms of profilins for the species analyzed. The intensity of the reactive bands was quantitated by a densitometric analysis: pink color plot corresponded to 13.7kDa bands, and blue to 14.2 kDa. Red asterisks highlighted the differential reactivity (very high or very low) of defined species to different antisera, whereas blue asterisks highlighted the differential reactivity among cultivar to defined

antiserum.

**E**

**A**

**B**

**C**

**D**

**Figure 3.** Protein profile of crude protein extract from pollen of 5 individual plant species. 30μg of total protein was loaded in each line.

Profilin immunodetection was performed by using the same antisera described above for olive. In this case, different antisera are able to distinguish up to two reactive bands, with molecular weights of 13.7 and 14.2 kDa (Figure 4).

Clear differences can be appreciated when compared protein extracts reactivity of different species to individual antisera, as well as the reactivity of an individual protein extract to the different antisera assayed.

Cross-immune reactivity analysis between protein extracts from the five species with different antisera made against profilins from olive and maize pollen showed large differences both qualitative (intensity of bands) and quantitative (number of reactive bands) concerning profilins of MW around 13.7 and 14.2 kDa (Figure 4).

Statistical analysis of densitometric quantitations was performed. The variance analysis for the different antisera against different protein extracts showed significant differences among the 5 species (F-ratio= 8.13, p<0.05).

The reactivity values were inside of a normal distribution (test de Shapiro-Wilk: 0.95, p>0.05), while the Levene test indicated non-homogeneity of variances (Levene: 2.86, p<0.05).

protein was loaded in each line.

different antisera assayed.

the 5 species (F-ratio= 8.13, p<0.05).

molecular weights of 13.7 and 14.2 kDa (Figure 4).

concerning profilins of MW around 13.7 and 14.2 kDa (Figure 4).

**birch, hazel, timothy-grass and maize profilins**

17kDa, which is the expected size for profilin isoforms.

**3.2. Profilin expression and characterization of the differential reactivity of**

SDS-PAGE analysis of protein extracts of mature pollen from *Betula pendula*, *Corylus avellana, Phleum pratense* and *Zea mays* displayed distinctive protein profiles in the figure 3. Defined protein bands corresponding to profilin are clearly distinguishable in the interval of 14-

**Figure 3.** Protein profile of crude protein extract from pollen of 5 individual plant species. 30μg of total

Profilin immunodetection was performed by using the same antisera described above for olive. In this case, different antisera are able to distinguish up to two reactive bands, with

Clear differences can be appreciated when compared protein extracts reactivity of different species to individual antisera, as well as the reactivity of an individual protein extract to the

Cross-immune reactivity analysis between protein extracts from the five species with different antisera made against profilins from olive and maize pollen showed large differences both qualitative (intensity of bands) and quantitative (number of reactive bands)

Statistical analysis of densitometric quantitations was performed. The variance analysis for the different antisera against different protein extracts showed significant differences among

The reactivity values were inside of a normal distribution (test de Shapiro-Wilk: 0.95, p>0.05),

while the Levene test indicated non-homogeneity of variances (Levene: 2.86, p<0.05).

**Figure 4.** Immuno-reactivity analysis of crude protein extract from pollen of 5 plant species. Reactivity of proteins from 5 plant species were assayed against different maize profilin antisera, A) anti-PRA, B) anti-ZmPRO3, C) anti-ZmPRO5, D) anti-ZmPRO4, E) as well as against olive profilin antiserum anti-Ole e 2. It was appreciable up to 2 reactive bands about 13.7 and 14.2 kDa, corresponding to different isoforms of profilins for the species analyzed. The intensity of the reactive bands was quantitated by a densitometric analysis: pink color plot corresponded to 13.7kDa bands, and blue to 14.2 kDa. Red asterisks highlighted the differential reactivity (very high or very low) of defined species to different antisera, whereas blue asterisks highlighted the differential reactivity among cultivar to defined antiserum.

Multiple comparison among the antisera showed statistically significant differences (p<0.05) between anti-ZmPRO3 and anti-PRA, anti-ZmPRO4, and anti-ZmPRO5, respectively, with Games-Howell test results of 65010.5, 64564.3 y 71150.2, respectively.

Differential Immune-Reactivity and Subcellular Distribution Reveal

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 81

**Figure 6.** Immune-reactivity analysis of crude protein extract of mature olive pollen (cv. Picual) before and after *in vitro* germination. Reactivity of proteins extracts from mature pollen, as well as different stages of *in vitro* germination were assayed against different maize profilin antisera, a) anti-PRA, b) anti-ZmPRO3, c) anti-ZmPRO5, d) anti-ZmPRO4, e) as well as against olive profilin antiserum anti-Ole e 2. It was appreciable up to 5 reactive bands about 13.0, 13.7, 14.2, 14.9 y 15.7 kDa, corresponding to different isoforms of profilins. The intensity of the reactive bands was quantitated by a densitometric analysis: blue color plot corresponded to 13.0kDa bands, pink, yellow, turquoise, and brown color to 13.7, 14.2,

14.9 and 15.7 kDa, respectively.

**D**

**C**

**B**

**A**

On the other hand, analysis of reactivity among species against individual antiserum showed statistical significant differences between *Olea europaea* L. and *Phleum pratense*, *Olea europaea* L. and *Corylus avellana*, *Zea mays* and *Phleum pratense*, and *Corylus avellana* and *Zea mays* for the antisera anti-PRA, anti-ZmPRO5, anti-ZmPRO4 and anti-Ole e 2, respectively.

Reversely, it is possible to observe clear differences between antisera for defined species, such as *Corylus avellana* and *Phleum pratense* for anti-ZmPRO3, and *Phleum pratense* for anti-Ole e 2.

#### **3.3. Analysis of olive pollen profilin during** *in vitro* **germination**

The study of the olive pollen germination was aimed to analyze the differential expression of profilin isoforms during the germination process. Figure 5 showed the protein profiles of olive pollen extracts (cv. Picual) obtained after hydration, and at different times of germination (5 min, 1h, 4h, 7h and 18h). No bands were distinguishable in the blue Coomassie blue stained gel around the molecular weight corresponding to profilins.

**Figure 5.** Protein profile of crude protein extract of mature olive pollen (cv. Picual) before and at different times of *in vitro* germination. 30μg of total protein was loaded in each line.

On the contrary, clear bands were obtained with immunoblotting experiments with the different antisera. 5 different bands can be distinguished corresponding to 5 different profilin isoforms (Figure 6), with calculated MW of 13.0, 13.7, 14.2, 14.9 and 15.7 kDa, respectively.

respectively.

respectively.

Ole e 2.

Multiple comparison among the antisera showed statistically significant differences (p<0.05) between anti-ZmPRO3 and anti-PRA, anti-ZmPRO4, and anti-ZmPRO5, respectively, with

On the other hand, analysis of reactivity among species against individual antiserum showed statistical significant differences between *Olea europaea* L. and *Phleum pratense*, *Olea europaea* L. and *Corylus avellana*, *Zea mays* and *Phleum pratense*, and *Corylus avellana* and *Zea mays* for the antisera anti-PRA, anti-ZmPRO5, anti-ZmPRO4 and anti-Ole e 2,

Reversely, it is possible to observe clear differences between antisera for defined species, such as *Corylus avellana* and *Phleum pratense* for anti-ZmPRO3, and *Phleum pratense* for anti-

The study of the olive pollen germination was aimed to analyze the differential expression of profilin isoforms during the germination process. Figure 5 showed the protein profiles of olive pollen extracts (cv. Picual) obtained after hydration, and at different times of germination (5 min, 1h, 4h, 7h and 18h). No bands were distinguishable in the blue

Coomassie blue stained gel around the molecular weight corresponding to profilins.

**Figure 5.** Protein profile of crude protein extract of mature olive pollen (cv. Picual) before and at

On the contrary, clear bands were obtained with immunoblotting experiments with the different antisera. 5 different bands can be distinguished corresponding to 5 different profilin isoforms (Figure 6), with calculated MW of 13.0, 13.7, 14.2, 14.9 and 15.7 kDa,

different times of *in vitro* germination. 30μg of total protein was loaded in each line.

Games-Howell test results of 65010.5, 64564.3 y 71150.2, respectively.

**3.3. Analysis of olive pollen profilin during** *in vitro* **germination**

**Figure 6.** Immune-reactivity analysis of crude protein extract of mature olive pollen (cv. Picual) before and after *in vitro* germination. Reactivity of proteins extracts from mature pollen, as well as different stages of *in vitro* germination were assayed against different maize profilin antisera, a) anti-PRA, b) anti-ZmPRO3, c) anti-ZmPRO5, d) anti-ZmPRO4, e) as well as against olive profilin antiserum anti-Ole e 2. It was appreciable up to 5 reactive bands about 13.0, 13.7, 14.2, 14.9 y 15.7 kDa, corresponding to different isoforms of profilins. The intensity of the reactive bands was quantitated by a densitometric analysis: blue color plot corresponded to 13.0kDa bands, pink, yellow, turquoise, and brown color to 13.7, 14.2, 14.9 and 15.7 kDa, respectively.

The expression pattern of profilin is similar during *in vitro* germination, although conspicuous differences of the antisera reactivity can be pointed out for the protein extracts. Level of protein isoforms expression in mature pollen and hydration stage were quite similar. On the other hand, there was a notable decrease of protein expression level, equally for all the isoforms at the end of germination (7-18 hours). Proteins expression level between 5 min and 4 h of germination was variable for the different profilin isoforms, particularly for the variants of 13.7 and 14.2 KDa.

Differential Immune-Reactivity and Subcellular Distribution Reveal

**Pathway**

**Others (Cytoplasm, Microsomes)**

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 83

The immunoblotting analysis of seed proteins with anti-Ole e 2 showed at least two reactive bands located at 13.7 and 14.2 kDa (Figure 7B). In addition, there were quantitative differences in the expression level of profilin concerning both tissues (cotyledon and endosperm) and cultivar. Thus, profilin in endosperm of cultivar Picual showed a higher level of immune-reactivity in comparison with profilins of cotyledon from the same cultivar. Protein extracts from olive seed cultivars Acebuche and Picual were used in immunoblot experiments with antiserum anti-Ole e 2. A) SDS-PAGE of crude protein extract from olive seeds tissues (endosperm and cotyledon) of Acebuche and Picual cultivars. B) Inmunoblot of seeds protein samples from (A). Reactive bands were observed at 13.7 and 14.2 kDa, corresponding to vegetative profilins. C) Plot corresponding to the quantitation of reactive bands: blue lines were depicted for 14.2 kDa bands, whereas pink color was used for 13.7

**Chloroplast Mitochondria Secretory**

*pendula* **- 14.4±1.1 8.6±0.5 11.7±0.3 65.3±1.0**

*pratense* **- 6.6±0.2 5.0±0.3 27.9±0.7 61.5±1.4**  *Zea mays* **- 7.8±0.1 7.2±0.1 19.7±0.4 65.4±0.4**

**Table 1.** Score calculated for the probability of finding a specific profilin in a particular cellular location. Bold numbers indicate that the score calculated for these sequences markedly differed from the average

**- 14.4±0.1 8.1±0.1 13.2±0.5 64.6±0.4**  DQ663545 8.4±0.0 6.8±0.0 22.3±0.0 62.5±0.0 DQ663547 6.5±0.0 4.2±0.0 27.7±0.0 61.6±0.0

X73280 2.5±0.0 9.9±0.0 27.1±0.0 60.5±0.0

**- 13.2±1.6 8.2±0.8 9.8±0.5 68.8±0.7**  DQ640909 5.9±0.0 4.4±0.0 39.9±0.0 49.8±0.0 DQ640910 7.6±0.0 7.0±0.0 20.0±0.0 65.4±0.0 DQ640906 5.8±0.0 5.3±0.0 32.2±0.0 56.7±0.0 DQ640903 9.7±0.0 7.4±0.0 14.2±0.0 68.7±0.0 DQ640908 7.9±0.0 7.8±0.0 17.0±0.0 67.3±0.0 DQ317580 6.7±0.0 4.8±0.0 28.4±0.0 60.1±0.0 DQ640904 8.2±0.0 6.8±0.0 15.2±0.0 69.8±0.0 DQ663553 6.7±0.0 4.8±0.0 28.4±0.0 60.1±0.0 DQ663554 6.7±0.0 4.8±0.0 28.5±0.0 60.0±0.0 DQ663555 6.9±0.0 4.4±0.0 28.2±0.0 60.5±0.0 DQ663556 6.7±0.0 4.8±0.0 28.5±0.0 60.0±0.0 DQ663558 8.7±0.0 6.8±0.0 20.0±0.0 64.5±0.0 DQ640905 7.1±0.0 8.4±0.0 16.5±0.0 68.0±0.0 DQ60907 8.2±0.0 6.8±0.0 15.3±0.0 69.7±0.0

kDa reactive bands.

**Sequence GeneBank Accession N°**

**Specie**

*Olea europaea* L.

*Betula*

*Corylus avellana*

*Phleum*

value.

#### **3.4. Analysis of cross-immunoreactivity between vegetative and reproductive profilins**

In order to determine the putative cross-reaction between reproductive profilins (see sections 3.1 to 3.3) and profilins from vegetative tissues, we have tested two of the antibodies used above (anti-ZmPRO4, and anti-ZmPRO5) against vegetative isoforms of maize profilins.

For this purpose, we have used protein extracts from olive seeds (cotyledon and endosperm) (cv Picual and Acebuche). The analysis of olive seed proteins Figure 7A showed a protein profile completely different to these of protein extracts from pollen. In this case, the mayor protein bands corresponded to different polypeptides of seed storage proteins, with MW ranging from 20 to 47kDa (Alché et al. 2006).

**Figure 7.** Immune-reactivity analysis of crude protein extract of vegetative profilins from olive seed tissues, cotyledon and endosperm.

The immunoblotting analysis of seed proteins with anti-Ole e 2 showed at least two reactive bands located at 13.7 and 14.2 kDa (Figure 7B). In addition, there were quantitative differences in the expression level of profilin concerning both tissues (cotyledon and endosperm) and cultivar. Thus, profilin in endosperm of cultivar Picual showed a higher level of immune-reactivity in comparison with profilins of cotyledon from the same cultivar.

82 Current Insights in Pollen Allergens

**profilins**

particularly for the variants of 13.7 and 14.2 KDa.

ranging from 20 to 47kDa (Alché et al. 2006).

tissues, cotyledon and endosperm.

The expression pattern of profilin is similar during *in vitro* germination, although conspicuous differences of the antisera reactivity can be pointed out for the protein extracts. Level of protein isoforms expression in mature pollen and hydration stage were quite similar. On the other hand, there was a notable decrease of protein expression level, equally for all the isoforms at the end of germination (7-18 hours). Proteins expression level between 5 min and 4 h of germination was variable for the different profilin isoforms,

**3.4. Analysis of cross-immunoreactivity between vegetative and reproductive**

In order to determine the putative cross-reaction between reproductive profilins (see sections 3.1 to 3.3) and profilins from vegetative tissues, we have tested two of the antibodies used above (anti-ZmPRO4, and anti-ZmPRO5) against vegetative isoforms of maize profilins.

For this purpose, we have used protein extracts from olive seeds (cotyledon and endosperm) (cv Picual and Acebuche). The analysis of olive seed proteins Figure 7A showed a protein profile completely different to these of protein extracts from pollen. In this case, the mayor protein bands corresponded to different polypeptides of seed storage proteins, with MW

**Figure 7.** Immune-reactivity analysis of crude protein extract of vegetative profilins from olive seed

Protein extracts from olive seed cultivars Acebuche and Picual were used in immunoblot experiments with antiserum anti-Ole e 2. A) SDS-PAGE of crude protein extract from olive seeds tissues (endosperm and cotyledon) of Acebuche and Picual cultivars. B) Inmunoblot of seeds protein samples from (A). Reactive bands were observed at 13.7 and 14.2 kDa, corresponding to vegetative profilins. C) Plot corresponding to the quantitation of reactive bands: blue lines were depicted for 14.2 kDa bands, whereas pink color was used for 13.7 kDa reactive bands.

**Table 1.** Score calculated for the probability of finding a specific profilin in a particular cellular location. Bold numbers indicate that the score calculated for these sequences markedly differed from the average value.

#### **3.5. Cellular localization of profilin**

#### *3.5.1. Predicting the cellular localization of profilin*

Predictions of the cellular location for profilins were carried out based in their primary sequence, and the putative presence of signal peptides responsible for targeting these proteins to specific cellular locations.

Differential Immune-Reactivity and Subcellular Distribution Reveal

**Sequence GeneBank Accession N°**

**Nuclear Targeting Motif**

DQ663545 RGKKGAGGITVKKT

X77583 RGKKGAGGITIKKT

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 85

hazel and timothy-grass. These changes can represent differences in the affinity for

*avellana*

*Phleum pratense*

DQ640910 RGKKGAGGITVKKT DQ663547 RGKKGAGGITVKKT

DQ640906 RGKKGAGGITIKKT Y09546 RGKKGAGGITIKKT DQ640908 RGKKGAGGITVKKT Y09457 RGKKGAGGITIKKT DQ317574 RGKKGSGGITSKKT Y09458 RGKKGAGGITIKKT DQ663553 RGKKGAGGITIKKT DQ663535 RGKKGAGGITIKKT DQ663554 RGKKGAGGITIKKT DQ663536 RGKKGAGGITIKKT DQ663555 RGKKGAGGITIKKT DQ663537 RGKKGAGGITIKKT DQ663556 RGKKGAGGITIKKT DQ663538 RGKKGAGGITIKKT DQ663557 RGKKGAGGITIKKT DQ663539 RGKKGAGGITIKKT DQ640905 RGKKGAGGITVKKT DQ663540 RGKKGAGGITIKKT DQ138358 RGKKGTGGITIKKT DQ663541 RGKKGAGGITIKKT DQ138352 RGKKGSGGITIKET DQ663542 RGKKGAGGITIKKT

**Motif Specie**

localization of particular profilin isoforms in defined cellular locations.

**Nuclear Targeting**

DQ640909 RGKKGAGGITIKKT *Corylus*

DQ138336 RGKKGAGGITIKKT

DQ138354 RGKKGSGGITIKET

*3.5.2. Experimental approach for profilin cellular localization*

**Table 3.** Changes in the motif targeting to a nuclear localization of profilin sequences.

Sequence of nuclear motif is characterized by the sequence RGKKGXGG(I/V)T(I/V)KKT, where X is the amino acid serine (**S**) in the majority of the analyzed sequences. The variable amino acids were

The experimental approach for profilin localization was performed to determine whether there is really a differential distribution of profilin isoforms. Immuno-localization assays were performed by transmission electron microscopy (TEM) in ultrathin sections of germinated pollen grains of olive (cv. Picual) using different antisera: anti-Ole e 2 and anti-PRA (Figures 8 and 9), anti-ZmPRO3 (Figure 10), anti-ZmPRO4 (Figure 11), anti-ZmPRO5

All immune-localizations showed that profilins (gold particles) were preferentially located in the cytoplasm (Figures 8A and 9-12A), in addition to both nuclei of vegetative/generative cell (Figures 8A and 9A). Moreover, abundant gold grains were located in the pollen apertures (Figures 8C, 10C and 11C), in along the pollen wall, pollen tube and the pollen tip (Figures 8A and 9-12B), as well as in the material associated with the pollen grain exine (pollen coat) (Figures 8B, 11B and 12C). No significant number of labeling were found in the negative controls, for which were omitted the primary antiserum (Figure 9C). The overall number of gold grains in the sections was variable, and depending on the antiserum used.

**Specie**

*Olea europaea* L.

(Figure 12).

**Sequence GeneBank Accession N°**

highlighted in bold and red color.

Probability of profilins location was calculated by using the tools TargetP (www.cbs.dtu.dk) and v2.0 PSORT (psort.hgc.jp). Table 1 shows the average values of probability for profilins location in different cellular compartments.

Overall, profilins exhibited high probability for cytoplasm localization. However, some sequences had a significant score for being localized in mitochondria and chloroplasts, while others were targeted to the secretory pathway. These data were confirmed by the program SignalP 3.0 Server (www.cbs.dtu.dk) (results not shown).

In addition, it was calculated the average probability of nuclear localization of profilins in the table 2, where different sequences from species exhibited a higher or lower probability of localization in comparison with an average score. Based in the average score, profilins from *Olea europaea* L. are most likely localized in nucleus compared with the other species.

Plant profilins analyzed have a targeting motif for nuclear localization which sequence is (RGKKGXGG(I/V)T(I/V)KKT) (Yoneda 1997).

**Table 2.** Score of probability for nuclear distribution of profilins. Bold numbers indicate the average probability.

The polymorphism of the profilin sequences concerning this motif is depicted in the table 3. Overall, micro-heterogeneities in this motif were identified for several sequences of olive,

hazel and timothy-grass. These changes can represent differences in the affinity for localization of particular profilin isoforms in defined cellular locations.

84 Current Insights in Pollen Allergens

**3.5. Cellular localization of profilin**

proteins to specific cellular locations.

location in different cellular compartments.

(RGKKGXGG(I/V)T(I/V)KKT) (Yoneda 1997).

*Olea europaea* L.

*Phleum pratense*

*Zea mays*

probability.

SignalP 3.0 Server (www.cbs.dtu.dk) (results not shown).

*3.5.1. Predicting the cellular localization of profilin*

Predictions of the cellular location for profilins were carried out based in their primary sequence, and the putative presence of signal peptides responsible for targeting these

Probability of profilins location was calculated by using the tools TargetP (www.cbs.dtu.dk) and v2.0 PSORT (psort.hgc.jp). Table 1 shows the average values of probability for profilins

Overall, profilins exhibited high probability for cytoplasm localization. However, some sequences had a significant score for being localized in mitochondria and chloroplasts, while others were targeted to the secretory pathway. These data were confirmed by the program

In addition, it was calculated the average probability of nuclear localization of profilins in the table 2, where different sequences from species exhibited a higher or lower probability of localization in comparison with an average score. Based in the average score, profilins from

Plant profilins analyzed have a targeting motif for nuclear localization which sequence is

**Accession N°**

*Betula pendula* **- 25.5±0.7**  *Corylus avellana* **- 29.1±0.8**

**Table 2.** Score of probability for nuclear distribution of profilins. Bold numbers indicate the average

The polymorphism of the profilin sequences concerning this motif is depicted in the table 3. Overall, micro-heterogeneities in this motif were identified for several sequences of olive,

**Probability of Nuclear Location (%)**

**- 34.8±3.3**  DQ138337 19.0±0.1 DQ138325 18.0±0.1 DQ117904 19.0±0.1

DQ663545 17.0±0.1

**- 27.8±1.5**  X77583 33.0±0.1 Y09546 32.0±0.1 Y09457 31.0±0.1 Y09458 32.0±0.1

**- 26.9±2.0**  X73279 32.0±0.1 X73280 35.0±0.1

*Olea europaea* L. are most likely localized in nucleus compared with the other species.

**Specie Sequence GenBank**

**Table 3.** Changes in the motif targeting to a nuclear localization of profilin sequences. Sequence of nuclear motif is characterized by the sequence RGKKGXGG(I/V)T(I/V)KKT, where X is the amino acid serine (**S**) in the majority of the analyzed sequences. The variable amino acids were highlighted in bold and red color.

#### *3.5.2. Experimental approach for profilin cellular localization*

The experimental approach for profilin localization was performed to determine whether there is really a differential distribution of profilin isoforms. Immuno-localization assays were performed by transmission electron microscopy (TEM) in ultrathin sections of germinated pollen grains of olive (cv. Picual) using different antisera: anti-Ole e 2 and anti-PRA (Figures 8 and 9), anti-ZmPRO3 (Figure 10), anti-ZmPRO4 (Figure 11), anti-ZmPRO5 (Figure 12).

All immune-localizations showed that profilins (gold particles) were preferentially located in the cytoplasm (Figures 8A and 9-12A), in addition to both nuclei of vegetative/generative cell (Figures 8A and 9A). Moreover, abundant gold grains were located in the pollen apertures (Figures 8C, 10C and 11C), in along the pollen wall, pollen tube and the pollen tip (Figures 8A and 9-12B), as well as in the material associated with the pollen grain exine (pollen coat) (Figures 8B, 11B and 12C). No significant number of labeling were found in the negative controls, for which were omitted the primary antiserum (Figure 9C). The overall number of gold grains in the sections was variable, and depending on the antiserum used.

Differential Immune-Reactivity and Subcellular Distribution Reveal

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 87

**Figure 8.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-Ole e 2 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls C) and the apertural region. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: material

adhered to the pollen walls (pollen coat). The bars represent 1 μm.

**Table 4.** Gold grains count for each antiserum used in this study. Measures corresponded to gold grains/μm2. Profilin counting values corresponding to the different subcellular localization were plotted. **C**= Cytoplasm; **PC**= Pollen Coat; **A**= Aperture; **NC**= Negative Control; **PGM**= Pollen Germination Media.

In order to determine differences in the gold grain distribution for the different antisera used as markers for profilin isoforms, we proceeded to count the gold particles present on each of the above mentioned compartments. The results of this quantitation are showed in the table 4. The most abundant immunolabeling was observed in sections incubated with individual antiserum following the next order: anti-ZmPRO3 > ZmPRO4 > ZmPRO5. Antisera anti-ZmPRO5 and ZmPRO3 showed a preferential cytoplasmic immunolocalization, whereas anti-PRA and anti-ZmPRO4 showed a preferential localization in the apertural regions of the pollen grain.

Differential Immune-Reactivity and Subcellular Distribution Reveal the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 87

86 Current Insights in Pollen Allergens

Germination Media.

**0**

**10**

**20**

**30**

**40**

**Number of gold grains /**

**μ**

**m2**

**50**

**60**

**70**

**80**

regions of the pollen grain.

**Antiserum Cytoplasm Pollen**

**Profilin distribution**

Anti-PRA 6.06±3.94 7.83±4.67 8.22±2.22 2.00±0.42 27.13±8.89 Anti-ZmPRO3 34.70±9.66 8.83±4.54 4.86±2.04 5.00±0.87 48.56±23.76 Anti-ZmPRO4 5.91±3.02 4.34±1.32 10.83±3.06 2.00±0.38 32.75±9.63 Anti-ZmPRO5 13.00±3.35 5.14±1.95 2.20±0.45 3.00±0.44 18.70±17.36

Anti-PRA

Anti-ZmPRO3 Anti-ZmPRO4 Anti-ZmPRO5

**Table 4.** Gold grains count for each antiserum used in this study. Measures corresponded to gold grains/μm2. Profilin counting values corresponding to the different subcellular localization were plotted. **C**= Cytoplasm; **PC**= Pollen Coat; **A**= Aperture; **NC**= Negative Control; **PGM**= Pollen

In order to determine differences in the gold grain distribution for the different antisera used as markers for profilin isoforms, we proceeded to count the gold particles present on each of the above mentioned compartments. The results of this quantitation are showed in the table 4. The most abundant immunolabeling was observed in sections incubated with individual antiserum following the next order: anti-ZmPRO3 > ZmPRO4 > ZmPRO5. Antisera anti-ZmPRO5 and ZmPRO3 showed a preferential cytoplasmic immunolocalization, whereas anti-PRA and anti-ZmPRO4 showed a preferential localization in the apertural

**C PC A NC PGM**

**Profilin cellular distribution**

**Coat Aperture Negative**

**Control**

**Pollen Germination Media**

**Figure 8.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-Ole e 2 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls C) and the apertural region. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: material adhered to the pollen walls (pollen coat). The bars represent 1 μm.

Differential Immune-Reactivity and Subcellular Distribution Reveal

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 89

**Figure 10.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-ZmPRO3 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls, and C) apertural region. The location of the gold particles is

highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: pollen coat.

The bars represent 1 μm.

**Figure 9.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-PRA antiserum. A) General view of the pollen tip, B) longitudinal section of a pollen tube, and C) negative control. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; Tp: pollen tube; V: vesicle, asterisks: pollen coat. The bars represent 1 μm.

**Figure 9.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-PRA antiserum. A) General view of the pollen tip, B) longitudinal section of a pollen tube, and C) negative control. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; Tp: pollen tube; V: vesicle,

asterisks: pollen coat. The bars represent 1 μm.

**Figure 10.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-ZmPRO3 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls, and C) apertural region. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: pollen coat. The bars represent 1 μm.

Differential Immune-Reactivity and Subcellular Distribution Reveal

the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 91

**Figure 12.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-ZmPRO5 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls, and C) apertural region. The location of the gold particles is

highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: pollen coat.

The bars represent 1 μm.

**Figure 11.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-ZmPRO4 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls, and C) apertural region. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: pollen coat. The bars represent 1 μm.

Differential Immune-Reactivity and Subcellular Distribution Reveal the Multifunctional Character of Profilin in Pollen as Major Effect of Sequences Polymorphism 91

The bars represent 1 μm.

**Figure 11.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-ZmPRO4 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls, and C) apertural region. The location of the gold particles is

highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: pollen coat.

**Figure 12.** TEM immune-localization of olive pollen profilin in sections of mature pollen (cv Picual) during in vitro germination by using anti-ZmPRO5 antiserum. A) General view of the vegetative cell cytoplasm, B) pollen grain walls, and C) apertural region. The location of the gold particles is highlighted with circles and arrows. Ap: apertures; CV: vegetative cell cytoplasm, Ex: exine, In: intine, M: mitochondria, N: nucleus, P: plastid, ER: endoplasmic reticulum; V: vesicle, asterisks: pollen coat. The bars represent 1 μm.

## **4. Discussion**