R Pérez Sánchez

B Jurado
email: jurado@cenbg.in2p3.fr

P Marini

M Aiche

S Czajkowski

D Denis-Petit

Q Ducasse

L Mathieu

I Tsekhanovich

A Henriques

V Méot

O Roig

Experimental set-up for the simultaneous measurement of fission and γ -emission probabilities induced by transfer or inelastic-scattering reactions

Keywords: Fission probabilities, γ-emission probabilities, Si telescopes, solar cells, C6D6 scintillators, Germanium detectors

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Understanding the de-excitation process of heavy nuclei at excitation energies of about 10 MeV is important both for fundamental nuclear physics and for the development of the reaction models used in nuclear astrophysics and in nuclear applications. In this excitationenergy range, an excited heavy nucleus decays via different competing channels: γ-ray emission, particle emission (e.g. neutrons or protons) and fission. The de-excitation process is ruled by fundamental properties of nuclei such as level densities, γ-ray strength functions, particle transmission coefficients and fission barriers. However, when no experimental data are available, the existing nuclear-structure models give very different predictions for these properties, which lead to discrepancies between the calculated cross sections as large as two orders of magnitude or more [1,2].

Fission probabilities induced by transfer and inelastic-scattering reactions with light projectile nuclei have been used since many years to explore the fission threshold and infer fissionbarrier parameters [3,4]. In particular, transfer-and inelastic-scattering-induced fission probabilities are the only way to obtain information on the fission barriers of fissile nuclei, i.e. nuclei whose fission barrier is lower than the neutron separation energy Sn. To constrain the other critical model parameters that rule the competition between fission, γ-ray emission and 2 particle emission, we have developed an experimental set-up that allows one to simultaneously measure fission and γ-emission probabilities. The latter measure the likelihood that the excited nucleus decays only by γ-ray emission. Since the sum of the probabilities of all open decay channels is 100%, the simultaneous measurement of fission and γ-emission probabilities gives also the possibility to constrain the parameters describing particle emission. In addition, the simultaneous measurement of decay probabilities is interesting because the data are collected and analysed under the same conditions, ensuring consistency between them and avoiding the sometimes difficult comparison of results from different experiments.

For measuring γ-emission probabilities, we need to detect the γ rays emitted by the nucleus that is excited by the reaction. This is challenging when the excited nucleus is fissionable because one has to disentangle the γ rays emitted by the decaying nucleus from those emitted in the de-excitation of the fission fragments. The measurement is most difficult for fissile nuclei where the contribution of γ rays emitted by the fission fragments is dominant over a large excitation-energy range. This work is structured as follows. In section 2 we describe the method used to infer the decay probabilities and identify the requirements that have to be fulfilled by our set-up. In section 3 we present the details of our experimental set-up and show some selected results, which demonstrate its performances in terms of detector response and efficiency. The conclusion and outlook are given in section 4.

Method to infer the decay probabilities

The decay probability P in the outgoing decay channel χ (fission or γ-emission) of the excited nucleus A* produced in the two-body reaction X(y,b)A* between a projectile y and a target X can be obtained as:

( *) ( *) ( *) ( *) C S N E P E N E E χ χ χ ε = ⋅ (1)
Here, N S (E*) is the so-called "singles spectrum", i.e. the total number of detected ejectiles b as a function of the excitation energy E* of the nucleus A*.

( *)

C N E χ is the "coincidence spectrum", corresponding to the number of ejectiles b detected in coincidence with the observable that identifies the decay mode, i.e. a fission fragment or a γ-ray cascade. εχ is the efficiency for detecting the exit-channel χ for the reactions in which the outgoing ejectile b is detected. The quantity N S (E*) corresponds to the total number of A* nuclei and The decay probabilities are measured at a given emission angle of the ejectile θeje. This is interesting because the populated angular momentum of the decaying nucleus A* depends on this angle. Therefore, the comparison of decay probabilities measured at different ejectile angles can help to study their angular-momentum dependence. This aspect is particularly relevant for studies on the surrogate-reaction method, whose aim is to use decay probabilities induced by transfer or inelastic scattering reactions to infer neutron-induced cross sections of short-lived nuclei that cannot be directly measured [5][6][7][8][9].

Subtraction of γ-ray background

As said above, the γ-emission probability Pγ measures the probability that the nucleus A* decays only through a γ-ray cascade. At excitation energies above Sn or the fission threshold, this probability rapidly decreases with excitation energy E*, because of the competition with the neutron-emission and/or the fission channels. Our aim is to measure the γ-emission probability up to typically E*=Sn + 1.5 MeV. To obtain Pγ, the measured γ-coincidence spectrum has to be corrected for two backgrounds: (i) the γ rays emitted by the nucleus (A-1)*, which is produced after the emission of one neutron by nucleus A* and (ii) the γ rays emitted by the fission fragments.

For a given excitation energy E* of nucleus A*, the γ rays emitted after neutron emission have a maximum possible energy E*-Sn. Therefore, to remove these γ rays we fill the γ-coincidence spectrum with events for which the measured γ-ray energy is above a threshold Eth equal to the maximum γ-ray energy, i.e. > Eth=E*-Sn. The γ-cascade detection efficiency is evaluated for each threshold. The validity of this subtraction procedure was demonstrated in [8].

The background of γ rays emitted by the fission fragments is removed by using the expression:

, , ( *) ( *) ( *) ( *) C f C C tot f N E N E N E E γ γ γ ε = - (2)
Here, C N γ is the final number of γ-ejectile coincidences needed to evaluate the γ-emission probability according to eq. ( 1), , C tot N γ is the total number of measured γ-ejectile coincidences after application of the Eth threshold, , C f N γ is the number of triple fission-fragment/γray/ejectile coincidences and εf is the fission detection efficiency. Thus, , C f N γ / εf is the number of detected γ-rays emitted by the fission fragments. More details on the correction of fission-fragment γ rays can be found in [9]. Determining the triple-coincidences spectrum , C f N γ implies having sufficiently high detection efficiencies, which is challenging. If one wants to limit the number of detectors used, as it is in our case, this requires a very compact geometry.

Let us emphasize that the γ-ray activity of the targets does not generate a background in C N γ because for the actinides we investigate most of the emitted γ-rays are well below our electronic threshold, which is a few hundred keV, and the few remaining γ-rays can easily be removed by selecting the coincidences with the ejectiles. Reactions on the target support and on light-element target impurities (e.g. oxygen) can, however, generate a background in the γcoincidence spectrum. We have shown in [8,9] that we can cope with this background by detecting the ejectiles at backward angles (see section 3.1).

Uncertainties

Our aim is to measure fission probabilities with relative uncertainties ΔPf/Pf < 10% and γemission probabilities with ΔPγ/Pγ < 25%. Our previous work has shown that with these uncertainties it is possible to fix model parameters [4] and to investigate the surrogatereaction method [6,8,9]. In refs. [4] and [9] we have performed a very thorough uncertainty analysis of the decay probabilities, taking into account the covariances between the different measured quantities. Using the equations developed in section G of [9], we can estimate the impact of the uncertainty in the detection efficiencies εf and on the measured decay probabilities. If we make the following assumptions:

-A relative statistical uncertainty of typically 1% in the determination of N S at a particular emission angle θeje and excitation energy E* -Decay probabilities Pf =Pγ=50% -A fission efficiency εf = 60% -A γ-cascade detection efficiency = 10% at the threshold energy Eth=E*-Sn

It results, that we have to determine εf with a relative uncertainty Δεf/εf = 5-10%, and with a relative uncertainty Δ / of 20%, in order to be able to determine the fission and γemission probabilities with a relative uncertainty of 5-10% and 23-25%, respectively. Therefore, we not only need the largest possible fission and γ-cascade detection efficiencies, we also need to know their values with sufficiently good precision.

Main set-up requirements

In the following we summarize the main requirements for the detectors composing our set-up:

-A particle telescope is needed to identify the ejectiles and determine their kinetic energy and emission angle. The latter quantities should be measured with a precision such that the corresponding E* resolution is of the order of 100 keV. This resolution is needed to investigate the rapid variation of the decay probabilities with increasing E* near the neutronemission and the fission thresholds.

-The fission detector should be located as close as possible to the target to maximize the fission efficiency. This implies that the detector should cope with very high rates of elastic scattered beam particles, which can damage the detector and generate pile-up signals that have to be discriminated from those of the fission fragments. In addition, it should have sufficiently good time resolution to make possible the selection of fission events detected in coincidence with the telescope and the γ-ray detectors. Last, it should be segmented in order to allow us to measure the angular distribution of the fission fragments, which has to be taken into account to determine the fission detection efficiency.

-The γ-ray detectors should allow detecting γ rays with energies up to 7-8 MeV (about 1.5 MeV above the Sn of the nuclei we want to investigate) and to discriminate γ rays from neutrons. They should also have sufficiently good timing properties to make possible the selection of coincidence events.

Experimental set-up

The upper part of figure 1 shows a drawing of the external view of the experimental set-up. A reaction chamber is surrounded by two types of γ-ray detectors: six high-purity germanium detectors and four C6D6 liquid scintillators. The target airlock, seen in the figure, is needed to isolate the radioactive targets or sources from the environment during the transportation from the target/source handling area to the experimental setup. The airlock is removable and has its own valve. In the handling area, the target is mounted on a target ladder, which is inserted into the airlock. The valve is then closed and the airlock is transported to the experimental area and fixed to the reaction chamber. The lower part of figure 1 shows a picture of the setup during a measurement at the tandem accelerator of the IPN of Orsay in France. The reaction chamber is operated at a pressure of about 10 -6 mbar, it houses the target, two position-sensitive particle telescopes (ΔE-E) and a fission detector made of solar cells. Our reaction chamber has three openings, two on the sides and one in the center. The central opening is located in the bottom of the chamber and serves to fix the airlock and insert the target ladder. The target ladder allows for three positions. One position is used for the actinide target, which has typical thicknesses ranging from 100 to 200 µg/cm 2 and is deposited on a target backing made of natural carbon of 40-100 µg/cm 2 . The target is placed in such a way that the beam goes first through the carbon backing and then through the target. A second position contains a 208 Pb target of 100 to 200 µg/cm 2 , which is used for calibration purposes, see below. In the last position we place a target backing alone. Measurements with the target backing are necessary to evaluate and subtract the background coming from reactions taking place on it, see [4,9]. The airlock includes a high-precision positioning system to place the center of the targets on the beam axis. The inner detectors are placed on either side of the target; they are fixed to the lateral chamber flanges. Figure 2 shows a drawing of the inner detectors together with their supports and the chamber flanges. The two telescopes are located upstream the target. The fission detector is divided in two parts located upstream and downstream the target, each part is composed of several solar cells. In the following sections we give the details of the different detectors composing our set-up.

Particle telescopes

Each telescope is composed of a thin ∆E detector, whose thickness varies between 100 and 300 μm depending on the experiment, followed by a 5 mm-thick Si(Li) E detector. The ΔE detectors are 16x16 channels double-sided silicon-strip detectors (DSSSD), with a surface of 5x5 cm 2 , manufactured by Micron Semiconductor Ltd [10]. As seen in figure 3, we have placed our telescopes at backward angles with respect to the beam direction. This is to minimize the contribution to the singles spectrum from reactions on the carbon backing and on light-element target contaminants. Due to two-body reaction kinematics, ejectiles from these parasitic reactions appear in the excitation-energy spectrum of the nucleus of interest A* at high excitation energies, thus leaving a large range of E* in the singles spectrum free of contaminant peaks. The telescopes are centered at 138° (polar angle θeje) with respect to the beam axis at a distance of 5.5 cm from the target, see figure 3. This was found to be the optimum position considering the available space. The covered polar angles range from 119 to 157° and the associated uncertainty (Δθeje, standard deviation) is about 2°. A 30 µm aluminum foil is placed in front of each ΔE detector to prevent fission fragments and the alpha particles emitted by the radioactive actinide targets to impinge on the Si detectors. The Al foils are biased to -300 V to repel δ electrons emerging from the target. As shown in figure 3, the E detector has a smaller surface (22.1 cm 2 ) than the ΔE detector and defines the geometrical efficiency. The sum of the geometrical efficiency of both telescopes is 8.3%. The efficiency of the two telescopes at a given ejectile angle θeje ± Δθeje is ~ 0.6%, which is sufficient to measure the number of single events with a relative statistical uncertainty of ~1%, as discussed in section 2. Indeed, the cross sections of the reactions that we plan to investigate are of the order of 0.1 mb at backward angles, the beam intensity is about 10-20 enA and the measurement time is typically one week. Our data acquisition system is triggered when a particle is detected by the ΔE and E detectors of one of the telescopes. The trigger rate varies from a few tens to a few hundred events per second, depending on the reaction. Hence, the dead-time effects are very small. In any case, the dead time of the acquisition system is the same for the single and the coincidence events. Therefore, it cancels in the ratio of eq. ( 1) and does not have to be determined. The measurement of the ejectile kinetic energy is crucial for the determination of the E* of the excited nucleus A*. In our experiments, each ΔE strip and the corresponding portion of the E detector are individually calibrated using reactions on 208 Pb. We typically use the 208 Pb target and 3 He or 4 He beams to populate the first states of 209 Bi*, 207 Pb* and 208 Pb* via the 208 Pb( 3 He,d) 209 Bi*, 208 Pb( 3 He, 4 He) 207 Pb* and 208 Pb( 4 He, 4 He') 208 Pb* reactions, respectively. The E* of these states is known with high accuracy and the associated kinetic energies of the ejectiles fall in the range of interest for the measurement. The upper part of figure 4 shows a two-dimensional spectrum representing the energy loss ΔE and the residual energy E of the ejectiles measured by one of the strips of our telescopes for the 3 He + 208 Pb reaction at 24 MeV incident beam energy. The first states of 207 Pb and 209 Bi used for the calibration are indicated. More details on the calibration procedure can be found in [4]. Similar identification plots as the upper panel of figure 4 are obtained with the actinide targets. However, due to the larger level density of actinides, the first excited states cannot generally be well distinguished.

The lower part of figure 4 shows the number of alpha ejectiles as a function of the E* of 207 Pb, or in other words, the singles spectrum of 207 Pb*. The root-mean-square (RMS) deviation of the peaks corresponding to the first excited states gives the excitation-energy resolution of our measurements, which ranges between 50 and 100 keV, depending on the experiment. This resolution includes the beam-energy resolution, the energy straggling due to the passage of the ejectiles through different dead layers (target, target backing and Al foil), the variation of the ejectile kinetic energy with θeje within the telescope strip, as well as the intrinsic resolution of the ΔE and E detectors. The obtained excitation-energy resolution is well suited to study the rapid variations of the fission and the γ-emission probabilities at the fission or the particle-emission thresholds.

The fission detector

Solar cells, the devices that are routinely used to convert the energy of sunlight into electricity, represent a particularly interesting option for the detection of fission fragments in our experiments. They were first proposed as fission detectors by Siegert [11], and have been used as fission detectors within large γ-detector arrays as Euroball [START_REF] Theisen | Proceedings of the Second International Workshop on Nuclear Fission and Fission-Product Spectroscopy[END_REF]. The CENBG collaboration has many years of experience using them for the measurement of fission probabilities [4,6,[START_REF] Petit | [END_REF].

The thickness of solar cells varies between 300-500 µm but their depletion depth is less than 1 µm, hence very small, and it cannot be increased by applying a bias voltage because this increases the electronic noise, due to their very low resistivity of a few Ω•cm. The very small depletion depth leads to a very large capacitance, of the order of 40 nF/cm 2 . To obtain good timing performances with such a high capacitance we use specially designed, current-mode preamplifiers [START_REF] Theisen | Proceedings of the Second International Workshop on Nuclear Fission and Fission-Product Spectroscopy[END_REF]. The typical time resolution that can be obtained is of a few ns, which makes these detectors well suited for coincidence measurements.

Because of the very thin depletion depth, most of the energy deposition occurs in the neutral substrate. The charge collection in the cell is possible thanks to the "funneling" mechanism [14,15], where the high density of ionization produced along the fragment track locally changes the depletion region into a funnel-like shape extending to the substrate and enclosing the track. This enables the collection of a significant part of the charge produced by the fission fragments via ionization. The funneling efficiency strongly depends on the ionization density profile and it is very small for light particles. Therefore, the response of the cells to light nuclei falls into the detector noise and gives a very impressive pile-up suppression in the fission-fragment region. For this reason, solar cells are much better suited than Si detectors to investigate fission events in the presence of a high background of light charged particles. As mentioned in section 2, this is exactly the situation of our measurements, where the cells are located near the target and are subject to a strong flux of elastic scattered projectile nuclei. Figure 5 shows the spectrum of fission fragments measured by one solar cell in coincidence with the telescopes for the 238 U( 3 He,d) 239 Np* reaction. As we can see, the spectrum is not polluted by random coincidences with the elastic scattered beam. Moreover, the doublehumped structure due to the different kinetic energies of the light and heavy fission fragments can be clearly distinguished, reflecting the fairly good energy resolution of solar cells. For comparison, figure 4 of ref. [16] shows the fission-fragment energy spectrum measured with a Si detector for the 238 U( 3 He,p) 240 Np* reaction at 29 MeV incident energy. The spectrum is polluted by a very intense peak produced by light ions, which clearly overlaps with fission events of low kinetic energies. Also, the separation between heavy and light fission fragments is less pronounced than in our spectrum in figure 5, probably due to the deterioration of the energy resolution caused by radiation damage effects. Indeed, an additional advantage is that solar cells are much more resistant to radiation damage than Si detectors [17,18]. In [19], we investigated the neutron-induced fission of 240 Pu and 242 Pu target nuclei using solar cells. The cells were subjected during one week to a very intense flux of alpha particles emitted by the Pu target samples. A rate of alpha particles on the cells of 75 kHz only led to a weak performance degradation (see figure 4 in ref [19]). Our aim is to use the present set-up with a 240 Pu target of 100 µg/cm 2 thickness and 9 mm diameter, corresponding to an alpha activity of 534 kBq. The geometry of our fission detector (see below) is such that the rate of alpha particles on the individual cells will vary between 2.7 and 48 kHz, which is well below the 75 kHz mentioned above. Therefore, no performance degradation is expected from the alpha radioactivity of the 240 Pu target. Solar cells are also very cost effective and robust. They can be cut into different shapes without showing any deterioration and are thus very well suited to build position-sensitive fission detectors within a very compact geometry. The conducting grid on the surface, which is generally made of very thin silver wires, reduces the sensitive area of the cells because fission fragments are stopped by these wires. The intrinsic efficiency of the cells we use is typically 95%. One can determine the intrinsic efficiency by calculating the ratio of the spontaneous-fission activity of a 252 Cf source measured with the solar cell and with a Passivated Implanted Planar Silicon (PIPS) detector [20], which has no grid and therefore 100% intrinsic efficiency. As shown in figure 6, the fission detector is made of two parts placed upstream and downstream the target. Each part has several detector planes of 40 mm length and 20 mm width each. The downstream part is placed at (6.0 ± 0.4) mm from the target. The distance from the target along the beam axis of the upstream part is (7.5 ± 0.4) mm. We can see in the lower part of figure 7 that the downstream part has the shape of a regular pentagonal prism. The distance from each plane to the beam axis is (12.6 ± 0.3) mm. This distance was chosen to avoid very forward angles where the flux of elastically scattered beam particles is too intense, even for radiation-resistant detectors such as solar cells. Each detector plane is composed of two cells. The length of the two cells composing each side of the prism varies from side to side, i.e. two sides have two cells of (19.5 ± 0.5) mm each, two other sides two cells of (9.5 ± 0.5) and (29.5 ± 0.5) mm, and the remaining side two cells of (29.5 ± 0.5) and (9.5 ± 0.5) mm. With this segmentation we can detect fission fragments at different polar angles θf ranging from 15 to 65°. The upstream part is made of six solar cells located on three planes, see upper panel in figure 7. The distances to the beam axis of the upper and lower detector planes are (28 ± 0.2) and (19.5 ± 0.2) mm, respectively. These distances were chosen to prevent that the cells overshadow the Si telescopes. This geometry leads to an angular coverage θf =110 to 155°. Therefore, with the described segmentation it is possible to measure the fission-fragment angular distribution at forward and backward polar angles. The angular resolution (Δθf, standard deviation) depends on the size of the cells and varies from 8° for the smallest to 30° for the largest cells.

Fission efficiency

As described above, to obtain the fission and the γ-emission probabilities it is necessary to determine the fission efficiency with good precision. The fission efficiency εf is given by the geometrical efficiency of the fission detector, by the intrinsic efficiency of the solar cells and by the angular anisotropy of the fission fragments. The latter depends on two factors: (i) the angular distribution of the fission fragments in the center of mass reference system, which is determined by the angular-momentum distribution of the fissioning nucleus, and (ii) the kinematical focusing of the fission fragments in the direction of the fissioning nucleus, which depends on the velocity of the fissioning nucleus. We determine the geometrical efficiency with a 252 Cf source of known activity. A Monte-Carlo simulation allows us to include the angular anisotropy effects and infer the "effective" fission efficiency εf. The geometrical description of the fission detector included in the simulation is validated with the data obtained with the 252 Cf source. The fission-fragment angular distribution in the center of mass W(θf,cm), where θf,cm is the polar angle of the fragments with respect to the recoiling fissioning nucleus, is obtained by counting the number of fission fragments detected by each cell and dividing this number by the solid angle of the corresponding cell. This solid angle includes the variations due to kinematical effects (e.g. cells that are placed in the direction of the fissioning nucleus detect more fragments) and is determined, together with θf,cm, via the Monte-Carlo simulation. The experimental angular correlations obtained with our set-up are generally found to be consistent with the form W(θf,cm)=a•cos 2 (θf,cm)+b, whose parameters a and b are determined by a fit to the measured angular distribution. The coefficients for higherorder terms of cos(θf,cm) are very small and do not have a noticeable impact on the quality of the fits. The function W(θf,cm) is finally inserted into the Monte-Carlo simulation to obtain the effective fission efficiency εf. For more details on the determination of the fission efficiency see [4].

We have used our set-up to investigate the 240 Pu( 4 He, 4 He') 240 Pu* inelastic scattering reaction at an incident beam energy of 30 MeV. This reaction represents very well the type of reactions we want to study with our set-up. We measured an angular anisotropy of the fission fragments of W(θf,cm =0°)/W(θf,cm =90°) = 2.28 ± 0.32 at an excitation energy of 240 Pu of 6.5 MeV and a recoil angle of 240 Pu of 19° (corresponding to a kinetic energy of 240 Pu of 1.5 MeV). This anisotropy value is in good agreement with previous results reported in [21]. Our Monte-Carlo simulation shows that when this angular anisotropy is included, the fission efficiency increases from (55.5±4.2)% to an effective fission efficiency εf = (61.1±5.6)%. The final uncertainty in the effective fission efficiency is dominated by the uncertainties in the geometry. The obtained efficiency and the relative uncertainty Δεf/εf are very close to the reference values given in section 2, implying that with the described set-up it is possible to measure Pf(θeje) with a relative uncertainty of 10%.

The γ-ray detection systems

As described above, we use two arrays with two different types of γ-ray detectors, four liquid scintillators filled with purified deuterated benzene (C6D6) and six high-purity germanium detectors. Figure 8 shows the geometrical arrangement of the detectors. The upper panel shows that the central axes of the C6D6 detectors are included in the plane containing the target. The central axes of the germanium detectors are tilted 45° with respect to this plane. The lower panel shows the angles between adjacent detectors. The distance of the C6D6 and Ge detectors from the target is 93 and 130 mm, respectively.

One of the main factors that determined our choice for the γ-ray detectors is the presence of neutrons coming from the de-excitation of the heavy decaying nucleus or from the fission fragments. C6D6 detectors are an alternative to the very usual, non deuterated variety NE-213 liquid scintillators. The replacement of hydrogen by deuterium in the scintillation liquid strongly suppresses γ-rays originating from neutron captures inside the detector itself. Another important advantage of these detectors in the context of our experiments is their ability to provide neutron/γ-ray discrimination via the pulse-shape analysis technique. Thanks to this, events originating from the interaction of neutrons with the scintillation material can be removed from the measured coincidence spectra. All this makes C6D6 detectors very well adapted for counting γ-rays with energies up to 7 or 8 MeV in coincidence with the Si telescopes. However, the response function of the C6D6 detectors is dominated by Compton events and extends from the electronic threshold (in our case about 250 keV) up to the Compton edge, see figure 9. Therefore, C6D6 detectors are not well suited for accurately measuring the energy of the emitted γ rays. Germanium detectors have a much better energy resolution than C6D6 detectors (see figure 9). They can be used to measure low-lying γ-ray transition intensities and determine the probabilities for observing specific γ-ray transitions as a function of the excitation energy of the decaying nucleus. As shown recently in [22], this is another valuable observable to constrain models describing the de-excitation process. However, we also want to use the Ge detectors to count γ rays and infer the γ-emission probability. For this reason, we have duplicated the output signals of the Ge detectors. One of the output signals goes to a spectroscopic amplifier with a gain such that the maximum acceptable amplitude of our amplitude-to-digital convertor corresponds to a γ-ray energy of 2 MeV. The other output signal goes to another spectroscopic amplifier with a much lower gain leading to a maximum treatable γ-ray energy of 8 MeV. The high-gain signals are used to study specific transitions, while the low-gain signals are used to infer the γ-emission probabilities. In the case of highgain signals only the photoelectric component of the measured γ-ray spectrum is considered, whereas in the case of low-gain signals we consider the entire spectrum. It should be noted that pulse-shape discrimination is not possible with Ge detectors. However, for fissile nuclei the neutrons emitted by the fission fragments can be removed by the subtraction of the triple coincidences (see section 2) below Sn, provided that the time window selecting the telescope-Ge coincidences is sufficiently large to include the fission neutrons. In this case, the γemission probabilities obtained with Ge detectors below Sn are not contaminated by events coming from the interaction of neutrons with the germanium. From the comparison of the telescope-Ge time spectra measured at E* below and above the onset of fission of 240 Pu*, we deduce that the background of fission neutrons is distributed within a time window of 35 ns and represents less than 14% of the detected events.

The γ-cascade detection efficiency

Our γ detector array has a small solid angle and we generally detect only one γ ray of the cascade, in the very few cases where more than one γ ray of the same cascade is detected, we randomly select one of the γ events to fill the coincidence and γ-ray energy spectra. This way, the number of coincidences corresponds to the number of detected γ-ray cascades. To determine the efficiency for detecting a γ-ray cascade, we use the EXtrapolated Efficiency Method (EXEM) that we developed in [23]. In transfer or in inelastic scattering reactions, it is possible to populate excitation energies below the limiting excitation energy, * , where the only possible de-excitation mode is γ-ray emission. Above * , fission and particle emission start to compete with γ-ray emission. Therefore, for excitation energies below * the γemission probability Pγ = 1 and, according to eq. ( 1), the γ-cascade detection efficiency, (E*), can be directly obtained from the ratio between the γ-coincidence and the singles spectra. The EXEM assumes that the measured dependence of the γ-cascade detection efficiency on E* below * can be extrapolated to excitation energies above * . We demonstrated the validity of this assumption in [23,24]. As discussed in section 2.1, a threshold on the γ energy (Eth) is applied to eliminate γ-rays emitted after neutron emission. The γ-cascade detection efficiency is determined for each Eth from the ratio of the corresponding γ-coincidence and singles spectra. Figure 10 shows the ratio of the γ-coincidence and singles spectra obtained with the C6D6, the Ge detectors and the sum of all the γ-ray detectors for Eth = 266 keV. The data were measured for the 240 Pu( 4 He, 4 He') 240 Pu* inelastic scattering reaction. We can see that all the curves increase with excitation energy up to about 4.5 MeV, above this energy the curves decrease because fission sets in. Indeed, the fission threshold of 240 Pu is significantly lower than its neutron separation energy Sn=6.5 MeV. Therefore, to determine (E*) we fit the data from E*=2 to 4 MeV with a linear function (red dashed lines in figure 10) and take the values of the fit function evaluated at E* above the fission threshold of 4.5 MeV (blue dashed lines). The uncertainty on is obtained from the uncertainties on the fit parameters. The resulting uncertainty range includes the values of obtained when varying the lower and upper limits of the E* interval used in the fit by ±400 keV. For the Ge array, the γ-cascade detection efficiency increases from a value of about (4.8 ± 1.4)%, near 4.5 MeV, to about (7.7 ± 2.1)% at E*=7.5 MeV. The efficiency of the C6D6 array is somewhat larger, varying from nearly (6.0 ± 1.7)% at 4.5 MeV to (9.7 ± 2.3)% at 7.5 MeV. The efficiency of the ensemble of detectors is essentially the sum of the efficiencies of each type of array, it increases from (10.5 ± 2.4)% near 4.5 MeV to (17.9 ± 3.2)% at 7.5 MeV. This feature shows the interest of using also the Ge detectors for counting γ-ray cascades. This will allow us to measure the γ-emission probability between the fission threshold and Sn with efficiencies of the order of 14%.

The efficiencies and the associated relative uncertainties Δ / obtained with the C6D6 detectors and with the ensemble of the detectors imply that the γ-emission probabilities can be measured with a relative uncertainty ranging from 24 to 29%. Note that these uncertainties are related to the γ-emission probabilities measured at a particular ejectile angle Pγ(θeje) with the assumptions listed in section 2.2 (ΔNs/Ns=1% and Pf=Pγ=50%). The expected uncertainties are sufficient to constrain model parameters and investigate the surrogate-reaction method [25]. If the differences between the values of Pγ(θeje) measured at different angles are not significant, the corresponding γ-emission probabilities can be averaged, which will reduce the statistical error and thus the final uncertainty.

Conclusions and outlook

We have presented a set-up for the simultaneous measurement of fission and γ-emission probabilities induced by transfer and inelastic scattering reactions of light projectile nuclei impinging on heavy target nuclei. Our setup is composed of two position-sensitive Si telescopes to identify the ejectiles and measure their kinetic energies and emission angles. Fission fragments are detected in coincidence with the ejectiles by means of a segmented fission detector made of 16 solar cells. Solar cells are very well adapted for our measurements because they can be arranged in very compact geometries and are rather insensitive to the scattered beam particles. Two arrays of γ-ray detectors allow us to count the number of γ-ray cascades measured in coincidence with the ejectiles. One array is made of four C6D6 liquid scintillators and the other of six high-purity germanium detectors. Both arrays are used to count γ rays with energies ranging from the electronic threshold to 7-8 MeV. With this set-up we obtain a geometrical efficiency for the Si telescopes of about 8%, a fission efficiency of nearly 61% and a γ-cascade detection efficiency ranging from 6 to 16%, depending on the excitation energy and the detectors used. We have shown that our set-up fulfills the demanding requirements in terms of detection efficiencies necessary to remove the background of γ-rays emitted by the fission fragments and to determine the decay probabilities at various ejectile angles with fairly good precision, about 10% relative uncertainty for the fission probability and between 24 and 29% for the γ-emission probability.

The decay probabilities measured in the experiments carried out with a 3 He beam incident on a 238 U target, and with 4 He and 3 He beams on 240 Pu will be presented in future publications. We also foresee other measurements with the described set-up and 242,244 Pu targets. These future measurements will allow us to provide unique data on the competition between fission and γ emission below the neutron-emission threshold of other fissile nuclei produced by inelastic reactions such as 242 Pu* or 244 Pu*.

  the number of A* nuclei that have decayed via channel χ.The excitation energy E* is determined by measuring the emission angle θeje and the kinetic energy of the ejectiles b, and by applying energy and linear-momentum conservation laws.

Figure 1 :

 1 Figure 1: (Top) Drawing of the external view of the set-up performed with Computer-Aided Design (CAD) software. (Bottom) Picture of the set-up (side view) during a measurement at the Tandem accelerator of the IPN of Orsay, France. The picture also shows the supporting frame holding the reaction chamber and the γ-ray detectors.

Figure 2 :

 2 Figure 2: CAD drawings of the interior of the vacuum reaction chamber. The detectors located upstream and downstream the target are shown in the upper and the bottom panel, respectively, along with their supports, which are fixed to the chamber flanges.

Figure 3 :

 3 Figure 3: Schematic top view of the geometry of the two telescopes.

Figure 4 :

 4 Figure 4: (Top) Energy loss ΔE versus residual energy E of ejectiles measured by one strip of our Si telescopes for the 3 He + 208 Pb reaction at 24 MeV. The different ejectiles are indicated, the arrows show the states used for the energy calibration of the telescopes. (Bottom) Number of detected alpha particles as a function of the E* of 207 Pb*, the measured average excitation energy in MeV of each state of 207 Pb* is given together with the root mean square (RMS) deviation.

Figure 5 :

 5 Figure 5: Energy spectrum of fission fragments detected in one solar cell in coincidence with deuterons detected in the telescopes for the 238 U( 3 He,d) 239 Np* reaction at 24 MeV incident energy.

Figure 6 :

 6 Figure 6: Schematic side view of the geometry of the fission detector. Only some of the detector planes are visible.

Figure 7 :

 7 Figure 7: Details of the fission detector. The beam is represented by the black arrow. The solar cells are indicated in blue. (Top) Part of the fission detector placed upstream the target. This part is made of three detector planes including six solar cells of various sizes. The Si telescopes are also shown for completeness. (Bottom) Part of the fission detector located downstream the target; it is composed of five detector planes including ten solar cells. The different cell sizes can be observed. The supports of the detector planes are also shown.

Figure 8 :

 8 Figure 8: Geometrical arrangement of the γ-ray detectors. (Top) Top view of the detector arrays. The angle between the plane containing the central axes of the C6D6 detectors and the Ge detectors is given. (Bottom) Front view of the detector arrays. The angle between adjacent C6D6 and adjacent Ge detectors is indicated.

Figure 9 :

 9 Figure 9: Spectra of a 60 Co source measured with a C6D6 (top) and with a Ge (bottom) detector, the energies of the emitted γ rays are indicated.

Figure 10 :

 10 Figure 10: Ratio of the γ-coincidence ( >266keV) and the singles spectra as a function of the excitation energy of 240 Pu measured at θeje = 145° for the 240 Pu( 4 He, 4 He') 240 Pu* reaction. The histograms obtained with the coincidences measured by the Ge, the C6D6 and the sum of all the detectors are represented in red, blue and black, respectively. The vertical dotted line represents the neutron separation energy Sn of 240 Pu. The red dashed lines are linear fit functions adjusted to the data and the blue dashed lines are the extrapolation of the fitted functions to higher excitation energies.

Acknowledgements

This work was supported by the French "Defi Interdisciplinaire" NEEDS of the CNRS, by the University of Bordeaux and by the European Commission within the 7 th Framework Program through CHANDA (Project No 605203).


N Tazetta Ameneh Tarakeme

Majid Azizi
email: azizi@um.ac.ir

Vahid Rowshan

Hassan Salehi

Rosella Spina

François Dupire

Hossein Arouie

Dominique Laurain-Mattar
email: dominique.mattar@univ-lorraine.fr

Screening of Amaryllidaceae alkaloids in bulbs and tissue cultures of Narcissus papyraceus and four varieties of

Keywords: Galanthamine, lycorine, Narcissus, auxins, GC-MS, LC-MS

Narcissus spp. are an economically important crop for medicines in relation with the alkaloids production, mainly galanthamine, an acetylcholinesterase inhibitor used for the treatment of Alzheimer's disease. In this article an extensively study of the phytochemistry of both bulbs of different species and varieties of Narcissus grown in Iran and in vitro culture of these plants was investigated. In particular, the Amaryllidaceae alkaloid profile and the galanthamine and lycorine contents in wild bulbs of Narcissus papyraceus (G5) and four varieties of Narcissus

Introduction

Various species of Narcissus, bulbous flowering plants belonging to the Amaryllidaceae family, are known to synthesize Amaryllidaceae alkaloids. There is a growing interest for these plants due to the medicinal use of one of the major alkaloids in this genus, galanthamine. The register of the Royal Horticultural Society International lists more than 26,400 named daffodil varieties.

From N. pseudonarcissus, Gerrard in 1877 isolated lycorine, the first Amaryllidaceae alkaloids [START_REF] Bastida | Narcissus alkaloid[END_REF]. Several studies have been published about the distribution of galanthamine in different populations of these plants as well as in their different organs and during different periods of harvesting [START_REF] López | Galanthamine Pattern in Narcissus confusus Plants[END_REF]. Galanthamine is a long-acting, selective, reversible and competitive acetylcholinesterase (AChE) inhibitor, which is used in the world to treat the patients with mild to moderate Alzheimer's disease. Great interest in Narcissus species and varieties has risen as an industrial source for the production of galanthamine, because of its use as medicine.

Narcissus bulbs are considered one of the most important natural sources of galanthamine other than synthetic production. Besides galanthamine, there are a number of other alkaloids found in Narcissus such as lycorine, lycorenine, homolycorine, haemanthamine, narciclasine and tazettine [START_REF] Bastida | Chemical and biological aspects of Narcissus alkaloids[END_REF][START_REF] Rønsted | Phylogenetic selection of Narcissus species for drug discovery[END_REF]. Some studies have shown that these alkaloids also possess some interesting biological activities such as antimalarial [START_REF] Jin | Amaryllidaceae and Sceletium alkaloids[END_REF], antiviral, antitumor [START_REF] Fennell | Crinum species in traditional and modern medicine[END_REF][START_REF] Mcnulty | Structure-activity studies on the lycorine pharmacophore: A potent inducer of apoptosis in human leukemia cells[END_REF], antifungal [START_REF] Del Giudice | Interaction between yeast mitochondrial and nuclear genomes: Null alleles of RTG genes affect resistance to the alkaloid lycorine in rho0 petites of Saccharomyces cerevisiae[END_REF] and insect anti-feedant activity [START_REF] Evidente | Further experiments on structure-activity relationships among the lycorine alkaloids[END_REF]. Some species like N. confusus, N. pseudonarcissus, N. tazetta, N. poeticus, N. broussonetii, N. serotinus, N. asturiensis, N. jonquilla and different cultivars of Narcissus have been studied for their alkaloid content [START_REF] López | Galanthamine Pattern in Narcissus confusus Plants[END_REF][START_REF] Bastida | Chemical and biological aspects of Narcissus alkaloids[END_REF][START_REF] Lubbe | Seasonal accumulation of major alkaloids in organs of pharmaceutical crop Narcissus Carlton[END_REF][START_REF] Khonakdari | Quantification of galantamine in Narcissus tazetta and Galanthus nivalis (Amaryllidaceae) populations growing wild in Iran[END_REF][START_REF] Šafratová | Alkaloids from Narcissus poeticus cv. Pink Parasol of various structural types and their biological activity[END_REF][START_REF] De Andrade | Bioactive alkaloid extracts from Narcissus broussonetii: mass spectral studies[END_REF][START_REF] Gotti | Analysis of Amaryllidaceae alkaloids from Narcissus by GC-MS and capillary electrophoresis[END_REF][START_REF] Pigni | Alkaloids from Narcissus serotinus[END_REF][START_REF] Viladomat | Alkaloids from Narcissus asturiensis[END_REF][START_REF] Masi | Jonquailine, a new pretazettine-type alkaloid isolated from Narcissus jonquilla quail, with activity against drug-resistant cancer[END_REF][START_REF] Moraes-Cerdeira | Evaluation of four Narcissus Cultivars as Potential Sources for Galanthamine Production[END_REF]. However to our knowledge, no investigation was reported on Amaryllidaceae alkaloids diversity and accumulation in Narcissus papyraceus as well as in various varieties of N. tazetta (N. tazetta var. Shastpar, N. tazetta var. Meskin, N. tazetta var.

Panjehgorbei and N. tazetta var. Shahla), growing wild populations in Iran.

The aim of this study was to investigate both the Amaryllidaceae alkaloid profiles and galanthamine and lycorine contents of bulbs of N. papyraceus and four varieties of N. tazetta wild plants using GC-MS and LC-MS. GC-MS is a useful and reliable method for rapid separation and identification of complex mixtures of Amaryllidaceae alkaloids [START_REF] Shawky | HPTLC and GC/MS study of Amaryllidaceae alkaloids of two Narcissus species[END_REF][START_REF] Ptak | LCMS and GCMS for the Screening of Alkaloids in Natural and in Vitro Extracts of Leucojum aestivum[END_REF]. Due to the complexity of the extracts, one single analytical method is generally insufficient to identify all alkaloids. It is for this reason that the use of another analytical instrument, LC-MS, was necessary to obtain truly comprehensive informations. Also in this work, we combined various parameters which have previously shown positive effects on alkaloid accumulation in tissue cultures of Leucojum aestivum, i.e. differentiated tissues such as bulblets induced by auxins and feeding with the common precursor 4'-O-methylnorbelladine (MN) of Amaryllidaceae alkaloids [21,[START_REF] Saliba | Stimulating effect of both 4'-O-methylnorbelladine feeding and temporary immersion conditions on galanthamine and lycorine production by Leucojum aestivum L. bulblets[END_REF]. The level of the alkaloid biosynthesis is strongly influenced by cellular differentiation which may be influenced by growth regulators like auxins [START_REF] Tahchy | Effects of sucrose and plant growth regulators on acetylcholinesterase inhibitory activity of alkaloids accumulated in shoot cultures of Amaryllidaceae[END_REF][START_REF] Ivanov | Alkaloid patterns in Leucojum aestivum shoot culture cultivated at temporary immersion conditions[END_REF]. Also, we reported the metabolization of the deuterium-labeled precursor, by L. aestivum shoot cultures and its stimulating effect on galanthamine and lycorine biosynthesis [START_REF] Tahchy | New method for the study of Amaryllidaceae alkaloid biosynthesis using biotransformation of deuterium-labeled precursor in tissue cultures[END_REF]. Therefore, the biosynthetic pathway in these Iranian various varieties of Narcissus was estimated for the first time under the influence of various auxins and the Amaryllidaceae alkaloids precursor MN. Thin slices of leaves (about 3 -5 mm) isolated from N. tazetta var. Meskin (G2) and N. tazetta var. Shahla (G4) bulbs chilled at 4°C for 8 weeks were used as initial explants. Plant material was surface-sterilized in 70% ethanol (30 seconds), then shaken for 10 minutes in a solution of Domestos®: water (50 mL: 250 mL, v: v) [START_REF] Tahchy | New method for the study of Amaryllidaceae alkaloid biosynthesis using biotransformation of deuterium-labeled precursor in tissue cultures[END_REF] and rinsed three times in sterilized water containing 0.03% of NaClO [START_REF] Askari | In tissue culture of Lilium explants may become heavily contaminated by the standard initiation procedure[END_REF].

Materials and methods

Plant Materials

Bulbs

Callus initiation and bulblets induction

Initial explants were cultivated on the Murashige and Skoog (MS) [START_REF] Murashige | A revised medium for rapid growth and bioassays with tobacco cultures[END_REF] medium supplemented with various auxins (2,4-D, Picloram or NAA) at different concentrations (25 μM and 50 μM) and the cytokinin 6-benzylaminopurine (BAP) (0.5 μM). The MS medium was supplemented with 3% sucrose and gelling with 0.8% agar. The pH was adjusted to 5.5 before autoclaving.

The cultures were maintained at 25 ± 2°C under dark conditions and subcultured every 4 weeks.

Treatments were arranged in a completely randomized 2×3×2 factorial design with five replications. Analysis of variance was performed using the SAS software and means were compared using LSD's test (p ≤ 0.05). Six-month-old cultures (2g) were submerged in MS liquid-shake medium (20 mL) containing BAP (4 μM) and 2,4-D (10 μM) and precursor 4'-Omethylnorbelladine at various concentrations (0.05 and 0.15 g/L) in 100 ml Erlenmeyer. They were incubated at 25 ± 2°C and 150 rpm using the Infors Ecotron Ht Model Shaking Incubator for two periods of time (10 and 20 days). A stock solution for feeding experiments was prepared and was filter-sterilized directly into the flasks as reported by Saliba et al. [START_REF] Saliba | Stimulating effect of both 4'-O-methylnorbelladine feeding and temporary immersion conditions on galanthamine and lycorine production by Leucojum aestivum L. bulblets[END_REF].

Chemicals and reagents

All commercially available reagents were used without further purification. Triethylammonium acetate buffer, galanthamine, lycorine, BAP, Picloram, 2,4-D, inositol, agar-agar, magnesium sulphate heptahydrate (98%), manganese sulphate, potassium nitrate, and ethylene diamine tetra acetic acid iron (III) sodium salt were all from Sigma-Aldrich. Ammonium bicarbonate, ammonium formate, iron sulphate, zinc sulphate, copper(II)sulphate pentahydrate (99%), thiamine hydrochloride, NAA, absolute ethanol, and methanol (Hipersolv Chromanorum for HPLC -Isocratic Grade) were purchased from VWR international. Acetonitrile was acquired from Sigma-Aldrich. Pyridoxol hydrochloride, nicotinic acid, potassium dihydrogenophosphate and calcium chloride dehydrate were obtained from Merck AG Darmstadt (Germany).

Synthesis of the precursor

The precursor MN was synthesized according to Saliba et al. [START_REF] Saliba | Stimulating effect of both 4'-O-methylnorbelladine feeding and temporary immersion conditions on galanthamine and lycorine production by Leucojum aestivum L. bulblets[END_REF].

Alkaloid extraction

Alkaloids were extracted from plant material as previously described [START_REF] Tahchy | New method for the study of Amaryllidaceae alkaloid biosynthesis using biotransformation of deuterium-labeled precursor in tissue cultures[END_REF]. Methanolic crude extracts were purified by SPE procedure as reported by Saliba et al. [START_REF] Saliba | Stimulating effect of both 4'-O-methylnorbelladine feeding and temporary immersion conditions on galanthamine and lycorine production by Leucojum aestivum L. bulblets[END_REF].

GC-MS identification

Analyses were performed using QP2010-Shimadzu equipment operating in the EI mode at 70 eV. A agilent DB5MS column (30 m × 0.25 mm × 0.25 μm) was employed with a 29 min temperature program of 190-320 °C at 5 °C/min. The injector temperature was 280 °C, the flow rate of the carrier gas (helium) was 1 mL/min, and the split ratio was 1:5. The identification of the alkaloids was performed by comparing the measured data with those of authentic compounds (galanthamine, lycorine) or with literature data as specified in the text. An internal standard calibration method along with a nine-point calibration curve (R 2 =0.99) using authentic galanthamine and lycorine were used for quantitative analysis of alkaloids.

LC-MS analysis

The LC system consisted of an U3000-Dionex apparatus with an injector comprising a 1 µL loop and a UV detector at 280 nm. The analytical column used was an Acclaim MIXED MODE HILIC-1 ID 2.1 mm column (150 mm x 5 µm x 120 Å) and eluted at a flow rate of 200 µL/min using a gradient ranging from 2% solvent B to 25% solvent B in a time span of 26 min and 30 sec. Solvent A consisted of pure acetonitrile and solvent B consisted of 10 mM ammonium formate in H2O at pH 6.8. The ESI-HRMS was a micrOTOFQ TM (Bruker Daltonics) apparatus.

The LC coupled with high-resolution mass spectrometry (ESI/QTOF) was used in order to confirm lycorine and galanthamine identities in sample extracts. This system was able to detect the compounds in amounts lower than 0.02 µg/mL. Authentic galanthamine and lycorine displayed [M + H] + at an m/z of 288.1594 and 288.1234 Da, respectively. The analysis was performed in positive mode with the compass for otofSeries 1.7 software including otofControl 3.4 for acquisition and dataAnalysis 4.2 for process. The identification of the other alkaloids was performed by comparing the measured molecular mass with the calculated values ± 10 mDa.

Results and discussion

Amaryllidaceae alkaloid profile by GC-MS and LC-MS

There is no report in the literature concerning the alkaloid profiling of Iranian Narcissus tazetta and N. papyraceus bulbs. To investigate the various compounds present in the complex alkaloid fractions of four varieties of N. tazetta and one species of N. papyraceus, GC-MS and LC-MS were used. For the both methods of analysis, the identification of the alkaloids was performed by comparing the measured data with literature data [START_REF] Ptak | LCMS and GCMS for the Screening of Alkaloids in Natural and in Vitro Extracts of Leucojum aestivum[END_REF][START_REF] Singh | Transcriptome and metabolome profiling of Narcissus pseudonarcissus 'King Alfred' reveal components of Amaryllidaceae alkaloid metabolism[END_REF]. Capillary GC-MS was used according to the method previously described by El Tahchy et al. [START_REF] Tahchy | Effects of sucrose and plant growth regulators on acetylcholinesterase inhibitory activity of alkaloids accumulated in shoot cultures of Amaryllidaceae[END_REF]. Narcissus varieties bulbs (Fig. 1) and showed MS fragmentation patterns characteristic of the Amaryllidaceae alkaloids (Table 1). Tazettine was identified in all varieties of N. tazetta and not in N. papyraceus (G5). This last genotype (G5), N. tazetta var. Panjehgorbei (G3) and N. tazetta var. Shahla (G4) showed the lowest distribution of the alkaloids (eight compounds) while N. tazetta var. Meskin (G2) showed the highest distribution of the Amaryllidaceae alkaloids (ten compounds) (Table 1).

Untargeted LCHRMS profiling was performed to generate extensive mass list corresponding to a wide variety of alkaloids present in various extracts of four varieties of N. tazetta and one species of N. papyraceus. Analysis performed in positive ion mode detected between 13 (N.

tazetta var. Shastpar (G1) and 20 alkaloids (N. papyraceus (G5)) depending on the genotype of Narcissus studied (Table 2). It is important to note that the identification provided is a proposed identification. It has been reported that epimers like vittatine and crinine with the same masses show slightly different retention times [START_REF] Singh | Transcriptome and metabolome profiling of Narcissus pseudonarcissus 'King Alfred' reveal components of Amaryllidaceae alkaloid metabolism[END_REF]. In addition, the MZmine software identifies peaks via searches through an online database in which only a few Amaryllidaceae alkaloids are These results are complementary to those obtained by GC-MS analysis. Nine alkaloids were identified both with the GC-MS and LC-MS analysis in the various bulb extracts of Narcissus studied: trisphaeridine, assoanine, ismine, 3-epimacronine, hippeastrine, lycorenine, lycorine, galanthamine, and tazettine. However, the identification of each of these alkaloids in one genotype depended on the method of analysis considered. For example, assoanine, ismine, and tazettine were detected in the extract of N. tazetta var. Meskin (G2) by GC-MS analysis and were not detected by LC-MS. In contrary, 3-epimacronine, hippeastrine, and tazettine were detected in the extract of N. papyraceus (G5) by LC-MS while they were not detected by GC-MS.

Lycorine and galanthamine contents

In order to investigate the contents of galanthamine and lycorine in the wild bulbs of two species of Narcissus, N. tazetta and N. papyraceus and also in different varieties of N. tazetta (G1 to G4) grown in Iran, a quantitative GC-MS analysis was employed according to the method previously described by El Tahchy et al. [START_REF] Tahchy | Effects of sucrose and plant growth regulators on acetylcholinesterase inhibitory activity of alkaloids accumulated in shoot cultures of Amaryllidaceae[END_REF]. It is the first time that quantitative analysis of two Amaryllidaceae alkaloids was reported for N. papyraceus and for all the varieties of N.

tazetta, Shastpar (G1), Meskin (G2), Panjehgorbei (G3) and Shahla (G4). All the varieties contained lycorine and galanthamine however the concentration in lycorine is much higher (from 393 µg/g DW in N. tazetta: Shastpar (G1), to 2645 µg/g DW in N. papyraceus (G5))

comparatively to the galanthamine contents (from 8 µg/g DW in N. papyraceus (G5) to 105 µg/g DW in N. tazetta var. Meskin (G2)) (Fig. 2). It is worthy to note that the bulb of N. tazetta var. Meskin (G2) showed the highest content in galanthamine (0.10 mg/g DW) and a high content in lycorine (1.8 mg/g) comparatively to the other varieties. However N. papyraceus (G5) has shown to have the highest content in lycorine (2.6 mg/g) and the lowest amount of galanthamine (6 µg/g DW) comparatively to the other varieties studied. In various parts of plants of L. aestivum, it has been reported the concentration of galanthamine between 0.02 to 0.60 mg/g DW and lycorine between 0.11 to 0.23 mg/g DW [START_REF] Petruczynik | Comparison of different HPLC systems for analysis of galantamine and lycorine in various species of Amaryllidaceae family[END_REF].

In vitro culture initiation

The effects of three auxins (2,4-D, Picloram and NAA) in two concentrations (25 and 50 µM) on the induction of callogenesis and organogenesis in the two varieties of Narcissus: Meskin (G2) and Shahla (G4), showing the highest concentrations of lycorine in bulbs, were studied (Table 3).

After 12 weeks of culture, calli were observed on the whole surface of the explants of the both varieties. All auxins and all concentrations of auxins induced calli formation. However, the

Influence of auxins on the alkaloid profile

We have shown previously that Amaryllidaceae alkaloid profile in tissue cultures of L. aestivum is correlated with cellular differentiation controlled by various hormonal conditions [21,[START_REF] Tahchy | Effects of sucrose and plant growth regulators on acetylcholinesterase inhibitory activity of alkaloids accumulated in shoot cultures of Amaryllidaceae[END_REF]. In the present study, the alkaloid profile of N. tazetta var. Meskin (G2) and N. tazetta var. Shahla (G4) in vitro cultures (calli, bulblets and roots) was correlated with the type of auxin (2,4-D, Picloram and NAA) and its concentration (25 and 50 µM) used in the medium (Table 4).

Quantitative GC-MS analysis was used according to the method previously described for the analysis of in vivo bulbs. Following the alkaloid extraction and purification of all tissue culture samples, alkaloid fractions suitable for GC-MS analysis were obtained. The presence of alkaloids varied with auxin used for the tissue culture. It is worthy to note that galanthamine and lycorine were detected in all tissue cultures, undifferentiated cells or in roots and bulbets, with all auxins whatever the concentration used for the both varieties. These both alkaloids were also detected in all in vivo bulbs of the two species and four varieties of Narcissus studied.

Two others compounds, demethylmaritidine, and tazettine were found in differentiated tissue cultures cultivated on the medium that contained NAA (25 or 50 µM). These two compounds were not identified in undifferentiated cells excepted in calli initiated with Picloram at the concentration of 50 µM. Demethylmaritidine was not detected in the both varieties of N. tazetta (G2 and G4) bulbs from natural habitats while tazettine was present only in N. tazetta var.

Shahla (G4) bulbs.

Effect of 4'-O-methylnorbelladine on the alkaloid accumulation and profile

Calli and bulblets of N. tazetta var. Meskin (G2) were subcultured in medium containing precursor 4'-O-methylnorbelladine at various concentrations (0.05 and 0.15 g/L) and incubated for two periods of time (10 and 20 days) as reported previously by El Tahchy et al. [START_REF] Tahchy | New method for the study of Amaryllidaceae alkaloid biosynthesis using biotransformation of deuterium-labeled precursor in tissue cultures[END_REF] and Saliba et al. [START_REF] Saliba | Stimulating effect of both 4'-O-methylnorbelladine feeding and temporary immersion conditions on galanthamine and lycorine production by Leucojum aestivum L. bulblets[END_REF] in Leucojum aestivum tissue cultures. After harvesting the calli and the bulblets, the precursor and the Amaryllidaceae alkaloids were extracted from the tissue cultures and the compounds were identified using capillary GC-MS. Regardless of the incubation duration and the concentration of precursor, the latter was detected both in calli and in bulblets indicating that it was transported from the liquid medium into the plant cells (Figure 3). The highest concentrations of the precursor were 550 µg/g in calli and 800 µg/g in bulblets in the presence of 0.15g/L of 4'-O-methylnorbelladine in the liquid medium after 10 days of culture.

The concentrations of galanthamine and lycorine (µg/g DW) in calli and in bulblets are shown in Figures 4 and5, respectively. Galanthamine was detected at the highest concentration in bulblets (82 µg/g DW) cultivated in the presence of 0.05 g/L and 0.15g/L of precursor during 20 and 10 days respectively. In these conditions, lycorine was also detected at the highest concentration of 1883 µg/g DW. Therefore, the competition between galanthamine and lycorine biosynthetic pathways was not observed in the presence of the precursor. Indeed bulblets accumulated high quantities of both alkaloids at the same time as it has been previously reported in Leucojum aestivum bulblet culture [START_REF] Saliba | Stimulating effect of both 4'-O-methylnorbelladine feeding and temporary immersion conditions on galanthamine and lycorine production by Leucojum aestivum L. bulblets[END_REF]. However, the stimulating effect of the precursor on the alkaloid accumulation is not so clear when it is present in the culture medium of calli. The concentration of galanthamine and lycorine reached the maximum (1.17 and 58.5 µg/g respectively) in calli cultivated in the presence of 0.15 g/L and 0.05g/L of MN after 10 and 20 days of culture, respectively. In the others conditions of culture, the culture in the presence of the precursor led to the decrease of the accumulation of the galanthamine.

Capillary GC-MS was used in order to identify the various alkaloids (Table 5) present in the fractions of bulblets of N. tazetta var. Meskin (G2) cultured during 10 and 20 days with the precursor 4'-O-methylnorbelladine at various concentrations (0.05 and 0.15 g/L). Only galanthamine and lycorine were identified in the control bulblets after 10 days of culture and two alkaloids in addition (demethylmaritidine and tazettine) in the control bulblets after 20 days of culture. However, eight alkaloids were observed after 10 or 20 days of incubation with the precursor (0.05 or 0.15 g/L): galanthamine, lycorine, demethylmaritidine, tazettine homolycorine, narcissidine, chlidanthine, and methyl norbelladine. These results show that the precursor 4'-O-methylnorbelladine could be biotransformed in bulblets of N. tazetta var.

Meskin and gives Amaryllidaceae alkaloids.

Conclusion

The analysis of Amaryllidaceae alkaloids in extracts of bulbs after flowering of Narcissus papyraceus and four varieties of N. tazetta grown in Iran were performed for the first time using both GC-MS and LC-MS. It is well established that alkaloid profiles vary with the species and the varieties studied and with the analytical techniques used: 13 and 30 alkaloids were identified respectively by GC-MS and LC-MS. The obtained results of the phytochemical analysis of bulbs revealed that N. tazetta var. Meskin (G2) is a potential source of Amaryllidaceae alkaloids of interest. This study showed also that the medium containing NAA (50 µM) is appropriate not only for callus, roots and bulblets induction, but also for leading to the highest diversity of alkaloid profile in this variety Meskin. In the same way, the 4'-O-methylnorbelladine feeding had a significant stimulating effect on both galanthamine and lycorine biosynthesis. The tissue culture of N. tazetta var. Meskin in the presence of both NAA and precursor 4'-Omethylnorbelladine can be an interesting approach for Amaryllidaceae alkaloids production.

  of N. tazetta var. Shastpar (G1), N. tazetta var. Meskin (G2), N. tazetta var. Panjehgorbei (G3), Narcissus tazetta var. Shahla (G4), and N. papyraceous (G5) were harvested 2 months after full flowering stage from Behbahan, Ahvaz province in Iran in April 2016. The species have been registered and deposited in the herbarium of Fars Research Center of Agriculture and Natural Resources, Shiraz, Iran (N° 12822, N° 12823, N° 12824, N° 12825 and N° 12826 respectively).

  Following the alkaloid extraction and as shown earlier by Tram et al. [29], derivatization was not required since the Amaryllidaceae alkaloids retain their characteristic EI/MS fragmentation patterns when employing GC conditions. Galanthamine and lycorine standards were injected in order to compare and confirm their EI/MS fragmentation patterns with literature results. The distribution of the alkaloids varied according to the Narcissus varieties. Six compounds (ismine, trisphaeridine, galanthamine, lycorine, masonine, chlidanthine 1,2-dihydro) were found in all

  callogenesis was observed from 35 % of explants for Picloram 50 µM to 96 % of explants for NAA 25 µM. For the both varieties, NAA with the both concentrations tested led to the best callogenesis. In addition, 2,4-D (25 and 50 µM) induced a good callogenic response for the genotype G2 only. In contrary, Picloram (25 µM) led to the best induction of callus in Leucojum aestivum[21].In our experiment, bulblets and roots of Narcissus were formed after approximatively 6 weeks of callus cultivation. A significant number of bulblets and roots of N. tazetta var. Meskin (G2) and N. tazetta var. Shahla (G4) were obtained in the presence of NAA (25 and 50 µM) only.The highest numbers of bulblets and roots were obtained on the callus grown in the presence of 25 µM NAA (92 % of explants and 77 % of explants respectively) for genotype G2 only and the lowest on the medium with 50 µM NAA (55.20 % of explants and 53.20 % of explants respectively) for genotype G4. Picloram and 2,4-D led to no bulblet and no root development for any varieties. However Picloram is known to be the most effective auxin in initiation of embryogenic callus of bulbous plants including Leucojum aestivum[21].

FFigure 1 .Figure 2 .Figure 3 .

 123 Figure 1. Lycorine (A), galanthamine (B), ismine (C), trisphaeridine (D), masonine (E) and chlidanthine 1,2-dihydro (F) detected in all varieties of Narcissus tazetta (G1: N. tazetta var.Shastpar, G2: N. tazetta var. Meskin, G3: N. tazetta var. Panjehgorbei, G4: N.tazetta var. Shahla) and in Narcissus papyraceus (G5).

Figure 4 .

 4 Figure 4. Galanthamine (A) and lycorine (B) concentrations in calli of N. tazetta var. Meskin (G2) during feeding with various concentrations of precursor (control, 0.05 and 0.15 g/L). The data represent the average of three replications with standard deviations. Different letters indicate the statistically significant differences (LSD's multiple range test, p<0.05) among different treatments at each time point.

Figure 5 .

 5 Figure 5. Galanthamine (A) and lycorine (B) concentrations in bulblets of N. tazetta var. Meskin (G2) during feeding with various concentrations of precursor (control, 0.05 and 0.15 g/L). The data represent the average of three replications with standard deviations. Different letters indicate the statistically significant differences (LSD's multiple range test, p<0.05) among different treatments at each time point.

Acknowledgements

The authors thankfully acknowledge Pascal Lemière from Platform of Chromatography, L2CM laboratory, Institut Jean Barriol, Université de Lorraine, Lorraine Université Excellence (LUE) for financial support and also the Ministry of Science, Research and Technology of the islamic republic of Iran for providing a scholarship.

Table 1. Amaryllidaceae alkaloids identified par GCMS in bulbs of four genotypes of Narcissus tazetta (G1-G4) and one genotype of Narcissus papyraceus (G5) G1: N. tazetta var. Shastpar, G2: N. tazetta var. Meskin, G3: N. tazetta var. Panjehgorbei, G4: N. tazetta var. Shahla, G5: N. papyraceus.