Mr Mr Nicot Philippe

Poessel

Keywords: Secondary metabolites, phenol contents, inhibition, susceptibility Résumé

Jean-Luc and Madam QUILOT Bé né dicte, my supervisors, for helping me to quickly integrate within the

general objective is to improve the efficiency of apple and peach breeding programmes by multidisciplinary approach, including genetics, genomics, ecophysiology and bioinformatics (http://www.fruitbreedomics.com/).

Peach: a traditional and important culture.

The peach (Fig. 1), Prunus persica L. Batsch, is classified with the almond (P. dulcis D. A. Webb) in the subgenus Amygdalus, distinguished from the other subgenera by the presence of a deeply-rough stone. It belongs to the family Rosaceae of the order Rosales.

The fruit has yellow or whitish flesh, a delicate aroma, and a skin that is either velvety (peaches) or smooth (nectarines) in different cultivars. Today, 3000 identified varieties of P. persica show wide morphological diversity: purple leaves; double flowers; flat, round, or elongated fruits; smooth or pile skin; red, white or yellow flesh... [START_REF] Bassi | Botany and Taxonomy[END_REF].

The center of origin of the peach is considered to be in the North of China and the domestication of this species is estimated to have lasted since 5000 years ago, along with that of apricot. In Northern Europe, the peach was considered a rare and valuable fruit as the climate does not allow its culture. It is mainly grown today in the southern half of France, especially in the Provence-Alpes-Côte d'Azur region.

In 2009, the world production of peaches and nectarines reached 18.6 million tons, representing 3.34% of the total world production of fruit. The first producing country is China with 45.9% of world production, followed by Italy, Spain and the United States (FAOSTAT, 2010). Increasing consumer demand for peach and nectarines requires continued improvements in yield and quality of their production.

A B C

Monilinia: a key fungal pathogen in the peach production system

The disease: brown rot and blossom blight. Among the variety of pests and diseases affecting peach production worldwide, brown rot (BR) and Blossom blight (BB) caused by Monilinia sp. is considered as a key problem as it affects the health of the plant and has a direct impact on yield and fruit quality [START_REF] Adaskaveg | Diseases of Peach Caused by Fungi and Fungal-like Organisms: Biology, Epidemiology and Management[END_REF]. This disease causes economically important losses if favorable climatic conditions occur during the blossoming or pre-harvest and harvest periods [START_REF] Willetts | Cytology, histology, and histochemistry of fruit infection by Monilinia species[END_REF].

BB is the first symptom in spring, which appears first on sepals, anthers and stigmata

as the blossoms open. Blight symptoms are expressed when the fungus girdles the peduncle. Among the stone fruits, apricot is the most susceptible to blossom blight (BB), followed in order by prune, sweet cherry, peach, sour cherry and plum [START_REF] Holb | Brown rot blossom blight of pome and stone fruits: symptom, disease cycle, host resistance, and biological control[END_REF]. For a given fruit species, losses also vary with the susceptibility of the cultivars.

According to VIENNOT-Bourgin (1949), the manifestation of the disease on the fruit (BR) is the largest and most damaging. The attack occurs after a superficial lesion. The fungus spreads rapidly in the wound surface and at depth. The flesh appears bruised and turns brown, finally becomes soft place by maintaining a fibrous texture. The skin comes off easily and is covered with tawny gray pads.

The pathogens: Monilinia sp.. Several species of Monilinia have been reported to cause BR of stone fruits world wide. In France, three species are currently described: M. laxa (Aderhold & Ruhl.) Honey (also Sclerotinia laxa Aderh. & Ruhl.), M. fructigena (Aderhold & Ruhl.) Honey and M. fructicola (G. Wint) Honey [START_REF] Mercier | Monilioses du pê cher, dé terminer les espè ces et é valuer leur é partition[END_REF]. The latter species is considered as a quarantine organism [START_REF] Lane | A synoptic key for differentiation of Monilinia fructicola, M. fructigena and M. laxa, based on examination of cultural characters[END_REF]. In many regions, including France, M. laxa is considered as the most common and serious species attacking both blossoms (BB; Fig. 2 and3) and fruits (BR) (Fig. 3). A special form of M. laxa f.sp.

mali can also infect blossoms of pome fruits [START_REF] Byrde | The Brown Rot Fungi of Fruit: Their Biology And Control[END_REF].

This species of the genus Monilinia (order Helotiales, class Leotiomycetes, phylum Ascomycota) can be distinguished from other species based on morphological traits [START_REF] Batra | First Authenticated North American Record of Monilinia fructigena, With Notes on Related Species[END_REF]. Several other diagnostic features have also been used; the part of the host plant infected, the color of pustules and the time of appearance of the first pustules give preliminary information to determine the species (van Leeuwen and van Kesteren, 1998).

In the last decade, several conventional multiplex polymerase chain reaction (PCR) assays were introduced from all three for differentiation of Monilinia species [START_REF] Côté | Identification of Monilinia fructigena, M. fructicola, M. laxa, and Monilia polystroma on Inoculated and Naturally Infected Fruit Using Multiplex PCR[END_REF]; et al., 2007;[START_REF] Van Brouwershaven | A real-time (TaqMan) PCR assay to differentiate Monilinia fructicola from other brown rot fungi of fruit crops[END_REF]. According to [START_REF] Côté | Identification of Monilinia fructigena, M. fructicola, M. laxa, and Monilia polystroma on Inoculated and Naturally Infected Fruit Using Multiplex PCR[END_REF], the multiplex PCR consistently produced a 402-bp PCR product for M. fructigena, a 535-bp product for M. fructicola, and a 351-bp product for M.laxa based on a common reverse primer (MO368-5) and three species-specific forward primers (MO368-8R, MO368-10R, and Laxa-R2).

The conidia of M. laxa are oval in shape, 12-18 µm long and 9-10 µm wide. Both extremities are more or less stretched. Colonies of M. laxa have lower growth rates than other species of Monilinia on potato dextrose agar (PDA) grown at 22 °C under 12 h of light per day [START_REF] Lane | A synoptic key for differentiation of Monilinia fructicola, M. fructigena and M. laxa, based on examination of cultural characters[END_REF]Fig. 4).

Disease prevention and control. In France, several chemical substances are registered to control Monilinia diseases, including cyproconozole, difenoconazole and myclobutanil for orchard application, then fludioxonil and fenhexamid for postharvest application (http://e-phy.agriculture.gouv.fr/). Chemical control may be difficult; however, as fungicide resistance has developed repeatedly in the past among Monilinia populations [START_REF] Guizzardi | Resistance monitoring of Monilinia laxa (Aderh. & Ruhl.) Honey to benzymidazole and dicarboxymides in postharvest stage[END_REF][START_REF] Sanoamuang | Persistence and fitness of carbendazim-and dicarboximide-resistant isolates of Monilinia fructigena (Wint.) Honey in flowers, shoots and fruit of stone fruit[END_REF][START_REF] Ma | Identification and Characterization of benzimidazole resistance in Monilinia fructicola from stone fruit orchards in California[END_REF]. Several studies have shown that hot water treatments by themselves or in combination with other treatments can substantially control postharvest diseases of peaches and nectarines [START_REF] Margosan | Combination of hot water and ethanol to control postharvest decay of peaches and nectarines[END_REF][START_REF] Karabulut | Control of brown rot and blue mold of peach and nectarine by short hot water brushing and yeastantagonists[END_REF]. However, control programs are often inefficient and significant levels of brown rot may occur during storage, transport and marketing. In view of the possible genetic resistance to brown rot, the use of resistant or tolerant cultivars is known to be one of the best means of disease control.

Resistance to Monilinia in stone fruits

Some genotypes are known to have a high level of resistance to Monilinia sp. [START_REF] Feliciano | Monilinia fructicola resistance in peach cultivar Bolinha[END_REF][START_REF] Adaskaveg | Comparative studies of resistance in peach genotypes to Monilinia fruticola[END_REF]. Morphological and biochemical factors have been shown to account for differences between peach genotypes susceptible and resistant to M. fructicola [START_REF] Feliciano | Monilinia fructicola resistance in peach cultivar Bolinha[END_REF]. Based on the research of Bostock et al.

(1998), peach genotypes with a high level of resistance have fewer trichomes and a thicker cuticle with a higher phenolic content than other fruits of similar maturity from less resistant genotypes. Even for susceptible cultivars, young fruits are usually quite resistant to colonization by the pathogen [START_REF] Gell | Relationship between the incidence of latent infections caused by Monilinia spp. and the incidence of brown rot of peach fruit: Factors affecting latent infection[END_REF] and they gradually become susceptible with increasing maturity. Such changes in susceptibility have been related to significant changes in volatiles, organic acids, phenolic compounds and cell wall composition in the fruit [START_REF] Biggs | Early and Late-season Susceptibility of Peach Fruits to Monilinia fructicola[END_REF][START_REF] Ibbotson-Darhower | Susceptibility of peach and nectarine fruit at different developmental stages to Monilinia fructicola[END_REF][START_REF] Luo | Factors affecting latent infection of prune fruit by Monilinia fructicola[END_REF][START_REF] Villarino | High Chlorogenic and Neochlorogenic Acid Levels in Immature Peaches Reduce Monilinia laxa Infection by Interfering with Fungal Melanin Biosynthesis[END_REF].

Implication of phenolic compounds in peach resistance to Monilinia

Several phenolic compounds have been shown to decline in concentration in the exocarp of peach fruit during its maturation, concomitantly with an increase in susceptibility. They include: catechin (CC), epicatechin (ECC), caffeic acid (CA) and chlorogenic acid (CGA) [START_REF] Lee | Induction, Regulation, and Role in Pathogenesis of Appressoria in Monilinia fructicola[END_REF]. In addition, several investigators have pointed out fungitoxic properties of a few fruit phenolic compounds in vivo and in vitro,

and their particularly high contents in peach genotypes with a high level of resistance [START_REF] Gradziel | Breeding for brown rot (Monilinia fructicola) resistance in clingstone peach with emphasis on the role of fruit phenolics[END_REF][START_REF] Lee | Fruit exocarp phenols in relation to quiescence and development of Monilinia fructicola infections in Prunus spp.: A role for cellular redox?[END_REF]. However, the specific role of phenols in plant resistance to pathogenic fungi is not totally clear, due to the numerous external and internal variables in such host-pathogen interactions (Manibhusaurao et al., 1988).

In higher plants, the synthesis of phenolic compounds, such as CA, p-coumaric acid (PCA), ferulic acid (FA) and CGA, appear to be regulated by enzymes in response to infections by pathogens [START_REF] Kosuge | The role of phenolics in host response to infection[END_REF]. Gradziel and Wang (1993) have showed that an important antifungal role of the high phenolic activity on M. fructicola resistance is causally correlated with high enzymatic browning. Otherwise, Bostock"s group (1999) manifested that CA and CGA in peaches can suppress cutinase activity in M. fructicola which are crucial for its growth and colonization on a host. In the studies of De Cal and Melgarejo, a role for melanin-like pigments in the pathogenicity of M. laxa, such as that of melanised appressoria, has been described [START_REF] Cal | Effects of Pyroquilon on the Infection Process by Monilinia laxa[END_REF][START_REF] Cal | Effects of Penicillium frequentans and Its Antibiotics on Unmelanized Hyphae of Monilinia laxa[END_REF].

Objectives of the internship project

Based on this background, the objectives of my internship work were to characterize the inhibitory effect of individual phenolic compounds (i) on lesion development caused by M. laxa on flower petals of Prunus sp. (in vivo), and (ii) on M. laxa conidia germination and mycelial growth on the artificial media (in vitro). The eight phenolic compounds to be studied, CA, PCA, FA, 3, 5-dicaffeoyliquinic acid (DCQA), CGA, neochlorogenic acid (NCGA), CC and ECC, were known to be present in the exocarp of peach [START_REF]HPLC-DAD-ESIMS Analysis of Phenolic Compounds in Nectarines, Peaches, and Plums[END_REF][START_REF] Lee | Induction, Regulation, and Role in Pathogenesis of Appressoria in Monilinia fructicola[END_REF][START_REF] Maria | High Chlorogenic and Neochlorogenic Acid Levels in Immature Peaches Reduce Monilinia laxa Infection by Interfering with Fungal Melanin Biosynthesis[END_REF]. The "down-the-road" objectives of the general study are to evaluate their possible role in the resistance of specific peach cultivars to brown rot.

Materials and Methods

Fungal strain and inoculum production

Strain ML3 of Monilinia laxa. Single-spore isolate ML3 of M. laxa was used throughout this study. This strain was isolated in March 2011 from a mummified apricot fruit at the Gotheron experimental station of INRA. To limit the need for regular transfers of the fungus to fresh medium (and thus the risk of phenotypic drift), the strain was stored in Eppendorf tubes at -20°C as aliquots of a concentrated spore suspension in monopotassic phosphate buffer with 20% glycerol.

Production of conidia. To obtain conidia, the fungus was grown on V8 juice agar To produce inoculum, 6 µL drops of the stock suspension kept in the freezer were applied to Petri plates of V8 agar. The plates were then incubated in a growth chamber in 14 h of light per day (114 μmole m -2 s -1 ). The incubation temperature, 21 ± 2°C, was according to [START_REF] Tamm | Influence of temperature and moisture on growth, spore production, and conidial germination of Monilinia laxa[END_REF].

Conidia from 10 to 14-day-old cultures were collected in sterile water. The concentration of the suspensions was determined with the help of a Malassez hemacytometer and adjusted as desired with sterile water. For in vitro germination tests, an additional step was carried out prior to quantifying spores: the suspensions were filtered through 30 µm mesh sterile filters to remove possible mycelial fragments and ensure later a favorable counting view under the microscope.

Production of mycelium. Mycelial inoculum was produced on modified GG medium (Glucose Gé losé ) to foster mycelium production and limit sporulation of ML3. This "GG+" medium contained per liter: 15 g agar (Bacto TM , ref: 214010), 2 g yeast extract (Bacto TM , ref: 288620) and 1 g glucose (LABOSI, ref: 288620). The medium was autoclaved for 20 min at 120 °C, and then poured into 55 mm diameter Petri plates (7 mL per plate). The plates were inoculated with 6 µL drops of the stock suspension of ML3 and incubated in a growth chamber as described above.

Preparing stock solutions of phenolic compounds

The 8 phenolic compounds used in this study were purchased from different suppliers (Table 1). These compounds were first prepared as 40 mM stock solutions dissolved in pure methanol. Due to its particularly low solubility, NCGA was prepared as a 20 mM stock solution. On the day of an experiment, the stock solutions were prepared at room temperature, using a very precise Mettler AE160 balance (0.0001 g). For most tests, the solutions were used immediately. The stock solutions remaining after each test were stored at -20°C in the dark and were exceptionally used for certain additional tests.

Effect of the phenolic compounds on the development of M. laxa lesion on flower petals of Prunus

Plant material. Flower petals of Prunus sp. including apricot (P. armeniaca), almond (P. amygdalus), sweet cherry (P. avium) and peach were tested successively in this study (Fig. 5). Flowering branches were collected from UR GAFL field sites in Avignon, France, brought to the laboratory and kept at 4°C until use. To obtain a maximum of open flowers, branches were placed at room temperature one day before a test. On the day of a test, random samples of healthy petals were gently picked by hand and placed on a wet absorbing paper in transparent polystyrene boxes. The color of the absorbing paper was blue to facilitate disease assessment with image analysis software as described below.

Inoculations. Each petal was inoculated in its center with a 2 µL drop of conidial suspension containing the desired concentration of the compound to be tested (Table 1). To prepare these suspensions, identical volumes of a double-concentrated conidial suspension and a double-strength compound solution were prepared separately and mixed immediately before the inoculation. The polystyrene boxes containing the inoculated petals were closed with lids to keep high moisture inside and they were incubated in the growth chamber as described above.

As traces of ethanol (used as solvent in the stock solutions of phenolic compounds)

were present in all mixes containing phenolic compounds, the possible effect of ethanol on disease development was assessed in a preliminary test. Petals of almond ZH4 were inoculated with spore suspensions containing final ethanol concentrations of 0%, 10%, 20%, 30%, 40% and 50% (V/V) prepared from absolute ethanol.

In all the subsequent tests, two types of controls without phenolic compound were included: petals inoculated with spores in water and with spores in ethanol. For a given experiment, the ethanol concentration in the control was identical to the highest possible ethanol concentration present in the phenolic compound modalities (Table 2).

In addition, a third type of control was systematically included. For each experiment, two boxes containing non-inoculated petals were prepared to assess their physiological condition and detect the possible presence of latent infections by natural pathogens.

Disease assessment. Lesions caused by M. laxa on the petals were photographed on the first and second day post inoculation (dpi) with a digital camera and the lesion size (mm² ) was assessed using image analysis software Assess 2.0 (APS Press, St Paul, MN, USA).

To determine the relationship between lesion development and M. laxa germination, observations on the surface of petals were performed independently with epifluorescence and light microscopy 24 h after inoculation. The inoculated or non-inoculated petals were colored by 0.05% toluidine blue for 10 min and were observed under the microscope (Olympus BX60) after discoloration in sterile water; or colored by 0.1% calcofluor for 5 min and instantly observed under the microscope by using ultra violet (UV).

Experimental design and data analysis. All tests were conducted with at least 10 replicate petals for each modality (5 petals in each of two polystyrene boxes). However, higher numbers of petals were often used depending on the availability of flowers and the number of modalities to be tested in a given experiment (Table 2). Each phenolic compound was tested independently on at least 4 species of Prunus with at least 3 concentration of application.

Lesion surfaces were analyzed using analysis of variance, Newman-Keuls and critical ranges tests of statistical software STATISTICA. The F test was considered significant at p = 0.05. To show the protective effect of phenolic compounds, protection indices (PI) were computed as PI = 100 * (S control -S tested ) / S control , where S control was the average of lesion sizes on control petals (mm² ) and S tested was the average of lesion sizes on petals in the presence of a phenolic compound (mm² ). (A) Explants of 5 mm diameter were collected from each medium with a sterile cork borer and placed in separate wells in a 24well tissue culture test plate;

(B) A 2 µL drop of a conidial suspension adjusted to 250 conidia / µL as described in "Production of conidia" was deposited gently on the surface of the explants in each test plate.

Conidial suspension

Control Compound 1

Compound 3 Compound 2

Effect of phenolic compounds on the germination in vitro of M. laxa conidia

Media preparation. All germination tests were carried out on a GG medium containing per liter: 5 g of agar (Bacto TM , ref: 214010), 0.5 g of glucose (LABOSI, ref: 288620) and appropriate concentrations of the 8 phenolic compounds tested. For all compounds except NCGA, the final concentration in the medium was 2 mM (1 mM for NCGA). This was prepared by mixing 2300 µL of double-strength GG medium with an identical volume of a 10% dilution (in sterile water) of a compound's stock solution. The media thus contained also 5% ethanol. To avoid solidification of the agar medium, both components and the final media were maintained at 60°C in a water bath. A volume of 4 mL of each medium was then poured into a 55 mm diameter Petri plate and cooled to room temperature in sterile conditions. For FA, additional concentrations were tested, obtained by mixing identical volumes of double strength GG medium with 5%, 2.5% or 0.5% dilutions of the stock solution. The resulting concentrations were thus 1, 0.5 and 0.1 mM.

The concentration of ethanol was adjusted so that all final media contained 5% ethanol.

Preparation of replicates and inoculations. Each germination test was carried out on 6 replicates per phenolic compound and per concentration. To this end, 5 mm diameter explants were collected from each medium with a sterile cork borer and placed in separate wells in a 24-well tissue culture test plate (Fig. 6 -A). A 2 µL drop of a conidial suspension adjusted to 250 conidia / µL as described in "Production of conidia" was deposited gently on the surface of the explants in each test plate (Fig. 6 -B). The test plates were covered to keep high humidity and protect against contamination. These inoculated test plates were then incubated for 16 hours in a growth chamber at 21 ± 2°C (10 h night then 6 h day).

Quantification of germination.

The plates were examined under the microscope and at least 100 conidia were observed per well. A conidium was considered as germinated if the size of the germination tube was at least equal to the length of the conidium. To avoid bias related to the time needed to examine the conidia, the wells were randomly selected for reading on the plates. A germination rate (GR) was computed for each well as the number of germinated conidia per 100.

Experimental design and data analysis. Each test plate contained four sets of 6 replicates, one set with explants of 5% ethanol control medium, and three with different compounds or concentrations (Fig. 6 -A). Each test was repeated independently at least four times. Analyses of variance were carried out on GR values and Newman-Keuls and critical ranges test were performed when appropriate, using STATISTICA.

An index of inhibition (II) was computed as

II = 100 * (R control -R tested ) / R control ,
where R control and R tested were the average germination rates on the control medium and on the medium containing the phenolic compound under study, respectively.

Effect of compounds on M. laxa mycelial growth in vitro

Media preparation. This study was carried out only with 3 phenolic compounds, CA, PCA and FA. The final concentrations of each compound in the media were 0.1, 0.5, 1 and 2 mM with 1% ethanol. Controls (without phenolic compound) containing either 1% ethanol or only sterile water were also included. The base medium was GG + described above (section "Production of mycelim") and the media with the appropriate compound concentrations were prepared as described above. A volume of 2 mL of each medium was then poured into a 45 mm diameter glass Petri plate and cooled to room temperature in sterile conditions.

Before assessing the effect of the compound on mycelial growth, the effect of ethanol concentrations on the mycelial growth of M. laxa was studied. The final ethanol concentrations in the medium were 0.25%, 1.25%, 2.5%, 5% and 10% (V/V).

Inoculations. After 11 days of incubation as described in the section "Production of mycelim", 2 mm diameter mycelial plugs were excised with a sterile cork borer from the growing margin of the colony. Each plug was placed carefully in the centre of a Petri plate and then the plates were covered and sealed with plastic film "Cello frais", and then incubated in the growth chamber.

Quantification of mycelial growth. The size of the developing colonies was measured twice (2 dpi and 4 dpi for ethanol tests; 3 dpi and 6 dpi for compound tests) with a ruler. On each date, two diameters were measured (perpendicularly to each other) per plate and the values were averaged.

Experimental design and data analysis. Three replicate plates were used for each concentration of each tested compound and for each of the two controls. Colony sizes were compared by analysis of variance, followed when appropriate by Newman-Keuls and critical ranges tests with STATISTICA.

Inoculum concentration (conidia / µL) 1 day post inoculation 2 days post inoculation 2 days post inoculation

Results and Discussion

Protective effect of phenolic compounds on petals of Prunus sp.

Effect of ethanol on disease development. The preliminary test with ethanol showed that certain concentrations of this chemical (used as a solvent for all phenolic compounds under study in this work) had a significant effect on the development of Monilinia lesions on petals of almond ZH4. Concentrations of 30%, 40% and 50% (V/V) totally prevented lesion development by M. laxa. At a concentration of 20%, ethanol almost completely inhibited disease development on petals inoculated with low conidial loads of the pathogen and significantly (P < 0.05) reduced lesion size at high inoculum concentrations (Fig. 7). In contrast, 10% ethanol never caused significant inhibition of disease. Based on the solubility of the phenolic compounds and the impact of ethanol, the maximum ethanol concentration in the final phenolic compound solution was fixed at 10% for the rest of the study.

Effect of inoculum concentration on disease development. The concentration of M.

laxa inoculum applied to the petals significantly affected lesion size (Fig. 7). With the lower conidial concentrations, disease severity was very low. So as to obtain visible symptoms on the petals and also to economize plant material, only inoculum concentrations of 250 conidia / µL and 50 conidia / µL were used in the rest of the study.

Diversity in the susceptibility of petals to M. laxa among Prunus cultivars.

Among the 10 genotypes of Prunus sp. compared in this study, a wide range of susceptibility was observed (Fig. 8). At 2 dip, lesion size of peach "7970" and sweet cherry "ce" were significantly (P < 0.05) larger, while peach "8858" was significantly (P < 0.05) smaller (Fig. 8). The susceptibility of the six almond genotypes was intermediate and showed little variability. For a given genotype, petals from branches kept longer in cold storage for replicate tests appeared more sensitive (detailed data not shown), suggesting an evolution of susceptibility with the physiological state of the flowers. This further suggests that tests with flowers should (1) be carried out with large numbers of independent repetitions and (2) that care should be taken to document well the physiological state / storage conditions of the flowers used in such tests in the laboratory.

Effect of phenolic compounds on disease developement.

In the course of this work, each of the 8 compounds could be evaluated at a concentration of 2 mM in 7 to 15 replicate Compared with the ethanol control, each compound significantly reduced lesion size (P < 0.05) on at least three genotypes when observed at 1 dip and two when observed at 2 dip.

Compound tested

For the sake of concision, the detailed data are documented only in Annex 1 and the average inhibition index over all replicate tests is presented for each compound in Fig. 9.

At 1 dpi, FA had a consistently high inhibition index, with an average of 98% and a low standard error (Fig. 9 -A

Study of microscopy.

To understand the mode of lesion growth, inoculated petals showing lesions or remaining symptomless, and un-inoculated petals showing lesions were colored and observed at 1 dpi (Fig. 10). Conidial germination of M. laxa was detected (stained with toluidin blue) both on inoculated petals showing lesions and on those remaining symptomless. Treatments with certain compounds such as FA disrupted the morphology of the germination tubes and mycelia, probably resulting in the observed absence of symptoms (Fig. 10 -C). This finding suggests that M. laxa could infect flower petals without developing symptoms. A similar phenomenon had been reported on peach fruit [START_REF] Lee | Induction, Regulation, and Role in Pathogenesis of Appressoria in Monilinia fructicola[END_REF].

Observations made with calcofluor were not informative. The essential advantage of this dye is that its use does not require discoloration of the plant tissue, thus reducing the possibility of destroying the spores or mycelium on the surface of petals. It could be used in the study of germination rate. But it did not color the filaments once they penetrated inside the plant tissue and it could be affected by ethanol and mostly phenolic compounds (Fig. 10 -B). Consequently, it did not turn out to be suitable for the study of compounds.

Effect of phenolic compounds on the germination in vitro M. laxa conidia

Tests with a high concentration of the phenolic compounds. Only three of the eight compounds (CA, PCA and FA) significantly (P < 0.05) reduced the germination of M. laxa conidia, when present at a concentration of 2 mM in the nutrient medium (1 mM for NCGA). In seven independent experiments with FA, this compound systematically provided near complete inhibition of germination. For PCA, significant inhibition was observed in six of seven independent tests, with a wide variability in the Inhibition Index (II from 7.8 to 80.2%). Among the seven independent tests with this compound, some level of variability was also observed in the germination rate on the control medium without phenolic compound (5% ethanol), prompting the investigation of a possible relationship between the inhibition efficacy of the compound and the rate of germination of the fungus on the control medium (Fig. 11). Regression analysis showed that the correlation was statistically significant (R² = 0.808; P = 0.0059), with a linear relationship:

II PCA = 174.3 -1.723 GR control,
where II PCA was the Inhibition Index for the germination of conidia on medium containing PCA and GR control was the germination rate of the conidia on the control medium.

For CA, significant inhibition was observed in only two of seven independent tests, with overall low values of the Inhibition Index (II from 0.4 to 16%). As for PCA, a significant linear relationship (R² = 0.948; P = 0.0002) was found between II and the rate of germination of the fungus on control medium:

II CA = 45.73 -0.47 GR control ,
where II CA was the Inhibition Index for the germination of conidia on medium containing CA and GR control was the germination rate of the conidia on the control medium.

For the five other compounds under study (DCQA, CGA, CC, ECC and NCGA) germination was not significantly inhibited (II < 8%) regardless of the germination rate of conidia on the control medium (Fig. 11 -B). Future work could include testing these compounds at higher doses, although 2 mM is already considered as a high concentration in biological terms [START_REF] Bostock | Suppression of Monilinia fructicola Cutinase Production By Peach Fruit Surface Phenolic Acids[END_REF][START_REF] Lee | Induction, Regulation, and Role in Pathogenesis of Appressoria in Monilinia fructicola[END_REF]. The findings were complementary with results of in vivo tests at an equivalent concentration of compounds (2 mM). FA showed also nearly total inhibition on conidial germination. CA and PCA had significant effects in vivo, and the rest of the compounds none. This finding strengthens our hypothesis that the inhibitory effects of those compounds relates with host genotype.

Dose effect for ferulic acid. As 2 mM of FA provided near complete inhibition of the germination of M. laxa conidia, lower concentrations were also tested. Significant inhibition was observed (P < 0.05) in all four independent experiments with 1 mM of FA, but II was overall low (4.2~60.8%, with a mean of 20.5%) and it varied depending on the germination rate of the fungus on the control medium (Fig. 11 -C). At a concentration of 0.5 mM, significant inhibition was observed on only one of four replicate experiments (II = -3.5~20.6%; with a mean of 4.5%) and at 0.1 mM no significant inhibition was observed (II = -0.9~10.4, with a mean of 2.5%).

Differences of concentration effects increase with the rate of germination of the fungus on the control medium. Upwards of 95% germination rate of control, great difference of II appeared even between 2 mM and 1 mM. That could explicate why no visible inhibition on lesion growth in vivo with the lower concentrations (under 2 mM) tested.

Effect of phenolic compounds on mycelial growth in vitro

Inhibitory effect of ethanol. Based on results, mycelia of M. laxa were sensitive to ethanol (Fig. 12). At 2 and 4 dip, upward of 5% ethanol has a full inhibitory effect on mycelial growth. A concentration of 2.5% ethanol significantly reduced mycelial growth (P < 0.05) compared with the control (sterile water), while below 1.25%, ethanol has no significant effect. To limit the effect of ethanol in experiments with the phenolic compounds, the concentration of ethanol in the media was fixed at 1%.

Inhibitory effect of CA, PCA and FA. According to the results on the germination of M. laxa conidia, three compounds (CA, PCA and FA) were chosen for a study of their effect on mycelial growth. No significant difference was found between the growth of the fungus on the two types of control (sterile water and 1% ethanol) at 3 (A) and 6 (B) dip (Fig. 13), showing that this dose of ethanol was not deleterious for the fungus. None of the three compounds inhibited completely the mycelial growth of the fungus at any of the concentrations under study. However, all three compounds significantly (P < 0.05) reduced mycelial growth at the highest concentration (2 mM) at both times of observation. The reduction relative to the ethanol control was quite substantial, amounting to 20, 29 and 43% for CA, PCA and FA, respectively at 6 dpi. Smaller but statistically significant reductions were also observed for PCA and FA at 1mM. This finding accord with results of inhibition on lesion growth and on conidial germination that capacity of inhibition on infection of M. laxa was: FA > PCA > CA.

conidial germination has been noted at the same concentration as tests in vivo (2 mM). So their inhibitory effects are inferred to be associated with the host genotype.

In In fruit, constitutive natural barriers such as the cuticle, exocarp or phenolic compounds are the first defense mechanisms against necrotrophs. The role of phenolic compounds on plant defense against M. laxa has been frequently studied [START_REF] Tamm | Phenological Analysis of Brown Rot Blossom Blight of Sweet Cherry Caused by Monilinia laxa[END_REF][START_REF] Villarino | High Chlorogenic and Neochlorogenic Acid Levels in Immature Peaches Reduce Monilinia laxa Infection by Interfering with Fungal Melanin Biosynthesis[END_REF]. The techniques used in this study were initial and developed.

Future studies will confirm the sensibility of genotypes and assess the pathway of inhibitory effects of each phenolic compound.

Fig. 1 .

 1 Fig. 1. Physiology of peach. (Adaskaveg et al., 2008) (A) Diagram of a peach flower. (B) Cross section of a peach fruit. (C) Stages of peach fruit and seed growth.

Fig. 3 .Fig. 2 .

 32 Fig. 3. Monilinia spp. Life cycle. (Cruz, 2010)

Fig. 4 .

 4 Fig. 4. Morphology of Monilinia spp. colonies grown on 4% PDA (10 days, 12 h light / 12 h dark at 22°C) (Lane, 2002). Monilinia fructicola isolate 1: (A) upper surface; (B) lower surface; M. laxa isolate 8: (C) upper surface; (D) lower surface; M. fructigena isolate 18: (E) upper surface; (F) lower surface.

  containing per liter 200 mL of V8 juice (Campbell), 20 g of agar (Bacto TM , ref: 214010), 2 g of yeast extract (Bacto TM , ref: 288620), 2 g of glucose (LABOSI, ref: 288620), 1 g of calcium carbonate (LABOSI, ref: A4759201) and 800 mL of sterile water. The pH was adjusted to 5.2 with NaOH or HCl and the medium was autoclaved for 30 minutes at 115 °C. It was then poured into 55 mm diameter Petri plates (7 mL per plate).

Fig. 5 .

 5 Fig. 5. Diversity of petal morphology among Prunus sp genotypes tested. Petal size is indicated by the length of yellow lines (Values in mm in parentheses).

Fig. 6 .

 6 Fig. 6. Experimental design of in vitro tests of Monilinia laxa conidial germination.

Fig. 8 .

 8 Fig. 8. Variability in susceptibility of petals to Monilinia laxa. among genotypes of Prunus sp. The petals were inoculated with 2µL drops containing 50 conidia / µL. Data represent the means and standard deviations of at least 10 replicate petals. Column values labeled with the same letter were not significantly different (α = 0.05) according to the test of Newman and Keuls.

Fig. 7 .

 7 Fig. 7. Effect of ethanol and inoculum concentration on the development of lesions on almond petals by Monilinia laxa. Petals were inoculated with 2 µL drops containing different combinations of conidial concentrations and ethanol (20%, 10% and 0% V/V) in sterile water. Data represent the means and standard deviations of 10 replicate petals. For a given graph, column values labeled with the same letter were not significantly different (α = 0.05) according to the test of Newman and Keuls.

Fig. 9 .Fig. 10 .

 910 Fig. 9. Inhibitive effect of phenolic compounds (2 mM with 5% ethanol) on the development of lesions on Prunus petals by Monilinia laxa: (A) 250 conidia / µL on 1 day post inoculation; (B) 50 conidia / µL on 2 day post inoculation. Data represent the means and standard deviations for at least 7 replicate experiments. Abbreviation: CA: caffeic acid; PCA: p-coumaric acid; FA: ferulic acid; DCQA: 3, 5-dicaffeoyliquinic acid; CGA: chlorogenic acid; NCGA: neochlorogenic acid; CC: catechin; ECC: epicatechin.

  ). For PCA, CC and ECC, the average indices were between 25 and 50% while those of CA, DCQA, CGA and NCGA were very low, with high standard errors due to negative values (stimulation of disease) for certain cultivars. At 2 dpi (Fig.9 -B), the inhibition indices of FA, PCA and CC were somewhat reduced compared to 1 dpi, and those of CA, CGA, NCGA, DCQA and ECC were increased. The standard errors were all increased, showing an aggravation of the variability between 1 and 2 dpi.Due to time constraints, it was not possible to complete the analyses of the data for tests with lower concentrations of the compounds (1, 0.5 and 0.1 mM during the time frame of the internship.

Fig. 11 .

 11 Fig. 11. Inhibitive effect of phenolic compounds on the conidial germination in vitro of Monilinia laxa. The artificial media were inoculated with 2 µL of a conidial suspension (250 conidia / µL) and incubated for 16 hours (10 h night then 6 h day) at 21 ± 2°C. Each point is the average of 6 replicates. For each compound or concentration of ferulic acid, column values labeled with "*" are significantly different (α = 0.05) with 5% ethanol control according to the test of Newman et Keuls. Abbreviation: CA: caffeic acid; PCA: p-coumaric acid; FA: ferulic acid; DCQA: 3, 5-dicaffeoyliquinic acid; CGA: chlorogenic acid; NCGA: neochlorogenic acid; CC: catechin; ECC: epicatechin.

Fig. 12 .Fig. 13 .

 1213 Fig. 12. Effect of ethanol on the mycelial growth of Monilinia laxa. Colony diameters were recorded at 2 and 4 days post inoculation (dpi). Data represent the means and standard deviations of 3 replicates. For a given day, column values labeled with the same letter are not significantly different (α = 0.05) according to the test of Newman et Keuls.

  an ongoing companion study of UR GAFL (internship of Y. Ye; same Master Program), the concentrations of PCA in the epidermis of peach "zephir 143" decreased significantly from stage I (43 days after flowering) to stage II (43~100 days after flowering), and then increased significantly at stage III (137 days after flowering). The change of the concentrations of CC is completely the opposite. At the same time, the sensibility of each stage of peach fruit was compared by inoculations with the same isolate ML3 of M. laxa which was used in the present study. According to results, stage II was more susceptible than stages I and III. The finding suggested that phenolic compounds PCA and CC may be involved in the natural defense of peach fruit against M. laxa.

Table 1 . Phenolic compounds under study and stock solution concentrations. Reviations Chemical names Structures Molecular weight Suppliers/ References/ Purity level Stock solutions in pure methanol

 1

	Test on lesion growth	Test on conidial germina-tion	Test on mycelial growth

(-)-epicatechin (2R-3R)

Table 2 . Dates and conditions of tests with phenolic compounds on petals of Prunus against Monilinia laxa.

 2

					Modalities
	Date of the tests	Phenolic compounds	Prunus species / cultivars	(inoculations x concentrations) Inoculum concentra-Compound (+ ethanol)	Replicates per modality (petals x
				tions	concentrations	box)
				(spores/µL)
					5 mM, 10% ethanol,
	Mar. 07	CGA	Almond ZH4; Apricot ce;	250, 125, 50, 25;	0.05 mM, 0.1% ethanol 0.5 mM, 1% ethanol,	x 2
	Mar. 19	CA, PCA, CGA, CC;	Peach 7970; Almond p3606, xa1;	250, 50;	2 mM, 5% ethanol;	x 2
	Mar.20	DCQA, CC, ECC; Almond p3606, xa2, xb;	250, 50;	2 mM, 5% ethanol;	x 2
	Mar.21	PCA, FA, DCQA, NCGA;	Almond p3606, xa2;	250, 50	2 mM, 5% ethanol (10% ethanol for NCGA);	x 2
					2 mM, 5% ethanol,
	Mar.26	CGA, DCQA;	Almond ZH81;	250, 50	1 mM, 2,5% ethanol,	x 2
					0.5 mM, 1.25% ethanol;
					2 mM, 5% ethanol,
	Mar. 27	CA, PCA, FA;	Almond ZH81;	250, 50;	1 mM, 2,5% ethanol,	x 2
					0.5 mM, 1.25% ethanol;
					2 mM, 5% ethanol
	Mar. 28	CA, PCA, FA, NCGA, CC, ECC;	Almond ZH81;	250, 50;	1 mM, 2,5% ethanol, 0.5 mM, 1.25% ethanol;	x 2
					(double ethanol for NCGA)
					2 mM, 5% ethanol
	Mar. 29	DCQA, CGA, NCGA, CC, ECC;	Almond ZH81;	250, 50;	1 mM, 2,5% ethanol, 0.5 mM, 1.25% ethanol;	x 2
					(double ethanol for NCGA)
					2 mM, 5% ethanol
	Apr. 02	CA, DCQA, CGA, NCGA;	Peach 8858;	250, 50;	1 mM, 2,5% ethanol, 0.5 mM, 1.25% ethanol;	x 2
					(double ethanol for NCGA)
					2 mM, 5% ethanol
	Apr. 03	CA, DCQA, CGA, NCGA;	Sweet cherry ce;	250, 50;	1 mM, 2,5% ethanol, 0.5 mM, 1.25% ethanol;	x 2
					(double ethanol for NCGA)
					2 mM, 5% ethanol
	Apr. 04	CA, PCA, FA, CC, ECC;	Peach 8858; Sweet cherry ce;	250, 50;	0.5 mM, 1.25% ethanol; 1 mM, 2,5% ethanol,	x 2

Abbreviations: CA: caffeic acid; PCA: p-coumaric acid; FA: ferulic acid; DCQA: 3, 5-dicaffeoyliquinic acid; CGA: chlorogenic acid; NCGA: neochlorogenic acid; CC: catechin; ECC: epicatechin.

férulique, 3, 5-dicaféoylquinique, chlorogénique et neo-chlorogenique, la catéchine et l'épicatéchine sont des composés phénoliques présents dans l'épiderme des pêches (Prunus persica). Les objectifs de mon travail de stage étaient d'évaluer leur effet sur la germination des conidies et la pathogénicité de Monilinia laxa sur pétales. Les six génotypes d'amandier testés et le génotype "8858" de pêcher étaient relativement résistants à M. laxa. À une concentration de 2 mM, tous les composés ont montré un effet inhibiteur significatif du développement de M. laxa sur les pétales d'amandier "ZH81". L'acide férulique à 2 mM a inhibé presque entièrement le développement des lésions sur les pétales de tous les génotypes de Prunus spp. ainsi que la germination des conidies et la croissance du mycélium sur des milieux artificiels. À des doses plus basses jusqu'à 0,5 mM, il a significativement inhibé M. laxa in vivo. Les acides caféique et p-coumarique avaient un effet inhibiteur sur la croissance des lésions sur pétales, ainsi que sur la germination des conidies et la croissance du mycélium in vitro. Autres composés ont montré des effets inhibiteurs variables sur la croissance des lésions, mais aucun effet significatif sur la germination des conidies. L'hypothèse proposée est que les 8 composés phénoliques étudiés ont différents modes d'action pour leur effet inhibiteur, en relation avec leur structure chimique, qui sont

Acknowledgments

I would like to thank firstly, all the faculty of the University of Avignon and the professionals implicated in the training of the Masters "Quality Management of Plant

unit, for allowing me to conduct this internship.

Conclusions and Future Prospects

The inoculation technique used in this study simulated natural M. laxa infection on humid and wet Prunus sp. petals. Based on results of our study, susceptibility of tested genotypes was: peach "8858" < almond "xa1", "xa2", "xb", "p3606", "ZH4" and "ZH81" < apricot "A2312" < peach "7970" and sweet cherry "ce". Some of them such as ZH81 and 8858 present a stable capacity of resistance against M. laxa, while the others were relatively variable. Their physiological state and sensitivity to storage conditions could explain this different variability among cultivars. This further suggests that tests with flowers should (i) be carried out with large numbers of independent repetitions and (ii) that care should be taken to document well the physiological state / storage conditions of the flowers used in such tests in the laboratory.

The concentrations of 10% ethanol did not have any significant inhibitory effect on lesion growth on petals compared with sterile water, while, upward of 1.25% ethanol significantly inhibited mycelial growth in vitro. Ethanol at concentrations of 10% and 20% has been used together with hot water to control postharvest decay of peaches against Monilinia diseases [START_REF] Margosan | Combination of hot water and ethanol to control postharvest decay of peaches and nectarines[END_REF]. For this study, the effects of ethanol had always be checked and limited.

Observations of lesion growth and microscopy of the petal segments clearly showed that FA (2 mM) was effective in inhibiting lesion development even though germination of M. laxa was not systematically inhibited on petals. On artificial substrates, the significant inhibition by FA of conidial germination and mycelial growth occurred at a relatively low concentration of 0.5 mM.

Compounds CA and PCA have a same base of chemical structure (dihydroxycinnamic acid) as FA, with a difference in the functions combined (table 1). The compared inhibitory effect in vivo and in vitro of those three compounds was concordant: FA > PCA > CA. The role and position of the phenolic function could be hypothesized to be related to the inhibitory effect.

Compounds CGA and NCGA are isomers, as well as CC and ECC and DCQA has a same part of the chemical structure as CGA and NCGA (caffeoylquinic acid which has two available phenolic functions). However, in vivo and in vitro data of these five compounds were generally varied. On petals of Prunus, inhibitory effects were observed on specific genotypes such as almond ZH81. But on artificial media, no-significant inhibition of

ANNEX. I. Effect of phenolic compounds on disease development.

Abbreviation: CA: caffeic acid; PCA: p-coumaric acid; FA: ferulic acid; DCQA: 3, 5-dicaffeoyliquinic acid; CGA: chlorogenic acid; NCGA: neochlorogenic acid; CC: catechin; ECC: epicatechin. PI: protection indices (%).


Nicolas Picard

Laurent Saint-André

Matieu Henry

published or not. The documents may come

Expert meeting on tree volume, biomass allometric equations and biomass expansion factors

• Manual for tree allometric equations

-

  -André (CIRAD -INRA), and M. Henry (FAO) From the idea….(born in 2005) Students are not familiar with the appropriate and up-to-date fitting techniques û the "magic" R2 is usually preferred to the biological meaning of the equations û Models are fitted without considering the structure in the data set (source of variations) û And so on …. There was a strong need to make a new review on tree allometric equations Including biological concepts, up-to-date statistical procedures and training examples Outliers are too easily removed from the data set while they can bring information on the structure of the dataset û ……To the result (2012) Picard N., Saint-André L., Henry M. 2012. Manuel de construction d'équations allométriques pour l'estimation du volume et la biomasse des arbres: de la mesure de terrain à la prédiction. Organisation des Nations Unies pour l'alimentation et 'agriculture, et Centre de Coopération Internationale enThere are some range of variations of wood production at a given top height (variations related to the stockability issue)


Results

Least Cost Paths

Capacity to choose the LCP depends on complete landscape knowledge LCP may not be the best route for feeding,breeding or resting

Circuit models

Resistance surface optimization

  distance subdivided into land-use types, weight of land-uses optimized 3. Distance (m) along the Least Cost Path 4. Pair-wise resistance

Forest

  patches in agricultural landcapes are not the same as oases in the desert But not all forest patches provide a wealth of resources Both secondary forest and agricultural areas may provide resources But all agriculture and secondary forests do not provide the same resources Annual changes in crops and management may impact pollinator behaviour more than fragmentation Use of bee hives may change pollination patterns from year to year Straight lines out-perform least cost path and resistance surfaces Habitat Models and Resource Models may both applydepending on the density of resources in the landscape? Conclusions Pollination does not occur in a binary landscape of habitat and non-habitat Land-use matters! Conclusions


Marie-Anne A Lelu-Walter

M Vallance

C Teyssier

C Le Metté

P Label

Towards the integration of somatic embryogenesis in Larix breeding program : from understanding the developmental pathway to clonal propagation

Genetic information processing

  Protein • ihp RNA early stage of SE LmGER1-GUS expression during SE maturation Mathieu et al. Plant Mol Biol 2006 LmGER1-GUS expression in IR-PTGS transformed embryonal masses (9 independant lines T1-T9) I R O N MENT Scion 14th February 2012 Decrease during maturation : 73 spots Increase during maturation : 90 spots 163 significant spots (p value < 0,001, ratio >1.8)

-•

  High efficiency in plant regeneration -Maintenance of juvenility via cryopreservation To maximize breeding efficiency of forest trees For accelerating deployment of improved varieties 1957: first provenance trials for European and Japanese larches • 1970: establishment of European (350 clones) and Japanese (300 clones) larch breeding populations • 1979: first hybrids produced by control crosses • 1978-1985: plantation of pure species + hybridisation seed orchards • 1981-1989: development of 'bulk' vegetative propagation by cutting • 1990-1999: development of somatic embryogenesis • 2005: certification of a new hybrid variety Larix eurolepis (Larix decidua x L. marschlinsii) INRA H1, REVE VERT


domain: sdv sde

text:
Jérôme Ogée

Lisa Wingate

A process-based interpretation of high-resolution tree-ring stable isotope variations: from simple to more complex models

. This model comparison will be carried out against a new high-resolution stable isotope tree-ring dataset from five coniferous FLUXNET sites spanning a significant gradient of moisture (MAP range of 280 to 930mm) and temperature (MAT range of -1 to 18 o C). This environmental gradient allowed us to test the need for added complexity in process-based models and understand better the drivers of tree-ring isotope signals from a plant physiological perspective.


Laurent Chaunier

Anne-Laure A.-L Reguerre

Denis Lourdin

HAL is

 EUFOAM 2012Conference Lisbon, Portugal, 8 -11 July, 2012Submitted for Eufoam 2012

SHAPE MEMORY AND THERMOMECHANICAL PROPERTIES OF STARCH-BASED FOAMS

Laurent Chaunier, Anne-Laure Réguerre and Denis Lourdin INRA-UR1268, Unité Biopolymères Interactions et Assemblages. F-44300 Nantes chaunier@nantes.inra.fr Shape-memory polymers are an emerging class of smart materials [Liu, 2007]. Recent studies evidenced the possible storage of residual stresses in vitreous starch, leading to shape memory capabilities [Chaunier, 2009;Véchambre, 2010]. In the present work, the shape recovery of starch-based extruded foams was investigated when triggered by heating in oil, or water bath. Its efficiency was linked to their thermo-mechanical properties.

Maize flour was formulated with sugars and extruded as dense and expanded materials (Ødie=2mm, Tdie= 170°C, SME=190J/g). When cooled below their glass transition temperature (Tg) at the outlet of the die, a first "permanent" shape S1 was obtained : straight cylinders (L=50mm). The moisture content was equilibrated at 9% (wb) under a stable relative humidity (RH=59% at 20°C). The density was 0.6g/cm 3 for the expanded products and 1.5g/cm 3 for the dense materials. Tg was measured by Differential Scanning Calorimetry (DSC) at 52°C. A second shape, S2, was given above Tg by bending each straight specimen to θmax=180°. This "temporary" shape was fixed when cooling below Tg and the bent samples were stored at a low humidity level. Then, each specimen spontaneously recovered its "permanent" straight shape when heated or submitted to moisture uptake. The shape recovery was assessed in thermostated bath by images acquisition and analysis (Fig. 1-a), to determine the recovered angle (θ) and to obtain the recovery ratio (Rr), as presented on Eq.1 : Rr=(θmax-θ)/θmax*100 (1).

Figure 1: Assessment of the recovered angle (θ) by images acquisition and analysis on immersed specimen in thermostated bath (a). Evolution of the recovery ratio, Rr, in oil bath at Tg+50°C () and in water at 85°C () (b).

An important recovery was obtained with starch-based foams when triggered by heating in oil bath (Rr=80% after 2min at Tg+50°C, Fig. 1-b). Values were less important in the case of their recovery in water (Rr=46% after 4min). This was mainly due to their loss of stiffness, because of the water sorption. It led to a decrease of the modulus, measured by DMA from E'=2 GPa to 0.3 MPa, for the dense material constitutive of their gaseous cells walls.

In the light of these results, starch-based foams can be designed with an interesting shape recovery, especially when triggered by heating. This opens the field of new self-deploying smart biodegradable foams, even being edible.

EUFOAM2012 Topic : C -Particles in Foams, Solid Foams Preferred type of presentation (Oral or Poster) : Oral


François Balfourier

Audrey Didier

Marion Deloche

Lionel Bardy

A worlwide bread wheat sample for the French BREEDWHEAT project

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

Context: BREEDWHEAT is a "genomics to breeding" precompetitive national project built along a chain starting with the establishment of tools, methods and plant material for association genetics and ecophysiolgical studies of yield and quality components under abiotic and biotic stress, down to the evaluation of new breeding methods and the creation of prebreeding material that will support the selection of improved wheat varieties. In the framework of this project, a specific task in work-package 3 (WP3) is dedicated to the definition of a worldwide wheat sample of 4600 accessions from the global INRA collection, in order to analyse genetic diversity in wheat germplasm and deliver two panels of 'easy to use accessions' for association analyses on biotic and abiotic stress tolerance in other WPs.

Conclusion:

This sample should permit to answer to the objectives of the BREEDWHEAT project. Furthermore, deliverable molecular data of WP1(400.000 SNPs) on this sample of 4600 accessions should allow diverse population genetic analyses, such as multiple comparisons of genetic diversity evolution (between countries, between regions within country, between registration periods, between breeders, …) and analysis of diversity at different time and eco-geographical scales.

The initial INRA bread wheat collection consisted on 11960 accessions originating from 108 different countries. Available data on this collection mainly consist on passport data: geographical origin (country, region, state, department,..), status (landraces, breeding lines, cultivars, elite lines,..) registration period, habit (spring, intermediate or winter type) and pedigrees. Some molecular data, previously obtained on a part of the whole collection, highlighted the importance of both geographical and temporal effects in structuring the genetic diversity of this collection (Balfourier et al. 2007;Roussel et al. 2004Roussel et al. , 2005)).

The methodology used consists on sampling an optimal worldwide diversity sample mainly based on available passport data. The selected sample of 4600 accessions produces a balanced sample size between countries, regions and registration periods, able to reflect the genetic structure of wheat genepools.


Aude A Watrelot
email: aude.watrelot@avignon.inra.fr

Anne Imberty

Catherine M G C Renard

Carine Le

Carine Le Bourvellec

Calorimetric study of interactions between procyanidins and pectins

HAL is

Polyphenols and polysaccharides are located in two distinct compartments in vivo: vacuoles and cell walls respectively. When cells are ruptured during chewing for example, these compounds bind together, which limits bioaccessibility of polyphenols and extractability of polysaccharides. It has already been shown that procyanidins (condensed tannins) interact with polysaccharides and that the affinity of procyanidins for pectins is higher than for hemicelluloses [1]. The pectins -procyanidins adsorption mechanism involves hydrogen bonds and hydrophobic interactions [2]. We present here a characterization by microcalorimetry and phase diagram of interactions between procyanidins and pectins, and the impact of the structure of both pectins and procyanidins.

Procyanidins with intermediate and high degrees of polymerization (DP9 and 30) were extracted from freeze-dried pulps of cider apple cultivars (cv. "Marie Ménard" and "Avrolles" respectively) as described in [1]. Rhamnogalacturonans (RG) and homogalacturonans (HG) of low (30) and high (70) degrees of methylation were prepared from commercial apple pectin as described in [3]. Different hairy regions with a variation of neutral sugars composition were extracted from apple pomace (AHR), or from sugar beet pulp (SBHR) or from apple, pear and onion (MHRa, MHRp and MHRo). Those MHRs (Modified Hairy Regions) fractions were a kind gift from Dr Henk Schols. Pectic fractions (3.75 mmol/L galacturonic acid equivalent), dissolved in citrate/phosphate buffer pH 3.8 were titrated by procyanidins (7.5 mmol/L epicatechin equivalent) in VP-ITC instrument (Microcal®, GE Healtcare). After precipitation, supernatants of procyanidins in buffer and pectins in procyanidins solution were analyzed by HPLC-DAD after thioacidolysis and HPSEC.

Microcalorimetry demonstrated that association between procyanidins and commercial pectins, HG, RG, AHR and HR-H were driven by entropy indicating that hydrophobic interactions are implicated. However an unfavorable entropy contribution was obtained between procyanidins and MHRp and MHRo suggesting association via hydrogen bonds. Procyanidins DP9 associated with commercial pectins and hairy regions with comparable affinity constant (in the order of 10 3 M -1 ) but not with HG. Procyanidins of DP30 interacted with all pectic regions. The higher the degree of methylation of HG, the higher the affinity. Hairy regions (AHR and MHRp rich in arabinose, SBHR and MHRo rich in galactose) showed different affinity constants (574 M -1 for AHR and 875 M -1 for MHRp against 5390 M -1 for SBHR). The supernatant contained procyanidins with a much decreased DP (ΔDP = -20.5) after interaction with AHR, while DP increased (ΔDP of 5.8) with SBHR. The largest procyanidins preferentially aggregated with AHR, while the smallest aggregated with SBHR.

The structure and conformation of both pectins and procyanidins influenced the interactions. Others methods such as surface plasmon resonance will be used to determine kinetic of association and dissociation of procyanidins/pectins complexes.


Christian Wolf
email: christian.wolf@liris.cnrs.fr

-Gérald Gavin
email: gerald.gavin@liris.cnrs.fr

Inference and parameter estimation on belief networks for image segmentation

Keywords: Image segmentation, hierarchical model MOTS-CLÉS : Ségmentation d'images, modèles hiérarchqiues

We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains cycles. Each level of the hierarchical structure features the same number of sites as the base level and each site on a given level has several neighbors on the parent level. Compared to tree structured models, the (spatial) random process on the base level of the model is stationary which avoids known drawbacks, namely visual artifacts in the segmented image. We propose different parametrisations of the conditional probability distributions governing the transitions between the image levels. A parametric distribution depending on a single parameter allows the design of a fast inference algorithm on graph cuts, whereas the parameter is estimated with a least squares technique. For arbitrary distributions, we propose inference with loopy belief propagation and we introduce a new parameter estimation technique adapted to the model. RÉSUMÉ. Dans ce papier, on présente un nouveau réseau bayesien hiérarchique dédié à la segmentation d'images. Contrairement aux modèles classiques (e.g. le quad arbre), le graphe associé à ce réseau bayesien contient des cycles. Chaque niveau de cette structure hiérarchique contient autant de sommets que le niveau de base (qui contient lui-même autant de sommets que l'image à segmenter contient de pixels) et chaque sommet a plusieurs parents sur le niveau supérieur. Contrairement aux structures d'arbre classiques, ce modèle possède la propriété de stationnarité ce qui signifie qu'il est invariant aux translations de l'image. Le présence de boucles dans le modèle proposé rend le problème de l'inférence exacte délicat. L'apport majeur de ce papier, outre le modèle lui-même, est la présentation d'un algorithme d'inférence exact basé sur le problème classique de graphes, à base de maximisation de flots.

Introduction

Image segmentation techniques aim at partitioning images into a set of non overlapping and homogeneous regions taking into account prior knowledge on the results as well as a probabilistic model of the observation (degradation) process. Belief networks, but also undirected probabilistic graphical models are widely used to incorporate spatial dependencies between the image pixels into the classification process, very often modeling the problem as Bayesian estimation.

In their seminal paper [START_REF] Geman | Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images[END_REF], Geman and Geman introduced a maximum a posteriori (MAP) estimation technique for Markov random fields (MRF). An alternative to the two-dimensional MRFs are hidden Markov chains (MC) on onedimensional traversals (Hilbert-Peano scans) of an image [START_REF] Abend | Classification of binary random Patterns[END_REF] or hybrid MC/MRF techniques [START_REF] Fjortoft | Unsupervised Classification of Radar Images Using Hidden Markov Chains and Hidden Markov Random Fields[END_REF]. The Markov chain models have been extended to belief networks with a pseudo 2D graph structure [START_REF] Kuo | Keyword Spotting in Poorly Printed Documents Using Pseudo 2-D Hidden Markov Models[END_REF] and to full 2D connectivity [START_REF] Pieraccini | Dynamic Planar Warping for Optical Character Recognition[END_REF].

Hierarchical models introduce a scale dependent component into the classification algorithm, which allows the algorithm to better adapt itself to the image characteristics. The nodes of the graph are partitioned into different scales, where lower scale levels correspond to finer versions of the image and higher scale levels correspond to coarser versions of the image. Examples are stacks of flat MRFs [START_REF] Bello | A combined Markov random field and wave-packet transform-based approach for image segmentation[END_REF], pyramidal graph structures [START_REF] Kato | A hierarchical Markov Random Field Model and Multitemperature annealing for Parallel Image Classification[END_REF] and the scale causal multi-grid [START_REF] Mignotte | Sonar Image Segmentation Using an Unsupervised Hierarchical MRF Model[END_REF]. Bouman and Shapiro were among the first to propose a hierarchical belief network for image segmentation [START_REF] Bouman | A Multiscale Random Field Model for Bayesian Image Segmentation[END_REF] (refined by Laferte et al. [START_REF] Laferte | Discrete Markov image modelling and inference on the quad tree[END_REF]). A quad tree models the spatial interactions between the leaf pixel sites through their interactions with neighbors in scale. The main problem of the quad tree structure is the non stationarity it induces into the random process of the leaf sites, which results in "blocky" artifacts in the segmented image.

In the same paper a second model is proposed, where each node has three parents. At first sight, the structure of the dependency graph is similar to our solution (which features four parents for each site), however, the model proposed by Bouman is a pyramidal model in that the number of nodes decreases at each level. Moreover, as an approximation the inference algorithm proposes a change of the graph after each inference step, whereas in our work the whole graph keeps its full connectivity.

The work described in this paper concentrates on the solution to the lack of shift invariance of the quad tree structured network. Our new model combines several advantages:

-Adaptation to the image characteristics with a hierarchical graph structure (similar to the quad tree) -A stationary random process at the base level (where each site corresponds to one pixel of the input image).

-Fast inference using minimum cut/maximum flow algorithms for a subclass of transition probability distributions.

¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ £ £ £ £ £ £ £ £ £ £ £ £ £ £ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § ¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨© " " " " " " " " " " " " " " " " " # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ £ £ £ £ £ £ £ £ £ £ £ £ £ £ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § ¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨© " " " " " " " " " " " " " " " " " # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ Figure 1.
The quad tree structured model with and without observed nodes.

The paper is organized as follows: section 2 describes the quad tree structured network and section 3 extends it to the cube. Section 4 presents an inference algorithm using loopy belief propagation and section 6 presents a fast inference algorithm for a parametric class of transition probability distributions. Section 7 describes parameter estimation for the latter class of distributions and section 5 introduces an estimation technique for a nonparametric family of transition probability distributions. Section 8 discusses the computational complexity and memory requirements and section 9 experimentally valides the method. Finally, section 10 concludes.

Quad tree structured models

In the following we describe belief networks, thus graphical models defined on a directed acyclic graph G = {G, E}, where G is a set of nodes (sites) and E is a set of edges. The edges of the graph assign, to each site s, a set of parent sites (written as s -) and a set of children sites (written as s -). The hierarchical nature of the graph partitions the set of nodes into levels G (i) , i ∈ 0..L -1, G (0) being the base level corresponding to finest resolution.

Each site s is assigned a discrete random variable X s taking values from the label set Λ = {0, . . . , C -1} where C is the number of classes. X G , or short X denotes the field of random variables of the graph, whereas X G (l) denotes the field of random variables at level l. The space of all possible configurations of the field X is denotated as Ω = Λ |G| .

In the case of the quad tree structured model [START_REF] Bouman | A Multiscale Random Field Model for Bayesian Image Segmentation[END_REF][START_REF] Laferte | Discrete Markov image modelling and inference on the quad tree[END_REF], the graph G forms a tree structure with a single root node r ∈ G (L-1) , four children nodes for each node and a single parent node for each node except the root node (see Fig. 1). Each hidden variable X s is related to an observed variable Y s which is conditionally independent of the other observed variables given a realization of X s : P (y s |x) = P (y s |x s ) and P (y|x) = s∈G P (y s |x s ) (see Fig. 1) . The objective is to estimate the hidden variables x given the observed variables y. In this paper we

¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ § § § § § § § § § § § § § § § § § § § § § § § § § § § § ¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨¨© ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) (a) (b)
Figure 2. A one dimensional representation of the stepwise extension of the quad tree (shown as a dyadic tree) to the cube consider maximum a posteriori estimation (MAP) estimation which corresponds to the mode of the posterior distribution:

x = arg max x∈Ω p(x|y) = arg max x∈Ω p(x)p(y|x) [1]
The absence of cycles in the dependency graph allows the application of optimization techniques similar to the ones used for the Viterbi algorithm [START_REF] Jr | The Viterbi Algorithm[END_REF][START_REF] Viterbi | Error bounds for convolutional codes and an asymptotically optimal decoding algorithm[END_REF] computing the optimal configuration using dynamic programming.

The proposed cube structured model

The main disadvantage of the Markov quad tree is the non stationarity introduced into the random process of the leaf sites G (0) due to the fact that, at any given level, two neighboring sites may share a common parent or not depending on their position on the grid. We therefore propose an extension shown in Fig. 2b (for easier representation the one dimensional case -a dyadic tree -is shown)

First, a second dyadic tree is added to the graph, which adds a common parent to all neighboring leaf sites which did not yet share a common parent. In the full two dimensional case, three new quad trees are added. The problem is solved for the first level, where the number of parents increased to 4 (for the full 2D model). We repeat the process for each level. New trees connect sites of the original quad tree, but also sites of the trees added at the lower levels. The final result can be seen in Fig. 2b. Note, that the final graph is not a pyramid anymore, since each level contains the same number of nodes. In general, each node has 4 parents (2 in the 1D representation) except border nodes.

The whole graph can be efficiently implemented by a cube of dimensions N × M × log 2 max(N, M ) , N × M being the size of the image. In practice, the full height H of the cube is not always required. The parents and children of site s with coordinates x and y on level l are given as follows:

s -=        x + ∆ n , y + ∆ n x + ∆ n , y + ∆ p x + ∆ p , y + ∆ n x + ∆ p , y + ∆ p s -=        x + ∆ n , y + ∆ n x + ∆ n , y + ∆ p x + ∆ p , y + ∆ n x + ∆ p , y + ∆ p [2]
where

∆ n = -1 if l = 0 -2 l-1 else ∆ p = 0 if l = 0 2 l-1 else ∆ n = 0 if l = 1 -2 l-2 else ∆ p = 1 if l = 1 2 l-2 else [3]
The graph as it is described in Fig. 2d (in a 1D representation) corresponds to the hidden part, i.e. the prior model p(x) in the Bayesian sense. The full Markov cube including observed nodes is parametrized through three probability distributions: the discrete prior distribution of the top level labels p(x), the transition probabilities p(x s |x s -) and the likelihood of the observed nodes given the corresponding hidden nodes p(y s |x s ) -a probability density.

For the inference algorithm, observations at different cube levels are needed. In most cases this will require resampling the data in all levels except the finest one.

Inference with loopy belief propagation

Loopy belief propagation [START_REF] Pearl | Probabilistic Reasoning in Intelligent Systems[END_REF]) is an approximative inference technique for general graphs with cycles. In practice, convergence does occur for many types of graph structures. Murphy et al. present an empirical study [START_REF] Murphy | Loopy belief-propagation for approximate inference: An empirical study[END_REF] which indicates that with LBP the marginals often converge to good approximations of the posterior marginals.

Loopy belief propagation is equivalent to the sum-product (or max-product) algorithm proposed for factor graphs [START_REF] Kschischang | Factor Graphs and the Sum-Product Algorithm[END_REF]. Any directed or undirected dependency graph can be transformed into a factor graph which contains two different types of nodes: variable nodes corresponding to the random variables of the model and factor nodes corresponding to the factors of the joint probability distribution. Figure 3 shows the 1D representation of a Markov cube without observed nodes as well as a small part of the full 2D Markov cube with observed nodes and their corresponding factor graphs.

The sum-product algorithm operates by passing messages between the nodes of the graph, each message being a function of the corresponding variable node. Due to the nature of our graph, there are two types of messages: messages from a variable node to a factor node, and the opposite:

-messages from a variable node x s upwards to the factor node. -messages downwards to a variable node x s coming from the factor node.

¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ £ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¤ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ ¦ § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § § (a) (b) (c) (d)
-for each child x c of a variable node x s , a message from x s downwards.

-for each child x c of a variable node x s , a message upwards to x s .

The message passing schedule for the Markov Cube alternates between bottom up passes and top down passes.

Interpretation of the hidden variables

In this section, we propose a methodology to estimate the conditional probability distributions p(x s |x s -) by taking into account statistical invariance of images belonging to the same corpus. Concretely, we propose to give an interpretation of the hidden variables x s (i.e. the variables belonging to level l>0) such that :

1) the independence model given by the structure is satisfied. Given a topological numerotation of vertices, a variable x s should be independent of all smaller index variables given its parents x - s . 2) the conditional probabilities are significantly different of conditional probabilities obtained on randomly binary images.

3) the conditional probabilities are close for all images of the corpus For simplicity reasons, in the following we describe the binary case (C = 2), the adaptation to multiple labels is straightforward. The Let x s be a vertex of the Markov cube and l its level. We call U x the set of vertices of level 0 reachable by a directed path from x. U xs is a 2 l * 2 l square on the image. Then, we naturally define the class of x s as the class with the maximum number of variables U xs (in case of equality, we choose the class randomly). In order to achieve estimation, we just have to compute the frequency of label 0 (resp 1) for each parent configuration. In the corpus used in the experiments, the 3 issues claimed above were verified. This interpretions allows several strategies for unsupervised estimation of the conditional probabilities:

-Nonparametric definition of the conditional probabilities. Given initial labels at the base level, the labels at the upper levels are computed as described above and the probabilities are estimated using histograming.

-Parametric functions are fitted to the histograms. This strategy is pursued in the next section.

Inference with minimum cut/maximum flow

Algorithms calculating the minimum cut/maximum flow in a graph are a powerful tool able to calculate the exact MAP solution on a number of binary labeling problems (D.M. Greig et al., 1989;[START_REF] Boykov | An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision[END_REF][START_REF] Boykov | Fast Approximate Energy Minimization via Graph Cuts[END_REF]Kolmogorov et al., 2004) with low order polynomial complexity. It has been shown recently, that energy functions for which the optimal solution is equivalent to the minimum cut in an appropriate graph contain only "regular" terms on binary labels (Kolmogorov et al., 2004), where regular means that any projection of a term E(x i , x j , x k , . . . ) onto any subset of two of its arguments satisfies the following condition:

E(0, 0) + E(1, 1) ≤ E(0, 1) + E(0, 1) [4]
In the case of the proposed model, not all energy terms are regular, especially the terms corresponding to the logarithm of the transition probabilities ln p(x s |x s -), so the general model cannot be solved with graph cuts. However, for a large sub class with interesting properties, graph cut solutions can be found. We propose a regularizing term based on the number of parent labels which are equal to the child label:

P (x s |x s -) = 1 Z α ξ(xs,x s -) l [5]
where α l is a parameter depending on the level l, ξ(x s , x s -) is the number of labels in x -equal to x s and Z is a normalization constant. The such defined transition probabilities favor homogeneous regions which corresponds to the objective of an image segmentation algorithm. We then decompose it into a sum of binary terms:

ln p(x s |x s -) = s ∈s - [(ln α) δ xs,x s ] -Z [6]
where δ a,b is the Kronecker delta defined as 1 if a = b and 0 else. It should be noted that each binary term is regular in the sense of [START_REF] Kolmogorov | What Energy functions can be Minimized via Graph Cuts?[END_REF]. 3b, including the two terminal nodes S and T . For more than 2 labels, the expansion move algorithm ressorts to a similar graph.

term ln p(x s = 1)/p(x s = 0). Additionally, each non terminal node is connected to each of its parents with an undirected edge and weight ln α.

Minimum cut algorithms are restricted to binary labeling problems (C = 2). Discontinuity preserving energy minimization with multiple labels is NP-hard [START_REF] Boykov | Fast Approximate Energy Minimization via Graph Cuts[END_REF], but the α-expansion move algorithm introduced in [START_REF] Boykov | Fast Approximate Energy Minimization via Graph Cuts[END_REF] allows to find a local minimum with garantueed maximum distance to the global minimum. It consists of iteratively applying the minimum cut algorithm to the sub problem of labeling each node of the whole graph between two labels: keeping the current label and changing the a new label α, which is changed at each iteration.

Parameter estimation with least squares

We chose the unsupervised technique Iterated Conditional Estimation (ICE) [START_REF] Pieczynski | Convergence of the Iterative Conditional Estimation and Application to Mixture Proportion Identification[END_REF] for parameter identification. Given supervised estimators of the parameters from a realization of the full set of variables (X, Y ), an iterative procedure alternates between estimating the parameters and creating realizations of the label field based on the current parameters. The initial set of parameters can be obtained from an initial segmentation of the input image.

The prior probabilities of the top level labels β i can be estimated using histogram techniques. Similarly, for most common observation models, maximum likelihood estimators of the sufficient statistics of the conditional distributions are readily available. In this paper, we work with a simple observation model assuming Gaussian noise, requiring as parameters means and (co)-variances for each class. Arbitrary complex likelihood functions are possible using Gaussian mixtures.

For the parameters α l of the transition probabilities, we propose a solution based on least squares estimation similar to the works proposed by Derin et al. for the estimation of Markov random field parameters [START_REF] Derin | Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields[END_REF]. For each level l, we consider pairs of different site labels x s and x s (s ∈ G (l) ) with equal parent labels x s -= x s -. Note that the parent sites are different, whereas their labels are equal. From (5) the following relationship can be derived:

P (x s |x s -) P (x s |x s -) = α ξ(xs,x s -) l α ξ(x s ,x s -) l [7]
Expressing the conditional probabilities through absolute probabilities and taking the logarithm we get:

ln α l [ ξ(x s , x s -) -ξ(x s , x s -) ] = ln P (x s , x s -) P (x s , x s -) [8]
The right hand side of the equation can be estimated from the label process, e.g. by histogramming, whereas the factor in the left hand side can be calculated directly.

Considering a set of different label pairs, we can augment this to

b T [ln α l ] = a [9]
where b is a vector where each element corresponds to the value in the left hand side of equation ( 8) for a given label pair and each value in the vector a corresponds to the right hand side of equation ( 8) for a given label pair. The solution of the over determined linear system can be found using standard least squares techniques.

Complexity and storage requirements

Inference complexity for loopy belief propagation (LBP) can be given as

O(I • N • M • (H -1) • C 5
) where I is the number of iterations. H is the height of the cube and bounded by log 2 max(N, M ) . Storage requires N • M • (H -1) • 15C variables.

In practice, LBP in its original form is applicable for low numbers of classes (2, 3 or maximum 4), which is enough for a large number of problems. For higher numbers of classes, the classes may be quantisized and the message passing equations slightly changed.

Inference with minimum cut/maximum flow is considerable faster with a complexity bounded by O(E * f ), where E is the number of edges in the graph and F is the maximum flow. We use the graph cut implementation by [START_REF] Boykov | An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision[END_REF] which has been optimized for typical graph structures encountered in computer vision and whose running time is nearly linear in running time in practise [START_REF] Boykov | Fast Approximate Energy Minimization via Graph Cuts[END_REF]. Table 1 gives effective run times and memory requirements measured on a computer equipped with a single core Pentium-M processor running at 1.86Ghz and 1GB of RAM.

Experimental results

We applied the model to two common problems in document image analysis: binarization (C = 2) and ink bleed through, i.e. the removal of the verso side of the scanned image assuming that a verso scan is not available, which makes it a three class segmentation problem (C = 3).

In all experiments, we initialized the label field with k-means clustering after low pass filtering. The algorithms are vulnerable to numerical instabilities, we therefore resort to a widely used method calculating in the logarithmic domain.

We compared the cube model with different methods of the state of the art: flat MRF segmentation with a potts model and graph cut optimization (D.M. Greig et al., 1989;[START_REF] Boykov | Fast Approximate Energy Minimization via Graph Cuts[END_REF], a quad tree [START_REF] Laferte | Discrete Markov image modelling and inference on the quad tree[END_REF] and k-means clustering. The k-means algorithm is only method whose performance is improved when the image is low pass filtered before the segmentation.

To be able to evaluate the model quantitatively, we applied it to 30 synthetic images of size 512×512 (60 images total) and very low quality subject to multiple degradations: low pass filtering, amplification of ring shaped frequency bands causing ringing artifacts, low quality JPEG artifacts and additional Gaussian noice in various stages (with variances between σ=20 and σ=40). Table 1 shows the error rates on the different sets.

Figure 5 shows the results of the same methods applied to a real scanned document image. The images depict the restoration result, i.e. an image where the gray values of the pixels classified as "verso" have been replaced by the gray values of the nearest background pixels. As can be seen, the k-means result is noisy and the quad tree result tends to be blocky at some points. The MRF result is similar to the cube result, but tends to misclassify text pixels which are part of very fine structures.

Conclusion and discussion

In this paper we presented a new causal model which features the advantages of hierarchical models, i.e. scale dependent behavior and the resulting adaptivity to the image characteristics, without the main disadvantage of the quad tree model, i.e. the lack of shift invariance. Bayesian maximum a posteriori estimation on this model has been tested on binarization and ink bleed through removal tasks for document images and compared to widely used graphical models. Segmentation quality is better or equal to the results of a MRF model, the difference depending on the scale characteristics of the input image and the nature of the degradation. We proposed two inference algorithms: loopy belief propagation and an algorithm based on graph cuts for regular transition probability distributions. In future work we will extend the cube to a conditional (discriminative) model.

Figure 3 .

 3 Figure 3. A cube in 1D without obervations (a) and a small part in 2D with observations (b) and the corresponding factorgraphs (c-d).

Figure 4 .

 4 Figure 4. The cut graph constructed for the binary problem from the dependency graph shown in Fig.3b, including the two terminal nodes S and T . For more than 2 labels, the expansion move algorithm ressorts to a similar graph.

Figure 5 .

 5 Figure 5. Restoration results on real images. From top to bottom, left to right: input image, kmeans+filtering, quad tree, MRF-GC, Cube-LBP, Cube-GC.

Table 1 .

 1 Execution times, memory requirements and segmentation performance for images of size 512×512 and (C=2)

	Method	MB seconds Error rate
	K-means	1	1	27.01
	K-means (incl. low pass filter)	1	1	9.01
	Quad tree	5	1	7.57
	MRF-GC	∼20	2	6.28
	Cube-LBP (4 levels, non-parametric)	103	46	6.82
	Cube-LBP (4 levels, parametric)	103	46	6.91
	Cube-LBP (5 levels, parametric)	150	64	6.84
	Cube-GC (5 levels, parametric)	∼180	4	5.58

& & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & '


Carlos Lopez-Vaamonde

Rodolphe Rougerie

Applications of DNA barcoding to plant protection and biodiversity studies

Applications of DNA barcoding to plant protection and biodiversity studies


domain: sdv math info

text:
est destinée au dépôt

There is little empirical evidence for competitive exclusion resulting from antagonistic interactions between species exploiting a similar ecological niche. One robust framework of competition and coexistence theories states that spatial or temporal fluctuations in resource availability may consistently relax interspecific competition and thus favour species coexistence. However, if divergences in life-history traits between interacting species lead to asymmetrical abilities for resource exploitation, one would expect the more efficient species to be favoured whatever the level of resource availability and the less efficient one to be outcompeted. In southeastern France, the true cedar Cedrus atlantica displays years of large seed crops alternating with years of low or null seed crops, a phenomenon referred to as mast-seeding. The invasion of French cedar forests by the specialized seed chalcid Megastigmus schimitscheki Novitzky (Hymenoptera: Torymidae) in the mid 90's resulted in antagonistic interactions with a closely related resident species, M. pinsapinis Hoffmeyer, for the exploitation of such temporally variable seed resource. Here, we aimed at investigating if temporal fluctuations in cedar fructification may promote coexistence or competitive exclusion of M.schimitscheki and M. pinsapinis, which significantly diverge in their life-history.

A spatio-temporal demographic survey of M. pinsapinis (1977-2009) and M. schimitscheki (1994-2009) was conducted across the known ranges of these species in southeastern France. The demography of wasp species was assessed using annual seed infestation rates (SIR) in a total of 37 sampled sites. The pattern of temporal fluctuation in seed production was also characterized in 23 stands of C. atlantica from 2006 to 2011. We then developed a temporal population dynamics model for both M. schimitscheki and M. pinsapinis, integrating interannual variation in seed supply and earlier phenology, higher propensity to prolonged diapause and higher fecundity in M. schimitscheki than in M. pinsapinis. From 2006 to 2011, we found significant variation in inter-annual cedar seed production levels, with 2011 and 2009 being high seed production years whereas seed production was very low in 2010 and 2007. During the period preceding M. schimitscheki introduction (1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993), the mean SIR of M. pinsapinis was estimated to 16% ±2.12%. During the period following invasion (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009), the mean SIR of M. pinsapinis in sympatric areas with M. schimitscheki displayed a drastic decline (3.2% ± 0.5%) and reached the extremely low value of 0.19% (±0.12) in 2009. Parallely, SIR of M. schimitscheki had reached locally 79% during the same period. Our modelling approach suggested that propensity to prolonged diapause may directly influence the response of these wasps to fluctuations in resource availability. We thus describe here a very likely competitive exclusion of M. pinsapinis in sympatric areas with the invasive. Divergences in life histories may have a key role in the success of M. schimitscheki and the decline of M. pinsapinis despite a context of highly fluctuating resources. Key words: Interspecific competition, competitive exclusion, prolonged diapause, pulsed resource, Megastigmus, Cedrus.

  Diverging life-histories constrain the coexistence of two seed-specialized wasp species competing for a temporally fluctuating resource Cindy Gidoin, Lionel Roques, Jean-Noël Candau, Alain Chalon, Marion Sondo, Thomas Boivin To cite this version: Cindy Gidoin, Lionel Roques, Jean-Noël Candau, Alain Chalon, Marion Sondo, et al.. Diverging life-histories constrain the coexistence of two seed-specialized wasp species competing for a temporally fluctuating resource. IUFRO 7.03.01 "Cone and seed insects" and 7.03.04 "Diseases and insects in forest nurseries" Working Party Meeting., Feb 2012, Vilnius, Lithuania. 1 p.

hal-02805206 ABSTRACTS of joint IUFRO 7.03.01 "Cone and seed insects" and 7.03.04 "Diseases and insects in forest nurseries" Working Party Meeting. Vilnius, Lithuania, 16-20 September 2012 Diverging life-histories constrain the coexistence of two seed-specialized wasp species competing for a temporally fluctuating resource C. Gidoin 1 , L. Roques 2 , J.-N. Candau 1,3 , A. Chalon 1 , M. Sondo 1 and T. Boivin 1

	1 INRA, UR 629 Recherches Forestières Méditerranéennes, F-84914 Avignon, France
	2 INRA UR 546 Biostatistique et Processus Spatiaux, F-84000 Avignon, France
	3 National Resources Canada, Canadian Forest Service, Great Lakes Forestry Ctr, Sault Ste Marie, ON
	P6A
	2E5, Canada