Eric Rigolot
email: eric.rigolot@avignon.inra.fr

Jean-Luc Dupuy

Joël Maréchal

François Pimont

Comparing Pinus halepensis and Pinus pinea post fire mortality

Background: Mediterranean pines have developed different strategies to cope with fire. In that respect, Pinus halepensis and Pinus pinea have been classified as fire embracer and fire tolerater species respectively [START_REF] Keeley | Ecology and evolution of pine life histories[END_REF]. Preventive sylviculture needs to take into account the most recent knowledge on fire ecology of trees to implement successful guidelines. Self protection objective, the global post-wildfire survival of trees at the stand level, is certainly the most demanding option of preventive sylviculture.

Questions: Does differences in fire ecology of pines, justify developing specific preventive sylviculture guidelines?

Methods: An experimental fire has been carried out in early July 2011 in a mixed P. halepensis -P. pinea plantation of 16 years old, 20 km from Avignon, France. Five years before burning trees were pruned at 2 m high and stand density was reduced to 1500 stem/ha with even proportion of each species. P. halepensis were higher and bigger than P. pinea (Table 1). Undergrowth fuel was replaced by straw uniformly spread with a 10 t/ha load. Fire weather conditions were severe (IFM >100) with dry and hot (27°C) conditions and gusty wind (55 km/h). Fire was characterized by measuring fire rate of spread, and flame geometry. Fire temperatures were estimated using thermometer strips distributed along 30 vertical gradients installed in pine crowns (2, 3, 4 and 5 m AGL). Immediate fire effects on pines were measured using both crown and bole damage indicators. Post fire pine mortality was monitored until stabilization in early 2013.

Results and discussion: Fire rate of spread was 0.18 m/s, and mean flame heights were 1-1.2 m and 1.5-2 m for flank fire and head fire respectively. Immediately after fire, mean crown volume scorched was higher on P. halepensis (81%) compared to P. pinea (56%). Crown scorched heights were consistent with estimated temperature levels according to the lethal temperatures usually reported in the literature. In particular, when temperature levels indicated by thermometer strips at 5 m above ground level were higher than 65°C, scorching was always above 5 meters.

Conclusion:

High post fire survival of P. pinea under severe fire conditions suggests this species is a good candidate for preventive sylviculture including implementation of self protection objective in relatively young stands. Preventive sylviculture has to adapt to the specific fire ecology of pines.


Pierre-François Puech

F Cianfarani

H Albertini

HAL is

Dental care for Mozart

Abstract. Valuable informations leading to the identification of Mozart's skull (1756Mozart's skull ( -1791) ) were obtained with extracttion replicas for stripping of superficial cells, particles of the original teeth and bone as well as animal, vegetal and mineral deposits accessible to nvestigation. Such replicas have allowed the scanning electron microscope examination and micro-analysis and therefore it is strongly recommanded that historic skeletons should only be investigated with great care, using replica techniques to 'flick away' material adjacent to surfaces.

Introduction. The identification of human remains in situation where exposure and time elapsed since death had destructed a great proportion of the soft tissues has frequently been based on morphological assessment and biological skeletal individualization. If little or no attention is generally payed to the presence of a variety of microscopic deposits and histological surface findings, a small number of distinctive characteristics based on morphology, endoscopy and quantitative distribution of chemical elements of particularities have not only provided scientists with identity informations but have also assisted investigators to formulate positive hypothesis to construct models and deduce their consequences. As part of a forensic study to determine the identification of the skull of Wolfgang Amadeus Mozart, we noted the presence of several surface individual characteristics. This paper reports the initial investigation under the scanning electron microscope in order to present accumulation of factors of individualisation needed for a positive identification.

Materials and Methods. The skull of Mozart, deposited in Salzburg, was exhumed in 1801 at the Saint-Marx cemetery in Vienna (1). The osteometrical and osteological conditions correspond with the available data concerning Mozart. He had an ultrabrachycephalic cranium with a broad midface, maxillo-alveolar prognathism and a retruded mandible. Presence of further separate conditional traits have improved the reliability of the identification and we noted an undescribed temporo-parietal fracture with an extra-dural hematoma imprint that poisoned the last part of his life and led to a fatal coma (2, 3 and 4). The size, characteristics of a skull and prevention of even minimal destruction of this historic marterial did not allow analysis of the piece itself. We recorded selected areas for microscopic observation with a cellulosic negative replica technique that reliably reproduces the surface details. The bone and teeth surfaces where copied by means of nitro-cellulosic vernish dropped and spread to form a thin layer that may be stripped after about two hours. Thin portions or particles of the original object that remained attached have been subject to electron microprobe analysis. The method is fast, relatively uncomplicated and the microscopic detail resolution is very great. If the stripping of the replica film is sometimes difficult, it is the only method in which location of the areas is not extracted from the general picture. A condition required to identify without ambiguity.

Results and Discussion. The skull has had its base sawn off and scraping marks as well as cut marks have been detected. A few bone surface irregularities can be seen, a linear fracture with signs of healing can be followed on the left temporo-parietal bone with an imprint of a clot on the internal table, and the skull retains organic residues and deposits. The incisor crowns are broken off, the roots present in their sokets. The details described afford a glimpse of events which occured before and after death of the music composer. Fracture lesions are frequent on skeletal finds. The calcified epidural hematoma imprint, associated with bone


Multivariate

  BLUP predicts breeding values in three generation breeding program More than 20 million improved seedlings produced per year Ø 1 million hectares forest in southwestern France § Maritime pine (Pinus pinaster Ait.): fast growing species (rotation = 35 years) adapted to the constrained environment of the Landes region forest (poor sandy soils, hydromorphic soils in winter, dry summers) § 24% of French wood harvest (60% for saw timber, 40% for industrial wood) Ø A three generation breeding population § Breeding program since the early 1960s with a base population selected in the Landes forest (~600 G0 trees) and an additional population selected in Corsica § Recurrent breeding scheme: -double-pair mating and forward selection to create the next breeding generation -polycross mating and backward selection to select the best genotypes for seed orchards Ø Improved varieties for growth and sweep § Open-pollinated seed orchards with ~50 genotypes (one breeding zone) § Genetic gains estimated (variety "VF3"): +30% for growth and +30% for stem straightness trait relationships to increase gain in the French maritime pine breeding program.

Laurent BOUFFIER 1, , Annie RAFFIN 1 , Greg DUTKOWSKI 2 1

/ INRA, UMR1202, BIOGECO, Cestas 33610, France 2/ PlantPlan Genetics, Hobart, Australia This work was financially supported by the Conseil Régional d'Aquitaine and the project Xyloforest (n°ANR-10-EQPX-16).

505,875 genotypes in pedigree and 8.3M data points stored in DATAPLAN No strong adverse genetic correlations

	Ø DATAPLAN:
	Individual trial analyses (ASReml)
	ü Identify the best environmental model for
	each trait (spatial analysis)
	ü Multi-variate analysis contributes to the
	database of correlations
	ü Estimate additive variance for data
	standardisation
	Genetic correlation model
	ü Minimises the weighted error sum of
	squares between the model estimates and
	the database of correlations.
	ü Used to:
	§ Carry out multivariate analysis within
	each trial with fixed correlations
	§ Predict harvest age traits from the
	measured traits
	Circumference 0.69
	Sweep	0.17 0.31		ü Moderately unfavorable
	Wood density 0* -0.11 0.13			correlations
	Spiral grain	0.03 -0.19 -0.09 0.18			growth -sweep
	Branch diameter 0.53 0.70 0.28 0* 0*		ü No or slightly
	Branch angle -0.16 -0.27 0,01 0* 0* -0.14			unfavorable correlation
	Fork nber	0.16 0.30 0.12 0* 0* 0.41 0.21			growth -wood quality
	Ramicorn nber 0.11 0.27 0.15 0* 0* 0.41 0.22 0.63 Height Circumference Sweep Wood density Spiral grain Branch diameter Branch angle * = correlation not estimated due to limited number of measurements Fork nber (correlation fixed to 0)	ü Moderately unfavorable correlation growth -branching
			Height	Circumference	Sweep	Wood density	Spiral grain	Branch diameter	Branch angle	Fork nber	Ramicorn nber
		Heritability	0.34 0.18 0.24 0.42 0.46 0.15 0.17 0.06 0.08
		Coefficient of additive variation 4.8% 7.0% 19.6% 7.4% 51.0% 10.3% 11.0% 61.7% 37.9%

database designed for breeding progam pedigree and phenotypic data Ø Stores all data from the main trials established since the 1960s ü 44 progeny trials with tree data + 19 trials with family mean data (6,231 families) ü Data from a variety of cross types (open and control pollinated, polymix) Ø All trees measured for at least one trait get breeding values for all traits

		Sweep
	Height Circumference	Deviation from verticality	Wood

§ Accuracy depends on correlated traits and related trees evaluated § Harvest age traits breeding values integrate information from all traits and all ages

density Spiral grain Branch diameter Branch angle Fork nber Ramicorn nber Nber of trials evaluated

		70	71	42	9	7	7	7	15	20
	Evaluation mean age	9,4	11,0	8,8	16,7	14,1	11,4	11,4	8,5	8,4

Branching

Wood quality Growth

Ø 9 major traits evaluated


Dr Eric Lichtfouse
email: eric.lichtfouse@dijon.inra.fr

Pest Control and Remediation of Soil Pollutants Climate Change

Keywords: Intercropping, Pest Control and Benefi cial Microorganisms Sociology, Organic Farming, Climate Change and Soil Science Genetic Engineering, Biofertilisation, Soil Quality and Organic farming Biodiversity, Biofuels, Agroforestry and Conservation Agriculture Alternative Systems, Biotechnology, Drought Stress and Ecological Fertilisation Genetics, Biofuels

This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifi cally for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher's location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

Printed on acid-free paper

Springer is part of Springer Science+Business Media (www.springer.com)

Pref ace

I like farmers because they are not learned enough for wrong thinking

Montesquieu

Farming is a profession of hope

Brian Brett

Farmer Thinking

The global food demand will sharply increase in 2050 to feed an estimated population of nine billion. At that time, agricultural extension will not be possible anymore because production has already reached sustainable limits in many parts of the world due to environmental degradation and climate change. Worse, in the name of immediate profi ts industrial agriculture is actually producing contaminated food and water, increasing atmospheric CO 2 by burning soil carbon, and decreasing soil fertility in the long term. Industrial agriculture has also deepened the social gap between the farmers from the countryside and the customers from the cities, leading to many food security issues. As cleverly foreseen by Montesquieu, we should never have ignored farmer thinking. The actual challenge of agriculture is therefore to be sustainable and ecological and to produce safe food.

Agroecology

Agroecology is a scientifi c discipline that uses ecological theory to study, design, manage, and assess agricultural systems that are productive but also resource conserving, according to Altieri ( http://nature.berkeley.edu/~miguel-alt/what_is_ agroecology.html ; Altieri 2012; Altieri and Nicholls 2012; Altieri et al. 2012). The main agroecological goals are thus to feed the world without degrading natural resources and to sustain productivity by optimizing ecological processes. These overall principles are developed for decision makers in the FAO Save and Grow reports for sustainable intensifi cation of smallholder crop production (Food and Agriculture Organization 2011) and in the ONU special contribution of Olivier de [START_REF] Shutter | Agroecology, a tool for the realization of the right to food[END_REF][START_REF] Altieri | Convergence or divide in the movement for sustainable and just agriculture[END_REF]. The future of agriculture depends on how effectively we understand and manage both social and ecological factors. The science of agroecology involves by nature the study of the whole agrosystem. As a consequence, investigations must be multidisciplinary with contributions from all disciplines relevant to the farming system, such as biological, physical, and social sciences. The major breakthrough versus industrial agriculture is that agroecology does not rely solely on technical knowledge. Farmers and human networks are indeed considered central players of the system. As a consequence, the classical top-down directives are not effi cient anymore. Alternatively, bottom-up, participatory, and codesign studies will lead to sustainable innovations that will be accepted by farmers and the public.

Petit-Bourg , Guadeloupe

Harry Ozier-Lafontaine Le Lamentin , Martinique Magalie Lesueur Jannoyer Dijon , France Eric Lichtfouse

  On fi eld discussions on a seeder adapted to direct sowing in tropical wet areas. International Year of Family Farming. Most farmers worldwide practice family farming, which yields nearly 70 % of the global agricultural production. Family farming is a very good topic for agroecological investigations, because most of the time family farming involves the use of biological regulations in diversifi ed production systems instead of monoculture and chemical solutions. Family farming also provides local knowledge and know-how accumulated over centuries. Family farming is also a good case for agroecological studies, because it involves interactions at various scales and organization levels, from individuals to communities and territories landscapes.This book shows applications of agroecological principles. The overall fi nding is that farming diversifi cation and mixed cropping systems lead to both ecological intensifi cation of agriculture and to the mitigation of global change. Chapter 1 by Angeon et al. explains the design of agroecology with a focus on the connection of life with economic and social sciences to build sustainable systems. Chapter 2 by Preston and Rodrí guez reviews the recycling of farm products into feed, food and fuel. Chapter 3 by Ratnadass and Barzman reviews advances for crop protection. Chapter 4 by Alexandre et al. focusses on animal science, which is usually overlooked in agroecology. Chapter 5 by Clermont-Dauphin et al. explains how to manage soil biodiversity to design new cropping systems. Chapter 6 by Boval et al. reviews alternatives for grasslands intensifi cation in tropical areas. Chapter 7 by Valet and Ozier-Lafontaine reviews traditional farmer intercropping systems for free ecosystem services, with a focus on participatory and codesign research. Chapters 8 by Chave et al. reviews advances in biocontrol for soil pests. Chapter 9 by Cover crop trials in banana cropping systems. © 2013 Magalie Lesueur Jannoyer Preface viii Mixed cropping system: the example of the creole garden in the Caribbean. © 2013 Harry Ozier-Lafontaine Archimè de et al. reviews the potential of local tropical resources for livestock nutrition. Chapter 10 by Le Henaff and Cebesi highlights the need to remove language barriers for agroecological education. Chapter 11 by El Ramady et al. presents an exhaustive review of soil quality and plant nutrition. Chapter 12 by El Ramady et al. presents the advanced concept of micro-farms.

Acknowledgments

This book was initiated in 2012 during the summer school entitled Functional Traits and Sustainable Mixed Cropping System Design organized by the INRA and the CIRAD in Martinique. The main issue was the application of agroecology in tropical areas. We thanks all the contributors and school attendees who improved our vision and who helped widen the fi eld application of agroecology.

xiii

Contents


Bernard Carré

A model for calculation of growth and feed intake in broiler chickens on the basis of feed composition and genetic features of broilers

Keywords: poultry, chicken, avian, growth, energy, ME, protein, fat, model, feed intake 2015

. An equation (D) describing protein deposition as a function of protein intake is added to this previous system, in order to obtain a complete description of growth and feed intake depending on feed composition and genetic features of broilers. A calculation is conducted for lean and fat lines with various dietary protein contents. Lean and fat lines are distinguished through the equation expressing lipid deposition as a function of [protein/energy] ratio and protein efficiency, and through the equation (D). The model provides results that are typical of differences between lean and fat lines, with a higher dietary protein recommendation for lean than for fat line, lower feed conversion ratios (FCR) in lean than in fat line, and higher protein efficiencies in lean than in fat line.

Introduction

It was previously shown that the feed intake of broilers could be calculated from the knowledge of feed composition (metabolizable energy (ME) and crude protein (CP) contents) and body weights (BW) at beginning and end of a growth period [START_REF] Carré | Cross relationships between growth performance, growth composition and feed composition in broiler chickens, calculated from published data[END_REF]. Thus, BW and growth data were required to calculate feed intake. It is proposed in the current publication to improve this approach by introducing an equation allowing growth to be calculated.

Materials and methods

Calculations

Equations are the 6 equations E1 to E6 shown in a previous publication [START_REF] Carré | Cross relationships between growth performance, growth composition and feed composition in broiler chickens, calculated from published data[END_REF], with Equation E2 being replaced by Equation R5 [START_REF] Carré | Cross relationships between growth performance, growth composition and feed composition in broiler chickens, calculated from published data[END_REF]. To this system is added the following equation "(D)" describing the daily protein deposition as a function of protein intake with an asymptote "a" and an ascending line "L" having a slope value "P" and an intercept value "E" (Figure 1): (D): Y = a -b e (-c e dX ) With: Y = daily protein deposition (g) X = daily protein intake (g)

The slope P is assumed to depend on the amino acid composition of dietary protein and on the genetic feature of broilers. It is also assumed that P is higher in a lean line than in a fat line as expected from a previous study [START_REF] Leclercq | Further investigations on protein requirement of genetically lean and fat chickens[END_REF]. E represents the endogenous protein losses with the energy requirement being met.

Table 1. Equations of the nutrition model for broilers. Examples of calculations are shown in Table 2. 0.7 = initial body weight (kg) (this value is taken as an example) 28 = mean age (days) of broilers (this value is taken as an example) 14 = duration (days) of growth (this value is taken as an example) 13.01 = Apparent metabolizable energy value of diets, corrected to zero nitrogen retention (AMEn; MJ/kg) (this value is taken as an example) 20.00 = crude protein content (%) of diet (this value is taken as an example) A = final body weight (kg) = 0.7 + B / 1000 × 14 B = daily weight gain (g) = I / H C = (0.7 0.634 + A 0.634 ) / 2 D = (0.7 0.418 + A 0.418 ) / 2 E = daily feed intake (DFI; g) (proposed value) F = fat content of body weight gain (FCG; g/g) (proposed value) G = daily protein deposition (DPD; g) (proposed value) H = protein content of body weight gain (PCG; g/g) = (0.179 + 0.00169 × 28) (1-F) I = DPD (calculated value) for lean line = 13 -11.51e (-0.100 e (0.145 J) ) I = DPD (calculated value) for fat line = 13 -11.51e (-0.100 e (0.131 J) ) J = daily protein intake (DPI; g) = E × 20.00 / 100 K = apparent metabolizable energy value of diet (AME; MJ/kg) = 13.01 + 1000 (0.0344 B × H / 6.25 / E) L = daily intake of AME (MEI; MJ) = 0.68 C + 0.03918 × 1.116 B × F + 0.02369 × 1.388 B × H M = protein efficiency (PE; g/g) = I / J N = daily feed intake (DFI) (calculated value) = 1000 L / K O = fat content of body weight gain (FCG) (calculated value) for lean line = 12.99 (0.137 D + 0.025) e (-1.082 × 20.00 / 13.01 -2.09 M) O = fat content of body weight gain (FCG) (calculated value) for fat line = 15.20 (0.137 D + 0.025) e (-1.082 × 20.00 / 13.01 -2.09 M) P = feed conversion ratio (FCR; g For the calculations shown in the current study, a common asymptotic "a" value of 13g/day was attributed to each line. P values of 0.59 and 0.53 were attributed to lean and fate lines, respectively and a constant E value of 0.6 g/day was attributed to each line and each dietary protein concentration, which resulted in the fitted equations shown for "I" in Table 1. Fitting of these equations were obtained by fixing the Y and X values at Y = 0.95a; 0.75a; 0.62a; 0.50a, as shown in Figure 1.

/g) = N / B Q = (1 -E / N) 2 R = (1 -F / O) 2 S = (1 -G / I) 2
For the equations expressing the lipid content of weight gain shown for "O" in Table 1, the α values [START_REF] Carré | Cross relationships between growth performance, growth composition and feed composition in broiler chickens, calculated from published data[END_REF] of 12.99 and 15.20 were attributed to lean and fat lines, respectively, in agreement with the α values found for males from experimental lean and fat lines [START_REF] Carré | Cross relationships between growth performance, growth composition and feed composition in broiler chickens, calculated from published data[END_REF].

Results of calculations are shown in Table 2 for lean and fat lines, with dietary protein contents varying from 14 to 26%. Figure 2 is an illustration of Table 2.

Results and discussion

Results of calculations are illustrated in Figure 2. According to the growth curves shown by the model, the lean line requires a higher dietary protein content than the fat line for expressing the growth potential (Figure 2). The model calculation provides feed conversion ratios (FCR) that are lower in lean than in fat line (Figure 2). According to the model, protein efficiencies (PE) are higher in lean than in fat line (Figure 2). All these results are in agreement with experimental studies comparing lean and fat lines [START_REF] Leclercq | Further investigations on protein requirement of genetically lean and fat chickens[END_REF][START_REF] Carré | Cross relationships between growth performance, growth composition and feed composition in broiler chickens, calculated from published data[END_REF], which shows the reliability of the model. Distinguishing lean and fat lines is performed in the model through two equations using a specific 1 for lean and fat lines coefficient for each line. One of these equations concerns fat deposition ("O" in Table 1) with a higher fat deposition in the fat line; the other equation concerns protein deposition ("I" in Table 1) with a better protein efficiency in the lean line. When one of these equations does not express any difference between lines using the same coefficients for both lines, the model fails in expressing all the typical differences between the lean and fat lines. Thus, both equations are needed to express all the differences between lean and fat lines. Considering the process of fat deposition, the equation of fat deposition ("O" in Table 1) expresses the "pull" phenomenon, while the equation of protein deposition ("I" in Table 1) expresses the "push" phenomenon. Thus, it is probably logical that the model works only if the whole process is expressed (the "push" and "pull"). It is stated above that the slope "P" depends on the genetic feature of broilers and on the amino acid composition of dietary proteins. Knowledge about the relationship between "P" and this amino acid composition represents future developments of this model for computing dietary amino acid recommendations.

Figure 1 :

 1 Figure 1: curve describing the protein deposition (Y) as a function of protein intake (X). For a = 13, P = 0.53, E = 0.6: Y = 13 -11.51 e (-0.100 e 0.131X )

Figure 2 :

 2 Figure 2: curves obtained from the model shown in Table1for lean and fat lines

Table 2 .

 2 Examples of calculations of broiler growth performance from the feed composition (energy value and crude protein) and the protein and lipid deposition curve responses assumed from broiler genetics (maximum growth potential and fatness) and amino acid composition of dietary proteins (details of equations are shown in Table1).

	Calculated values
	Proposed values
	Calculated values

Values of E, F and G are found in order to obtain zero for Q, R and S, using the Excel solver system.

Initial BW is 0.7 kg. Mean age of broilers for growth period is 28 days. Duration of growth period is 14 days. AMEn value of diets is 13.01 MJ/kg. "L-14" and "F-14" mean broilers from lean and fat lines, respectively, fed a diet containing 14% crude protein (N×6.25).


Marwa Brahem

Catherine M G C Renard

Carine Le Bourvellec

Characterization of dietary fiber in stone cells and parenchyma cells in pear

Characterization of dietary fiber in stone cells and parenchyma cells in pear

Marwa Brahem, Catherine M.G.C. Renard & Carine Le Bourvellec UMR408 Sécurité et Qualité des Produits d'Origine Végétale, INRA, Avignon University, 84000 Avignon France Fruit fiber is composed primarily by structural components of cell-walls such as polysaccharides and lignin. Cell-walls are important features of plant cells and are implicated in evolution of fruit firmness and texture during ripeness. In most species, fruit flesh is predominantly composed of parenchyma cells. In pears (Pyrus communis L.), however, the cortical tissues also contain stone cells, which are sclerenchyma cells formed by secondary deposition of lignin on the primary walls of parenchyma cells (Cai et al., 2010). They are also known as sclereids and are a determinant of pear quality. The deposition of stone cells in pear plays an important role in fresh fruit texture and in post harvest processing. Therefore, the composition and ultrastructure of cell-walls in pear was characterized, differentiating skin and flesh tissue, and in the flesh differentiating parenchyma and stone cells. Skin and flesh were separated manually be peeling, and stone cells were separated from parenchyma cells by decantation. Cell Walls Material (CWM) were prepared using one perry pear variety "De Cloche" by a phenol: buffer method with acetone treatment as described in Renard (2005). Neutral sugars, uronic acids and methanol were determinated by GC and colorimetry. Aspect and distribution of CWM were examined using scanning electron microscopy SEM. Yields were much higher from skin, followed by stone cells and parenchyma cells. Calculating back to a typical pear fruit, 35% of dietary fiber came from the skin, 51% from the stone cells and 14 % from the parenchyma cells. Cell-walls from flesh and stone cells had high contents of glucose, xylose and galacturonic acid. Stone cells were characterized by higher xylose and less arabinose, as well as higher lignin content. Cell-walls from the skin cells were richer in xylose and had low amount of uronic acid. The degree of methylation of pectins was > 50 %, reaching 80 % in stone cells. Stone cells were observed in SEM as aggregates surrounded by parenchyma cells. Lignified cells were anatomically characterized by the presence of simple pits. In conclusion, stone cells and parenchyma cells present a different composition of neutral sugars and lignin. This difference may influence differently the evolution of cell-walls during ripening. Keys words: Pyrus communis L., cell-walls, sclereids, neutral sugars, lignin.

  Cai Y. Li G. Nie J. Lin Y. Nie F. Zhang J. Xu Y., 2010. Study of the structure and biosynthetic pathway of lignin in stone cells of pear. Scientia Horticulturae, 125,374-379. Renard C.M.G.C., 2005. Variability in cell wall preparations: quantification and comparison of common methods. Carbohydrate Polymers, 60, 515-522.


Céline Meredieu

Didier Bert

Xavier Capdevielle

Thierry Labbé

Gilles Saint-Jean

Raphael Segura

Predicting the spore infection depending on climate to model the Heterobasidion annosum dynamics in even-aged Pinus pinaster stands: results from FORRISK project

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

Title of the paper (less than 20 words long): should clearly summarize the topic of the abstract.

Predicting the spore infection depending on climate to model the Heterobasidion annosum dynamics in even-aged Pinus pinaster stands Name, organizational affiliation and email address of each author.

Main text of abstract (170-200 words).

Over the past 30 years, in the Landes de Gascogne forest (maritime pine; one million hectares), Heterobasidion root disease has increased its distribution. A previous study showed that it occurs more frequently in well-drained sites than in humid and dry, sandy soils.

Understanding how the forecast increase in warm dry summers and wet winters along the Atlantic coast of France will change the incidence of the pathogen is crucial for integrating the losses and managements costs against this disease. In order to investigate the intra-annual climate variability, a three-year experiment was carried out on air-borne infection. H.

annosum spore deposition was monitored on freshly cut wood discs exposed during 24h.

Another key point concerns growth losses in trees depending on annual and individual growth rate. Diameter growth loss was investigated by analyzing annual growth increment of pairs of healthy trees vs. infected trees during few years. After implementation of these results into a model, simulations were carried out with different levels of infected stumps.

The model provides a means of incorporating the impact of root disease into the future forest planning.

Division 7 -Forest Health

Session 8 : Modeling as a tool for improving the knowledge on forest vulnerability and risk exposure in a changing world

Didier.Bert@pierroton.inra.fr

	Celine Meredieu, INRA, UMR1202 BIOGECO, Celine.Meredieu@pierroton.inra.fr (
	Didier Bert, INRA, UMR1202 BIOGECO, Xavier Capdevielle, INRA, UMR1202 BIOGECO, Xavier.Capdevielle@pierroton.inra.fr
	Thierry Labbé, INRA, UMR1202 BIOGECO,

Thierry.Labbe@pierroton.inra.fr Raphaël

Segura, INRA, UMR1202 BIOGECO, Raphael.Segura@pierroton.inra.fr Gilles Saint-Jean, INRA, UMR1202 BIOGECO, gilles.saint-jean@bordeaux.inra.fr Brigitte Lung-Escarmant, INRA, UMR1202 BIOGECO, Lung@bordeaux.inra.fr

Key words or phrases (up to 5).

Risk, forest management, Heterobasidion annosum, Pinus pinaster


The JRU ISP comprises 14 research teams that are grouped into three thematic divisions according to the infectious diseases studied being caused by bacteria, parasites or viruses in:

 humans at the UFRT;

 livestock species at the INRA Centre Val de Loire;

The JRU ISP also includes the following core / facilities: flow cytometry, histology and imaging facilities, the International center for microbial resources dedicated to pathogenic bacteria and a research team in chemistry.

We provide practical trainings for Master's and PhD students, and we welcome and support postdoctoral researchers striving to develop a career as independent researchers.

In close proximity to the JRU ISP at the INRA Centre Val de Loire, the Platform for Experimental Infections (PFIE) provides state-of-the-art high containment (BSL3) animal experimental facilities for infection experiments with:  farm animals: cattle, sheep, goats, pigs, equids, and poultry;  laboratory animals.

The experiments can be only performed following approval by the local ethics committee (CEEA VdL).

Together the JRU ISP and the PFIE form a closely collaborating research infrastructure dedicated to animal infectious and zoonotic diseases that is unique in France.

The "Surgery and Imaging for Research and Education (SIRE") platform provides further unique experimental facility at the INRA Centre Val de Loire. This platform permits to perform surgery accompanied by high-end imaging (CT scan and NMR) on small ruminants or pigs under conditions similar to those available in hospitals.

The JRU ISP coordinates the VetBioNet research infrastructure project (2017-22) that is financed by the European H2020 funding framework and involves 30 international partner organisations. Do not hesitate to contact the JRU ISP team leaders and/or researchers to obtain further information about training opportunities and our portfolio of researches. We are looking forward to your request -See you in Tours / A bientôt Redaction : Marion Duchet-Suchaux Creation date : 27 January 2016 Updated : 12 December 2016

Home page Postgraduate / PostDoc To apply

How to apply

The inquiry for training opportunities in our JRU is on your own initiative.

The availability of PhD projects is announced on the internet presentation of the Doctoral School "Health, Biological Sciences and Life Chemistry", section B " Infectiology and vaccinology, Immunology".

For the realisation of a Master's degree practical training you are advised to send your request three to six months ahead of the envisaged start of the training. This will enable the necessary administrative preparations.

To apply, you may directly contact the leader of the team in which you wish to integrate. Contact details are given in the research header of the ISP website. Alternatively, you may to send your request via the contact link, recipient "Human resources".

Please note that to permit the realisation of your training, a tripartite agreement has to be signed between INRA, the academic institution and yourself. ICMVAT contact: dimier@univ-tours.fr IDOH contact: master-emjmd-idoh@univ-tours.fr

  Redaction : Marion Duchet-Suchaux Creation date : 13 December 2016 Updated : 16 December 2016 Home page Postgraduate / PostDoc Masters Master's degree We are currently involved in two different Master's degree programmes:  The French Master's degree "Cellular and Molecular Infectiology, Vaccinology and Therapeutic Antibodies (ICMVAT)" at the University of Tours.  The Erasmus Mundus Master's degree "International Master of Sciences in Infectious Diseases and One Health (IDOH)" (PDF) involving three core partners: University of Tours/INRA, Universitat Autònoma de Barcelona/CReSA and University of Edinburgh/Roslin Institute. The associated partners of the IDOH programme comprise 34 partners: academic and public research institutions and industrial partners.In France, Master 1 students receive no payment during their practical training if the internship lasts less than 8 weeks. However, Master 2 students receive a 554,40 € allowance per month. No bench fees will be requested for the realisation of the practical trainings.Students interested in the IDOH Master's degree programme are encouraged to apply for a scholarship from the European Commission. This scholarship covers participation costs, travel fees and monthly subsistence allowance for the 2 years duration of the master programme.

Welcome to the ISP internet presentation

The comprehensive research unit "Infectious Diseases and Public Health" (Infectiologie et Santé Publique -ISP) is dedicated to the research on major infectious diseases in veterinary and human health. ISP is a Joint Research Unit (JRU) affiliated with the French National Institute for Agricultural Research (INRA) and the University François-Rabelais of Tours (UFRT). The UFRT and INRA laboratories are located on

Home page Postgraduate / PostDoc PhD

PhD

A number of stipends for PhD students are financed totally by the Région Centre, by both INRA and the Région Centre, or by the University of Tours. These stipends are validated each year by the Doctoral School "Health, Biological Sciences and Life Chemistry", section B "Infectiology and vaccinology, Immunology" . They relate to a 3-years research project being proposed by an ISP researcher and selected by the Doctoral School's Scientific Committee. The availability of a PhD project is generally announced by the Doctoral School in February/March to start in October. To apply, you should directly contact the designated thesis supervisor. The thesis supervisor will usually select three candidates to present their previous works and the proposed PhD project in front of jury delegates from the Doctoral School. The jury will then select the candidate for the PhD project.

For PhD projects that are funded by other research grants, the thesis supervisor may select the student candidate on his own; nevertheless the PhD student will be integrated in the curriculum of the Doctoral School "Health, Biological Sciences and Life Chemistry". The latter also applies to students with stipends from international academic exchange organisations. The student may start his/her thesis anytime in the year.

Students' life: PhD students are totally involved in the research and day-to-day activities of their hosting laboratory. Next to the design and the performing of experiments, the writing of thesis reports and scientific papers, they also take part in various other activities: contract deal, technical work groups, journal clubs, PhD day presentations, ISP seminar series, international congresses, etc. Students are also represented in the different administrative and scientific committees at the INRA Centre Val de Loire.

It is mandatory that the thesis is supervised by a principal investigator with an "HDR" degree, e.g. a postdoctoral research qualification. Today about 30 scientists are holding this degree in our JRU. All PhD students are enrolled in the Doctoral School "Health, biological sciences and life chemistry" that is associated to the Universities of Tours and Orléans.

A thesis committee consisting of minimum three scientists (ISP and/or external researchers) reviews and validates the student's research project and the technical approaches for its realisation. This committee meets once at the end of every year for the two first years of thesis.

Postdoctoral researchers

Following the completion of their PhD, postdoctoral researchers may apply for a fixed-term employment in our JRU.

The available postdoctoral positions are usually funded by research grants and have a contract duration of 1-2 years.

Postdoctoral researchers with a fellowship from international research organisations and being attracted by one of our teams' research agenda are invited to directly contact the respective team leader.

In some cases, young scientists and independent researchers with a proven record of competitive research wish to integrate in one of our teams. Consequently, they are strongly advised to consult the continuous project calls from the Agreenskills and Studium programmes, both of which are dedicated to promote international mobility.

Accommodations

Ten university dorms are located across Tours. They are managed by the students' welfare office (CROUS) of Orléans-Tours. E-mail sve-tours@crous-orleans-tours.fr; phone number: 33 2 47 60 90 37.

The INRA Centre Val de Loire provides accommodation in a number of council flats located in Tours-North, Monnaie, Château-Renault and Nouzilly. PhD students and postdoctoral fellows may take advantage of this opportunity after validation of their training request. They will have to file a request at the administrative division of the INRA Centre Val de Loire.

Lunch

There is a self-service restaurant that is open from 11:45 am to 1:30 pm at the INRA Centre Val de Loire.

In Tours, university restaurants and cafeterias managed by the CROUS are located close to the faculties of Pharmacy and Medicine.

Transport

To reach INRA

The INRA Centre Val de Loire is located 25 km from Tours. INRA makes buses available that are free of charge for all students and staff. The buses shuttle people from Tours to INRA in the morning and back in the evening, with several stops from/to the north and the south of Tours.

To move around Tours

There are public tramway and bus services available to move around Tours and its suburbs. Bikes can also be rented in the town.

About the region

You can get information through h the website of Tours tourism office.

Redaction : Marion Duchet-Suchaux Creation date : 13 December 2016 Updated : 13 December 2016


Justine Faure

Alexandre Fonseca

; Florence

Typology of the Noir de Bigorre pig farming systems

Keywords: Socio-economic aspects Presentation: Oral Communication Gascon breed, Outdoor, Hierarchical clustering, socio-economic dynamics

Intensive pig production systems are facing economic and environmental challenges that outdoor systems relying on local pig breeds may overcome. The Noir de Bigorre (NDB) pork chain located in South West of France is organized as a cooperative including farmers and processers. NDB products recently obtained national "AOC" label required for Protected Designation of Origin (PDO) registration. Therefore, within the European TREASURE 1 project, a typology of the NDB pig farming systems was constructed for further evaluation of their sustainability. A dataset was built including the 49 active farms involved in the chain. The dataset contained information on farm size, farm grassland and woodland areas, seniority in the chain, number of sows, piglets and pigs produced per year as well as proportion of on-farm produced feed. Principal Component Analysis (PCA) and Hierarchical Clustering (HC) were performed on these data. The first and second axes of the PCA explained respectively 39% and 34% of the variability. HC constructed 4 classes, with class 1: small farms with high seniority in the chain (n=19), class 2: pig breeding farms with small grassland / woodland areas (n=13), class 3: pig fattening specialized farms (n=9) and class 4: large farrow-to-finish farms with lowest seniority in the chain and highest proportion of on-farm feed production (n=8). This typology highlights the structure and the dynamics of the NDB farming systems. The expected evolution includes large farms (class 4, producing the maximum yearly number of pigs allowed in the PDO), with a fattening unit or both farrowing and fattening units. The typology will be useful for further sustainability assessment of the NDB pork chain.


Environmental heterogeneity in woodlands of north-central Florida Gradients of water availability, soil fertility, and fire frequency and severity Hypothesis: Oak species partition these gradients, allowing many species to coexist

How does high species diversity can be maintained within communities?

How is it that so many species can co-exist? Why are some species common and others rare?

How is it possible for a number of species to coexist in a relatively unstructured environments all competing for the same resources?

What / Which main factors drive community assembly?

Questions at the interface of Functional Ecology and Community Ecology

To find the general rules that allow to explain … 6  Functional Ecology … the relationships between the functions of biological systems and the environmental conditions

 Community Ecology

… the coexistence of species living together at a given place and at a given time 1987 Because: Mechanistic explanations of community assembly state that "community membership is constrained to those species with the appropriate functional traits to reach a site and establish under the circumstances set by the environment and other organisms"

Why are these questions at this interface?

Questions at the interface of Functional Ecology and Community Ecology

Why are these questions at this interface?

Because:

In the framework of the Biodiversity-Ecosystem Function debate, the functional significance of biodiversity arises primarily from diversity of functional traits among the species in a community.

Questions at the interface of Functional Ecology and Community Ecology

Huge amount of research studies to characterize the functional diversity of species Many ecologists believe that the key to understand these questions depends on our understanding of intra-and interspecific variation in plant functional traits Functional diversity of leaf traits 14 tree species in French Guiana There are fundamental differences among species in functional traits and in the trade-offs of these functions Functional traits provide an important tool in community ecology as they reflect trade-offs that determine species performance in a given environment and consequently species abundances along environmental gradients

The quantification of these trade-offs as multivariate trait spectrums is consistent with the idea of Plant Strategies

Plant strategies is central to developing a trait-based theory of community assembly and a general understanding of the dynamics and functioning of ecosystems

14
Correlation and trade-off among traits Grime introduced the CSR theory : "Each plant species has a blend of three strategies" : C (competitive), S (stress tolerant) and R (ruderal, or rapid propagation).

Species differ in the "proportion" of these strategies

According to habitat, each species must adopt a predictable compromise with regard to how they use the resources in order to survive.

The compromise involves the investment of resources in either the effort to acquire more resources, the tolerance of factors that reduce metabolic performance, or reproduction.

Plant strategies

This theory states that environmental stress and disturbance agents are providing the principal constraints on plant evolution and community structure. A term used to describe a species' habitat and distribution or a place in the environment that can be empty or filled?

• Predators cannot invade a habitat where there are no prey • Abiotic conditions limit species ranges (e.g. temperature, presence of soil, etc)

21

Community assembly

A lynx just exercising! A lynx being a predator! Assembly rules:

• Predators cannot invade a habitat where there are no prey • Abiotic conditions limit species ranges (e.g. temperature, presence of soil, etc) • Priority rules: species that arrive first can potentially exclude later-arriving species

22

Community assembly

Assembly rules:

• Only some combinations of species exist, some never do Hubbell showed that the neutral model well predicted the species richness and relative abundance in the area.

BUT it must be pointed out that as early as in 1997, Hubbell doesn't dispute that some species differ in their ability to compete! But he suggested that competition was not really an important factor in determining what plants grew where! Many ecologists remain skeptical of the assumption that species are essentially equivalent in how they function in the community!

)

  Baraloto et al. in prep. Oecologia Correlation and trade-off among traits Study on seedlings of 32 species in French Guiana Leaf functional and performance traits

  The ecological niche describes how an organism or population responds to the distribution of resources and competitors and how it in turn alters those same factorsEcological nicheHutchinson, 1957: Fundamental nichehypervolume (>3 axes) within which a species can survive or reproduceThe niche defines the total ecological space in which a species could survive http://bblonder.wordpress.com/2014/02/26/the-ecological-niche-and-the-n-dimensional-hypervolume/ Many definitions:

•

  Species not randomly distributed across the Florida landscape • Clear patterns of ecological sorting and specialization along the environmental gradients (soil moisture, soil fertility, and fire regime) • Niche differentiation can explain species diversity as well as functional diversity Niche vs. Competition vs. Neutrality debate Theories of neutrality or niche differentiation and environmental filtering still largely debated

Community Assembly

Community assembly

Functional Plant Diversity

The distribution of species in a given environment is related to stochastic processes operating at the different levels: This theory implies that biodiversity arises at random, as each species follows a "random walk"

The probabilities of immigration from the metacommunity, and the probabilities of survival and reproduction of all species, are equal (demographic neutrality).

Subsequent population dynamics in the local community are determined purely by random drift.

30

Neutral theory

So, even if one cannot rule out other potential mechanisms to explain patterns, why are these null models so welldescribing some of the community assemblage? "Surprisingly", this theory is able to quite-well summarize a large array of empirical patterns of species abundance! Particularly in highly-diverse tropical rainforests

Environmental filtering

The influence of environmental filtering on tree species throughout the ontogeny

Competitive exclusion Niche based

With competition, the niche space of a species may be reduced Trait-based filtering was the most important process at the 1-ha scale (34%), whereas demographic stochasticity was the most important at smaller scale (37-53%) Strategy differentiation among species, rather than stochastic processes, contribute to the maintenance of diversity in these highly diverse forests

Author conclude: "Forces included in neutral theory (such as demographic stochasticity and dispersal limitation) may not be sufficient to explain species distributions and the maintenance of diversity in these forests, even though they are occurring."

Taken solely, none of these models (environmental filtering, niche differentiation, neutrality) are able to perfectly simulate observed species distribution in communities Conclusions Natural distributions are probably resulting from all three processes, with different degrees according to species richness and local environmental conditions Perspectives How do these processes act in the context of climate / environmental changes? How will environmental changes affect community assemblage, and how can we predict them? How can we combine Community Ecology and Evolutionary biology?

How genetic variation and evolution within one species can shape the ecological properties of entire communities? How community context can govern species evolutionary processes and patterns?

Thanks for your attention


domain: sdv sde

text:
Nicolas N Saby

D J Brus

Hakima Boukir

Vera Laetitia Mulder

Approximating the

teaching and research institutions in France or abroad, or from public or private research centers.

N.P.A. Saby a , D.J. Brus b , H Boukir a , V.L. Mulder a

The sites of the French soil monitoring network are selected by systematic random sampling (SY). It consists of a 16 x 16 km grid, leading to a total of about 2200 sites. These sites are sampled every 10 to 15 years. SY leads to good spatial coverage, i.e. the sites are uniformly spread over France, enhancing the precision of design-based estimates of spatial means and totals. Besides, SY is a suitable sampling design for spatial mapping e.g. by kriging. SY therefore is a flexible sampling design: SY samples can be used both for design-based estimation of means and totals, and for mapping. With SY the sample average is an unbiased estimate of the mean. No unbiased estimator exists for the sampling variance of this estimator This paper investigates 5 approximations of the sampling variance using a simulation study and a case study in France on several soil properties.

Study area, monitoring sites and domains

A map of NDVI as obtained by MODIS was used as reality. The was sampled one million times by SY, using the 16 km grid-spacing of FSMN. For each SY sample from a parent material unit the mean of NDVI was estimated. The variance of the ? estimated means served as the benchmark value (horizontal line in figure). Each SY sample was used to approximate the sampling variance (box plots)  SI always strongly overestimated the sampling variance, whereas Moran always underestimated the variance; both should therefore not be used  STSI and Geary were on average the best approximation methods  MBzero approximated the variance better than MB for two out of the three units  The variogram is central in the MB method

The study was performed in mainland France, excluding Corsica, and covers approximately 542.0*10 3 km². First, the map units of the 1:1 000 000 soil map of Europe were aggregated on the basis of information on soil parent material (level 1) within these map units. We selected 4 aggregated units (see figure). We selected also the watershed of the Loire river.

In the simulation study the true sampling variance of the estimated mean of NDVI for these three units was determined by repeated SY sampling. The approximated sampling variances were compared with this true sampling variance. In the case study the data of the first campaign of the French Soil Monitoring Network (FSMN) were used for approximating the sampling variances of the estimated means of several topsoil properties.

Variance approximation

  = 𝑉 𝑆𝐼 𝑧 . 𝑟 * Model-based prediction requires a variogram. A square grid is not ideal for estimating a variogram, because no pairs of points at short distance are available, which are crucial for estimating the nugget parameter. For that reason we computed two model-based approximations, one with the variogram as fitted (MB), and one with a variogram in which the fitted nugget parameter is replaced by a spherical model with a sill equal to the fitted nugget parameter and a range equal to the grid-spacing (16 km). (MBZero)


text:
Estelle Nisse

Sissi Miguel

Benoit Mignard

Alain Hehn

Frederic Bourgaud

New plant models for the production of recombinant proteins: why not the carnivorous plants?

The system we developed allows the production and the secretion of functionnal GFP in transgenic Drosera and Nepenthes digestive fluids.

PAT Friday ® will now be extended to the expression of relevant recombinant therapeutic proteins such as monoclonal antibodies, cytokines, and gastric proteins.

The protocol for genetic transformation of Drosera rotundifolia (Hirsikorpi et al., 2002) was adapted to Drosera capensis. A new protocol was set up for Nepenthes mirabilis.

Transgenic plants overexpressing the Green Fluorescent Protein (GFP), were grown in a confined greenhouse, without insects or other prey, and the digestive secretions were collected. Carnivorous plants are able to attract, trap, retain, kill, and digest prey thanks to traps differentiated from leaves (Juniper et al., 1989).

Drosera and Nepenthes are two carnivorous plant genera able to produce and excrete out of their tissues a digestive fluid containing proteins which are mostly hydrolytic enzymes (Juniper et al., 1989). Natural protein concentration can reach up to 200 mg.L -1 in the digestive fluid.

Introduction

Results

Materials and Methods

Conclusion

  or by direct observation of the fluorescence (for Drosera rotundifolia and Drosera capensis).

Fig. 4 :

 4 Fig. 4: Leaf tentacles of Drosera rotundifolia producing GFP. The leaves were observed with a fluorescence microscope (x400). A: Tentacles from Wild Type Drosera. B and C: Tentacles from transgenic plants. From Biteau 2009.

Fig. 5 :

 5 Fig. 5: Dot Blot immunodetection of the GFP produced in the digestive secretions of transgenic Nepenthes mirabilis. A: Wild Type plant. B and C: Transgenic plants. From Miguel 2013.

Fig. 3 :

 3 Fig. 3: Drosera capensis secretions. A: Normal light, B: UV light. From Nisse 2014.


A set of experiments of PROHEALTH was designed to investigate a hypothesis about genetic selection in pigs that has been repeatedly formulated, but so far was lacking scientific evidence: It was hypothesized that improved productive traits (e.g. growing fast or using feed efficiently) are gained at the expense of reduced robustness, i.e. reduced capacity of the animal to be in good health and to maintain its performance in suboptimal environments. The reasoning behind this hypothesis is that selection for productive traits might impact the metabolism of the animal in a way that nutrients are increasingly used for productive functions (growth and protein deposition) and less for non-productive functions such as stress and defence responses.

Investigating the effects of selection for feed efficiency

PROHEALTH experiments compared two lines of pigs selected for residual feed intake (RFI), which is a measure of the efficiency of the conversion of feed to meat. RFI corresponds to the difference between the actual observed and the predicted feed intake. Pigs with a high-RFI eat more than predicted and are thus less efficient at converting the feed to meat than pigs with a low-RFI. These two lines are an interesting model to determine the consequences of genetic selection on animal physiology and health.

Three trials were conducted under controlled conditions to evaluate low-RFI and high-RFI line susceptibility to: 1) weaning stress, with special emphasis on digestive disorders, such as postweaning diarrhoea; 2) leg disorders, lameness and osteochondrosis occurrence when pigs are housed on concrete floors; 3) respiratory and inflammatory diseases, such as pneumonia caused by poor hygiene of the housing conditions. Pig characteristics measured included individual growth rate and feed intake, behaviour, health, compositions of blood, organs, tissues and carcass at slaughter, as well as meat quality.

Trial 1: Piglet health during weaning stress

In pig farms, piglets are usually separated from the sow at a young age (3 to 4 weeks of age). This early weaning is a stressful and critical phase for pig production, because of the relative piglet immaturity and the stress caused by the weaning (e.g. separation from the sow, new feed, and new environment). Antibiotic treatments are still commonly used after weaning to control digestive diseases that often occur after weaning. The genetic background is suspected to influence piglet health at weaning, but it remains poorly documented. Piglets from both RFI lines were weaned at 28 days of age and individually assessed for growth rate and health characteristics for five weeks after weaning. Piglets from the low-RFI line were more affected by weaning than piglets from the high-RFI line. In the first week after weaning, they ate and grew less (Figure 1), had more diarrhoea and a higher inflammatory status. However, they recovered during the second and third weeks and both lines had similar performance and physiological characteristics at the end of the postweaning period.

Trial 2: Housing large groups of pigs on concrete floors

Locomotory disorders, and more specifically lameness, have been identified as one of the significant production diseases for growing-finishing pigs and sows. Lameness is a complex problem with multifactorial causes. Among these causes, osteochondrosis has a very high prevalence in all common pig breeds. Osteochondrosis is a local failure of blood circulation at the top of long bones that causes cracks of joint cartilage (Figure 2). However, the proportion of lameness that can be linked to osteochondrosis is difficult to evaluate and is still unknown. Pigs from high and low RFI lines were housed on concrete floors in a room equipped with an electronic weighting device allowing pigs access to electronic self-feeders. Measurements were collected throughout the growing-finishing period for behavioural activity, lameness, osteochondrosis lesions, and growth rates. The study confirmed the high prevalence (55 to 90% of pigs depending on the joint) of osteochondrosis lesions during the growth period. Lesions were more frequently observed in low-RFI pigs -without any correlation with lameness, which affects a low proportion of pigs in both lines.

Trial 3: Hygienic conditions during the growing phase

Poor housing hygiene and the lack of respect of biosecurity rules are risk factors for pig health. Both low-RFI and high-RFI pigs were housed in either clean or dirty housing environments for the first six weeks of the growing phase (see Le Floc'h et al., 2014 for a description of the mod-el). Prevalence of respiratory lesions at slaughter was higher in dirty conditions, including inflammation of lung tissue (pneumonia) or the surrounding membrane (pleurisy). The pig growth rate was on average 20% lower in dirty conditions, and this reduction was unexpectedly greater for the high-RFI line than the low-RFI line (26 vs 12%). Poor hygiene conditions induced a systemic inflammatory response (Figure 3) and oxidative stress, and this response was greater in high-RFI pigs, which is the opposite of the initial hypothesis. Meat quality evaluated at slaughter (seven weeks a er all pigs were housed back in clean conditions) was not dramatically affected by poor hygiene during early growth, but body weight at slaughter was still lower for pigs having being reared in poor hygiene conditions (5.5 and 13.4 kg difference between clean and dirty for low-RFI and high-RFI, respectively).

Conclusions

Whilst various characteristics of the post-weaning response differ between RFI lines in the early stages of piglet weaning, no difference was observed by the end of the weaning period. Piglets from the low-RFI line were transiently more affected by undernutrition caused by the stress of weaning, but this could be overcome by tailored nutritional strategies. Poor hygiene conditions impacted pig health during the growing-finishing phase and pig weight at slaughter. Pigs from the high-RFI line were clearly more affected than the more efficient low-RFI pigs. These experimental studies indicate that selection of pigs for low RFI (high production efficiency) has no negative impact on the robustness, health and coping capacity of pigs by the end of the weaning period. Floc'h, N., Knudsen, C.,Gidenne, T., Montagne, L., Merlot, E., Zemb, O. (2014). Impact of feed restriction on health, digestion and faecal microbiota of growing pigs housed in a good or poor hygiene conditions Animal,8(10),1-11.http://doi.org/10.1017/S1751731114001608.

Source: Le