Jean Pierre Huiban

Camilla Mastromarco

Antonio Musolesi

Michel Simioni

The impact of pollution abatement investments on production technology: new insights from frontier analysis

Keywords: Pollution, Porter Hypothesis, Food Processing Industry, Frontier analysis, Non and semiparametric econometrics JEL Classication: I31, J21, J22

This paper estimates the impact of pollution abatement investments on the production technology of rms by pursuing two new directions. First, we take advantage of recent econometric developments in productivity and eciency analysis and compare the results obtained with two complementary approaches: parametric stochastic frontier analysis and conditional nonparametric frontier analysis. Second, we focus not only on the average eect but also on its heterogeneity across rms and over time and search for potential nonlinearities. We provide new results suggesting that such an eect is heterogeneous both within rms and over time and indicating that the eect of pollution abatement investments on the production process is not monotonic. These results have relevant implications both for modeling and for the purposes of advice on environmentally friendly policy.

Introduction

Pollution clearly appears to be an undesirable output of production. Because producing cleanly is more expensive than polluting, environmental regulation may be necessary in order to incite rms to make investments devoted to pollution reduction and to pursue a sustainable process of economic development.

A standard view among economists is that environmental regulation aiming to reduce pollution is a detrimental factor for rms' competitiveness and productivity [START_REF] Jorgenson | Environmental Regulation and U.S. Economic Growth[END_REF]). Since the early 1990s, however, this view has been challenged by numerous economists. In particular, [START_REF] Porter | America's Green Strategy[END_REF] and [START_REF] Porter | Toward a New Conception of the Environment-Competitiveness Relationship[END_REF] argued that more stringent but properly designed environmental regulations do not inevitably hamper rms' competitiveness but could enhance it. This new paradigm has become known as the `Porter hypothesis'. Since then, such a hypothesis has received much attention. It was initially criticized for its lack of an underlying theory [START_REF] Palmer | Lightening Environmental Standards The Benet-Cost or the No-Cost Paradigm[END_REF] and for being inconsistent with the empirical evidence [START_REF] Jae | Environmental Regulation and the Competitiveness of U.S. Manufacturing: What Does the Evidence Tell Us[END_REF]), while today a more solid theory exists [START_REF] André | Strategic Eects and the Porter Hypothesis[END_REF]) but also mixed empirical evidence, so that the validity of the Porter hypothesis continues to be one of the most contentious issues in the debate regarding environmental regulation. All this suggests that further research is clearly needed in this area (Ambec et al. (2013), p. 10).

This paper aims to contribute to the literature by pursuing two new directions. First, within a methodological perspective, we aim to assess the eect of pollution abatement investments on the production technology of rms by adopting methods that have been recently developed by the econometric literature on productivity and eciency analysis and that leave room for the consideration of external factors of production. External variables are generally dened as variables that cannot, at least totally, be controlled by the producer but may have an inuence in the production process (B din et al., 2012). The available measures of rms' eorts to reduce pollution, such as pollution abatement investments, can be seen as these kinds of variables, as they are expected to be stimulated by environmental regulation and, at the same time, to have some kind of eect on the production technology of rms.

A second novel aspect of this paper is its modeling and policy-oriented perspective. Specically, we focus not only on the average eect but also on its variability across rms and over time and search for potential nonlinearities. These aspects have been recognized as extremely relevant by the theoretical literature and have important implications, but until now, they have been neglected by the existing empirical literature. Indeed, as already pointed out by previous works (Ambec et al. (2013)), the controversy over the Porter hypothesis centers on the likelihood that the regulatory costs may be fully oset or not. The critics say that although some anecdotal empirical evidence in the direction suggested by Porter could be found, a complete oset should be seen as the exception. Porter and van der Linde also admit that such a complete oset does not always occur. Moreover, the linearity and monotonicity of the relation can also be questioned, as it is not reasonable to assume that the eect of environmental regulation is monotonic [START_REF] André | Strategic Eects and the Porter Hypothesis[END_REF], p. 29) since it could be that taking advantage of regulation will become more dicult if the stringency of environmental regulation will increase too much.

In order to model pollution abatement investments as external factors of production and to address the above issues, two complementary approaches are adopted in this paper: parametric stochastic frontier analysis (SFA) and conditional nonparametric frontier analysis (CNFA). They present relative advantages and drawbacks; comparing their results may be useful to provide a more nuanced and thorough picture of the eect of pollution abatement investments on the production technology of rms. It may be also important to provide more robust results. SFA has the relative advantage of having a well-developed statistical theory which allows for statistical inference. Therefore, using SFA we can test alternative specications as well as dierent hypotheses on eciency. We can focus our attention on input elasticities, on their heterogeneity across rms and on all the other estimated parameters of the production frontier and get information on scale economies, eciency, etc. Conversely, CNFA has the relative advantage over SFA that it does not make any assumptions, either about specic parametric functional form for the production frontier or about distributional assumptions on the noise and ineciency component, and may be useful to detect complex nonlinear relations. At the same time, however, this exibility comes at a price since CNFA does not allow the estimation of some key elements of production econometrics (such as input elasticities, scale economies, etc.) and inference is less straightforward than in SFA.

More specically, concerning SFA, the most common approaches in the literature model the impact of external factors either on the structure of the technology or on technical eciency [START_REF] Coelli | Environmental Inuences in Stochastic Frontier Models: with Application to International Airlines[END_REF]). We follow and extend these trends and consider alternative models to include pollution abatement investments in the production process and then use the [START_REF] Vuong | Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses[END_REF] test in order to select the most likely one. When switching to CNFA, we use an approach similar to [START_REF] Mastromarco | Eect of FDI and Time on Catching up: New Insights from a Conditional Nonparametric Frontier Analysis[END_REF] where the conditional nonparametric eciency measures are obtained and are used as exploratory tools to determine the nature of pollution capital investment: favorable input or undesirable output?

In summary, to the best of our knowledge, this is the rst work estimating the eect of pollution abatement investments on the production technology of rms using methods that model pollution abatement investments as external factors of production and, at the same time, focusing on some aspects such as heterogeneity and nonlinearity that have been shown to be relevant by the theoretical literature and have important implications for rms and society as a whole in terms of advice on environmentally friendly policy.

The present paper is organized as follows. Section 2 gives a brief review of the related literature. Section 3 presents the econometric methodologies while the description of the data and some descriptive statistics are provided in section 4. Section 5 details the results and section 6 concludes.

literature

In this section, we present the general ideas and the dierent versions of the Porter hypothesis. We also briey review the theoretical literature, specically highlighting the economic mechanisms allowing for a possible positive relation between pollution abatement investments and rm-level productivity. For a more exhaustive discussion on both theory and empirics, the reader is referred to the recent surveys by Ambec et al. (2013) and [START_REF] André | Strategic Eects and the Porter Hypothesis[END_REF].

According to a standard view among economists, at least until the 1990s, pollution abatement eort due to environmental regulation may be benecial in terms of environmental performance but would negatively aect rms' economic performances since it forces them to allocate the production inputs to pollution reduction, pushing them away from optimal production choices and thus inducing technological and allocative ineciency.

Since the early 1990s, however, this traditional paradigm has been challenged by what has become known as the `Porter hypothesis' [START_REF] Porter | America's Green Strategy[END_REF]; [START_REF] Porter | Toward a New Conception of the Environment-Competitiveness Relationship[END_REF]). Porter and Van der Linde (1995), p. 98, suggest that Strict environmental regulation can trigger innovation (broadly dened) that may partially or more than fully oset the traditional costs of regulation .

Since then, the Porter hypothesis has attracted a great deal of attention, theoretically as well as empirically. However, a diculty that arises when addressing such a hypothesis is clarifying its interpretation, as the Porter hypothesis is not a hypothesis in a statistical sense but it represents a general idea illustrated with real-life examples and, at least in its original formulation, lacked an underlying theory [START_REF] Palmer | Lightening Environmental Standards The Benet-Cost or the No-Cost Paradigm[END_REF]). [START_REF] Palmer | Environmental Regulation and Innovation: A Panel Data Study[END_REF] help in the interpretation of the Porter hypothesis by distinguishing between the `weak', `narrow' and `strong' versions of such a hypothesis. According to the weak version, environmental regulation may stimulate innovation, while the narrow version argues that certain types of environmental regulation, but not all, spur innovation. This idea that regulation can stimulate innovation is based on the concept of induced innovation and goes back to Hicks (1932). It is generally accepted and has been validated by many previous studies, even those specically about environmental regulation.

The core of the controversy lies in the strong version, which argues that in many cases this innovation more than osets the regulatory costs, ultimately enhancing rms' competitiveness and economic performances. From a theoretical point of view, after some initial criticisms [START_REF] Palmer | Lightening Environmental Standards The Benet-Cost or the No-Cost Paradigm[END_REF], the literature has provided alternative explanations supporting the strong version, such as rms' behaviors departing from the assumption of prot maximization [START_REF] Ambec | Can Environmental Regulations be Good for Business? An Assessment of the Porter Hypothesis[END_REF]), market failure [START_REF] André | Strategic Quality Competition and the Porter Hypothesis[END_REF]), organization failure [START_REF] Ambec | A Theoretical Foundation to the Porter Hypothesis[END_REF]), and knowledge spillovers [START_REF] Mohr | Technical Change, External Economies, and the Porter Hypothesis[END_REF]).

It should also be noted that while Porter and van der Linde claim that rms become more competitive , the concept of competitiveness is quite general and allows for alternative measurements. As a consequence, the above-mentioned theoretical works have considered alternatives measures of competitiveness such as cost reduction, increased prots or higher market shares. At the same time, however, empirical research has focused on the estimation of production functions or productivity equations. Somewhat more closely related to this empirical literature, [START_REF] Mohr | Technical Change, External Economies, and the Porter Hypothesis[END_REF] emphasizes productivity increases and justies the Porter hypothesis by adopting a general equilibrium model where a key role is played by external economies and in particular the nature of knowledge as a public good. According to such a model, rms' output benets from knowledge spillovers. The amount of this common knowledge is equal to the cumulative production experience of all rms using the same technology. Thus, a specic rm will switch to a new (greener) technology only if enough other rms have done it rst. This is because, even if new and greener technology will be, ceteris paribus, more productive, at least initially there is much more accumulated experience in the old technology than in the new one and, as a consequence, the productivity of the new technology will be lower than that of the old one. Environmental regulation can thus solve the coordination problem, inciting rms to adopt the greener technology, which will increase the global stock of knowledge of the new technology, and ultimately lead to an improvement in the level of productivity of those rms.

Methodology

There is a huge body of empirical literature testing the strong version of the Porter hypothesis, but it provides rather mixed empirical evidence (Ambec et al. (2013)). This literature focuses on the estimation of production functions or productivity equations augmented with some measures of pollution abatement eorts. We follow the stream of the literature using a direct measure of the expenditures or investments engaged by the rms (see e.g., [START_REF] Shadbedgian | Pollution abatement expenditures and plant-level productivity: a production function approach[END_REF]) and estimate value-added production frontiers where the pollution abatement eorts are measured with the stock of capital devoted to pollution reduction (a detailed description of the data is in section 4).

The methodology we use departs from previous studies in that it is inspired by recent developments in the econometric literature on productivity and eciency analysis that allow the consideration of external factors of production. SFA and CNFA provide useful frameworks for dealing with this issue. This section shows how these two approaches can be used to model the impact of pollution abatement capital on the production process.

Stochastic frontier analysis

The most common approaches in the SFA literature model the impact of external factors either on the structure of the technology or on technical eciency (Kumbhakar and Lovell, 2000). We follow and extend these trends and consider two alternative models to include pollution abatement capital in the production process.

Input model

In a rst model, which we label as the input model, we assume that pollution abatement capital inuences the production process itself, or, put dierently, enters the production function, F (.), as an additional factor of production in the stochastic production frontier model

Y it = F (t, K it , L it , Z it )τ it w it .
(1)

The output of a rm i at time t, Y it , is thus assumed to be determined not only by the levels of usual inputs, i.e. labor input, L it , and physical capital, K it , but also by pollution abatement capital, Z it . The time trend t captures technological change over time and we do not assume Hicks-neutrality. The w it , which are assumed to be independent and identically distributed random errors, capture the stochastic nature of the production frontier. τ it denotes technical eciency with 0 < τ it ≤ 1 and τ it = 1 when the rm produces on the frontier.

The stochastic production frontier model in Eq. ( 1) is parameterized using a translog specication achieving local exibility (also called Diewert exibility, see e.g., [START_REF] Fuss | A survey of functional forms in the economic analyses of production[END_REF] and outperforming other Diewert-exible forms [START_REF] Guilkey | Comparison of the Performance of Three Flexible Functional Forms[END_REF]:

y it = α + β τ t + β k k it + β l l it + β z z it + γ τ t 2 2 + γ k k 2 it 2 + γ l l 2 it 2 + γ z z 2 it 2 + +δ τ k tk it + δ τ l tl it + δ τ z tz it + δ kl k it l it + δ kz k it z it + δ lz l it z it -u it + v it (2)
where lower case letters indicate variables in natural logs, i.e. y it = ln(Y it ), and so on. It is worth noting that this specication is more general than the one chosen by [START_REF] Coelli | Environmental Inuences in Stochastic Frontier Models: with Application to International Airlines[END_REF] which restricts the eect of external factors only to the shape of the technology by imposing γ z = δ τ z = δ kz = δ lz = 0 in Eq.

(2). Put dierently, we do not exclude the case where pollution abatement capital aects the technology of the rms as an input under the control of the rm manager choosing the optimal level of pollution abatement investments given some external constraints (such as environmental regulation) and within its maximization program. The error term in Eq. ( 2) is composed of two components, the two-sided noise component v it = ln(w it ) and the non-negative technical ineciency component u it = -ln(τ it ). The noise component, v it , is assumed to be independently and identically distributed as N (0, σ 2 v ) and distributed independently of u it . The technical ineciency component, u it , is assumed to be time-varying. Two dierent assumptions about the distribution of this component can then be made. First, we can assume that the technical ineciency component is of the multiplicative form:

u it = (t, T ) × u i
where u i is distributed as N µ, σ 2 u truncated at zero and (t, T ) is written as

(t, T ) = exp( T t=2 γ t d t ) (3)
where d t denote year dummies.1 Hereafter we will refer to this specication as multiplicative.

A second specication for the ineciency component, which we label as additive, builds on [START_REF] Battese | A Model for Technical Eciency Eects in a Stochastic Frontier Production Function for Panel Data[END_REF] and [START_REF] Coelli | Environmental Inuences in Stochastic Frontier Models: with Application to International Airlines[END_REF] with u it distributed as N µ it , σ 2 u truncated at zero and

µ it = µ + T t=2 γ t d t (4)
The two specications of the technical ineciency component dier in the way they model time-varying ineciency. In the multiplicative specication, the underlying truncated normal variable u i is scaled by the exponential function of time. The ineciency component in this specication varies in a systematic way with respect to time. [START_REF] Greene | Reconsidering Heterogeneity in Panel Data Estimators of the Stochastic Frontier Model[END_REF] denes this specication of the ineciency component as timedependent rather than as time-variant. The other ineciency specication is a pooled model where the time variation of ineciency depends on the way time aects the mean of the truncated distributed variable u it .

Eciency model

In the input model, pollution abatement capital is assumed to inuence production directly, by aecting the structure of the production frontier relative to which the eciency of rms is estimated. An alternative model associating variation in eciency with variation in pollution abatement capital can be also considered. In this model, which is labeled as the eciency model, Eq. ( 1) becomes

Y it = F (t, K it , L it )τ it (Z it )w it .
(

) 5
where we assume now that pollution abatement capital, Z it , inuences production, Y it , indirectly, through its eect on technical eciency, τ it . The stochastic production frontier model in Eq. ( 5) is parameterized using a exible translog specication as

y it = α + β τ t + β k k it + β l l it + γ τ t 2 2 + γ k k 2 it 2 + γ l l 2 it 2 + δ τ k tk it + δ τ l tl it + δ kl k it l it -u it + v it (6)
Here too, the error term in Eq. ( 6) is composed of two components, the two-sided noise component v it = ln(w it ) and the non-negative technical ineciency component u it = -ln(τ it ). We assume again that the noise component, v it , is independently and identically distributed as N (0, σ2 v ) and distributed independently of u it . Two alternative specications of the distribution of the technical ineciency component, u it , are considered, a multiplicative one and an additive one, as for the input model. But now, the multiplicative form of the ineciency component in the multiplicative model becomes

u it = (t, T, Z it ) × u i ,
where u i is distributed as N µ, σ 2 u truncated at zero and (t, T, Z it ) is written as

(t, T, Z it ) = exp( T t=2 γ t d t + θZ it ), (7)
Meanwhile, the assumptions in the additive model become u it distributed as N µ it , σ 2 u truncated at zero and

µ it = µ + T t=2 γ t d t + θZ it (8)
To sum up, we have four parametric models: input model with multiplicative ineciency component, input model with additive ineciency component, eciency model with multiplicative ineciency component, and eciency model with additive ineciency component. These four models are estimated by maximum likelihood. Since they are non nested, in order to choose the preferred specication, we perform the modied likelihood-ratio test proposed by [START_REF] Vuong | Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses[END_REF] to compare non-nested models.

Conditional Nonparametric Frontier Analysis

The parametric approach allows the estimation of some key parameters of production econometrics, such as elasticities, scale economies, etc. However, even if a exible form is used to represent the production technology, such an approach might suer from misspecication problems due to imposing a specic functional form on the production process and assuming known statistical distributions on the errors terms.

2 The use of nonparametric methods serves to relax these restrictive parametric assumptions, even if these methods do not allow the estimation of parameters for economic interpretation. Moreover, using recent developments in nonparametric frontier literature, it is possible to disentangle the potential eects of conditioning variables (in our case, pollution abatement capital) to identify eects on the boundary (the shape of the frontier) and eects on the distribution of the ineciencies in a full nonparametric setup.

We follow [START_REF] Cazals | Nonparametric frontier estimation: a robust approach[END_REF], [START_REF] Daraio | Introducing environmental variables in nonparametric frontier models: a probabilistic approach[END_REF], Daraio and Simar (2007) and, mainly, Mastromarco and Simar (2015) who introduce the time dimension into the conditional frontier model. The production process generates random variables (X, Y, Z) in an appropriate probability space, where X ∈ R p + denotes the vector of inputs, Y ∈ R q + denotes the vector of outputs, and Z ∈ R r + denotes the vector of variables describing external factors, i.e. factors that may inuence the production process and the eciency pattern (in our case, pollution abatement capital and time). As suggested by [START_REF] Mastromarco | Eect of FDI and Time on Catching up: New Insights from a Conditional Nonparametric Frontier Analysis[END_REF], time can be handled as a Z variable.

For each time period t, the attainable set Ψ z ⊂ R p+q + is dened as the support of the conditional probability 3

H X,Y |Z (x, y|z) = Prob (X ≤ x, Y ≥ y | Z = z) .
The function H X,Y |Z (x, y|z) is simply the probability for a rm operating at level (x, y) to be dominated by rms facing the same external conditions z. Accordingly, the conditional output-oriented technical eciency of a production plan (x, y) ∈ Ψ z , i.e. facing external conditions z, can be dened as [START_REF] Daraio | Introducing environmental variables in nonparametric frontier models: a probabilistic approach[END_REF])

τ (x, y|z) = sup {τ |(x, τ y) ∈ Ψ z } = sup{τ |S Y |X,Z (τ y|x, z) > 0}.
where S Y |X,Z (y|x, z) = Prob(Y ≥ y|X ≤ x, Z = z) is the (nonstandard) conditional survival function of Y, nonstandard because the condition on X ≤ x and not X = x. Equivalently, the unconditional measures are: τ (x, y) = sup{τ |S Y |X (τ y|x) > 0}.

We also calculate partial frontiers, introduced by [START_REF] Daouia | Nonparametric Eciency Analysis: A Multivariate Conditional Quantile Approach[END_REF], enabling us to obtain results that are robust to some extreme observations. Conditional (unconditional) output-oriented robust orderα quantile eciency measures are dened for any α ∈ (0, 1) as:

τ α (x, y|z) = sup{τ |S Y |X,Z (τ y|x, z) > 1 -α}
As stated in [START_REF] Badin | How to measure the impact of environmental factors in a nonparametric production model[END_REF], the eect of external factors on the shape of the frontier can be investigated by considering the ratios of conditional (τ (x, y|z)) to unconditional (τ (x, y)) eciency measures, which are measures relative to the full frontier of respectively, the conditional and the unconditional attainable production sets:

R O (x, y|z) = τ (x, y|z) τ (x, y) .

(9)

By construction, R O (x, y|z) ≤ 1, whatever the triplet (x, y, z). In turn, the eect of external factors on the distribution of technical eciencies can be investigated using the ratios of conditional to unconditional output-oriented robust order-α quantile eciency measures for dierent values of α, i.e R O,α (x, y|z) = τ α (x, y|z) τ α (x, y) .

(10)

Here the ratios R O,α (x, y|z) can be either

≤ 1 or ≥ 1. But as α → 1, R O,α (x, y|z) → R O (x, y|z)
For the output orientation, when the ratios (9) are globally increasing with an external factor, this indicates a favorable eect on the production process, and the external factor can be considered as a freely available input. Indeed, the value of τ (x, y|z) is much smaller (greater eciency) than τ (x, y) for small values of the factor than for large values of it. In our case with Z as pollution abatement capital, this may be explained by the fact that rms facing small values of the external factor do not take advantage of the favorable environment, and when the value of the external factor increases, they benet more and more from the environment. On the contrary, when the ratios (9) are globally decreasing with the external factor, there is an unfavorable eect of this factor on the production process. The external factor is then acting as an unavoidable output. In this situation τ (x, y|z) will be much smaller than τ (x, y) for large values of the external factor.

As explained in [START_REF] Badin | How to measure the impact of environmental factors in a nonparametric production model[END_REF], the full frontier ratios ( 9) indicate only the eects of external factors on the shape of the frontier, whereas with the partial frontier ratios (10), these eects may combine eects on the shape of the frontier and eects on the conditional distribution of the ineciencies. For our purpose of analyzing the impact of Z on the distribution of eciencies, we are interested in the median, by choosing α = 0.50. If the eect on partial frontier ratios is similar to the one shown with the ratios with full frontier, we can conclude that we have a shift of the frontier while keeping the same distribution of the eciencies when the external factor changes. If the eect with the median (α = 0.5) is greater than for the full frontier, this indicates that in addition to an eect on the shape of the frontier, we also have an eect on the distribution of the eciencies.

Data

We build a new and rich rm-level panel data set concerning the French food processing industries and covering a relatively long period (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007). The French food processing industry is particularly relevant for such a kind of analysis because it is one of the most polluting sectors with respect to several indicators -especially concerning the eects of total nal consumption of the produced goods (European Environmental Agency, 2006) -and it is one of the sectors investing more in pollution abatement.

4 It is 4 In 2007, the food processing industry was found to be the third biggest spender on pollution abatement investments in France (e167 million), only exceeded by the energy (e437 million) and chemicals, rubbers and plastics (e204 million) industries.

nally also relevant in terms of size, representing a large proportion of manufacturing in France (about 550,000 employees in 2011, i.e. 18% of manufacturing employment).

Data for the French food processing industries on pollution abatement investments are collected annually in a survey conducted by the French ministry of Agriculture, called Enquête Annuelle sur les Dépenses pour Protéger l'Environnement (ANTIPOL), since the early 1990s. To our knowledge, this paper represents the rst attempt to use this survey for academic purposes. The ANTIPOL survey provides information on pollution abatement investments dened as the purchase of buildings, land, machinery or equipment to limit the pollution generated by production activity and internal activities or the purchase of external services improving the knowledge to reduce pollution . Next, the pollution abatement capital stock at rm level is built using the perpetual inventory method with a depreciation rate of 15%. This is a standard rate adopted in the literature for investments in pollution abatement [START_REF] Aiken | Pollution Abatement and Productivity Growth: Evidence from Germany, Japan, the Netherlands, and the United States[END_REF]).

The Enquête Annuelle d'Entreprise (EAE) is an annual rm-level survey covering almost all rms with 20 or more employees, conducted by the French National Institute for Statistics. This survey provides a measurement for output, i.e. value-added, deated by its annual industry price index, and for the usual inputs, i.e. labor measured by the number of employees expressed in annual full-time equivalent workers, and capital measured by the amount of xed assets, deated by the annual price index for capital goods.

The two data sets are merged, nally resulting in an unbalanced panel data set composed of 8391 observations and 1130 rms covering the period 1993-2007. Table 1 presents some descriptive statistics for the variables used to estimate the production function: value added, labor (number of workers), physical capital stock, and pollution abatement capital stock.This table shows that average pollution abatement capital stock is about one-ftieth of average physical capital stock. Also note that a fraction of rms has never invested to reduce pollution, the corresponding stock of capital presents many zeros (18.21% of the total number of observations), but all the explanatory variables are expressed in logarithms when using a translog specication. To include all the observations for the variable Z, we follow [START_REF] Battese | A Note on the Estimation of Cobb-Douglas Production Function when Some Explanatory Variables have Zeros[END_REF], and set z ≡ ln (Z + D) where D = 1 if Z = 0, and D = 0 if Z > 0, as explanatory variable instead of ln (Z) which is not dened when D = 1. [START_REF] Battese | A Note on the Estimation of Cobb-Douglas Production Function when Some Explanatory Variables have Zeros[END_REF] also introduces the variable D as a shifter of the constant term. As we introduce sectoral dummies to capture unobserved heterogeneity across sectors, we do not introduce the dummy D. Indeed, sectoral dummies can capture the eect of omitted variables that explain the heterogeneity of pollution abatement investment behaviors across sectors, making the dummy D redundant. The same denition, z ≡ ln (Z + D), is also adopted when implementing conditional nonparametric frontier estimation.

[Table 1 about here.] 5 Results

SFA

Model selection

The four parametric models proposed above are estimated and then the [START_REF] Vuong | Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses[END_REF] test is performed to select the most likely one.

5 Results are reported in Table 2. The Vuong test indicates that the multiplicative specication of eciency is preferred to the additive one, for both the input and eciency models. It also shows that the input model is preferred to the eciency model when comparing them in the multiplicative case. Consequently, we select the multiplicative input model as the most likely one at the end of the model selection procedure.

[Table 2 about here.]

We then proceed to test the null hypothesis that pollution abatement capital aects only the shape of the production technology as in the Coelli (1999) model, i.e. we test the null hypothesis that γ z = δ τ z = δ kz = δ lz = 0 in Eq. ( 2).The likelihood ratio test statistics whose value is 18.616 with a p-value equal to 0.001, allow us to reject such a hypothesis.

5 Sectoral xed eects have been included in the translog specication. Detailed results are available upon request to the authors.

Estimation of the preferred model

The estimated values of the parameters of the preferred model, i.e. the multiplicative input model, serve to compute the output elasticities with respect to K, L and Z and are noted as ε Y,K , ε Y,L and ε Y,Z . While the average values of ε Y,K , ε Y,L and ε Y,Z are equal to 0.255, 0.780 and 0.018, respectively, we mainly focus our attention on the estimation of the underlying density functions. They are of interest in order to have information about the variability across rms and over time of such elasticities. In particular, we estimate the conditional densities of the above elasticities conditioned on time. Time being an ordered variable, we adopt the approach by [START_REF] Hall | Cross-validation and the estimation of conditional probability densities[END_REF] which uses generalized product kernels to deal with mixed data and cross-validation to choose the smoothing parameters.

[Figure 1 about here.]

Figure 1 reveals that the distributions of ε Y,K and ε Y,L are clearly unimodal. Conversely, and very interestingly, it can be observed that the density of ε Y,Z is bimodal and appears to be a mixture of two underlying densities, a rst one with a negative mode and a second one with a positive mode. Overall, about 80% of the rms have a positive elasticity. This result has two interpretations. First, it suggests that the traditional view about the eect of environmental regulation on productivity and the Porter hypothesis may coexist. Second, it reinforces the view that the rms' eorts to reduce pollution do not always positively aect the rms' performances, but they do in many cases, as also stressed by Ambec et al. (2013). Concerning the time evolution of the distributions of such elasticities, Figure 1 also reveals that the distribution of ε Y,Z has clearly evolved over time -the smoothing parameter for time is 0.44and shows a positive shift. Indeed, while at the beginning of the period, a relevant fraction of the rms are characterized by a negative elasticity, at the end of it, almost all the rms have a positive elasticity.

Also note that this result could be considered as consistent with the theoretical paper by [START_REF] Mohr | Technical Change, External Economies, and the Porter Hypothesis[END_REF] since it is observed that the annual share of rms investing in pollution abatement increased over the period. According to this model, rms benet from knowledge spillovers where the amount of knowledge equals the cumulative experience of all rms using the same technology so that a specic rm will switch to a new (greener) technology only if enough other rms have done so rst.

Other characteristics of the technology can also be estimated using the preferred model, such as elasticities of substitution and eciency measures. However, they are not a central interest of this paper and detailed results on these characteristics are available upon request.

CNFA

To complement the previous analysis, we conduct the CNFA analysis detailed above. CNFA may serve to detect a possibly complex nonlinear eect of pollution abatement capital on the production process.

Moreover, CNFA also permits us to understand whether external factors aect both the shape of the frontier and the distribution of eciencies. We investigate the ratios of conditional and unconditional eciency measures for full and partial frontiers. The conditional DEA estimates are computed with the localizing procedure described in [START_REF] Mastromarco | Eect of FDI and Time on Catching up: New Insights from a Conditional Nonparametric Frontier Analysis[END_REF] and optimal bandwidths have been selected by least squares cross-validation. Figure 2 shows the ratios from a marginal point of view, i.e.

as a marginal function of pollution abatement capital. The full frontier ratios (top panel of Figure 2)

show a nonlinear eect of pollution abatement capital on the shape of the frontier. This nonlinear eect takes the shape of an inverted U relation suggesting the existence of a positive eect on the shape of the frontier when pollution abatement capital increases at low values of capital (pollution abatement capital acts then as a favorable input), and a decreasing eect for large values of capital. In order to check the robustness of our result and to inspect whether some extreme observations would hide an eect, we calculated the ratios for partial frontiers with α = 0.99, and obtained very similar results, which are available upon request.

Turning to low order partial frontier ratios, looking at the center of the distribution (α = 0.5) (eect on the median of the distribution of Y given that X ≤ x), The results are very stable to changes in the quantile. Detailed results obtained for other values of α are available upon request.

[Figure 2 about here.]

To sum up, these results complement the previous ones obtained using parametric frontiers. Indeed, on the one hand, comparing these nonparametric ndings with the elasticity obtained from the preferred parametric input model, provides conrmation of the existence of a heterogeneous eect of pollution abatement capital on the shape of the frontier but also suggests a particular shape (inverted U) without imposing a specic functional form. On the other hand, when we estimated the parametric eciency model in equation ( 7) we found that pollution abatement capital has a positive -but low in magnitude and not signicant -eect on eciency. This possibly was the result of the imposed parametric specication and distribution assumptions on the error terms, since the second-step nonparametric regression performed in this section indicates a rather complex nonlinear relation. To our knowledge, this is the rst econometric work showing the existence of a non-monotonic eect as suggested, for instance, by [START_REF] André | Strategic Eects and the Porter Hypothesis[END_REF].

Conclusion

This paper estimates the impact of pollution abatement investments on the production technology of rms, using a novel and rich panel data set covering the French food processing industries over the period 1993-2007. It aims to contribute to the literature by pursuing two new directions. First, with respect to a methodological perspective, we take advantage of recent developments in productivity and eciency analysis that allow the consideration of external factors of production. Specically, we compare the results obtained with two complementary approaches: parametric stochastic frontier analysis and conditional nonparametric frontier analysis. These methods present relative advantages and drawbacks and comparing their results may be useful to provide a more robust and thorough picture of the eect of pollution abatement investments on the production technology of rms. A second novel aspect of this paper is its modeling and policy-oriented perspective, since we pay attention not only to the average eect but also on its variability across rms and over time, and search for eventual nonlinearities. These aspects have been recognized as extremely relevant by the theoretical literature and have important implications for rms and society as a whole in terms of advice on environmentally friendly policy.

We provide new results suggesting that the eect of pollution abatement capital on the shape of the production frontier is heterogeneous both within rms and over time, and reinforcing the view that rms' eorts to reduce pollution do not always positively aect their performances, but do in some cases.

We have also documented that the substitutability between pollution abatement capital and physical capital increases constantly over the period. Finally, when switching to a fully nonparametric framework, relevant complementary results are provided. In particular, using this approach it was possible to uncover a nonlinear and non-monotonic eect of pollution abatement capital, both on the shape of the frontier and on the conditional eciencies. These results have relevant implications both for modeling purposes and in terms of policy advice.

Figure 2 (

 2 bottom panel) displays a slightly favorable eect of pollution abatement capital. We observe a very at relation for most of the range of pollution abatement capital which becomes positive for the highest values of such a variable. 6 6

FigureFigure 2 :

 2 Figure 1: Estimated conditional densities of elasticties

Table 1 :

 1 Summary statistics

	Variable	Label	Mean	Std. dev.
	Value-Added (K Euros)	Y	27605.71	52847.71
	labor (Number of workers)	L	418.03	534.38
	Capital stock (K Euros)	K	47756.40	104830.80
	Pollution Abatement Capital stock (K Euros)	Z	980.53	2575.60

Table 2 :

 2 Model selection resultsThe Vuong statistic, V , is asymptotically distributed as standard normal distribution. If V > 1.96, then the rst model is favored at 5% signicance level. If V < -1.96, then the second model is favored at 5% signicance level. Otherwise, for -1.96 ≤ V ≤ 1.96, neither model is preferred.

	Null Hypothesis

By construction, a constant term in Eq. (3) capturing the eect of the rst year cannot be identied simultaneously with the mean of the truncated normal so the value of the constant term is set to zero.

For instance,[START_REF] Guilkey | Comparison of the Performance of Three Flexible Functional Forms[END_REF] have shown that the translog approximation outperforms other Diewert-exible forms such as the generalized Leontief and the generalized Cobb-Douglas, but also provides a reliable approximation only if the complexity of the underlying technology is not too high.

From now on, we use capital letters for random variables and lowercase letters for the values these random variables take.


Loup Rimbaud
email: loup.rimbaud@inra.fr

Julien Papaïx

Benoit Moury

Luke Barrett

Pete Thrall

Improving the durability and efficiency of plant resistance deployment using eco-evolutionary modelling [poster]

Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs very quickly after resistance is deployed, resulting in significant crop losses and a continuing need to breed new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolutionary potential of pathogen populations and thus increase resistance durability. These strategies mainly rely on using different combinations of resistance genes (e.g. qualitative and/or quantitative resistance) in time, space, or both (e.g. via gene pyramiding, cultivar rotations, cultivar mixtures, field mosaics). However, experimental assessment of the efficiency (i.e. ability to reduce disease impact) and the durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of different deployment strategies presents a major challenge.

Therefore, we developed a spatially-explicit stochastic model to assess the epidemiological and evolutionary outcomes of the major deployment options described above, for both qualitative (major resistance genes) and quantitative resistance (e.g. QTLs affecting different pathogen life-history traits). In addition, we analysed the impact of landscape organisation (as defined by the proportion of fields cultivated with a resistant cultivar, and their spatial aggregation) and epidemiological or evolutionary parameters (e.g. mutation probability, cost of infectivity).

The model was first parameterised for cereal resistance to rusts (caused by fungi of the genus Puccinia), and is destined to be applied to other pathosystems including especially viruses of vegetable crops. Our main results on resistance to rusts indicate that evolutionary and epidemiological control are not necessarily correlated, and that no deployment strategies is universally optimal. Key words: deployment strategy, durable resistance, gene-for-gene, plant disease, quantitative resistance, spatially-explicit modelling.


Marc Vandeputte
email: marc.vandeputte@jouy.inra.fr

Khaled Horri

François Allal

Sebastien Ferrari

Marie-Odile Vidal

François Ruelle

Marie-Laure Bégout

Béatrice Chatain

Does early growth play a role in the sex determination of european seabass dicentrarchus labrax?

Keywords: Sex determination, quantitative genetics, growth

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

DOES EARLY GROWTH PLAY A ROLE IN THE SEX DETERMINATION OF EUROPEAN SEABASS Dicentrarchus labrax?

Vandeputte M. 1,2 § , Horri K. 1 , Allal F. 1 , Ferrari S. European sea bass has a polygenic sex determinism with temperature influences, which remains hard to predict and manipulate. To investigate the interactions between early growth and sex determination, we studied West Mediterranean domesticated sea bass from a 50♂x10♀ full factorial cross, reared as a single batch at 15°C to promote female sex determination. Temperature was increased to 25°C from 70 to 119 days post-hatching (dph) to increase growth. Fish were individually tagged at 95 dph (575 mg) with microtags and were individually weighed at 95,115,136,157,200,256 and 325 dph, and then sexed. Parentage was recovered with 12 microsatellites; 1134 fish had appropriate pedigree, sex and growth data. Multivariate sire models were run to investigate the links between growth and sex (considered a threshold trait with an underlying sex tendency). Heritability of sex tendency was 0.39±0.12 on the underlying scale. The sex dimorphism of body weight in favour of females rose from +27% at 95 dph (BW 95 ) to +40-45% between 115 and 325 dph, and the sex dimorphism of DGC was maximal for DGC 95-115 . If differential growth is seen as a consequence of phenotypic sex, growth should be corrected by a fixed sex effect. In this case, there was a positive, although not significant (r A =0.18±0.12) genetic correlation of sex tendency with DGC 95-115 , while it never exceeded 0.05 later than 136 dph. The genetic correlation of BW with sex tendency regularly decreased from 0.45±0.18 for BW 95 to -0.20±0.17 for BW 325 . If differential growth is seen as a cause of phenotypic sex, no fixed sex effect should be modelled, which then led to a r A of sex tendency with DGC decreasing from 0.60±0.11 for DGC 95-115 to 0.21±0.15 for DGC 256-325 , while the r A of BW with sex tendency also decreased from 0.72±0.10 for BW 115 to 0.48±0.14 for BW 325 . In all cases, the genetic and environmental correlation of growth and sex tendency was maximal at the earlier stages, especially before the first reported signs of sex differentiation. This leads us to think that post-larval growth is, at least partially, a cause and not a consequence of sex determination in sea bass.

  3 , Vidal M.-O. 1 , Ruelle F. 1 , Bégout M.-L. 3 , Chatain B. 1 1 Ifremer UMR9190 MARBEC, Chemin de Maguelone, 34250 Palavas-les-Flots, France 2 INRA, UMR1313 Génétique animale et Biologie intégrative, 78350 Jouy-en-Josas, France 3 Ifremer, Ressources Halieutiques de La Rochelle, Place Gaby Coll, 17137 L'Houmeau, France


Christel Marie-Etancelin

Beatrice Gabinaud

Géraldine Pascal

Regis Tomas

Jean Marie Menras

Francis Enjalbert

Charlotte Allain

Helene Larroque

Rachel Rupp

Annabelle Meynadier

Genetic determinism of dairy sheep ruminal microbiota

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Genetic determinism of dairy sheep ruminal microbiota

C. Marie-Etancelin 1 , B. Gabinaud 1 , G. Pascal 1 , R. Tomas 2 , J.M. Menras 2 , F. Enjalbert 1 , C. Allain 1 , H. Larroque 1 , R. Rupp 1 and A. Meynadier 1 . 1 GenPhySE, INRA, INPT, ENVT, Université de Toulouse, Castanet-Tolosan, France. 2 INRA, Experimental Unit of La Fage, Saint-Jean et Saint-Paul, France.

The microbiota of herbivorous animals plays a central role in the nutrition of its host, directly affecting his health and his ability to produce. Very few publications reported results concerning the impact of host genetics on the composition of ruminal microbiota (Rowe et al., 2015). Thus, we proposed to study the genetic determinism of bacterial relative abundances of sheep rumen microbiota. 369 dairy Lacaune ewes raised indoor at the INRA Experimental Farm of La Fage, had a sampling of their rumen fluid done. These ewes were adult animals, fed with a 93% hay-silage based diet and belonged to 4 different lines (lines divergently selected on somatic cells count or on milk persistency). Ruminal metagenome were sequenced using 16s rRNA gene with Illumina Miseq technology. Bioinformatics analysis of the microbiota sequences were implemented with FROGS pipeline to obtain relative abundances of bacteria (Escudié et al., 2017) and R Phyloseq package to estimate biodiversity indices. Fixed effects included in the genetic analyses of relative abundances were the "lines", the "parity" and the "day of sampling" effects. Heritability estimates of the square root of relative abundances were computed in single trait using the VCE 6.0 software (Neumaier and Groeneveld, 1998).

FROGS pipeline allowed clustering the 4,944,307 informative sequences into 2,135 OTUs, which represented 247 bacteria taxas (140 genera, 50 families, 31 orders, 17 classes and 9 phyla). Significant differences between lines were observed: 4 bacteria generas have abundancies differences according to CCS lines (Olsenella, Prevotella 1, Prevotellaceaea Ga6a1, Syntrophococcus with always higher values for CCS+) and 4 others according to PERS lines (Coprococcus 1, Olsenella, Succonivibrionaceae U2, Syntrophococcus). At the genera scale, heritabilities estimates ranged from 0.00 to 0.49 with a standard error of 0.11 on average: 22% of genera had heritabilities higher than 0.1, which is lower than Estellé et al. (2015) on Large White (50% genera with h 2 >0.1). The most heritable genera (h 2 >0.25) were RuminococcaceaeUCG002, Lachnospira, Atopobium and Oscillospira which also were taxa with low abundances.


.07

Multispecies sown grasslands and breeding

Mainly in binary mixtures containing one legume and one grass species

Empirical tests of varieties

Comparison of varieties for the performance in mixture: yield, species proportion, survival

ARVALIS

No selection for performance in mixture With exceptions .08

Multispecies sown grasslands and breeding GMA for the biomass of each species or any other trait Direct effect on the target species Indirect effect on the companion species 'Performance in mixture' : a new breeding trait

The efficiency of this GMA approach assumes that:

 the SMA effects are small

 the progress in one target species will improve the performance of the whole plant community

A high GMA means that the variety has a high performance on average with any variety of the companion species

Limitations

• GMA estimation could not be transferred beyond the specific tested material

• Large number of possible combinations to be tested

'

  Evolutionary plant breeding' method (Suneson, 1956) Selection of individuals after several years (fitness) Initially in multiline mixtures (barley, wheat) Also for grassland species Select plants have experienced the interactions within the cover In multispecies mixtures context => can allow the simultaneous selection of several species.

• On average, selection in pure stand was 40 % less efficient than selection in mixed stand • Specific breeding for intercropping is a key point for species undergoing severe competition

	Annicchiarico et al (2019)
	Advances in Agronomy

We need a specific breeding…  'Performance in mixture' seen as a new breeding trait  Evolutionary plant breeding  'Functional' approach

	GMA: mean value of a cultivar in mixture
	SMA of 1+2 = P12 -(mean P1 + mean P2)/2
	.09

'Performance in mixture' : a new breeding trait

	'Performance in mixture' : a new breeding trait
			Species 1 Cultivar 1	Species 1 Cultivar 2	Species 1 Cultivar 3	Species 1 Cultivar 4	GMA Species 1
	Species 2		P11,21	Cultivar 1 P12,21	Cultivar 2 P13,21 Cultivar 3	Cultivar 4 P14,21	Mean P21
	Cultivar 1	Cultivar 1	P1		P12	P13	P14
	Cultivar 2 Species 2	Cultivar 2 P11,22	P21	P12,22	P2	P23 P13,22	P24 P14,22	Mean P22
	Species 2	Cultivar 3 P11,23	P31	P12,23	P32	P3 P13,23	P34 P14,22	Mean P22
	Cultivar 3	Cultivar 4	P41		P42	P43	P4
	Cultivar 4 Species 2	GMA	P11,24	Mean P1 P12,24	Mean P2	Mean P3 P13,24	Mean P4 P14,24	Mean P22
	GMA Species 1 Mean P11	Mean P12	MeanP13	Mean P14

Initially used to design mixtures of varieties (1970 )

GMA/SMA: General/Specific Mixing Ability approach Evaluation of biomass or other traits of each mixture .010

GMA can also be used with species mixtures

in mixture' : a new breeding trait

		Sp1	Sp1	Sp1	Sp1	Sp1	Sp1	Sp1	Sp1	Sp1	Sp1
		Cult1	Cult2	Cult3	Cult4	Cult5	Cult6	Cult7	Cult8	Cult9	Cult10
	Sp 2
	Tester 1
	Sp 2
	Tester 2
	GMA	P11	P12	P13	P14	P15	P16	P17	P18	P19	P110
	Sp 1

I. Litrico -B. Julier / Strategy avenues for breeding plants for multispecies grasslands .012 => Limit the number of combinations with the concept of 'tester' 'Performance Lucerne biomass in mixture with a forage fescue, g

.019

To create a more general framework for selection of plants to be used in complex mixtures Based on the concepts and theories of community and functional ecology => Complementarity for resource use and acquisition

The functional approach The functional approach .021 .021

Genotype per species => Intra-species variance of interaction traits could be required Dry Irrigated

.022

The functional approach

Breeding

If we known the optimal mean and variance of the interaction traits that maximize the value of the species mixture => the usual scheme of recurrent selection can be applied for each species separately

To obtain a certain variance for the interaction traits:

 pooling a number of cultivars, each with low variance for interaction traits but with contrasting means of these traits The functional approach

.026

Conclusion…

 Need to increase our knowledge on all species used in grasslands and their interactions within a multispecies composition  Screening of the current genetic resources of grassland species to estimate the variability of interaction traits and the genetic correlations between the interaction traits and the agronomic traits  Need to develop proofs of concept with experimental selections Several approaches to improve multispecies grasslands Choice of the method depends on the expected level of performance yield, species composition, …

Quantative genetics and functional analyses to improve the multispecies grasslands

.027

Thank you for your attention!


domain: sdv shs

text:
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Tree-related Microhabitat co-occurrences: towards easier monitoring?


text:
Laurent Larrieu

Benoit Courbaud

Michel Goulard

Wilfried Heintz

Daniel Kraus

Thibault Lachat

Fabien Laroche

Sylvie Ladet

Jörg Müller

Yoan Paillet

Andreas Schuck

Jonas Stillhard

Miroslav Svoboda

Tree-related Microhabitat (TreM) spatial patterns in European beech-dominated forests

A TreM is a specific above-ground tree morphological singularity

• distinct, well delineated structure

• borne by standing living or dead trees

• essential substrate or life-site for taxa • encompassing decaying wood (=saproxylic TreM) or not (=epixylic TreM) 2 Drawings L. Apfelbacher Examples of supplementation (s) and complementation (c) resources 55 sites, 408 plots (0.05-1ha), 20346 living and standing dead trees L. Apfelbacher 11TreM-subgroups selected from Larrieu et al. EI 2018 Set of 6 TreMs common to all databases International standardized TreM database: 267 sites, 1492 plots, 86 754 trees, 17 TreM groups General case Aggregation of TreM-bearing trees Repulsion and very rarely… Local conditions are the main driver of TreM occurrence  dbh ***, but low explanatory power (3%)  Time since the last harvest (dbh*time) ***, medium explanatory power (17%)  Site (dbh*site)***, high explanatory power (36%)  Site-plot (dbh*site-plot)***, the highest explanatory power (42%) Same trend observed at the individually TreM level!

TReMs are key features for many taxa and participate in a complex functional habitat network in species life cycles

•••

  By harvesting TreM-bearing trees, management impacts both TreM density and diversity (e.g. Larrieu & Cabanettes 2012) • We observe poorer communities of TreM-dwelling taxa in managed stands (e.g. Bouget et al. AC 2014) • Is this lower biodiversity due to a lower TreM supply only or also to changes in spatial distribution pattern? -plot scale/Plot scale/Set of plots scale/Forest massif scale/TreM/Set of TreMs Conclusion Hypothesis 1: TreM distribution is spatially structured in old-growth forests (Beech-dominated (>50% trees) stands Tree coordinates >20 trees/plot >10 TreM/plots An analysis focusing on beech-dominated stands, recently harvested or not • 2 time categories since the last harvest < 50 y: managed forest > 100 y: old-growth forest • Set of 6 TreMs pooled • 11 individual TreMs • Binomial GLM • Y (tree bears at least a TreM)~dbh+ 6 Set of 6 TreMs pooled • Binomial GLM • Y (tree bears at least a TreM)~dbh+site+site-plot +time since the last harvest scale/Set of plots scale/Forest massif scale/TreM/Set of random distribution of the TreM-bearing trees Confidence interval L1,1 (r) function: counts the nb of TreM-bearing trees in the r-radius disc M&M Results: Plot scale/Set of plots scale/Forest massif scale/TreM/Set of TreMs Conclusion d d GLM binomial Y=tree bears a TreM or not for 50 % of the plots in Managed forest for 25% of the plots in Old-growth forest Neighbourhood features have a significant effect on TreM bearing tree occurrence + 10% of variance explained by neighbourhood (in addition to dbh) + 18% of variance explained by neighbourhood (in addition to dbh)


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Cell proliferation and cell migration are two essential processes during wound healing and development. These cellular functions are regulated by phosphoinositide 3-kinase (PI3K), and PI3K activity is modulated by the G-protein Rac GTPase. Rac GTPase signaling activates AKT, leading to a cascade of protein interactions with downstream effects that activate mTOR. Thus, PI3K activity ultimately downregulates apoptosis, and upregulates the cell cycle to increase proliferation (Rafalski and Brunet, 2011; Peltier et al, 2007). However, the role of PI3K in cell motility is not as clearly defined. What is known is that an interaction between Ras and PI3K increases cell motility, as preventing Ras binding to PI3K results in upregulation of E-cadherin expression, due to an increase in expression of the protein Reelin. This increase in focal adhesion protein decreases cell motility and migration (Castellano et al, 2016;Shujun et al, 2015). Additional data has shown that PI3K also regulates the actin cytoskeleton through regulation of the protein cofilin, thus providing an additional link between PI3K and motility machinery (Kolsh et al, 2008).

To study the effects of PI3K inhibition on cell migration and proliferation, we used cell tracking reagents, proliferation assays, and live cell kinetic assays, to perform a quantitative analysis of wound healing and closure using dermal fibroblast and epidermal keratinocyte cell models. Using these tools, we reveal that pharmacological inhibition of PI3K activity results in a dosedependent decrease in cell migration and proliferation, thus adversely affecting wound healing rates of both cellular models. The cytoplasmic membrane is a key target for injury induced by chemical compounds during bacterial cultures. A constant intracellular environment must be kept to achieve vital cell functions, and for that, the membrane functionalities must be preserved. When the cytoplasmic membrane cannot adapt by changing its lipidic composition, bacterial cells die consequently.

Microbiology and Aquatic Sciences (B262)

491/B262

Lignocellulosic biomass is an alternative to beet and wheat to produce carbohydrates for the fermentation medium. But the pre-treatment to fractionate lignocellulosic biomass into cellulose, hemicellulose, and lignin, generates phenolic compounds such as vanillin and ferulic acid, carboxylic acids, and furans, all toxic for bacterial growth. In a previous work, we proposed a method to eliminate carboxylic acids and furans, but the phenols remained within the medium. The aim of this work is to assess how phenolic compounds act on the bacterial cytoplasmic membrane.

Materials and Methods:

Strain and culture: Bacillus subtilis 168 was inoculated in MBS medium (xylose 10g/L, Yeast extract 2,5g/L, Bacto Yeast nitrogen base 3.35g/L, with or without, vanillin (3.3mM) or ferulic acid (10.3mM).

Flow cytometry analysis: Bacterial cells were analyzed by flow cytometry (CyFlow Space, SYSMEX) after staining for measurements of viability/mortality (cFDA/PI), membrane polarization (DiBAC), and membrane fluidity (DPH). This last measurement was performed by fluorescence anisotropy. For that, the flow cytometer was equipped with an UV laser, vertical and horizontal polarizers, a half-wave retarder plate, and two photomultipliers for I v and I H .( 1)

Results: With vanillin, the lag phase was extended by 2 hours, compared to the reference, but when growth began, it was similar to the reference. During the lag phase, the cytoplasmic membrane was depolarized, but the membrane polarization increased along the growth, and at last, the membrane was more polarized than the reference at the end of the culture. The membrane fluidity changed like the reference, with rigidification increasing slightly between lag phase and stationary phase.

With ferulic acid, growth began at the same time as the reference, but after 6 hours of culture the viability decreased, at 8 hours, 90% of cells had died (loss of membrane integrity), and all the cells were strongly depolarized. The membrane was more and more rigid. The fluorescence anisotropy of viable cells changed from 0.19 (4h) to 0.23 (7h), while that of dead cells was 0.25. In presence of a mix of vanillin and ferulic acid, a synergic effect on membrane fluidity was observed.

Conclusion:

Vanillin and ferulic acid are known to have antimicrobial effects, and can be used as food preservatives. But mechanisms of action on bacterial cells are not known. This study intended to bring a contribution to this understanding.

Microbial flow cytometry is an established fast and economic technique for complex ecosystem studies and enables visualization of rapidly changing community structures, by measuring characteristics of single microbial cells. Cytometric evaluation routines are available, such as flowCyBar, which are useful for automatic data processing.

In this study, a cytometric workflow was established, which allows routine analysis of salivary microbiomes, as with this example of 10 oral healthy subjects. First, saliva was collected within a 3-month period, cytometrically analyzed, and the evolution of the microbiomes followed, as well as the calculation of their intra-and inter-subject similarity. Second, the respective microbiomes were stressed by exposition to high sugar or acid concentrations, and immediate changes were recorded. Third, bactericide solutions were tested on their impact on the microbiomes.

In all three set ups huge intra-individual variations in cytometric community structures were found to be largely absent, even under stress, while inter-individual diversity was obvious. The bacterial cell counts of saliva samples were found to vary between 3.0x107 and 6.2x108 cells per sample, and subject in undisturbed environments. The application of the 2 bactericides did not cause noteworthy diversity changes, but the loss in cell numbers by about 50% was high after treatment. Illumina® sequencing of whole microbiomes, or sorted sub-microbiomes, revealed typical phyla such as Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Fusobacteria.

This approach is useful for fast monitoring of individual salivary microbiomes, and automatic calculation of intra-and inter-individual dynamic changes and variability, and opens insight into ecological principles leading to their sustainment in their individual environment.

Flow

  cytometry: a relevant tool to assess the integrity, polarization, and fluidity of bacterial cytoplasmic membrane Marielle Bouix, Sarrah Ghorbal, Axel Fayet, Marie-Laure Lameloise To cite this version: Marielle Bouix, Sarrah Ghorbal, Axel Fayet, Marie-Laure Lameloise. Flow cytometry: a relevant tool to assess the integrity, polarization, and fluidity of bacterial cytoplasmic membrane. 33. Congress of the International Society for Advancement of Cytometry (CYTO 2018), International Society for Advancement of Cytometry (ISAC). Bethesda, Maryland, INT., Apr 2018, Prague, Czech Republic. pp.284. hal-01777539

Flow Cytometry: A Relevant Tool to Assess the Integrity, Polarization, and Fluidity of Bacterial Cytoplasmic Membrane Marielle Bouix 1 , Sarrah Ghorbal 1 , Axel Fayet 2 , Marie- Laure Lameloise 3

1 Biological Science and Process Engineering, AgroParisTech-INRA, Grignon, France, 2 Biological Science and Process Engineering, AgroParisTech, Pomacle, France, 3 Biological Science and Process Engineering, AgroParisTech-INRA, Massy, France


Delphine Lallias

Edwige Quillet

Maria Bernard

Nicolas Dechamp

Jean-Michel Le Calvez

Marjorie Bideau

Lionel Goardon

Laurent Labbé

Mathilde Dupont-Nivet

Analysis of genetic variability of DNA methylation in response to an early temperature stress in rainbow trout

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Funding: This study was carried out within AQUAEXCEL 2020 funded by European Union's Horizon 2020 research and innovation programme under grant agreement No 652831.

ANALYSIS OF GENETIC

We aim to investigate the potential role of epigenetic marks in the expression of phenotypes and their variability in fish, in particular genetic variability of epigenetic marks in response to an environmental stress.

In this context, rainbow trout isogenic lines are the material of choice. Within each line, all fish have the same genome i.e. there is no genetic variability. This allows the comparison of epigenetic marks among several individuals with the same genotype. The environmental stress chosen here is temperature because several studies have reported genetic determinism of thermotolerance. Moreover, rainbow trout isogenic lines have recently been characterized for their response to temperature and the existence of a high between-line variability was shown. The aim of this study is to contribute to the understanding of why certain lines are more tolerant to temperature stress than others, by investigating the implication of epigenetic mechanisms in the variability of the response to temperature. More specifically, the objective of this study was to test whether temperature regime experienced during early development leads to epigenetic modifications within and between lines. Nine rainbow trout isogenic lines were chosen. For each line, half of the eggs were incubated at standard temperature (12°C) and the other half at high temperature (16°C), from eyed-stage to hatching. At eyed-stage just before hatching, analysis of global DNA methylation was performed with LUMA (LUminometric Methylation Assay) on 3 pools of 5 eggs per line and per incubation temperature. LUMA analysis revealed significant differences between lines but little or no effect of incubation temperature. Also, for 6 out of the 9 isogenic lines, genomewide patterns of methylation were analysed by EpiRADseq on the same biological material. EpiRADseq is a reduced-representation library-based approach which has been recently developed and tested on a single clone of water fleas. The protocol was here modified to account for genetic variability and allow both within and between-lines comparisons. Globally, very few loci were differentially methylated between the two incubation temperatures. Thus, in the future, the impact of a longer exposure to high temperatures during early development will be tested.

Keywords: epigenetics, DNA methylation, temperature, early stress, rainbow trout


Arece Garcia
email: carine.marie-magdeleine-chevry@inra.fr

VARIOUS CONDENSED TANNINS FROM TROPICAL PLANTS POTENTIAL MULTIPURPOSE NUTRACEUTICS IN RUMINANT FEED

INTRODUCTION

Condensed tanins (CT) are complex polyphenolic secondary metabolites from plants. Protein-CT complexes in ruminants could result in affection of rumen fermentation (Min et al., 2001), allow availability of aminoacids and induce a gastrointestinal nematicidal action (Marie-Magdeleine et al., 2010).

  Study of CT from 5 tropical plants : Manihot esculenta, Chrysobalanus icaco, Cajanus cajan, Terminalia catappa, Leucaena leucocephala. • Chemical quantification and elucidation: Vanilin-H 2 S0 4 assay; thiolysis, HPLC, LC-MS. • Biological activity : Anthelmintic (in vitro against H. contortus exsheathment, with 6 concentrations and repetitions, PBS control). Fermenting (incubation of pure plant substrates in rumen mixed bacteria cultures (2:1, v/v) for 24h at 39°C; with 3 repetitions and perennial ryegrass (PRG) as control). on the Nutrition of Herbivores , Herbivore Nutrition supporting sustainable intensification and agro-ecological approaches ISNH, 2018, Clermont-Ferrand, France

Figure 2 .Figure 1 .

 21 Figure 2. Anthelmintic and fermenting activitiy, relative to CT content

Table 1 . Condensed tannins elucidation Plant CT content in extract (mg/100mg) mDP PC/PD ratio cis/trans ratio % galloyl groups

 1

	T. catappa	1.69	15.32 10.69 24.69	19.23
	C. cajan	11.39	7.84	0.85	3.25	0.00
	L. leucocephala	26.77	3.27	0.59	2.38	26.44
	M. esculenta	44.31	7.23	0.16	2.18	37.44
	C. icaco	58.97	9.19	0.01	1.67	4.51

•Qualitative and quantitative CT variability in plant species •Plants with high CT content •Some high Galloylation levels (biological activity,)


D De Guibert

M Hennetier

Y Gu

F Martin

A Riaublanc

G Delaplace

R Jeantet

Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, Flow process and heating conditions modulate the size and properties of whey protein aggregates

Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures

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Science & Technology of Milk & Egg

Rennes A multidisciplinary and multiscale approach, reinforced by two high-calibre facilities:

Dairy



  Dairy processing and cheese making: toward sustainable dairy systems  Microbial interaction: food matrix and host cell Please visit http://www6.rennes.inra.fr/stlo_eng 83 standing fellow workers Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, At pilot scale, does the process parameters influence the characteristics of fractal aggregates obtained, in relation to different transport phenomena (heatdocument : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, structure and an increase of aggregates size is obtained in transient flow regime AGGREGATES SHAPE AND SIZE ARE MODIFIED IN INTERMEDIATE FLOW REGIME Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, has no impact on aggregate size compared to flow regime in the range investigated. varying Heating residence time at constant Reynolds number of 2000. Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, final size of aggregates depends on particle collision and breakage Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, residence time, 100% of βlg is unfolded at the exit of the heating zone. No additional reactive material should be expected while increasing heating residence time Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, .012 Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. (2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, Domitille de Guibert (INRA) 7 November 2018

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Comment citer ce document : De Guibert, D., Hennetier, M., Delaplace, G., Jeantet, R., Riaublanc, A., Gu, Y. ( 2018). Flow process and heating conditions modulate the size and properties of whey protein aggregates. Presented at 32nd EFFoST International Conference: Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations,

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Effost 2018 / Domitille de Guibert (INRA) 7 November 2018


Geneviève Jolivet

Erwana Harscoet

Nathalie Daniel-Carlier

Laurent Boulanger

Nathalie Daniel

Cloé Pierson

Eric Pailhoux

Estrogens are key differentiating hormones in rabbits

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domain: sdv info

text:
Andrew A Ponter
email: andrew.ponter@vet-alfort.fr

Alexandra Eymard

Ophélie Dhumez

Christine Duvaux-Ponter

Nicolas C Friggens

Nutritional management of health and welfare The response to an oral drench of propylene glycol is modified in dairy goats previously fed straw for two days compared to control fed goats

Take home message The composition of the diet given to goats influences their response to a propylene glycol drench.

Introduction Plasma concentrations of glucose and insulin are known to increase in response to dietary propylene glycol (PG) (Miyoshi et al., 2001). PG is a gluconeogenic precursor widely used in the prevention and treatment of ketosis. It increases the molar percentage of ruminal propionate in postpartum dairy cattle (Christensen et al., 1997). After oral administration, a portion of PG is fermented in the rumen to propionate, but the majority escapes the rumen untransformed and is converted to glucose by the liver (Rizos et al., 2008). High levels of glucose stimulate pancreatic insulin secretion which in turn reduces plasma non-esterified fatty acids (NEFA) if animals are mobilising adipose tissue reserves. We tested whether causing lipomobilisation by giving a straw diet had an influence on the metabolic response to PG.

Material & methods Sixteen dairy goats were selected at parturition and fed ad libitum a TMR to cover dietary requirements for lactation. On day 21 after parturition the goats received an initial PG drench (1 mL/kg LW). Starting on day 26 the goats received straw ad libitum instead of the regular diet and on day 28 the goats received a second PG drench (1 mL/kg LW). Blood samples were taken at -10, 0, 15, 30, 45, 60 and 120 min in relation to each drench and plasma was analysed for insulin, glucose and NEFA. Statistical analysis was performed with PROC Mixed in SAS using the Repeated statement to account for a time effect.

Results

The glucose and insulin response to the PG drench was rapid in control animals but delayed when they received straw for 2 days prior to the drench (Fig. 1). Plasma NEFA were significantly higher in straw + PG compared to control + PG goats (respectively 1.65 ± 0.06 mmol/L vs. 0.56 ± 0.06 mmol/L, p < 0.0001) but did not decrease after the PG drenches in either group (results not shown).

Conclusion

Feeding straw for 2 days prior to a PG drench delayed the increase in plasma glucose and insulin compared to control fed goats. This may be due to a slower rumen emptying rate caused by the straw compared to the lactation diet and this may mean that more time was required for the PG to reach the liver and be converted into glucose. It is unclear why NEFA concentrations were unaffected by PG.

Figure 1

 1 Figure 1 Plasma glucose and insulin after a propylene glycol drench in dairy goats fed either a control diet (control + PG) or straw for 2 days (straw + PG) (n=16, lsmean ± s.e., a,b at a time point indicate a difference between treatments, p < 0.05).

Acknowledgements

The authors would like to thank the goat unit of UMR INRA-AgroParisTech MoSAR for care of the animals, B. Lagofun for technical assistance and DIFAGRI, France for the PG.


Avelyne Villain

Azélie Hazard

Carole Guérin

Alain Boissy

Céline Tallet

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

Vocal expression of emotions in pigs during anticipation of positive social contexts: Impact of human animal relationship.

Avelyne S Villain

Pegase Research Unit, INRA, France

Co-authors

Azélie Hazard; Carole Guérin; Alain Boissy; Céline Tallet 'Emotions' have long been considered as a human specificity. We now know that animals have emotional states characterised by their valence and arousal. Vocal signals carry emotional information and they provide a way to assess the origin and evolution of emotions. We thus studied vocal expression of emotions in domestic pigs, which use several call types in various contexts and are known to be able to anticipate events. We chose to focus on anticipation, which is supposed to trigger more intense emotions than the situations itself. Using a two-way associative learning assay, 60 pigs were trained to learn to anticipate a reunion with either their conspecifics (positive event) or a human. Half of the pigs were habituated to human repetitive positive interactions and were expected to form a positive relationship with the caretaker. The other half were expected to express fear of the caretaker and then get used to this neutral event. This paradigm allowed us to assess how pigs do express anticipatory emotions differing in their valence and arousal. Behaviours, heart rate and vocal expression were monitored. By decoding vocal flexibility in pigs, we provide perspectives for assessing positive emotions in pigs, which may have application to assessing pig welfare.


Iciar Pavez -Zouhair Bouhsina

Dealing with the variability and heterogeneity of raw materials: the governance of sustainable fruit-based supply chains

Introduction

Agricultural products are living materials characterized by their variability and heterogeneity.

 This complexity makes difficult for growers and processors to control the food quality which is increasingly relevant and demanding.

Quality has evolved towards a more comprehensive concept that beyond the organoleptic and nutritional attributes, involve the respect for sanitary, social and ecological considerations.

Our research question is:

How do firms manage the variability and the heterogeneity of fruits within the supply chains ? Our main framework applied is New Institutional Economics: Institutional analysis by Menard (2017Menard ( , 2018) ) and Transaction Cost Economics (Wiliamson 1996(Wiliamson , 2008)). • Level of pathogens (toxins)

Approach

Grower

• Contaminants (pesticide residues, heavy metals, radioactivity) • Other: varietal mix, origin of food materials • Parameters  from generic to customer-specific First processor stage,

• The homogenization and standardization of the industrial product • The valorization of the heterogeneity as means of differentiation

Institutional linkages

Meso-institutions

Variability and heterogeneity:

 Intrinsic characteristics of agricultural products and strongly linked with food quality.  Increase in transaction costs (e.g. measurement).

 Coordination of actors within the supply chains through:  Multilayer institutions influencing technological decisions (e.g. Mesolevel: label for responsible supply chain management e.g. Vergers écoresponsables)  Homogeneization and standardization of the industrial product (predominant strategy)  Valorization of the heterogeneity as means of differentiation  As specific investments increase transactions are governed by tighter forms of governance.

Conclusion:

Thank you for your attention


Nathan Cebron

Sarah Maman Haddad

Pascal Rainard

Gilles Foucras

Local Th17 immunity upon mammary immunization is protective against E. coli mastitis

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

International Veterinary Immunology Symposium

ORAL ABSTRACTS

Results: Vaccine induced protection and individual calf IFN-γ responses to vaccination were variable, allowing us to investigate the correlation between observed protection at slaughter and immune response to vaccination and challenge. Load of MAP in tissues at termination was not associated with level of Vaccine-specific IFN-γ production at early or late time points after vaccination. Mapspecific (PPDj) IFN-γ production appeared as a surrogate of disease with a direct positive correlation with level of MAP in tissues at slaughter. Polyfunctional T cells were induced by vaccination, but were not correlated with protection and could not be sustained during the long-term infection although Vaccine-and MAP-specific IFN-γ levels increased throughout the study period. Current vaccines to Escherichia coli mastitis have shown some albeit limited efficacy. Their mode of action is poorly documented and the immune response protecting the mammary gland against E. coli is not completely understood. To improve our knowledge of mammary gland immune defenses, we compared the response of three groups of six cows that received either an intramuscular or an intramammary protocol of immunization against E. coli P4 before a homologous challenge. The control group received adjuvant only. Local immunization modified favorably the course of infection, by improving bacterial clearance while limiting inflammation. Systemic clinical score was also reduced and mammary secretion was preserved (Herry, 2017). High-throughput profiling using a newly developed cytokine 15-plex assay indicated a diminished TNFα production while increased IFNγ was detected in the immunized groups. Antibody response did not correlate with protection, but cellular immunity better related to protection of the mammary gland. Indeed, a transcriptome analysis performed using RNA sequencing on blood samples collected during immunization and infection phases shows that the lymphocyte response was activated in all groups 12 hours after inoculation and correlated with lower clinical scores as shown by weighted correlation network analysis. At the same time, neutrophils were produced and recruited with a moderate neutropenia in immunized groups. Type I interferon response correlated with intensity and persistence of inflammation during the late phase of mastitis. Furthermore, to assess the local T cell response in mammary tissues of locally immunized and control cows, CD4pos T cells were isolated by fluorescence cell sorting upon mammary tissue digestion of challenged and control glands, and their transcriptome determined by RNA sequencing. Results show that IL-17 expression was increased during E. coli infection and Th17 response was significantly enriched in immunized glands. These findings indicate

IVIS2019.ORG

ORAL ABSTRACTS

that protective mechanisms linked to local immunization rely on IL-17-mediated immunity.

O71

Type III interferon protects cattle against bovine viral diarrhea virus infection

Quintana M.E. 1,2 , Pereyra R. 1,3 , Cardoso N.P. 1,2 , Barone L.J. Background: Bovine viral diarrhea virus (BVDV) is an important pathogen of cattle that can cause significant economic losses in livestock industries, mainly due to reproduction failures and immunosuppression that predispose to opportunistic infections. It is known that infected animals elicit type-III interferon; however, there is no information on the antiviral activity of this cytokine in cattle.

Method: Recombinant bovine interferon lambda 3 (rIFNλ) was expressed in HEK-293 cells. Safety was assessed in 90-daysold calves (n=12) inoculated with two doses of 1.5, 3 and 6 U/kg, verifying the absence of hepatic and hematological toxicity. In a second experiment, 21 days-old BVDV-free calves (n=6) were infected with a BVDV-2 non-cytopathic field strain which produces a well-characterized respiratory disease. Calves (n=4) were inoculated with 6 U/kg of rINFλ two days before and after infection, while another group (n=2) was mock-treated. Presence of BVDV-NS3 protein and cytokines in serum samples and nasal swabs were measured using commercial ELISA kits from 2 to 21 days post-infection (dpi).

Results: Untreated calves developed respiratory disease, clinical signs appeared at 2 dpi and reached a maximum score at 4 dpi. Shedding was detected from 4 to 7 dpi and viremia persisted from 2 to 7 dpi. Systemic TNF-α was induced at 2 dpi. Conversely, rIFNλ-treated calves did not develop clinical disease, none of them shedded the virus and viremia was completely abolished in 3 of the calves, while the other animal had significantly lower NS3-serum levels (p< 0.05) than untreated-calves at all time-points. TNF-α was not detected and systemic IL-10 levels were increased, suggesting a role of rIFNλ in controlling inflammation.

Conclusion:

These results demonstrate that rIFNλ is safe in cattle and capable of protecting these animals against the clinical disease caused by BVDV. This is the first report of the efficacy of type-III INF therapy in cattle.

O70 Local Th17 immunity upon mammary immunization is protective against E. coli mastitis

	Conclusion: Ag-specific
	IFN-γ response to vaccination is not a reliable
	predictor of protection and MAP-specific IFN-γ
	response to PPDj is a predictor of level of
	infection rather than level of immunocompetent
	response to challenge.
	Cebron N. 1 , Maman S. 2 , Rainard P. 3 , Foucras
	G. 1
	1 IHAP, Université de Toulouse, ENVT, INRA,
	Toulouse, France, 2 SIGENAE, INRA, Bio-
	informatics platform, Toulouse, France, 3 ISP,
	INRA, Université de Tours, Nouzilly, France