J L Gourdine
email: luc.gourdine@antilles.inra.fr

A C Sørensen

L Rydhmer

Keywords: breeding goal, inbreeding, local breed, optimal contribution selection

Selection progress must be carefully balanced against the conservation of genetic variation in small populations of local breeds. Well-defined breeding programs with specified selection traits are rare in local pig breeds. Given the small population size, the focus is often on the management of genetic diversity. However, in local breeds, optimum contribution selection can be applied to control the rate of inbreeding and to avoid reduced performance in traits with high market value. The aim of this study was to assess the extent to which a breeding program aiming for improved product quality in a small local breed would be feasible. We used stochastic simulations to compare 25 scenarios. The scenarios differed in size of population, selection intensity of boars, type of selection (random selection, truncation selection based on BLUP breeding values, or optimum contribution selection based on BLUP breeding values), and heritability of the selection trait. It was assumed that the local breed is used in an extensive system for a high-meatquality market. The simulations showed that in the smallest population (300 female reproducers), inbreeding increased by 0.8% when selection was performed at random. With optimum contribution selection, genetic progress can be achieved that is almost as great as that with truncation selection based on BLUP breeding values (0.2 to 0.5 vs. 0.3 to 0.5 genetic SD, P < 0.05), but at a considerably decreased rate of inbreeding (0.7 to 1.2 vs. 2.3 to 5.7%, P < 0.01). This confirmation of the potential utilization of OCS even in small populations is important in the context of sustainable management and the use of animal genetic resources.

There is room for selection in a small local pig breed when using optimum contribution selection: A simulation study 1,2

INTRODUCTION

Local breeds are defined as those that occur in only 1 country [START_REF] Fao | The global strategy for the management of farm animal genetic resources and the Interlaken declaration[END_REF]. European local pig breeds of-ten differ from the major breeds and commercial lines, which are mostly related to Duroc, Hampshire, Landrace, Large White, and Pietrain pigs. [START_REF] Ollivier | An assessment of European pig diversity using molecular markers: Partitioning of diversity among breeds[END_REF] used a sample of 68 European pig breeds, including 29 local breeds, to study genetic diversity. The local breeds accounted for 56% of the total betweenbreed microsatellite diversity. The local pig breeds represent 48% of the total number of pig breeds [START_REF] Fao | The global strategy for the management of farm animal genetic resources and the Interlaken declaration[END_REF], and biodiversity can be maintained by keeping and using a sufficient number of breeds. This will secure the availability of important genes for future needs [START_REF] Fimland | Genetic diversity and sustainable management of animal genetic resources, globally[END_REF]. Furthermore, "loss of local breeds will cause cultural erosion and diminish the ability of communities to maintain their cultures and livelihoods," as stated in the Global Plan of Action for animal genetic resources and the Interlaken Declaration (FAO, 2007, p. 29). Thus, the maintenance of local breeds in pork production seems to be strategically important. Except for the large Iberian pig population, selection for genetic improvement of local pig breeds in well-defined breeding programs is rare.

For the majority of local breeds, such as the Basque [START_REF] Mercat | Analysis of genetic variability of the Basque and Gasconne breeds using genealogical information[END_REF] and the Majorcan [START_REF] Jaume | The Mallorca Black pig: Production system, conservation and breeding strategies[END_REF], the focus is on management of genetic diversity. This agrees with the Convention on Biological Diversity, which states that the components of biological diversity should be used in a way and at a rate that does not lead to a long-term decline of that diversity, thereby maintaining its potential to meet the needs and aspirations of present and future generations (CBD, 2004). However, with pedigree information, optimum contribution selection (OCS; [START_REF] Meuwissen | Maximizing the response of selection with predefined rate of inbreeding[END_REF][START_REF] Grundy | Dynamic selection for maximizing response with constrained inbreeding in schemes with overlapping generations[END_REF] can be applied to control inbreeding rates and simultaneously avoid reduced performance in valuable traits. According to [START_REF] Gandini | Strategies for moving from conservation to utilisation[END_REF], strategies for moving from conservation to utilization include defining the relevant breeding goal and marketing products to secure profitability. If the products are being marketed as "high quality," it may be advisable to select for improved meat quality of the breed.

The main objective of the present paper was to show, using stochastic simulation, that it is possible to design a breeding program to improve a key trait in a small local breed population without increasing the rate of inbreeding above the recommended rate. A meat quality trait (MQT) was chosen as the trait under selection, but the results apply to any trait of importance in the marketing of high-quality products from a local breed.

MATERIALS AND METHODS

Animal Care and Use Committee approval was not obtained for this study because no animals were used.

Scenarios

A number of scenarios were designed to emulate different breeding strategies in populations of local breeds of pigs. A total of 25 scenarios were modeled for 3 population sizes, 2 selection intensities of boars, 2 heritabilities of the trait under selection, and 3 selection strategies (Table 1).

Selection Strategies

Random selection (RS) within sex was used as a benchmark of the least possible rate of inbreeding. These scenarios were performed for only 1 heritability (h 2 ) because this parameter had no impact in this case. The second selection strategy was truncation selection (TS) based on BLUP breeding values. The third selection strategy was OCS based on BLUP breeding values. In principle, OCS is obtained by maximizing the term C, defined as follows [START_REF] Wray | Increasing long-term response to selection[END_REF]:

C = x′â + λx′Ax.
Here x is a vector of contributions in which the contribution x i of animal i to the next generation is x i = 1/2(n i /N), with n i being the number of offspring from animal i and N being the total number of offspring; â is a vector of EBV, and λ is the weight relative to breeding values given to the average relationship between candidates and all potential breeding animals in the population weighted according to their proposed contribution (x′Ax). A is the relationship matrix among those animals. The term λ (which has a negative value) can be interpreted as the cost of inbreeding, paid in reduced genetic gain and genetic gain not expressed because of inbreeding depression. The maximization of C in this study was performed by the software EVA (Evolutionary Algorithms) developed by [START_REF] Berg | EVA Interface User Manual[END_REF]. The EVA software uses an evolutionary algorithm to find the solution vector containing n i , for all selection candidates, that maximizes C, when n i is expressed as

x i .
As pointed out by [START_REF] Sørensen | Optimal genetic contribution selection in Danish Holstein depends on pedigree quality[END_REF], it is difficult to specify the weight λ because this depends on various factors, such as inbreeding depression, time horizon, and genetic gain. In this study, preliminary simulations were undertaken to specify λ before running the final OCS scenarios. Values of λ from -1 to -150 were used in the scenario with the smallest population size (scenario OCS30NS.4) over 5 yr (Figure 1). With λ equal to -50, the rate of inbreeding did not exceed 1% per generation. This value of λ was used thereafter in all OCS simulations.

Population Structure

A pig population with the characteristics of a small local breed was simulated. It was assumed that the local breed was reared in an extensive system, with a constant number of 10 or 24 sows in each herd. The population sizes and structures varied between 300 female reproducers in 30 herds, 840 female reproducers in 35 herds, and 1,848 female reproducers in 77 herds. The production system was small-scale commercial production of high-quality products for a niche market. The breeding goal consisted of 1 MQT, recorded at the slaughterhouse. The products were marketed as "high-quality meat from a local breed." To obtain meat of high quality, slaughter weight was heavy and age at slaughter was greater than the age of first service. Each sow weaned 3 female and 3 male piglets and produced 2 litters per year, to a maximum of 6 litters. This corresponded to a rate of annual sow replacement of 17%. Of the male piglets, at random 2 were castrated and 1 was kept intact in each litter. Castration was performed within the first week after birth.

In an extensive production system, where animals are kept outdoors on pasture or in the forest, it is important to keep sow families together. Thus, the replacement of sows involved the selection of the best gilts as substitutes within the herd, and there was no exchange of gilts between herds. Figure 2 summarizes the simulated structure within a herd. Two types of mating, resulting in 2 different selection intensities of boars, were simulated: natural service (NS) and AI. In the first, only NS was performed. There was 1 boar per herd in scenarios with 30 herds and 2 boars per herd in other scenarios, which corresponded to a mating ratio of 10 or 12, respectively. Selection of NS boars was performed across herds, but selected boars were exchanged between herds only if there were not exactly 2 boars selected within that particular herd. Herds with fewer than 2 boars selected received a boar at random from a herd with more than 2 boars selected. With AI, the ex-istence of an AI station and a functional infrastructure for semen delivery was assumed. Regular semen collection in mature boars was performed, resulting in 500 doses of semen per boar and year, which was sufficient to inseminate 50 sows twice per year with triple inseminations, assuming an average rate of return to estrus after insemination. Thus, with AI, a mating ratio of 48 was assumed. With OCS, the maximum number of matings per boar was set to 10 or 12 for NS scenarios, and was set to 48 for AI scenarios. This meant that it was possible to select more boars under OCS than under TS, whereas some of them would be used less intensively. Mating of selected animals was performed randomly.

Genetic Model and Breeding Value Estimation

The effect of selecting for an MQT with a relatively low h 2 (h 2 = 0.22), such as ultimate pH, was compared with the effect of selecting for a trait with a relatively high h 2 (h 2 = 0.44), such as intramuscular fat content [START_REF] Rosenvold | Factors of significance for pork quality-A review[END_REF][START_REF] Van Wijk | Genetic parameters for carcass composition and pork quality estimated in a commercial production chain[END_REF]. Information on half-and full-sibs of the same generation was not available for gilts and young boar candidates at first service owing to their advanced age at slaughter. Because 2 candidates in a litter had the same information (from slaughtered relatives), withinlitter EBV were identical (litter EBV). The infinitesimal model was used to estimate BLUP EBV, with a fixed effect of herd year-season and a random additive genetic effect, together with a random maternal environmental effect and a residual. The additive genetic variance was set to 1, allowing the estimated genetic change to be expressed in genetic SD.

Computer Simulations

This study used the stochastic simulation program ADAM [START_REF] Pedersen | ADAM: A computer program to simulate selective breeding schemes for animals[END_REF] to calculate genetic progress and the rate of inbreeding per generation in each breeding scheme. The ADAM program uses the DMU program package [START_REF] Madsen | A User's Guide to DMU. A Package for Analysing Multivariate Mixed Models[END_REF] for genetic evaluation. For OCS scenarios, ADAM uses the software EVA [START_REF] Berg | EVA Interface User Manual[END_REF]. Both estimated genetic change in MQT and estimated rate of inbreeding in the population were followed over a period of 15 yr (including an initial 4 yr to stabilize the population). All scenarios were replicated 50 times. Statistical tests of differences between scenarios in the evolution of rates of genetic gain and inbreeding were performed using the MIXED procedure (SAS Inst. Inc., Cary, NC), with fixed effects of number of herds (30, 35, or 77; n = 3), type of mating (NS or AI; n = 2), selection strategy (RS, TS, or OCS; n = 3), and h 2 of selection trait (0.22 or 0.44, n = 2), and the effect of time (n = 11 yr). The repeated measurement option of the MIXED procedure of SAS was used with an autoregressive covariance structure to take into account the correlations between years. The observed accuracy of genetic evaluation and generation interval (GI) came from the same distribution across replicates and across time. Thus, accuracy and GI were analyzed with the ANOVA procedure (GLM procedure). A significance level of P < 0.05 was used when presenting the result. All multiple comparisons of mean values for genetic gain, rate of inbreeding, genetic interval, and accuracy were made using Tukey corrections (SAS Inst. Inc.).

RESULTS

Genetic gain, rate of inbreeding, GI, and accuracy are shown in Table 2. Number of herds, type of mating, selection rules, h 2 of the selection trait, and their interactions all had significant effects on genetic gain, inbreeding, and GI.

with AI schemes because of the random mating across herds. This difference was real, but it was an artifact of the starting of the simulation and not a property of the breeding schemes in equilibrium. Inbreeding in the TS schemes (Figure 4b) increased dramatically, and the cumulative inbreeding in the TS scenario exceeded the cumulative inbreeding for OCS from yr 7. The other schemes with different population sizes (30 and 77 herds) followed the same trend. The rate of inbreeding per generation was significantly less with Values with different superscripts within the same column are significantly different (P < 0.05). Accuracy values did not differ between scenarios. RS (0.50%) and OCS (0.97%) than with TS (4.20%; P < 0.01). The rate of inbreeding in the TS schemes was significantly affected by population size (P < 0.01), with values in the population of 77 herds (on average 2.60%) that were less than those in the population of 35 herds (on average 4.60%). With an h 2 of 0.44, the rate of inbreeding was less in TS schemes than it was with an h 2 of 0.22. The opposite was the case in the OCS schemes. With RS, the rate of inbreeding was less with AI than with NS, despite fewer boars being selected with AI. This occurred because of the substructuring caused by the limited gene flow between herds with NS. As a result, the rate of inbreeding in RS with NS was also greater (ΔF = 0.67%) than values predicted by the formula derived by [START_REF] Wright | Effective size of population[END_REF] ΔF = (8M) -1 + (8F) -1 , where M and F are the numbers of male and female parents; ΔF = 0.14%]. As pointed out by [START_REF] Woolliams | What is genetic diversity? Pages 55-74 in Utilisation and Conservation of Farm Animal Genetic Resources[END_REF], this formula frequently un- derestimates the achieved rate of inbreeding because it describes situations in which RS and mating occur among 2 sexes with unrestricted family sizes.

GI and Accuracy

The GI, ranging from 1.57 (OCS) to 1.83 yr (TS), differed significantly between TS schemes with NS (GI = 1.80 yr), OCS schemes (GI = 1.50 yr), and the other scenarios (RS schemes and TS schemes with AI; GI = 1.75 yr). The average accuracy was 0.46. It tended to be greater in the OCS schemes than in the TS schemes, but this difference was not significant (Table 2).

DISCUSSION

The main objective of this study was to show that it is possible to select for a goal trait in a small population of a local breed. The results showed that this was indeed the case. Using BLUP technology to predict the genetic merit of live animals was crucial in our case because the trait was recorded only on slaughtered animals. However, the use of BLUP values for TS resulted in very high rates of inbreeding because of the small population size and the high correlations between the breeding values of relatives. The use of BLUP values for OCS allowed a substantial genetic response, whereas the rate of inbreeding was only marginally greater than it was under RS.

Meat quality was chosen in our simulation because food quality is an important trait for marketing a highquality product and because marketing is an important component of any sustainable breeding program [START_REF] Woolliams | Genetic contributions and inbreeding[END_REF]. Pork from alternative, extensive production systems will always be more expensive than ordinary pork from an intensive system. Although consumers are willing to pay more for pork with enhanced "ethical quality" [START_REF] Liljenstolpe | Evaluating animal welfare with choice experiments: An application to Swedish pig production[END_REF], we assumed that the product quality must be at least as good as ordinary pork to justify a higher price. It could be argued that, in general, meat quality is no problem in pigs from local breeds reared extensively and slaughtered at an older age. Even so, the results generated by the application of OCS in this study are of general interest. Optimum contribution selection permits selection for a trait related to the weakest link of the production chain even in a small population. The trait could also be litter size or resistance to a specific disease. Such selection could make an alternative production system based on a local breed more economical and thus improve the sustainability of pig production. Optimum contribution selection could also be used with considerable weight being placed on the relationship of selected parents in populations in which the focus is on conservation and genetic progress is less important.

Genetic gain in the OCS and TS schemes differed significantly. On average, the genetic gain in the OCS schemes amounted to between 69% (smallest popula-tion, OCS30NS.2 and TS30NS.2) and 98% (largest population, OCS77AI.4 and TS77AI.4) of the gain in TS schemes. It should be noted that λ was the same for all OCS schemes. The rate of inbreeding should be below 1% in any breeding program claiming to be sustainable [START_REF] Fao | The global strategy for the management of farm animal genetic resources and the Interlaken declaration[END_REF]. If the aim is to keep the rate of inbreeding ≤1%, λ could be smaller (i.e., less weight could be placed on the average relationship relative to breeding value) in the larger population selected for the trait with an h 2 of 0.44. With a smaller λ, the difference in genetic gain between TS and OCS would be even smaller.

In our simulation, the population size was chosen to mimic a local breed production system. For instance, the population size used to simulate pig production from 35 herds (24 sows per herd) was comparable with Basque black pied production in France, which includes 29 herds of 18 sows on average [START_REF] Mercat | Analysis of genetic variability of the Basque and Gasconne breeds using genealogical information[END_REF]. The simulated population of 77 herds was comparable with, for example, Black Mallorcan pig production, which includes 79 herds of 20 sows [START_REF] Jaume | The Mallorca Black pig: Production system, conservation and breeding strategies[END_REF]. Today, no genetic evaluation is performed on the Basque black pig (J.-Y. Dourmad, French National Institute for Agricultural Research, UMR1079 Systèmes d'Elevage, Nutrition Animale et Humaine, Rennes, France, personal communication about Basque pigs). The Black Mallorcan pig is selected for growth rate, but the selection pressure is quite low (J. Gonzalez, IRTA Food Technology, Carcass and Meat Quality, Finca Camps i Armet, Monells, Spain, personal communication about Mallorcan pigs). The current study shows that, with OCS, it is possible to use genetic evaluation and selection while achieving limited rates of inbreeding even in a small population such as OCS30NS, which included only 300 female reproducers.

The implementation of a genetic evaluation in an OCS scheme requires investments in infrastructure to facilitate the recording of traits, the tracking of the identities of tested animals, and genetic analyses. In addition to producing high-quality products, local breeds have other economic value, such as being insurance for the future development of livestock production and having environmental and cultural functions [START_REF] Mendelsohn | The challenge of conserving indigenous domesticated animals[END_REF]. The entire economic value of local breeds could be an important argument to convince policy decision makers to design economic incentives to perform selection schemes of local breeds.

With an AI station, the demands on the infrastructure are even greater. In practice, farmers of local breeds seldom use AI [START_REF] Bonneau | Diversity of pig production systems at farm level in Europe[END_REF]. As reviewed by [START_REF] Bidanel | Apport des nouvelles biotechnologies aux pro-grammes d'amélioration génétique du porc[END_REF], although AI results in greater accuracy of EBV and more rapid access to improved genotypes, it also carries a greater risk of inbreeding. In our simulations, no difference was found in the accuracy of schemes using AI and schemes using NS. The generation interval was longer, and the amount of genetic gain was less in TS schemes with NS than in TS schemes with AI, where h 2 was 0.44. The longer GI is a function of the smaller rate of gain, causing older males to be competitive for a longer period [START_REF] Falconer | Introduction to Quantitative Genetics[END_REF]. With reduced h 2 , there was, however, no difference in genetic gain between TS schemes with NS and with AI. It is likely that the larger selection intensity in the AI schemes is counteracted by decreased accuracy of selection because of a stronger Bulmer effect. Managing an AI station and distributing semen are expensive. It is possible that within the economic constraints of an alternative production system based on a small population of a local breed, it is more valuable to invest in marketing than in AI.

Even if RS is performed, the rate of inbreeding increases by 0.8% in the smallest population. It should be noted, however, that the generation length in the present study was less than 2 yr. Longer GI could be used in a small population in which the conservation of genetic variation over defined time periods is the main focus. It should also be remembered that mating was performed at random, whereas in real populations, there are often rules about maximum coancestry between mates or about the maximum number of offspring per parent. The only rule applied in this simulation was that only 1 boar could be selected from each litter. The advantage of minimum coancestry mating over random mating, in terms of inbreeding rates, is approximately similar with TS and OCS [START_REF] Sonesson | Mating schemes for optimum contribution selection with constrained rates of inbreeding[END_REF]. This suggests that the advantage of OCS found in this study should be present even if sophisticated mating rules are applied. [START_REF] Henryon | Mating animals by minimising the covariance between ancestral contributions generates less inbreeding without compromising genetic gain in breeding schemes with truncation selection[END_REF] showed in a simulation study that minimizing the covariance between ancestral contributions (MCAC mating) generated less inbreeding and at least as much genetic gain as minimum coancestry mating. As long as a central organization manages the database and performs the genetic evaluation and OCS, OCS based on BLUP evaluations and MCAC mating should also be feasible in a small population without AI. However, when OCS is used, the pedigree data must be correct and complete, as shown by [START_REF] Sørensen | Optimal genetic contribution selection in Danish Holstein depends on pedigree quality[END_REF] and [START_REF] Oliehoek | Effects of pedigree errors on the efficiency of conservation decisions[END_REF].

In conclusion, an MQT was chosen as the selection trait in this simulation, but the results are relevant for any trait of importance for the marketing of high-quality products from a local breed. Optimum contribution selection can generate considerable genetic progress at a rate of inbreeding similar to that obtained by RS. Confirmation that OCS allows substantial genetic progress while keeping rates of inbreeding at an acceptable level, even in small populations, is both welcome and important in the context of sustainable management and the use of animal genetic resources.

Figure 1 .

 1 Figure 1. Effect of the weight λ on the rate of inbreeding in the scenario OCS30NS.4 (optimum contribution selection scenario with a structure of 30 herds using natural service and h 2 of 0.44); the error bars are 95% confidence limits.

1

  RS = random selection; TS = truncation selection based on BLUP breeding values; OCS = optimum contribution selection.

Figure 3 .

 3 Figure 3. Evolution of the genetic gain per year estimated in BLUP schemes with h 2 of 0.22, in a total of 30 herds (TS30NS.2: truncation selection scheme; OCS30NS.2: optimum contribution selection scheme). NS = natural selection.

Figure 4 .

 4 Figure 4. Cumulative genetic response (a) and inbreeding (b) estimated in optimum contribution selection (OCS), truncation selection based on BLUP breeding values (TS), and random selection (RS) schemes in a total of 35 herds with h 2 = 0.22. NS = natural selection.

Table 1 .

 1 Summary of input parameters for the 25 simulated scenarios

	Number			Selection	Scenario
	of herds	Type of mating	h 2 of trait	strategy 1	abbreviation
	30	Natural service	-	RS	RS30NS
			0.22	TS	TS30NS.2
			0.22	OCS	OCS30NS.2
			0.44	TS	TS30NS.4
			0.44	OCS	OCS30NS.4
	35	Natural service	-	RS	RS35NS
			0.22	TS	TS35NS.2
			0.22	OCS	OCS35NS.2
			0.44	TS	TS35NS.4
			0.44	OCS	OCS35NS.4
		AI	-	RS	RS35AI
			0.22	TS	TS35AI.2
			0.22	OCS	OCS35AI.2
			0.44	TS	TS35AI.4
			0.44	OCS	OCS35AI.4
	77	Natural service	-	RS	RS77NS
			0.22	TS	TS77NS.2
			0.22	OCS	OCS77NS.2
			0.44	TS	TS77NS.4
			0.44	OCS	OCS77NS.4
		AI	-	RS	RS77AI
			0.22	TS	TS77AI.2
			0.22	OCS	OCS77AI.2
			0.44	TS	TS77AI.4
			0.44	OCS	OCS77AI.4

Table 2 .

 2 Average genetic gain (±SE) per year (ΔG), average rate of inbreeding per generation (ΔF), generation interval (GI), and average accuracy (r) of simulations from yr 5 to 15

		Selection
	Scenario	strategy 1	ΔG, genetic SD	ΔF, %	GI	r
	RS30NS	RS	0.00 ± 0.01 a	0.80 ± 0.30 a	1.75 ± 0.001 a	-
	TS30NS.2	TS	0.35 ± 0.01 b	5.70 ± 0.70 b	1.85 ± 0.009 b	0.43 ± 0.08
	OCS30NS.2	OCS	0.24 ± 0.01 e	0.95 ± 0.60 a	1.69 ± 0.002 a	0.43 ± 0.09
	TS30NS.4	TS	0.39 ± 0.01 d	5.50 ± 0.70 b	1.85 ± 0.008 b	0.41 ± 0.08
	OCS30NS.4	OCS	0.31 ± 0.03 b	1.20 ± 0.80 a	1.69 ± 0.002 a	0.52 ± 0.09
	RS35NS	RS	0.00 ± 0.00 a	0.70 ± 0.10 a	1.75 ± 0.001 a	-
	TS35NS.2	TS	0.40 ± 0.01 d	5.00 ± 0.60 b	1.83 ± 0.005 b	0.48 ± 0.05
	OCS35NS.2	OCS	0.32 ± 0.01 b	1.00 ± 0.31 a	1.52 ± 0.003 c	0.51 ± 0.05
	TS35NS.4	TS	0.44 ± 0.02 e	5.10 ± 0.44 b	1.82 ± 0.004 b	0.55 ± 0.04
	OCS35NS.4	OCS	0.38 ± 0.01 c	1.20 ± 0.36 a	1.51 ± 0.006 c	0.58 ± 0.04
	RS35AI	RS	0.00 ± 0.00 a	0.30 ± 0.02 a	1.74 ± 0.002 a	-
	TS35AI.2	TS	0.42 ± 0.01 d	4.80 ± 0.26 b	1.77 ± 0.004 a	0.44 ± 0.05
	OCS35AI.2	OCS	0.35 ± 0.02 bc	0.97 ± 0.03 a	1.50 ± 0.005 c	0.47 ± 0.04
	TS35AI.4	TS	0.47 ± 0.02 f	4.00 ± 0.20 b	1.76 ± 0.001 a	0.51 ± 0.04
	OCS35AI.4	OCS	0.42 ± 0.02 d	1.00 ± 0.03 a	1.49 ± 0.005 c	0.55 ± 0.04
	RS77NS	RS	0.00 ± 0.01 a	0.64 ± 0.13 a	1.75 ± 0.001 a	-
	TS77NS.2	TS	0.40 ± 0.01 d	5.00 ± 0.69 b	1.83 ± 0.006 b	0.48 ± 0.04
	OCS77NS.2	OCS	0.37 ± 0.01 c	0.94 ± 0.22 a	1.52 ± 0.004 c	0.52 ± 0.04
	TS77NS.4	TS	0.45 ± 0.01 e	2.70 ± 0.19 c	1.82 ± 0.004 b	0.55 ± 0.03
	OCS77NS.4	OCS	0.41 ± 0.01 d	1.00 ± 0.25 a	1.53 ± 0.005 c	0.58 ± 0.04
	RS77AI	RS	0.01 ± 0.01 a	0.20 ± 0.01 a	1.75 ± 0.002 a	-
	TS77AI.2	TS	0.42 ± 0.02 d	2.88 ± 0.15 c	1.76 ± 0.003 a	0.44 ± 0.04
	OCS77AI.2	OCS	0.41 ± 0.01 d	0.76 ± 0.02 a	1.49 ± 0.005 c	0.48 ± 0.03
	TS77AI.4	TS	0.50 ± 0.02 f	2.30 ± 0.10 c	1.76 ± 0.003 a	0.52 ± 0.04
	OCS77AI.4	OCS	0.47 ± 0.02 f	0.73 ± 0.03 a	1.49 ± 0.004 c	0.55 ± 0.04
	a-f

at INRA Institut National de la Recherche Agronomique on August 14, 2013 www.journalofanimalscience.org Downloaded from

RS = random selection; TS = truncation selection based on BLUP breeding values; OCS = optimum contribution selection.

The authors gratefully acknowledge European Community financial participation under the Sixth Framework Programme for Research, Technological Development and Demonstration Activities, for the Integrated Project Q-PORKCHAINS FOOD-CT-2007-036245.

The authors also thank Karel de Greef, at the Animal Sciences Group of Wageningen University (Wageningen, the Netherlands), for inspiring discussions and valuable comments.

Genetic Change

Figure 3 shows the genetic gain per year with an h 2 value of 0.22, in OCS and TS schemes until yr 15 in populations with 300 female reproducers in 30 herds. The first 4 yr in the simulation show how the perturbations in the system diminished before stabilization from yr 5 and onward. Figure 4a illustrates the differences in cumulative genetic response in populations with 35 herds between the OCS, TS, and RS schemes. The other schemes with different population sizes (30 and 77 herds) followed the same trend. As expected, there was no genetic gain in the RS schemes. Annual genetic gain in the TS schemes was slightly greater than it was in the OCS schemes (on average 0.44 vs. 0.37 genetic SD, P < 0.05; Table 2). The smaller population size of schemes with 30 and 35 herds resulted in a difference in genetic gain between the TS and OCS schemes (on average +0.08 genetic SD in the TS schemes) that was greater than that observed in the 77-herd schemes (on average +0.03 genetic SD in TS schemes). No differences (P > 0.05) were observed in genetic gain between the TS schemes with 35 herds and the TS schemes with 77 herds because male and female selection intensities were unaffected by population size. In the OCS schemes, the genetic gain was, however, greater in the 77-herd schemes than it was in the 35-herd schemes or in the 30-herd schemes (on average +0.05 and +0.13 genetic SD, respectively, P < 0.01) because OCS allowed an increased selection intensity in males in a larger population without compromising the increase in relationship of selected animals. The genetic gain in schemes with AI was greater than it was in schemes with NS (on average +0.04 genetic SD, P < 0.05), except for TS schemes with an h 2 of 0.22 and OCS schemes with 35 herds and an h 2 of 0.22. The h 2 value significantly affected the genetic gain; a greater h 2 gave a greater gain (on average +0.05 genetic SD, P < 0.01).

Rate of Inbreeding

Figure 4b shows the trend in inbreeding coefficients over time in the OCS, TS, and RS schemes until yr 15, in populations with 35 herds with a value of 0.22 for h 2 . The first inbreeding occurred very quickly in the NS schemes because of the large within-herd recruitment of boars, whereas the first inbreeding occurred later


Alla Nesterenko

Isabelle Alric

Françoise Silvestre

Vanessa Durrieu
email: vanessa.durrieu@ensiacet.fr

Influence of soy protein's structural modifications on their microencapsulation properties: α α α α-tocopherol microparticles preparation

Keywords: Soy protein isolate, Acylation, Hydrolysis, α-Tocopherol, Microencapsulation, Spray-drying

Enzymatic and chemical modifications of soy protein isolate (SPI) were studied in order to improve SPI properties for their use as wall material for α-tocopherol microencapsulation by spray-drying. The structural modifications of SPI by enzymatic hydrolysis and/or N-acylation were carried out in aqueous media without any use of organic solvent neither surfactant.

Emulsions from aqueous solutions of native or modified SPI and hydrophobic α-tocopherol, were prepared and spray-dried to produce α-tocopherol microparticles. The effect of protein modifications and the influence of the core/shell ratio on both emulsions and microparticles properties were characterised. The obtained results demonstrated that oil-in-water emulsions prepared with modified proteins had lower droplet size (0.5-0.9 µm) and viscosity (3.6-14.8 mPa⋅s) compared to those prepared with native proteins (1.1 µm and 15.0 mPa⋅s respectively).

Efficiency of oil retention decreased after protein hydrolysis from 79.7 to 38.9%, but the grafting of hydrophobic chain by acylation improved efficiency of α-tocopherol retention up to 94.8%. Moreover, higher emulsion viscosity, particle size and process efficiency were observed with the increase of α-tocopherol amount.

Introduction

Vegetable proteins, being relatively word cheap, non-toxic, biocompatible and biodegradable biopolymers, are actually becoming a realistic alternative to animal proteins and even synthetic polymers for some specific applications [START_REF] Baniel | Functional properties of glycosylated derivatives of the 11S storage protein from pea (Pisum sativum L.)[END_REF][START_REF] Chel-Guerrero | Functional properties of flours and protein isolates from Phaseolus lunatus and Canavalia ensiformis seeds[END_REF][START_REF] Gennadios | Edible films and coatings from wheat and corn proteins[END_REF][START_REF] Mateos-Aparicio | Soybean, a promising health source[END_REF][START_REF] Vliet | Gelation and interfacial behaviour of vegetable proteins[END_REF]. Their use as wall material for active components microencapsulation reflects this actual tendency, particularly in nutritional, pharmaceutical and cosmetic fields [START_REF] Gharsallaoui | Utilisation of pectin coating to enhance spray-dry stability of pea protein-stabilised oil-in-water emulsions[END_REF][START_REF] Nori | Microencapsulation of propolis extract by complex coacervation[END_REF][START_REF] Patel | Quercetin loaded biopolymeric colloidal particles prepared by simultaneous precipitation of quercetin with hydrophobic protein in aqueous medium[END_REF][START_REF] Rascon | Carotenoid retention and storage stability of spray-dried paprika oleoresin using gum arabic and soy protein isolate as wall materials[END_REF]R. Wang, Tian, & Chen, 2011). The water solubility and amphiphilic properties, the ability to self-associate and interact with variety of substances, the high molecular weight and molecular chain flexibility of vegetable proteins give them excellent surfactant properties for emulsification. These proteins are thus very suitable for Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 3 microencapsulation techniques requiring preliminary emulsions such as spray-drying, coacervation and solvent evaporation. Finally, due to their facility for adhesion and good film formation, their resistance toward oils or organic solvents and gas barrier properties [START_REF] De Graaf | Requirements for non-food applications of pea proteins[END_REF], proteins are really good wall forming product.

Among vegetable proteins, soy protein isolate (SPI) has been extensively studied for numerous applications. As protein from legume seeds, it has a potential role as substrate for the development of delivery systems due to its functional properties and high nutritional value [START_REF] Pereira | Legumes seeds protein isolates in the production of ascorbic acid microparticles[END_REF]. Indeed, its good gelling, emulsifying, fat-absorbing and water binding properties [START_REF] Caillard | Physicochemical properties and microstructure of soy protein hydrogels co-induced by Maillard type cross-linking and salts[END_REF][START_REF] Hua | Heat induced gelling properties of soy protein isolates prepared from different defatted soybean flours[END_REF][START_REF] Nunes | Vegetable proteins and milk puddings[END_REF], make it very relevant on a microencapsulation point of view. For spray-drying microencapsulation, the selection of encapsulant agents is based on their interfacial functionality, good solubility and low viscosity at high solid content [START_REF] Kim | Microencapsulation properties of gum arabic and several food proteins: spray-dried orange oil emulsion particles[END_REF]. Soy protein possesses good solubility in water at pH higher than 9 and is able to form a dried matrix around dispersed compounds in dehydration processes, which entraps them inside the matrix and protect them from air oxidation and UV degradation [START_REF] Charve | Encapsulation performance of proteins and traditional materials for spray dried flavors[END_REF].

Microencapsulation of oil or water soluble substances with SPI was particularly investigated using spray-drying [START_REF] Augustin | Maillard reaction products as encapsulants for fish oil powders[END_REF][START_REF] Charve | Encapsulation performance of proteins and traditional materials for spray dried flavors[END_REF][START_REF] Kim | Microencapsulation properties of gum arabic and several food proteins: spray-dried orange oil emulsion particles[END_REF]Ortiz, Mauri, Monterrey-Quintero, & Trindade, 2009;[START_REF] Rascon | Carotenoid retention and storage stability of spray-dried paprika oleoresin using gum arabic and soy protein isolate as wall materials[END_REF][START_REF] Rusli | Stabilization of oils by microencapsulation with heated protein-glucose syrup mixtures[END_REF]Yu, Wang, Yao, & Liu, 2007), simple [START_REF] Gan | Evaluation of microbial transglutaminase and ribose cross-linked soy protein isolate-based microcapsules containing fish oil[END_REF] or complex coacervation [START_REF] Lazko | Soy glycinin microcapsules by simple coacervation method[END_REF][START_REF] Mendanha | Microencapsulation of casein hydrolysate by complex coacervation with SPI/pectin[END_REF][START_REF] Nori | Microencapsulation of propolis extract by complex coacervation[END_REF] and gelation [START_REF] Chen | Elaboration and characterization of soy/zein protein microspheres for controlled nutraceutical delivery[END_REF] techniques.

Soy protein is generally used as individual coating material, but also can be mixed with polysaccharides such as maltodextrin, pectin, etc. [START_REF] Augustin | Maillard reaction products as encapsulants for fish oil powders[END_REF][START_REF] Favaro-Trindade | The use of spray drying technology to reduce bitter taste of casein hydrolysate[END_REF][START_REF] Mendanha | Microencapsulation of casein hydrolysate by complex coacervation with SPI/pectin[END_REF][START_REF] Nori | Microencapsulation of propolis extract by complex coacervation[END_REF]Yu et al., 2007). In case of hydrophobic core, microencapsulation using SPI or SPI/polysaccharide blends, oil-in-water emulsion stabilization before spray-drying is often effectively carried out by high pressure homogenization.

The continuous need for multi-functional materials has required to develop different modification techniques (chemical, enzymatic or physico-chemical) to enhance and diversify protein functionalities, more appropriate to current microencapsulation techniques [START_REF] Magdassi | Surface activity of proteins chemical and physico-chemical modifications[END_REF]. Protein hydrolyzates have been shown to have various interesting properties such as higher solubility, foaming and emulsifying properties compared to the native proteins [START_REF] Kong | Enzymatic preparation of immunomodulating hydrolysates from soy proteins[END_REF]. Acylation was used to enhance protein surface hydrophobicity, Yin, Tang, Wena, Yang, & Yuan, 2010). Indeed, attachment of hydrocarbon chains may modify the charge and structural properties of watersoluble proteins, increasing their hydrophobicity, and enhancing the amphiphilic characteristics. Thus, protein affinity with oil should be reinforced, inducing an improved microencapsulation efficiency for hydrophobic active core [START_REF] Lazko | Soy glycinin microcapsules by simple coacervation method[END_REF].

This study was conducted to investigate the effect of soy protein isolates modifications on their microencapsulation properties, compared to native protein. Proteinic chains of SPI were modified by enzymatic hydrolysis and/or N-acylation. Acylation reaction was carried out with three different hydrophobic groups (8, 12 and 16 carbon atoms). Modified and native proteins were then used for α-tocopherol microencapsulation by spray-drying technique. In the context of green chemistry, all the modifications and preparations were carried out without use of organic solvent and chemical catalyst, that was appropriated to food industry [START_REF] Aider | Chitosan application for active bio-based films production and potential in the food industry: Review[END_REF][START_REF] Vilkhu | Applications and opportunities for ultrasound assisted extraction in the food industry -A review[END_REF]. The effects of proteins chemical modifications on emulsions properties, process yield, efficiency of oil retention, microparticles morphology and size distributions were examined. Finally, the soy protein/αtocopherol ratio was also varied in order to examine its influence on emulsions and microparticles properties.

Materials and methods

Materials

Soy protein isolate, 90% pure, was purchased from Lustrel Laboratoires SAS (Saint Jean de Vedas, France). All other chemicals were of analytical grade. α-Tocopherol, alcalase (protease from Bacillus licheniformis), amino acid standard, NaOH, HCl 37%, octanoyl chloride, dodecanoyl chloride, hexadecanoyl chloride and cyclohexane (HPLC grade) were purchased from Sigma (Saint-Quentin Fallavier, France).

SPI characterisations

Soy protein isolate was analysed for proximate composition -moisture, lipid, ash and protein contents. The moisture content and the ash content were determined by heating a

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 5 sample of the air-dried material in an oven at 105 and 550-600°C respectively to constant weight [START_REF] Aoac | Official method of analysis of AOAC International[END_REF]. The protein content was determined by Kjeldahl method (N×6.25) [START_REF] Helrich | Official methods of analysis of the association of official analytical chemists[END_REF][START_REF] Mcgeehan | Automated instrumental analysis of carbon and nitrogen in plants and soil samples[END_REF] and lipid content by conventional Soxhlet extraction in cyclohexane during 7 hours. These analyses were performed in triplicate.

Amino acid profile of SPI was identified after total acid hydrolysis. Initially, 1 g of SPI was hydrolyzed with 10 mL of 5.37 N HCl at 105°C for 24 hours under a nitrogen atmosphere in a sealed tube. Then liquid phase was removed by evaporation and the sample was dissolved in 10 mL of buffer (pH 2.2), filtered through a 0.45 µm PTFE membrane filter and analysed by using the Biochrom 30 amino acid analyzer (Serlabo Techonogies, Entraigues sur la Sorgue, France). All determinations were carried out in triplicate.

Protein solubility profile was determined by the following method (Zheng, Yang, Tnag, Li, & Ahmad, 2008). Protein samples were mixed with deionized water in the ratio of 5% w/w and the pH of the mixture was adjusted to 1.0-13.0 with 4 M NaOH or 4 M HCl.

Protein solubility was determined at room temperature and at 70°C. Due to the low solubility at room temperature, the temperature of 70 °C was chosen in order to obtain an improved solubility without protein denaturation, as the major globulin fraction of soy protein is still resistant to thermic denaturation in aqueous solution at 65-73°C [START_REF] Sun | Gelation properties of myofibrillar/pea protein mixtures induces by transglutaminase crosslinking[END_REF]. All suspensions with different pH values were stirred for 1 hour at both temperatures and centrifuged at 10000 g for 15 min (Sigma Laborzentrifugen, Osterode, Germany). Protein content in the supernatant was determined by Kjeldahl method. Protein solubility (S%, w/w) was calculated using the formula: S (%) = protein content in the supernatant/total protein content in solution×100

(1)

SPI Modifications

Enzymatic hydrolysis

The enzymatic hydrolysis was carried out according to the method described in literature [START_REF] Kong | Enzymatic preparation of immunomodulating hydrolysates from soy proteins[END_REF]. The controlled hydrolysis conditions were: time, temperature, pH, enzyme/protein ratio (0.002 w/w) protein concentration (5% w/w). SPI in water solution was prepared and incubated in a bath at 50°C for 10 min. When the protein solution reached 50°C, enzyme solution with the activity of 2.4 U/g was added. The pH of solution was maintained constantly at 7.0 by adding a 4M NaOH solution during 15 minutes of reaction.

The reaction was ended by adjusting the pH of the solution to 4.5 with a 4M HCl solution.

After the reaction period, the mixture was cooled, adjusted to pH 7.0 and heated at 95°C for The degree of hydrolysis (DH) was analysed by the method using o-phthaldialdehyde (OPA) [START_REF] Church | Spectrophotometric assay using o-phthaldialdehyde for determination of proteolysis in milk and isolated milk proteins[END_REF][START_REF] Goodno | A fluorimetric assay for available lysine in proteins[END_REF]. OPA reacts with primary amino groups i.e. N-terminal and lysine residues of proteins forming a chromophore with UV-absorbance optimum at 340 nm with UV Spectometer (UV-1800, Shimadzu, Kyoto, Japan). Non hydrolyzed, totally hydrolyzed (acid hydrolysis at 105°C during 24 h) and partially hydrolyzed proteins were analysed by OPA method, and DH was calculated using following equation:

DH (%) = (N h -N 0 )/(N t -N 0 )×100 (2)
where N h -molar quantity of amino groups per gram of partially hydrolyzed protein, N 0molar quantity of amino groups per gram of non hydrolyzed protein, N t -molar quantity of amino groups per gram of totally hydrolyzed protein. Analyses were carried out in triplicate.

N-acylation

N-acylation reactions were carried out with SPI or SPI hydrolyzates (started in the same medium after hydrolysis and enzyme deactivation), using octanoyl chloride (C8), dodecanoyl chloride (C12) or hexadecanoyl chloride (C16), following Schotten-Baumann reaction [START_REF] Rondel | Synthesis and properties of lipoamino acid-fatty acid mixtures: influence of the amphiphilic structure[END_REF]. SPI solution (5% w/w, pH 10) was prepared in deionized water and the fatty acid chloride was slowly added to this mixture. The molar ratios fatty acid chloride/NH 2 of protein used for reaction were 0.5 and 1.

Depending on these two ratios the protein samples obtained after acylation with C8 (C12, C16) were called M4 and M5 (M6 and M7, M8 and M9) respectively. The solution was stirred during 30 min at room temperature, then 180 min at 50°C. During acylation, pH was maintained constantly at 10.0 by addition of a 4M NaOH solution. Then the mixture was freeze-dried and the powder was stored at 4°C.

The degree of acylation (DA) was determined by OPA-method according to the same protocol as degree of hydrolysis. DA was calculated as:

DA (%) = (n-n a )/n ×100 (3)
where n -number of amino groups from non hydrolyzed or partially hydrolyzed protein, n anumber of amino groups from protein after acylation. Analyses were carried out in triplicate.

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 7

Emulsion preparation

Oil-in-water emulsions were prepared according to the following procedure: 8% w/w protein solution based on intact or modified SPI with pH adjusted to 10.5 was heated to 70°C

for 120 minutes under constant mechanical stirring up to maximal protein solubilisation. α-Tocopherol (T) was preheated to 70°C and quickly added to the protein solution under mechanical stirring at 500 tr/min for obtaining o/w pre-emulsion in which the ratio SPI/αtocopherol was 2/1 (11.5% w/w of total solids). To obtain a stable and uniform emulsion of αtocopherol in SPI solutions, homogenization was carried out at 50 MPa with double circulation through homogenizator (APV Systems, Albertslund, Denmark). The first circulation is known to disintegrate and disperse particles throughout the fluid, whereas the second would to break down the newly formed or re-agglomerated clusters of droplets after the first homogenization to enhance the emulsions quality (Yu et al., 2007). Proportions wall/core of 1/1 and 1/2 (14.8% w/w and 20.7% w/w of total solids) were also tested using SPI as a wall material to obtain the emulsions M0* and M0** or SPI acylated with C12 wall material to obtain the emulsions M6* and M6** respectively.

Emulsion characterisations 2.5.1. Emulsion droplet size measurements

Oil droplets size average and distribution in emulsions were measured by laser diffraction instrument (Zetasizer Nano-ZS, Malvern Instruments, Worcestershire, UK). To avoid multiple scattering effects, emulsions were diluted 100 times with deionized water before measurements. A relative refractive index n oil /n water =1.12 (n oil =1.49, n water =1.33) was used for the calculation of particle size distributions, assuming that all droplets were spherical in shape. The volume particle diameter (D 43 or D v ) was calculated as mean of three readings per sample.

Emulsion morphology

To complete the information obtained by laser granulometry, emulsions were visualised using an Eclipse E600 optical microscope (Nikon, Sendai, Japan), connected to a digital video camera (DXM1200, Nikon, Sendai, Japan) at magnication of 1000×.

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 8

Emulsion viscosity measurements

Emulsion viscosity before and after homogenization was determined at 20°C and shear stress variation between 0 and 1 N/m 2 during 3 min, using a Rheometer CSL100 (Carri-Med LTD, Dorking, UK) with cone-plate geometry of 6 mm diameter and 0.035 rad angle. All emulsions were characterized as Newtonian fluids.

Spray-dried microparticles preparation

Freshly homogenized emulsions were spray-dried in a Mini Spray Dryer B-290 (Büchi, Flawil, Switzerland) at the following process conditions, as follows: inlet air temperature at 120±4°C and outlet at 75±4°C, drying air flow rate of 470 L/h, liquid feed flow rate of 0.33 L/h and aspiration of 100%. Microparticles were collected from the container, closed hermetically in an opaque packaging and stored at 4°C. The yield of spray-drying was defined as follows:

Spray-drying yield (%) = M P /M SPI+T ×100 (4)
where M P -the mass of collected powder and M SPI+T -the initial mass of solid content added in emulsion including soy protein and α-tocopherol.

Microparticles characterisations 2.7.1. Moisture content

Moisture content of all the obtained powders was determined with infrared moisture balance (Sartorius, Goettingen, Germany) by drying at 105°C to constant weight.

Retention efficiency (RE)

Efficiency of α-tocopherol retention after microencapsulation was calculated as the percent ratio of estimated active agent (α-tocopherol) content of obtained particles or obtained powder (T exp ) on theoretical active agent content (T theo ):

RE (%) = T exp /T theo ×100 (5)
To determine the amount of α-tocopherol in the prepared microspheres, UV/VIS spectroscopy was used [START_REF] Faria | Characterization and singlet oxygen quenching capacity of spray-dried microcapsules of edible biopolymers containing antioxidant molecules[END_REF]. Initially, a calibration curve absorbance vs. concentration was prepared with the T dissolved in 9 cyclohexane (previously, protein insolubility in this solvent was verified) and analysed at λ max of 298 nm. After, 5 mg of microspheres containing α-tocopherol to be determined were broken in mortar and dissolved in 10 mL of cyclohexane. The solution was stirred 10 min and filtered through a 0.2 µm PTFE membrane filter. The absorbance of the solution was measured using a UV/VIS absorbance spectrometer at 298 nm. This procedure was carried out in triplicate.

Loading efficiency (LE) is the α-tocopherol content per 100 g of powder. This parameter was calculated as:

LE (%) = T theo ×RE (6)

Microparticles size distribution

Particle size distribution in dry powder was determined by the scattering pattern of a transverse laser light using the equipment Scirocco 2000 (Malvern Instruments, Worcestershire, UK), that determined the particle mean diameters ranging from 0.2 to 2000 µm. The used refractive index is 1.52, pressure of air of dispersion -4 Bars, degree of vibration -70%. The volume particle diameter (D 43 or D v ) was calculated as mean of three measurements per sample.

Microparticles microstructure

Morphology of the microparticles was examined by scanning electron microscopy (SEM). The particles were deposited on conductive double-faced adhesive tape and sputtercoated with silver. In order to examine the inner structure of prepared microparticles, the powder was froze in liquid nitrogen and broke in mortar. SEM observations were performed with a LEO435VP scanning electron microscope (LEO Electron microscopy Ltd., Cambridge, UK) operated at 8 kV.

Thermogravimetric analysis (TGA)

TGA was carried out using ATG/DSC Q600 from TA Instruments (New Castle, US) at a linear heating rate of 10°C/min. The weight of all samples was kept within 9-10 mg in a platinum pan. The temperature range was from 20 to 1100°C. Thermal stability of wall material (SPI), active core (T) and prepared microparticles (M0) was represented by TG curves.

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 10

Statistical analysis

The experimental data was statistically analyzed using Minitab 16 software (State College, USA). A one way analysis of variances (ANOVA) was performed to determine significant differences (P<0.05) among the samples. Tukey's test was adopted as the multiple comparison procedure.

Results and discussion

SPI characterization

According to obtained results, the wall material, SPI, was predominantly constituted of proteins (82.3% or 89.5% in dry matter), but also presented 1.6% of lipids, 5% of ahs and 8% of moisture. The carbohydrate content was calculated as the difference between 100% and the combined percentage of crude protein, lipid, ash and moisture. Amino acids composition of hydrolyzed SPI showed that this protein was principally made up of 16 amino acids (Fig. 1), that is characteristic for soy protein [START_REF] George | Determination of Amino Acid Composition of Soybeans (Glycine max) by Near-Infrared Spectroscopy[END_REF]Zamora, 2005). These observations are typical of soybean proteins [START_REF] Deng | Effects of replacing fish meal with soy protein concentrate on feed intake and growth of juvenile Japanese flounder, Paralichthys olivaceus[END_REF][START_REF] Solina | Volatile aroma components of soy protein isolate and acid-hydrolysed vegetable protein[END_REF]. The results in Fig. 2 show that solubility of SPI at alkaline pH was significantly higher at 70°C than solubility at room temperature. The protein higher solubility at alkaline pH values can be explained by protein functionality which is closely related to the conformational state, influenced by processing conditions (temperature, pH, solvent) [START_REF] Harwalkar | Thermal analysis of foods[END_REF] and affected by the equilibrium between proteinsolvent and protein-protein interactions [START_REF] Mo | Soybean glycinin subunits: characterisation of physicochemical and adhesion properties[END_REF]. Due to their high amount in aspartic and glutamic acids, proteins have negative net charges (COO -) on their surfaces at alkaline pH. The repulsion between polymeric chains increase and the proteinprotein interactions decrease, which favours the protein-water interactions and explains the maximum of SPI solubility at pH higher than 10 [START_REF] Fennema | Food Chemistry[END_REF]. The energy brought by heating has also a positive effect on the protein solubilisation, increasing the fraction of soluble SPI in solution. A good solubility of wall material before spray-drying is essential to enhance microencapsulation efficiency [START_REF] Gouin | Microencapsulation: industrial appraisal of existing technologies and trends[END_REF]. For this reason all the SPI/T emulsions were prepared with the soy protein solubilised at pH 10.5 at the temperature of 70°C.

Emulsion preparation and characterisation

Emulsion preparation is the first step involved in the process of microencapsulation by spray-drying. Emulsion parameters have significant influence on microparticles properties.

For example, different authors showed that retention of active compounds during spraydrying could be enhanced by reducing the mean emulsion droplet diameter of dispersed components during emulsification [START_REF] Mongenot | Effect of ultrasound emulsification on cheese aroma encapsulation by carbohydrates[END_REF][START_REF] Sheu | Microencapsulation by spray drying ethyl caprylate in whey protein and carbohydrate wall systems[END_REF][START_REF] Soottitantawat | Microencapsulation by spray drying: influence of emulsion size on the retention of volatile compounds[END_REF]. Accordingly, high-pressure homogenization has already been widely used in emulsion preparation for microencapsulation [START_REF] Augustin | Maillard reaction products as encapsulants for fish oil powders[END_REF][START_REF] Kim | Microencapsulation properties of gum arabic and several food proteins: spray-dried orange oil emulsion particles[END_REF][START_REF] Rascon | Carotenoid retention and storage stability of spray-dried paprika oleoresin using gum arabic and soy protein isolate as wall materials[END_REF][START_REF] Rusli | Stabilization of oils by microencapsulation with heated protein-glucose syrup mixtures[END_REF]Yu et al., 2007). Indeed, in addition to an evident emulsion stability improvement, the authors [START_REF] Rusli | Stabilization of oils by microencapsulation with heated protein-glucose syrup mixtures[END_REF]Yu et al., 2007) noted that the high pressure homogenization decreases slightly the emulsion viscosity of and the oil droplet average size.

To control the good dispersion of oil in protein solution, emulsions stability and uniformity of droplet size, preparations were analysed by light scattering and observed by optical microscope at 1 hour, 1 day and 1 week after homogenization (Fig. 3 and Fig. 4). The Emulsion viscosity is an important parameter affecting mainly the size of microparticles and the thickness of their wall [START_REF] Risch | Spray dried orange oil: effect of emulsion size on flavour retention and shelf stability[END_REF][START_REF] Rosenberg | Factors affecting retention in spraydrying microencapsulation of volatile materials[END_REF]. With viscosity increase, the residence time of emulsion in spray-dryer was higher and the droplets formation is more difficult. Thus, solvent evaporation rate is changing as well as droplet and microparticle size [START_REF] Lefebvre | Atomization and sprays: Taylor&Francis[END_REF]. The rheological properties were studied to determine the influence of homogenization pressure to the viscosity of the emulsions. Viscosity of emulsion M0 before homogenization was about 44 mPa⋅s and decreased significantly after homogenization to 15 mPa⋅s. That could be due to breaking of intermolecular hydrogen bonds and Van der Waals attractive forces between the proteins and water molecules during homogenization. Under giveng conditions soy proteins were not completely soluble and homogenization pressure caused the interruptions of all intermolecular bonds between protein chains and so affected the decrease of viscosity. Furthermore, the mechanical energy transfer to fluid particles under high pressure involves the microfluidization process, generating microstreams with increased velocity [START_REF] Ciron | Comparison of the effects of high-pressure microfluidization and conventional homogenization of milk on particle size, water retention and texture of non-fat and low-fat yoghurts[END_REF][START_REF] Tunick | Effect of high pressure microfluidization on microstructure of mozzarella cheese[END_REF] and formation of fine emulsion with reduced viscosity.

After stabilisation, emulsion M0 was spray-dried at inlet temperature of 120°C and the obtained powder of microparticles was collected for following analysis. Small mass loss at 100°C is related to residual water molecules presented in SPI and M0. The visible decrease of M0 TG curve after 400°C compared to SPI curve is attributed to evaporation of α-tocopherol situated in microparticles. Soy protein degradation was observed at temperatures higher than 200°C with maximal mass loss (more than 50%) between 200-400°C. The same thermal behaviour was described by other authors for the soy proteins [START_REF] Guerrero | Mechanical and thermal properties of soy protein films processed by casting and compression[END_REF][START_REF] Schmidt | Thermal stability of films formed by soy protein isolate-sodium dodecyl sulfate[END_REF][START_REF] Wang | Properties of molded soy protein isolate plastics[END_REF].

Thermal analysis

SPI modifications

Protein hydrolyzates have shown various interesting properties such as solubility, foaming and emulsifying properties compared to the intact proteins [START_REF] Kong | Enzymatic preparation of immunomodulating hydrolysates from soy proteins[END_REF].

Enzymatic hydrolysis resulted in decrease of protein molecular mass with less secondary structure, and in improvement of protein's functional properties and solubility. This method also permits the producing of more uniform products. Hydrolysis is very promising way for development of functional and nutritious ingredients. In our work, soy protein hydrolyzate

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 15 having a hydrolysis degree of 4% (acylated or not) was prepared and studied as a wall material for the α-tocopherol microencapsulation.

Soy proteins acylation is also known to affect their physico-chemical properties, particularly their emulsifying one [START_REF] Matemu | Improved emulsifying properties of soy proteins by acylation with saturated fatty acids[END_REF]. Indeed, attachment of hydrocarbon chains modifies the charge and structural properties of water-soluble soy proteins, increasing their hydrophobicity, thus improving their affinity for hydrophobic substrates such as α-tocopherol. The acylation rate of SPI and hydrolyzed SPI was determined as described previously. Table 1 shows the degree of these modifications.

Table 1. Modification degree of soy proteins.

Sample A NH 2 /fatty acid (n/n) DH B (%) DA C (%) M1 - 4±1 - M2 1/0.5 4±1 31±1.8 M3 1/1 4±1 61±2.5 M4 1/0.5 - 25±1.2 M5 1/1 - 31±2.3 M6 1/0.5 - 32±0.8 M7 1/1 - 38±1.3 M8 1/0.5 - 29±0.8 M9 1/1 - 31±1.8
A M1: hydrolysed soy proteins; M2, M3: hydrolysed and acylated with C12 soy proteins; M4, M5: acylated with C8 soy proteins; M6, M7: acylated with C12 soy proteins; M8, M9: acylated with C16 soy proteins; B DH: degree of hydrolysis determined by OPA method; C DA: degree of acylation determined by OPA method.

In case of protein's NH 2 /fatty acid ratio of 1/0.5, the protein (native or hydrolyzed) chain length and the hydrocarbon chain length had no significant influence on acylation degree (varying between 25 and 31%). The variation in the number of free amino groups accessible to interact with fatty acid induced by protein hydrolysis influenced significantly the acylation degree. For the ratio protein's NH 2 /fatty acid of 1/1, the acylation degree of hydrolyzed SPI was 61% (M3) and that of native SPI was 31-38% (M5, M7 and M9).

Concerning acylated SPI, the acylation degrees were similar whatever the protein's NH 2 /fatty acid ratio. The only difference between these samples (M4 and M5, M6 and M7, M8 and M9 respectively) was the residual fatty acid salt rate. This rate was about 0.18-0.19 mmol per gram of protein for M4, M6 and M8, and 0.34-0.37 mmol per gram of protein for Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 16 M5, M7 and M9. As these fatty acid salts have surfactant properties, they were maintained in the mixtures to eventually contribute to emulsion stabilisation.

Influence of SPI modifications on emulsions properties

Modified SPI/T emulsion characterisations are presented in Table 2. These emulsions were prepared with high pressure homogenization to ensure an effective dispersion of oil in protein solution, to limit droplets coalescence and to produce stable emulsions as shown in Fig. 6. The homogenization step did not involve significant changes in emulsion viscosity for almost of the samples, and in any case, obtained viscosities were all suitable for following spray-drying process. The results in table 2 showed that emulsion viscosity was affected by protein modifications. The decrease in emulsion viscosity after protein hydrolysis and acylation was observed. Protein molecular chain length reduction due to hydrolysis provided the fall of emulsion viscosity for the samples M1, M2 and M3. This can be connected to the relation between polymer molecular weight and its viscosity, usually described using the Mark-Houwink-Sakaruda equation. The same dependence of molecular weight and viscosity was also found in literature for other biopolymers [START_REF] Avaltroni | Maltodextrin molecular weight distribution influence on the glass transition temperature and viscosity in aqueous solutions[END_REF][START_REF] Burkus | Determination of the molecular weight of barley β-glucan using intrinsic viscosity measurements[END_REF]. During acylation reaction of proteins, the acid chloride reacted preferentially with the protein amine functions, because of their higher reactivity in aqueous media than the carboxylic function one. This resulted in the formation of amphiphilic macromolecules, having a polar moiety formed by the numerous carboxyl groups (hydrophilic part) and a non-polar carbon chain (hydrophobic part). This improved amphiphilic character

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 17 of protein and the addition of a small amount of surfactant, due to the residual carboxyl ions, explain the observed decrease of emulsion viscosity with protein acylation, compared with the intact protein. The oil droplet size in emulsions prepared with modified SPI and T stabilized by highpressure homogenization were examined by laser diffraction. We observed a decrease of average droplet diameter with protein acylation, due to higher surfactant properties as previously explained. In the same way, protein hydrolysis and thus protein molecular weight diminution also involved lower droplet size. Nevertheless, the emulsion droplet size distribution curves (Fig. 7) demonstrated the narrow size distribution from 0.5 µm for emulsion with hydrolyzed SPI/T to 0.7-0.9 µm for emulsion with acylated SPI/T, and the bimodal character, previously observed with SPI/T emulsion (Fig. 3).

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International,48 (2),387388389390391392393394395396 Moreover, the mean diameter values are significantly lower than those obtained in several studies dealing with native vegetable proteins as wall material for spray-drying microencapsulation [START_REF] Kim | Microencapsulation properties of gum arabic and several food proteins: spray-dried orange oil emulsion particles[END_REF][START_REF] Rascon | Carotenoid retention and storage stability of spray-dried paprika oleoresin using gum arabic and soy protein isolate as wall materials[END_REF][START_REF] Walstra | Effect of homogenization on fat globule size in milk[END_REF]. Small emulsion droplet average sizes prevent their coalescence during the spray-drying process and make emulsions more stable [START_REF] Rascon | Carotenoid retention and storage stability of spray-dried paprika oleoresin using gum arabic and soy protein isolate as wall materials[END_REF]. Thus, protein hydrolysis and acylation seemed to be efficient modifications for improving emulsion stability and properties.

Influence of SPI modifications on microparticles properties

The efficiency of oil retention, process yield, microparticles size and morphology were determined for spray-dried powders prepared from native SPI, native SPI/T and modified SPI (hydrolyzed and/or acylated)/T systems (Table 3). The yield of drying processes for all the emulsions were about 62±4 % whereas SPI solution (8% w/w) was spray-dried in the same conditions with a process yield of 83%. This undesirable decrease of spray-drying yield was mainly due to the addition of the hydrophobic and viscous oil -α-tocopherol to protein solution, resulting in a stickier liquid phase, which involves a higher microparticles accumulation inside the drying chamber. This was corroborated by the characterisation of samples M0*, M0**; M6* and M6 as discussed below. Nevertheless, the yields obtained in 19 our study were relatively high compared to those obtained literature, amounting to 30-60% [START_REF] Johansen | Technological considerations related to the up-scaling of protein microencapsulation by spray-drying[END_REF][START_REF] Su | Microencapsulation of Radix salvia miltiorrhiza nanoparticlesby spray-drying[END_REF]. Representative retention efficiency data presented in Table 3 indicate the effect of the wall material modifications. According to these results, significant differences in active core retention efficiency were observed between native and modified soy proteins. The lowest efficiency level (38.9%) was obtained with wall system consisting of hydrolyzed soy proteins (M1). This can be explained by the insufficient chain length of wall material to produce a sufficiently strong structural matrix to encapsulate the α-tocopherol. Proteinic chains accumulate at the air/water interface of emulsion droplets during drying and thus represent the surface of formed powder particles [START_REF] Faldt | Changes in surface composition of spray-dried food powders due to lactose crystallization[END_REF]. Nevertheless, increasing of hydrophobic protein character with acylation significantly improved the RE of spray-dried powders (87.4 and 88.9% for the samples M2 and M3 respectively), even exceeding the RE obtained with native SPI (79.7% for M0). These results confirmed those obtained for acylated 20 SPI/T microparticles, and showed the significant contribution of grafting a hydrophobic portion on SPI chains affinity with oil and on the RE. Indeed, for acylated SPI, whatever the alkyl chain length (C8, C12, C16), the RE values were all higher than the RE obtained with non modified SPI/T microparticles. The highest RE for T encapsulation (94.8%) was observed with using soy protein acylated with dodecanoyl chloride as a wall material (M6).

This significant RE improvement is mainly explained by the increase of hydrophobic character of SPI (and hydrolyzed SPI) after attachment of alkyl chains, resulting in an increased surface hydrophobicity of SPI and enhanced the amphiphilic characteristics of proteins.

Moisture content of spray-dried emulsions varied from 4.8 to 6.6% and no significant difference was detected between samples based on native and modified proteins. In spite of significantly different mean diameters of the obtained particles varied from 6.3 to 9.3 µm (Table 3), these results are coherent within the range expected for microspheres produced by spray-drying comprised between a few micrometers and a several hundred micrometers [START_REF] Gharsallaoui | Application of spray-drying in microencapsulation of food ingredients: An overview[END_REF]. It was observed that particle average diameters were relatively lower for modified SPI/T microparticles. These results can be related to the lower emulsion droplet average size and viscosity, as commented previously [START_REF] Rascon | Carotenoid retention and storage stability of spray-dried paprika oleoresin using gum arabic and soy protein isolate as wall materials[END_REF].

Influence of wall/core ratio on emulsion and microparticles properties

For specific applications, particularly nutritional and pharmaceutical ones, different content of active material in microparticles could be needed [START_REF] Elizondo | High loading of gentamicin in bioadhesive PVM/MA nanostructured microparticles using compressed carbon-dioxide[END_REF]. With the purpose to increase the T proportion in the microparticles, SPI/T (or acylated SPI/T) ratios of 1/1 and 1/2 were tested. Data of Table 4 indicate the effect of the active material concentration on emulsions and microparticles properties. A significant increase in emulsion viscosity after increasing core/wall ratio, particularly for acylated SPI microparticles, was observed. In literature similar results were obtained [START_REF] Rusli | Stabilization of oils by microencapsulation with heated protein-glucose syrup mixtures[END_REF] and authors gave two explanations for this phenomenon. The first one is the larger particle size and coalescence in the former emulsion. But, in our case, emulsion droplet size was not affected by the core/shell ratio and no coalescence was observed. The other explanation is the increase in total solid content due to the increase in T concentration. This explanation corroborates our results, as the protein concentration was kept constant (8% w/w) in our emulsions, while the T 21 concentration was increased. Moreover as T viscosity was higher than that of 8% SPI solution, its addition resulted in emulsion viscosity increase. Increasing the core/wall ratio from 1/2 to 2/1 resulted in a slow decrease in spraydrying yield from 65 to 51% for SPI based emulsion and from 62 to 52% for acylated SPI based emulsion. This effect was reflected by the presence of high quantity of oil in emulsion and the most important clamminess of powders during spray-drying process due to availability of surface oil. For the same reasons, and because of the emulsion viscosity increase, increasing T amount in emulsions resulted in microparticles agglomeration and growth of their medium size from 9.3 to 15.9 µm for SPI/T dried emulsions and from 7.7 to 12.9 µm for acylated SPI/T dried emulsions (Table 4, Fig. 8). Concerning RE, except for formulations M0 and M6**, no significant differences were observed between the other samples. Nevertheless, increasing the T concentration in emulsions involved higher efficiency levels, both for SPI/T and acylated SPI/T microparticles. This put in evidence the suitability of SPI (acylated or not) as wall material for spray-drying as microencapsulation process, even for high loaded microparticles. SEM micrographs in Fig. 9 showed that microparticles SPI/T obtained by spray-drying were surrounded by a continuous shell. The powder consisted of spherical particles, having diameter 2 to 14 µm, rounded shape and wrinkled surface without fissures, cracks or disruptions. This structure revealed the good film-forming property of SPI. The internal structure of obtained microparticles showed the porous nature of the soy protein matrix where α-tocopherol was located. With increasing of active core ratio, particles morphology becomes more complex, combining two structures into one: microcapsule, where core is presented as reservoir in wall film, and microsphere, where core is dispersed in wall porous matrix.

Conclusions

This study developed the use of native and functionalized soybean proteins in microencapsulation of α-tocopherol by spray-drying method. Enzymatic hydrolysis and/or Nacylation were studied in order to improve some physico-chemical properties of soy protein and make them more relevant as encapsulant agents.

Emulsions droplet average size and emulsion viscosity decreased with soy protein modifications. Emulsion viscosity fall and more efficient oil dispersion (resulting in smaller

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 24 droplets) can be explained by the presence of shorter proteinic chains after hydrolysis or by improved protein active surface properties after acylation.

Low retention efficiency of 38.9% was observed for hydrolyzed protein based microparticles, probably due to insufficient chain length of hydrolyzed proteins to produce a structural matrix strong enough for α-tocopherol efficient encapsulation. Nevertheless, acylation of these hydrolyzates, increasing their affinity with the hydrophobic α-tocopherol, allowed to reserve this phenomenon, and to obtain microparticles with retention efficiency better than those from native proteins (87.4% and 88.9% for hydrolyzed and acylated proteins based microparticles, and 79.7% for native proteins ones). Acylation of native proteins confirmed this result, involving a significant increase of oil retention efficiency up to 94.8% for C12 acylated proteins based microparticles.

Moreover, this improved retention efficiency after protein acylation was observed for different α-tocopherol ratios, demonstrating that soy proteins and acylated soy proteins are relevant encapsulant agents for hydrophobic active materials, even for high loaded microparticles (loading efficiency up to 71.9% was obtained with C12 acylated proteins based microparticles).

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023

Fig. 1 .Fig. 2 .

 12 Fig. 1. Amino acid composition of soy protein isolate.

  Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 12

  volume average diameter (D v ) of emulsion remained 0.95±0.1 µm. No significant change in oil droplet size in time was observed. Emulsions were remained stable and displayed bimodal distributions indicating the presence of small portion of coalesced particles.

Fig. 3 .Fig. 4 .

 34 Fig. 3. Droplet size distribution of SPI/α-tocopherol emulsion (M0) 1 hour, 1 day and 1 week after high pressure homogenization at 50 MPa. The oil/protein ratio of the emulsion was 1/2.

Fig. 5 Fig. 5 .

 55 Fig.5shows the TG mass loss curves of the soy protein isolate (SPI), α-tocopherol (T) and SPI/T microparticles (M0). The mass loss of α-tocopherol of 100% with complete

Fig. 6 .

 6 Fig. 6. Optical micrographs of SPI/T emulsion (M0) before and after high pressure homogenization at 50 MPa. Scale bar -25 µm.

Fig. 7 .

 7 Fig. 7. Droplet size distributions of native (M0), hydrolysed (M1), hydrolysed and acylated (M2), acylated with C8 (M4), C12 (M6) or C16 (M8) SPI/T emulsions 1 hour after high pressure homogenization at 50 MPa. The oil/protein ratio of the emulsion was 1/2.

Fig. 8 .

 8 Fig. 8. Particle size distributions of spray-dried SPI/T emulsions (M0) or acylated SPI/T emulsions (M6) with core/wall ratio of 1/2, 1/1 (M0* and M6*) and 2/1 (M0** and M6**).

  Different letters in the same line indicate a statistically difference between the mean values (P<0.05) A M0, M0*, M0**: samples prepared with non modified soy proteins; M6, M6*, M6**: samples prepared with acylated with C12 soy proteins; B RE: retention efficiency determined by UV spectroscopy; C LE: loading efficiency or α-tocopherol content per 100 g of powder.

Fig. 9 .

 9 Fig. 9. Scanning electron micrographs of spray dried M0, M0** and M6** emulsions (external and internal structures).

Table 2 .

 2 Properties of SPI/T emulsions prepared with native or modified protein.

	Sample A	Emulsion droplet	Emulsion viscosity before	Emulsion viscosity after
		size, D v (µm)	homogenization (mPa⋅s)	homogenization (mPa⋅s)
	M0	1.1±0.02	44.0±1.30	15.0±0.02
	M1	0.5±0.03	3.7±0.05	3.6±0.01
	M2	0.6±0.05	3.5±0.10	4.5±0.01
	M3	0.6±0.05	5.2±0.13	7.4±0.01
	M4	0.7±0.04	16.8±0.70	8.6±0.01
	M5	0.8±0.03	15.0±0.52	8.0±0.01
	M6	0.7±0.04	8.9±0.09	8.0±0.02
	M7	0.8±0.04	13.5±0.12	14.5±0.01
	M8	0.9±0.02	6.4±0.05	10.2±0.01
	M9	0.9±0.04	14.0±0.14	14.8±0.02
	A M1: hydrolysed soy proteins; M2, M3: hydrolysed and acylated with C12 soy proteins; M4, M5: acylated with
	C8 soy proteins; M6, M7: acylated with C12 soy proteins; M8, M9: acylated with C16 soy proteins.

  Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023

Table 3 .

 3 Characteristics of SPI and SPI/T powders, produced by spray-drying, and efficiency of this process.

	Sample A	Spray-drying	RE B (%)	LE C (%)	Moisture	Particle size
		yield (%)			content (%)	(µm)
	SPI	83	-	-	4.8±0.7	5.5±0.1
	M0	65	79.7±1.0 d	26.3±0.3 d	5.5±0.4 ab	9.3±0.1 a
	M1	57	38.9±2.4 e	12.8±0.8 e	6.5±0.9 ab	6.3±0.1 e
	M2	64	87.4±3.9 bc 28.8±1.3 bc	5.8±0.5 ab	8.0±0.2 bc
	M3	62	88.9±3.5 b	29.3±1.3 b	5.3±0.6 ab	6.9±0.3 de
	M4	63	83.0±1.4 cd 27.4±0.5 cd	6.6±0.4 a	7.6±0.2 bc
	M5	68	90.9±1.1 ab 30.0±0.4 ab	4.9±0.5 b	8.0±0.2 bc
	M6	62	94.8±2.2 a	31.3±0.7 a	5.8±0.3 ab	7.7±0.2 bc
	M7	59	88.1±2.6 bc 29.1±0.9 bc	5.3±0.2 ab	7.4±0.1 cd
	M8	60	87.9±1.2 bc 29.0±0.4 bc	5.8±0.5 ab	8.2±0.3 b
	M9	62	87.3±1.9 bc 28.9±0.6 bc	5.5±0.8 ab	8.9±0.3 a
	a-e Different letters in the same column indicate a statistically difference between the mean values (P<0.05)
	A M1: hydrolysed soy proteins; M2, M3: hydrolysed and acylated with C12 soy proteins; M4, M5: acylated with
	C8 soy proteins; M6, M7: acylated with C12 soy proteins; M8, M9: acylated with C16 soy proteins;
	B RE: retention efficiency determined by UV spectroscopy;
	C LE: loading efficiency or α-tocopherol content per 100 g of powder.

  Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023

Table 4 .

 4 Properties of SPI/Τ (Μ0) and acylated SPI/T (M3) emulsions and powders with different wall/core ratio.

	Sample A	M0	M0*	M0**	M6	M6*	M6**
	Ratio	1/2	1/1	2/1	1/2	1/1	2/1
	core/wall
	Emulsion	1.1±0.02	1.0±0.04	1.1±0.06	0.7±0.04	0.8±0.03	0.8±0.02
	droplet size,
	D v (µm)
	Emulsion	15.0±0.02 18.2±0.03 19.4±0.02 8.0±0.02 13.5±0.02 19.3±0.01
	viscosity after
	homogenizati
	on (mPa⋅s)
	Spray-drying	65	55	51	62	60	52
	yield (%)
	RE B (%)	79.7±1.0 c 92.6±3.1 b 96.4±2.4 b 94.8±2.2 b 95.1±4.3 b 107.8±4.5 a
	LE C (%)	26.3±0.6 e 46.6±1.5 c 63.6±1.5 b 31.3±0.7 d 47.6±2.2 c	71.9±3 a

Comment citer ce document : Nesterenko, A., Alric, I., Silvestre, F., Durrieu, V. (Auteur de correspondance) (2012). Influence of soy protein's structural modifications on their microencapsulation properties: -Tocopherol microparticle preparation. Food Research International, 48 (2), 387-396. , DOI : 10.1016/j.foodres.2012.04.023 22

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