Aquaculture 309 (2010) 193–202

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Influences of food particle size on growth, size heterogeneity, food intake and gastricevacuation in juvenile Nile tilapia, Oreochromis niloticus, L., 1758

M.S. Azaza a,⁎, M.N. Dhraief a, M.M. Kraiem a, E. Baras b

a National Institute of Marine Sciences and Technologies, Rue 2 mars 1934, 2025 Salammbô, Tunisiab IRD, UR 175, 361 Rue Jean-François Breton, BP 5095, F-34196 Montpellier cedex 05, France

⁎ Corresponding author. Tel./fax: +216 75 27 25 11.E-mail address: med.azaza@instm.rnrt.tn (M.S. Azaz

0044-8486/$ – see front matter © 2010 Elsevier B.V. Aldoi:10.1016/j.aquaculture.2010.09.026

a b s t r a c t

a r t i c l e i n f o

Article history:Received 3 August 2010Received in revised form 15 September 2010Accepted 16 September 2010

Keywords:Oreochromis niloticusFood particle sizeGrowth rateGrowth variationSocial hierarchiesGastric evacuation

This study aimed at determining the food particle sizes (diameter) that produce the fastest growth (Sopt) injuvenile Nile tilapia, and modeling the growth penalties for particles departing from Sopt. Three 14-dayexperiments were run with 3, 7 and 11 g juveniles, which were raised in 120-L flow-through cylindro-conicaltanks at 29±1 °C, fed at the optimum feeding level (Ropt) and weighed at weekly intervals. In eachexperiment, four different sizes of pellets (diameter) were evaluated (0.5-mm intervals, 1.0–3.5 mm; threereplications per pellet size). At the end of each experiment, food intake and gastric evacuation rate weredetermined by radiographic methods following the use of ballotini labelled feed.The results indicate that i) in all experiments, specific growth rates (SGRs) are significantly depressed for thelargest particles; ii) Sopt increases with increasing fish size (1.4 mm at 3 g, to 2.5 mm at 20 g); iii) the optimumparticle size relative to mouth width (MW) varies only slightly with fish size (28 to 25% MW from 3 to 20 g);iv) growth heterogeneity is proportional to food particle size; and, v) food intake and gastric evacuation ratesare inversely proportional to food particle size. A growth model (SGR) was constructed with a stepwisemultiple-regression analysis against fish size, feeding level and food particle size (R2=0.853, df=71). For aparticular fish size, the growth-to-particle size relationship is a log–log second order polynomial, whichimplies that the growth penalty is more severe when fish are fed small than large particles. By contrast,application of food particles slightly smaller than Sopt tends to minimize growth heterogeneity. As fish sizeincreases, the width of the SGR-to-S relationship broadens; so, the penalty for distributing particles departingfrom Sopt is lower, and feeding strategies are facilitated.

a).

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1. Introduction

Optimized feeds for fish have long been a major concern ofaquaculture. Not only should the food composition meet thenutritional requirements of the fish, it should also produce the bestfood conversion efficiency, fastest growth and lowest wastes. Morerecently, there have been growing concerns over the sustainability offish feed, in particular as regards the substitution of expensiveingredients such as fish meal, soybean meal and oil by othercompounds (Azaza et al., 2008a, 2009a,b; Pratoomyot et al., 2010;Saidi et al., in press; Salze et al., 2010; Silva et al., 2010). Theseadvances are crucial but they may not suffice, since many otherparameters of the feeding strategies also govern the food intake andfeeding efficiency of fish (synthesis in Houlihan et al., 2001): feedingfrequency (Johnston et al., 2008; Riche et al., 2004), meal timing(Bolliet et al., 2001), way of food distribution (Valente et al., 2001) andrearing environment (tank colour, light intensity; Kestemont and

Baras, 2001). Food particle size has also been found to influencegrowth and food conversion in a broad series of fish species: Atlanticsalmon Salmo salar (Wankowski and Thorpe, 1979), sharptoothcatfish Clarias gariepinus (Hossain et al., 2000; Uys and Hecht,1985), Arctic charr Salvelinus alpinus (Tabachek, 1988), commoncarp Cyprinus carpio (Hasan and Macintosh, 2008; Wang et al., 1994)and gilthead seabream Sparus aurata (Goldan et al., 1997). Foodparticle size acts through a series of physiological and behaviouralmechanisms (optimum foraging strategies; Stephens and Krebs,1986).

The rate of feeding is proportional to food density, and below athreshold density fish may halt feeding (Guldbransen, 1991). For aparticular feeding level (i.e. percent of biomass per day) the density ofparticles per unit water volume decreases rapidly as particle sizeincreases, so the motivation to feed can be lower with large than withsmall particles. On the other hand, small particle size makes it difficultfor a fish to orientate efficiently its foraging behaviour, especially inspecies whose feeding relies mainly on vision (Knights, 1983).Furthermore, confusion effects can take place when food items areoverabundant: fish can abandon a capture sequence and re-orientatetowards another item (Laurel et al., 2001). The energy content of a

Table 1Characteristics of the three experiments for testing the effect of food particle size on thegrowth, food intake and gut evacuation rate in Nile tilapia (three replications pertreatment, experiments running over 2 weeks, with weekly control for fish growth).Unless specified otherwise, values are the means±S.E.M. Statistics for the initial wetmass of fish (M) are the F and P of one-way ANOVA (12 groups per experiment, 30 fishsampled per group in trials A and B, all 40 fish weighed in trial C). Detailed informationon food composition and particle size (1–6) in Tables 2 and 3.

Trial A B C

FishInitial number of fish per tank 90 60 40Initial wet body mass (WM, g) 3.02±b0.01 7.00±b0.01 11.18±0.02

ANOVA F 0.227 0.012 0.953ANOVA P 0.9957 0.9999 0.4886

Coefficient of variation (CV, % WM) 5.94±0.01 4.51±0.01 5.19±0.34Skewness coefficient (Sk) −0.19±0.07 0.070±0.05 0.44±0.13Mouth width (MW, mm)a 5.0 6.8 8.0

FoodNumber of meals per day 6 4 4Feeding level (% WM day−1) 8 6 4Daily increase (% day−1) 6 4 3Particle size class testedb 1,2,3,4 2,3,4,5 3,4,5,6Particle size (% fish MW)

Class 1 20.9 – –

Class 2 29.8 21.8 –

Class 3 42.0 30.7 26.0Class 4 49.7 36.4 30.8Class 5 – 44.7 37.8Class 6 – – 43.1

a Mouth width was deduced from the model between gape height and body mass(Fessehaye et al., 2006) for O. niloticus, and from complementary measurements ofmouth width and gape height in this study. The model stands as: MW=0.520+0.370 M, where M is the wet body mass of fish (g).b See Table 3.

Table 2Formulation and chemical composition of the experimental diet.

g kg−1

Ingredient (g kg−1)Fish meal 240Soybean meal 500Maize meal 200Soybean oil 40CMC (binder)a 10Vitamin–mineral mixb 10

Proximate analyses (g kg−1 dry matter)Moisture 87.5Crude protein 378.1Crude lipid 57.8Crude fibre 66.6Ash 41.6Carbohydrate (by difference) 438.4Gross energy (kJ g−1) 18.7

a CMC = carboxymethylcellulose.b Vitamin premix and mineral premix were described in Azaza et al. (2008a, 2009a).

194 M.S. Azaza et al. / Aquaculture 309 (2010) 193–202

food particle is proportional to the cube of its diameter (http://math.about.com); whereas, the energy invested into its capture doesgenerally not follow the same ratio for different particle sizes. Hence,the net energy gain may be very low for small particles, therebyresulting in low food conversion efficiency and slow growth (DosSantos et al., 1993; Halver, 1989; Jobling and Wandsvik, 1983;Pandian and Vivekanandan 1985). Once the particle has beendetected and approached, the fish should be capable of swallowingor handling it within the shortest possible time. The relationshipsbetween handling time and particle size vary among fish species andsize, and among food types, but they are generally U-shaped andnegatively skewed, i.e. very large particles are much longer to handle(e.g. European eel Anguilla anguilla, Knights, 1983).

Food particle size also has a strong influence on the digestion andassimilation processes. Digestive enzymes attack the outer surface ofthe food particle. Small particles have a high surface:volume ratio andare digested more rapidly or more completely than larger ones(Hardy, 1989; Jobling, 1987; Persson, 1986). On the other hand, smallfood particles are evacuated more rapidly, and they can enter theintestine without sufficient gastric digestion, thereby reducing thenutrient absorption efficiency (Dos Santos et al., 1993; Hossain et al.,2000; Jobling, 1986a, 1988). These effects of food particle size on fishgrowth and food conversion are typically dependent on fish size, soparticle size is also likely to impact on growth heterogeneity, which isgenerally not desirable in fish culture.

The multiplicity of the factors that influence the efficiency of foodintake and digestion make it difficult to transpose results amongspecies or life stages, and to select an optimum food particle sizewithout experimental validation. At present there is no detailedinformation on how particle size impacts growth, food conversion andsize heterogeneity among tilapias, which are one of the majorcontributors to world aquaculture nowadays (FAO, 2009). Theobjective of this study was precisely to investigate this issue injuvenile (3–20 g) Nile tilapia, Oreochromis niloticus. In particular, itaimed at 1) determining the optimum food particle size relative to fishsize (SRopt), and whether SRopt varies between fish of different sizes,2) quantifying the penalty (in terms of growth, food conversion andsize heterogeneity) for feeding fish with particles smaller or largerthan SRopt, and 3) examining the relationships among food particlesize, food intake and gut transit time, which are both known to impacton food conversion.

2. Material and methods

The fish were O. niloticus Maryut, from a captive population thatoriginated from the Marine Centre of Tajoura (Lybia), and wastransferred to the Aquaculture Research Station of the TunisianNational Institute of Marine Science and Technology at Bechima Gabèsin 1999 (Turki and Kraïem, 2002).

2.1. Experimental design

Three separate experiments (A, B, and C) were conducted inidentical conditions, with fish of mean initial wet body mass (M) of 3,7 and 11 g, respectively (Table 1). In each experiment, fish wererandomly allotted to 12 tanks (90, 60 and 40 fish per group forexperiments A, B and C). Fish used in an experiment were neverreused in the next experiment(s). Efforts were made to reduce asmuch as possible the initial size heterogeneity within groups(Table 1), and to minimize discrepancies among groups. In eachexperiment, the mean initial body mass M did not differ amonggroups (one-way analysis of variance, ANOVA, F=0.23, P=0.9957,df=359; F=0.01, P=0.9999, df=359; F=0.95, P=0.4886,df=479, in experiments A, B and C, respectively).

No food was distributed on the day following the initial weighing.From the next day onwards, fish were hand fed formulated feed

(Table 2) during the hours of light. The feeding levels (8, 6 and 4% oftank biomass day−1, dry-matter basis in experiments A, B and C,respectively) were deemed close to the optimum food ration (Ropt) atthe rearing temperature (based on the studies in Azaza et al., 2008b).In order to maintain the feeding level as close as possible to Ropt

during the rearing period the amounts of food were incremented eachday (+6, 4 and 3% day−1, in experiments A, B and C, respectively)based on growth estimates of fish fed Ropt at 29 °C (Azaza et al.,unpublished data.).

Fish were hand fed until apparent satiation, six times a day (at08:00, 10:00, 12:00, 14:00, 16:00 and 18:00 h) for the experiment Aand 4 times a day (at 08:00, 11:00, 14:00 and 17:00 h) for theexperiments B and C (Table 1). Fish are considered to be satiatedwhen they no longer accept the offered food after a period of active

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feeding. In each meal, pellets were consumed during almost 15 min(satiation time) and were distributed slowly, allowing all fish to eatwithout feed wastage. So, the amount of wasted food was always verysmall or negligible on all rearing days in all three experiments andthus feed rations represent feed intake.

In each experiment, four food particle sizes (0.5-mm intervals)were evaluated in triplicate. The largest particle size was selected soas not to exceed 50% of the fish mouth width at the start of theexperiment (Table 1). Calculations were made by reference to mouthwidth rather than gape height, since the former is the shortest cross-sectional dimension of the mouth in O. niloticus. Mouth width (MW,mm) was deduced from the model between gape height and bodymass that was produced by Fessehaye et al. (2006) for O. niloticus, andfrom complementary measurements of mouth width and gape heightin this study: MW=0.520+0.370 M, where M is the wet body massof fish (g). In each experiment, food particle size remained unchangeddespite fish growth; so, the particle size relative to fish size decreasedthroughout the experiment. For this reason, the duration of eachexperiment was restricted to two weeks, as a compromise betweenthe need for maintaining this size relationship within a reasonablynarrow range, and the need for growing the fish over a sufficientperiod. At the end of each rearing week, fish were anaesthetised(tricaine methanesulfonate, 100 mg L−1), weighed individually(nearest 0.01 g) and returned to the rearing tanks. In the thirdexperiment, all survivors were measured; whereas, in the first twoexperiments, 30 fish were randomly sampled in each tank.

At the end of the 2-week rearing period, fish were deprived of foodover 48 h to ensure complete gut emptying. On the next day, theywere offered food labelled with glass beads, then sampled every 3 h,anaesthetised and X-rayed, in order to test whether the gutevacuation rates varied between fish sizes and food particle sizes.We used the same particles sizes as during the previous weeks, buthere food was given in excess. The period of food distribution wasrestricted to 30 min, in order to test whether the food intake over abrief period of time was dependent on food particle size.

2.2. Rearing conditions

Fish were raised in indoor 120-L cylindro-conical flow-throughfibreglass tanks. A flow-through system was used, to avoid recircu-lation of food debris. The tanks were supplied with geothermal water

Fig. 1. Screenshots of food particle size measurements from digital photographs using the imthrough the 1.12-mm sieve and remained in the 1.00-mm sieve.

(65–70 °C), which had undergone a cooling process (down to about30 °C) in a large storage tank, at a rate of 1–3 Lmin−1. Each tank wasequipped with a submersible air diffuser connected to a regenerativeblower. The tanks were searched daily for dead fish and siphoned toremove faeces and uneaten food (if any). Dead fish were weighed foradjusting the food ration and calculating the food conversionefficiency.

Water temperature was maintained at 29±1 °C throughout thethree experiments. No critical values were detected for dissolvedoxygen (N4.12 mg L−1). Nitrite (NO2-N: b0.009 mg L−1) and totalammonia-N (NH3-N+NH4

+-N: 0.35bmg L−1) remained within ac-ceptable ranges for O. niloticus (Ballarin and Hatton, 1979). A 12L:12Dphotoperiod was maintained with fluorescent lights controlled by anautomatic timer (Time switch, CHNT; 800 Lx during the hours of light).

2.3. Diet formulation and preparation

The practical feed used in this study (380 gkg−1 crude protein and17.40 kJ g−1 gross energy) had previously been demonstrated tosupport good growth performance inO. niloticus (Azaza et al., 2005). Itconsisted of powdered fish meal, soybean meal, maize meal, soybeanoil, vitamin and mineral premixes, and carboxymethylcellulose asbinder. The proximate biochemical analysis of the feed was carriedout for moisture, total ash, crude protein, crude fat (ether extract) andgross energy contents following standard methods (AOAC, 1990;Table 2).

All dietary ingredients were ground (Ultra Centrifugal Mill ZM 200Retsch GmbH, Haan, Germany) and mixed with vitamin–mineralpremix and soybean oil in a food mixer (model: CAM A30 RetschGmbH, Haan, Germany). Subsequently, water was added graduallyuntil a desirable paste-like consistency was reached, and then pelletswere produced with a kitchen meat grinder (model: amb TC22SL,Oni2, Bruxelles, Belgium) using 2 and 4 mmdie sizes. The pellets weresubsequently sun-dried. The diet was crumbled and sieved intodiscrete particle sizes using 12 sieves (TAMIS GMSP 400, Chatou,France) with the following mesh opening sizes: 1.00, 1.12, 1.40, 1.60,2.00, 2.24, 2.36, 2.50, 2.80, 3.15, 3.35 and 3.55 mm. For example, theportion that went through the 1.12-mm sieve and remained in the1.00-mm sieve is named a particle size class 1 (i.e. diameter of1.06 mm). Feed was packed in airtight polyethylene bags andmaintained at −20 °C until use.

age J software. In this illustration, the particle size measured was the portion that went

Table 3Characteristics of the food particle size (in text “size” refers to diameter) classes (1–6).

Food class Diameter (mm) Section (mm2) Volume (mm3) Number ofparticle per ga

1 1.041 0.853 0.592 1253.002 1.486 1.738 1.721 429.333 2.092 3.444 4.801 161.664 2.477 4.828 7.970 97.005 3.039 7.268 14.718 48.336 3.472 9.486 21.948 34.33

a Means of three replicates.

196 M.S. Azaza et al. / Aquaculture 309 (2010) 193–202

In order to determine the mean size i.e. diameter of the particlesretained by the successive sieves, a sample of each sieving (150–200particles) was collected, photographed with a digital camera(5.0 megapixel resolution), and analysed on the computer byreference to a graduated scale using Image J software (Fig. 1)(Abramoff et al., 2004). The mean number of each food particle sizeclass per gram was determined by counting the numbers of particlesin three samples of 1 g each (Table 3).

2.4. Food intake and gastric emptying

Food intake and gastric evacuation rate were determined with theradiographic method of Talbot and Higgins (1983), which wasadapted to fingerlings of O. niloticus (in terms of dose of anaestheticsfor immobilizing fish and optimum glass bead ratios for the particlesizes used in this study). Food composition and particle sizes wereidentical to those given in Tables 2 and 3, except that X-ray-dense leadglass beads (ballotini, type H, 450–600 μmdiam, DLO, Braine-L'Alleud,Belgium) were mixed (1.5%, M M−1) with the ingredients beforecompressing them into pellets.

The relationships between food mass (FM, g) and the number ofballotini (Nb) were calibrated from 30 samples of known weights(from 0.05 to 1.0 g) for three particle sizes (1.0, 2.0 and 3.5 mm). Forall three particle sizes, the relationships were highly significant(R2≥0.98), intercepts were ≤0.01 g and slopes were highly homo-geneous (0.0131±0.0001). This indicated that ballotini had beenwellmixed and occurred in very similar M:M ratios in all particle sizes; so,the same calibration curve could be used for all particle sizes FM (g)=0.0131 Nb+0.0066; (r2=0.989; df=29, Pb0.001 for the interceptand slope).

As indicated in the experimental design, the ballotini study wascarried out after the end of the growth study, because its protocol waspotentially more stressing for the fish, and required a 2-day period offood deprivation, which would have impacted on the growth of thefish. Fish were fed 30 min ad libitum; then the remaining food wasrapidly siphoned. Thereafter, four fishwere randomly sampled in eachtank (i.e. 12 fish per particle size per trial), anaesthetized (methane-sulfonate tricaine, 200 mg L−1), placed in lateral recumbence and X-rayed, using a Eklin Mark III™ portable digital radiography system(IDR, Vouziers, France) and Kodak Ma film (Kodak, X-OMAT MA). Theoperation was repeated every 3 h until 21 h after the end of fooddistribution. Radio-opaque ballotini were counted on photographs bytwo independent observers. The gut contents were deduced from theaforementioned calibration curve and related to the fish wet bodymass.

2.5. Calculations and statistical analyses

In all experiments, fish growth was expressed as the specificgrowth rate (SGR, % M day−1), which was calculated as: SGR1–2=100(lnM2− ln Mi) (t2− t1)−1; where ln is loge, and M2 and Mi are themean body masses of fish at times t2 and t1, respectively. The grossfood conversion efficiency (GCE, g g−1) was calculated as: GCE1–2=(M2−M1+Md1–2) F−1; where M1 and M2 are the mean body masses

(g) of fish at times 1 and 2, Md1–2 is the body mass of fish dyingbetween times 1 and 2, and F (g) is the total amount of fooddistributed during the rearing period.

The variation of within-treatment size during the study wasmeasured by the change in the coefficients of variation (ΔCV) of fishbodymass, i.e.ΔCV=CV2−CV1, where CV1 and CV2 are the initial andfinal coefficients of variation of fish body mass (M), which werecalculated as CV=100 S.D. M−1, where S.D. is the standard deviationof M. The asymmetry of the size distributions was characterised bytheir skewness coefficient (Sk), i.e. Sk=∑1−n ([xi−M] SD−1)3,where M and S.D. stand as previously mentioned.

Gut contents (GC, % M) at different times after feeding wereequated to the time elapsed since food distribution (T, hours) by anexponential regression analysis, i.e. log (GC)=a+b T. The gutemptying rate (GER) was estimated by the slope (b) of thisrelationship. Data points before evacuation had started or after theevacuation had (almost ceased) were not retained in the analysis.

In each experiment, all data were subjected to a one-way analysisof variance (ANOVA) using the general linear model (GLM) procedureof Statistica® Version 5.1 (Statsoft Tulsa, Oklahoma, USA). Tank meanvalues were considered as observation units. When the ANOVAidentified differences among groups, multiple comparisons amongmeans were tested using Duncan's multiple-range tests (DMRT).Arcsine transformations of percentage data were performed toachieve homogeneity of variance.

Stepwise multiple-regression analyses were used on the data fromall three experiments to test for the effects of particle size and fish sizeon weekly growth rate, food intake and gut evacuation rate. Simpleregression analyses were used when necessary. All differences wereconsidered significant at Pb0.05.

3. Results

Mortality was extremely low during the study and did not differsignificantly among treatments (chi-square with correction ofcontinuity, P=0.1293). No single fish died during experiments Band C (mean initial M of 7 and 11 g, respectively), and no more thanfour out of 1080 fish died during experiment A (initial M of 3 g).

3.1. Growth and food conversion

In each rearing week of the three experiments, specific growthrates (SGRs) varied significantly (Pb0.05) among food particlesizes (hereafter S; Fig. 2). The SGR-to-S relationship was dome-shaped in all cases, except for the second week of experiment 3. Theparticle size that produced the fastest growth increased amongexperiments, and between the two weeks of the first two experi-ments. Similar relationships were found between the gross foodconversion efficiency (GCE) and S (Fig. 2), which was expected, sincevery few fish died and almost no food was wasted during theexperiments.

These tendencies are reflected by the growth model in Table 4Aand illustrated by the regression curves in Fig. 3. The model, whichwas constructed by a stepwise multiple-regression analysis, accountsfor 85.5% of the variation of observed weekly SGR, based on foodration, fish body mass, food particle size (2nd order polynomial) andthe interaction between the last two variables. The pattern in Fig. 3shows that the particle size that produces the fastest growth(hereafter, Sopt) increases in fish of increasing size. By contrast, theoptimum particle size relative to mouth width (MW; SRopt) decreasesin a curvilinear (log–log) way as fish size increases (i.e. from 28% MWin a 3-g fish to 25% MW in a 15-g fish; model in Table 4B). The abacusin Fig. 3 also show that 1) the growth penalty for consuming foodparticles N mm smaller or larger than Sopt is less severe in large than insmall fish, and 2) for a given fish size, the growth penalty forconsuming particles N mm smaller than Sopt is more severe than for

Fig. 2. Variations of growth (SGR, weekly basis) and gross food conversion efficiency (GCE, g-wet-fish g-dry-feed−1) in juvenile O. niloticus, depending on wet body mass (M, g) andfood particle size class (mm). In each graph, bars and whiskers are the means and S.E.M. of three replicate groups. Treatments with a common letter are not significantly different(Duncan multiple-range tests, PN0.05).

197M.S. Azaza et al. / Aquaculture 309 (2010) 193–202

particles N mm larger than Sopt. However, by virtue of the log–lognature of themodel, the growth penalties for consuming particles thatare N times smaller or N times larger than Sopt are identical (log-logistic model in Table 4C).

3.2. Size heterogeneity

Size heterogeneity increased in all three experiments but theincrease was steeper in fish that were offered the largest food particlesize, except for the third experiment (Fig. 4A). The skewness

coefficient (Sk) of the size distributions also varied during theexperiments, but in slightly contrasting ways (Fig. 4B). Among thegroups that were offered the smallest particle sizes, Sk increasedduring the first experiment, remained stable during the second one,and decreased during the third one. These differences can be partlyaccounted for by the fact that Sk at the start of the rearing period wasnegative in the first experiment, close to zero in the second one andpositive in the third one (Table 1). By contrast, in all threeexperiments, Sk increased steeply in the groups that were offeredthe largest food particle sizes, thereby indicating that one or a few fish

Table 4A. Statistical model of growth in Nile tilapia (specific growth rate, SGR, weekly basis), obtained by stepwise multiple-regression analysis on all data (three experiments, four particlesizes with three replications per experiment, two rearing weeks). M is the fish wet mass (g) and S is the food particle size (mm) at the start of the rearing week. Variables arepresented in the sequential order of entrance in the model. B. Relationship between the optimum size of food particle relative to fish size (SRopt, % mouth width) and fish size (M). C.Growth penalty (GP, proportion of SGR) incurred by Nile tilapia when the food particle size (S, mm) departs from the size that produces the fastest growth (Sopt). The relationships inB and C are deduced from the model in A, so no detailed statistics are given.

Coefficient Std. error F-value Probability

A: Dependent variable: Log (SGR, % day−1)Predictor variables

F=96.83; df=71; R2=0.853

Intercept (value) 0.623 0.14 18.92 b0.0001[Food ration, % WM]2 0.012 0.002 40.91 b0.0001[Log S (mm)]2 −2.924 0.572 26.13 b0.0001Log WM×Log S 1.754 0.414 17.98 b0.0001Log WM (g) −0.559 0.135 17.03 b0.0001

B: Dependent variable: Log SRopt (%)Predictor variables

R2N0.999 (model derived from panel A)

Intercept (value) 1.480 b0.0001 – b0.0001Log WM −0.070 b0.0001 – b0.0001

C: Dependent variable: Log (GP/(1−GP))Predictor variables

R2=0.995, df=15 (model derived from panel A)

Intercept (value) −1.498 b0.0001 – b0.0001Log (S/Sopt) (absolute value) 4.329 b0.0001 – b0.0001

198 M.S. Azaza et al. / Aquaculture 309 (2010) 193–202

gained a major growth advantage over others with these large foodparticles.

3.3. Food intake and gut evacuation rate

In each of the three experiments, the gut content (% M) that wasmeasured 30 min after food distribution (GC30 min) was high andsimilar for the two smallest particles sizes; whereas, it wassignificantly (Pb0.05) lower for the largest particle sizes (Table 5).In each experiment, the standard error of measures (hereafter, S.E.M.)of GC30 min after food distribution varied very little among foodparticle sizes, thereby indicating a proportionally higher variabilityamong the groups fed with large particles, those fish consuming lessfood than others.

A stepwise multiple-regression analysis produced a model thataccounted for 97.5% of the variation of GC30 min, based on particle size(2nd order polynomial), fish size and their interaction (Table 6A). Theregression curves produced from this model (Fig. 5A) indicated thatfor all sizes of fish the food particle size that was associated with the

Fig. 3. Growth of O. niloticus, depending on food particle size and wet body mass (M of3, 6, 10 and 20 g). SGR is the specific growth rate (% M day−1) over one week. Thecurves were produced from the model given in Table 4A, using food rations of 6.5, 6, 5.5and 5% M, for fish of 3, 6, 10 and 20 g, respectively.

highest food intake was smaller than the food particle size thatproduced the fastest growth (Sopt; comparison with Fig. 3).

The variation in gut evacuation rate (GER, Table 5) as a function offish size and food particle size was also analysed with a stepwisemultiple-regression analysis. The effect of GC30 min was forced intothis model, because GER in fish is widely acknowledged to be stronglydependent on food intake. The optimum model included the effect offish size, particle size and their interaction; and, it was highlysignificant (R2=0.941; Table 6B). Graphical output from this model(Fig. 5B) indicated that particle size for which the GER was fastest wasalmost identical to the particle size that was associated with thehighest food intake, and thus well below Sopt.

4. Discussion

This study demonstrated that the food particle size that producesthe fastest growth (Sopt) increases in O. niloticus with increasing fishsize, but that the optimum particle size relative to fish size (SRopt)varies only slightly over the 3–20 g range (i.e. from 28 to 25% mouthwidth, MW). This finding is consistent with the fact that growth of O.niloticus during this ontogenetic interval is almost isometric. SimilarSRopt values have been found for several fish species (30% MW in 0.7–70-g S. salar, Wankowski and Thorpe, 1979; 32% MW in 1-g C.gariepinus, Hossain et al., 2000; 21–33% MW in 3–21 g S. alpinus,Tabachek, 1988). In S. alpinus, SRopt increased steeply in fish ofincreasing size; whereas, in O. niloticus, there was a moderatedecrease in SRopt as fish grew. It is possible that the differencebetween the ontogenetic variations of SRopt in these two species lies inthe difference in their trophic patterns: with increasing size, charrsbecome increasingly piscivorous; whereas, tilapias generally becomeincreasingly microphagous.

The preferred or optimum food particle size can be dependent onthe hardness of the food (e.g. sizes of 40–60% MW for hard pelletsversus up to 100% for soft paste balls in A. anguilla, Knights, 1983).Similarly, Fessehaye et al. (2006) provided evidence that youngcannibals of O. niloticus (0.5–15.0 g) could consume prey as large as92% MW, i.e. about 3.3 times bigger than the SRopt observed in thisstudy with hard pellets. The largest prey that a fish can manipulateand ingest may not be themost energetically profitable (Wanzenböck,1995). Fessehaye et al. (2006) did not test whether cannibals of tilapiaconsuming conspecifics of different sizes grew at different rates; so,no direct parallel can be drawn between their study and ours.

Fig. 4. The coefficient of variation of bodymass (ΔCVM) and of the skewness coefficient(ΔSk) over two weeks in O. niloticus offered different food particle sizes (mean initialwet body mass [Mi] of 3, 7 and 11 g, respectively). In each graph, bars and whiskers arethe means and S.E.M. of three replicates.

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Nevertheless, the comparison between these two studies suggeststhat the SRopt documented here may not apply to situations wherefood types of different hardness would be used.

Table 5Synthesis of the three experiments (A, B, and C) for measuring the effect of food particle sizeO. niloticus of different sizes. M is the wet fish mass, and GC is the gut content, as determinedeach experiment, 3-h intervals) (see Table 1 for additional information). In each experimsignificance (Duncan multiple-range tests).

Particle size class Fish WM (g) SR (%MW) GC0.5 h (%WM)Mean±S.E.M.

Trial A 1 8.7 13.56 3.68±0.19aTrial A 2 9.1 20.04 3.53±0.18aTrial A 3 9.3 26.49 2.59±0.16bTrial A 4 8.3 34.48 1.89±0.18cTrial B 2 12.5 17.80 2.87±0.11aTrial B 3 13.3 23.18 2.70±0.15aTrial B 4 13.3 28.99 1.88±0.14bTrial B 5 12.1 36.01 1.40±0.11bTrial C 3 17.2 21.08 2.15±0.13aTrial C 4 17.6 26.18 2.18±0.09aTrial C 5 16.3 32.27 1.78±0.13bTrial C 6 16.1 37.83 1.18±0.08c

This study enabled modeling the growth penalties incurred by fishof different sizes if the food particles departed from Sopt. In fish of aparticular body mass fed at a particular feeding rate, the modeledrelation between fish growth and particle size is a log–log, secondorder polynomial. Modeling approaches have not been frequentlyused for calculating the interactions among food particle size, fish sizeand growth.We re-examined the data presented by other authors andfound identical types of relationships among growth, fish size andparticle size (e.g. data on S. alpinus in Tabachek, 1988) or betweengrowth and particle size when a single fish size was under study (e.g.C. gariepinus, Hossain et al., 2000). This supports the idea that the typeof model that was described for O. niloticus in this study applies atleast to some other species (and probably to many others), and thusthat the growth penalty for consuming particles N mm smaller thanSopt is more severe than for particles N mm larger than Sopt.

Several factors account for why growth-to-particle size modelsfollow a log–log second order polynomial. Similar models have beenused to depict the interactions among temperature, fish size andgrowth (Baras et al., 2000). The log–log nature originates from the factthat the SGR-to-M relationship, and the relationship between thesurface:volume ratio of a food particle and its diameter both follow apower law. The energy content of a food particle is proportional to itsvolume; whereas, the surface of the particle influences its degradationin water, the probability of being detected by fish and the handlingtime, which altogether govern the energy intake per unit of time. Thesurface area of the particle also affects its rate of degradation bydigestive enzymes and the duration of its sojourn in the gut (Grove etal., 1985; Jobling, 1986a; Mac Donald et al., 1982; Medved, 1985),both of which increase at the expense of energy assimilation(Tabachek, 1988).

This study was not designed to identify precisely how particle sizeimpacted each of these factors in O. niloticus. However, theexperiment with ballotini labelled feed revealed that the relationshipbetween food intake and particle size can be described by a log–logsecond order polynomial, and that the maximum food intake over ashort period of time (30 min) is attained for particles smaller thanSopt. A similar trend can be deduced from the data on C. gariepinuspresented by Hossain et al. (2000) (i.e. based on the intercepts of themodels of gastric evacuation rate against particle size).

The results of this study onO. niloticus are in broad agreementwiththose of other studies showing that gut evacuation follows anexponential law, that the evacuation rate is proportional to foodintake, and that it is faster for small than for large food particles (DosSantos and Jobling, 1991; He and Wurtsbaugh, 1993; Hossain et al.,2000; Jobling, 1986a, 1987; Saether et al., 1999; for Oreochromis spp.,De Silva and Owoyemi, 1983; Riche et al., 2004). It can behypothesized that the fast evacuation rate in O. niloticus fed small

on the food intake within a limited period of time (0.5 h) and the gut evacuation rate ofby the radiographic analysis of fish fed ballotini labelled feed (12 fish per particle size inent, GC0.5 h values that share one letter in common do not differ at the 0.05 level of

Slope±S.E. Statistics: linear regression between Log GC andtime (h)

−0.042±0.002 R2=0.990; Pb0.0001 df=5−0.042±0.004 R2=0.970; P=0.0003 df=5−0.027±0.002 R2=0.990; Pb0.0001 df=5−0.009±0.001 R2=0.938; P=0.0015 df=5−0.046±0.003 R2=0.988; Pb0.0001 df=4−0.045±0.004 R2=0.961; P=0.0022 df=4−0.017±0.001 R2=0.973; P=0.0003 df=5−0.010±0.001 R2=0.963; P=0.0005 df=5−0.030±0.001 R2=0.992; Pb0.0001 df=5−0.029±0.003 R2=0.959; P=0.0006 df=5−0.014±0.001 R2=0.972; P=0.0003 df=5−0.013±0.002 R2=0.939; P=0.0016 df=5

Fig. 5. Food intake (gut content 30 min after food presentation, GC0.5 h, % M, A) and gutevacuation rate (GER, B) as functions of food particle size, inO. niloticus of different sizes(wet body mass, M, g). The curves were produced from the models given in Table 6Aand B, respectively. GER is the slope (b) of the relationship between log (GC, % M) andthe time (T, hours) elapsed since feeding, i.e. log (GC)=a+b T.

Table 6Regressionmodels of the variation in food intake during ameal (GC0.5 h, % M; A), and of gutevacuation rate (GER; B), as functionsof foodparticle size inO. niloticusofdifferent sizes. Themodels are based on the data shown in Table 5.M is the fishwet bodymass (g), S is the foodparticle size (mm) and SR is the food particle size relative to fish size (%mouthwidth,MW).GC0.5 h is thefish's gut content (%M)30 min after the start of fooddistribution andGER is theslope (b) of the relationship between log (gut content, GC, % M) and the time (T, hours)elapsed since feeding, i.e. log (GC)=a+b T. The effect of food intake (GC0.5 h) was forcedinto the GERmodel (usingmodeled relationships frompanel A), as it notoriously affects therate of gut evacuation in fish. Data of food intake and gut content were obtained byradiographic analysis of fish fed ballotini labelled feed (12 fish per food particle size at theend of each of the three experiments of this study).

Coefficient Std.error

F-value Probability

A: Dependent variable: Log (GC0.5 h)Predictor variables

F=68.78; df=11; R2=0.975

Intercept (value) −1.690 0.997 2.87 0.1340[Log S (% MW)]2 −3.592 0.680 28.94 0.0011Log S (% MW) 6.913 1.446 22.84 0.0020Log WM −3.274 1.185 7.63 0.0280Log S (% MW)×Log WM 1.980 0.822 5.80 0.0469

B: Dependent variable: Log GER (slope)Predictor variables

F=42.79; df=11; R2=0.941

Intercept (value) −1.893 0.384 24.23 0.0012[Log S (mm)/Log WM]2 −4.949 0.909 29.67 0.0006Log S (mm) 1.372 0.516 7.06 0.0289FI (% WM) 0.139 0.100 1.95 0.2002

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food particles served to maximise the food intake (FI). Fasterevacuation normally causes appetite to return sooner (Jobling,1986b; Jobling et al., 1995); so, when food is not limiting, inefficientdigestion might be compensated for by a higher food intake. Bycontrast, if the food supply is restricted and meals are distributed atfixed intervals, as was the case during this study, short gastric transittimes might result in slower growth because of the reduction ofassimilation efficiency. This interpretation might account for why thegrowth of O. niloticuswas slightly slower among the groups that wereoffered the smallest food particles sizes. The reason why fish fed thelargest food particles exhibited the slowest growth in this studywith afeeding level close to Ropt, remains a little more obscure. No food waswasted and the long gut transit time should have ensured a morethorough digestion of the food than with smaller particles. Alterna-tively, it can be hypothesized that, in spite of the long gastric transittime, these large particles had an insufficient surface:volume ratio forbeing fully digested by the fish. Other factors, such as higher energyexpenditures for longer handling time, can be invoked, but experi-mental evidence is lacking.

The platykurtic shape of the SGR-to-S relationship suggests thebreadth of the trophic niche, at least as regards particle size. Inparticular, the kurtosis coefficient of the growth-to-particle sizeabacus (after log transformation for particle size) might be anobjective indicator of whether a fish species or life stage is tolerantor exigent towards food particle size. For example, the kurtosiscoefficients are −1.051 (strongly platykurtic), +0.171 and +1.183(strongly leptokurtic), respectively for 1-g C. gariepinus (modeledafter Hossain et al., 2000), 3-g O. niloticus (this study), and 3-g S.alpinus (modeled after Tabachek, 1988). This comparison suggeststhat O. niloticus is more tolerant than S. alpinus but more exigent thanC. gariepinus as regards food particle size.

The model in Table 4C shows that the growth penalty forconsuming particles that are N% smaller or larger than Sopt isindependent of fish size. This is possibly because mouth dimensionsrelative to body size in O. niloticus vary only slightly within the sizerange under study. On the other hand, the absolute width of the SGR-to-S relationships broadens as fish grow (Fig. 3), so the growthpenalty incurred for distributing food particles Nmm smaller or largerthan Sopt decreases as O. niloticus increase in size. This observation

clearly supports the idea that it is more difficult to feed small thanlarge fish with pellets, which are generally sieved at regular intervals(e.g. 0.5 or 1 mm). Furthermore, small fish enjoy a higher capacity forgrowth than larger conspecifics, which implies that food particle sizeshould be incremented on a much more frequent basis to minimizeproduction losses. By virtue of the log–log nature of the growth-to-particle size model, it could be recommended to feed fish withparticles slightly larger than Sopt, because the penalty would be lesssevere than if the particles were smaller. However, this seeminglycareful recommendation overlooks the relationships between foodparticle size and fish size heterogeneity.

In all three experiments of this study, the distribution of foodparticles larger than Sopt resulted in an increase of the coefficient ofvariation of wet body mass (CV M) and of the skewness coefficient(Sk). Tabachek (1988) also found that size heterogeneity in juvenileArctic charr increased faster among fish fed pellets larger than Sopt,than among those receiving smaller food particles. This finding can beaccounted for in two complementary ways. First, large particles arecloser to the Sopt of large fish than to those of small fish; so, the growthpenalty is more severe for the latter than for the former. Second, largeparticles are scarcer, more easily defended, and their use facilitatesthe settlement or continuation of dominance hierarchies, whichgenerally benefit the largest individuals (Goldan et al., 1997; Joblingand Koskela, 1996; Kestemont et al., 2003; McCarthy et al., 1992). O.

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niloticus is an aggressive, territorial species that is known to exercisemarked dominance hierarchies when raised in groups (e.g. Corrêa etal., 2003). Feeding hierarchies are generally enhanced when the foodsupply is submaximal, as was the case in this study. This interpreta-tion is supported by the finding that food intake was more variablewhen O. niloticus were fed with large pellets than with small pellets(Table 5; i.e. the S.E.M. were similar, but the mean food intakes withlarge pellets were lower, so the relative variability was higher).

In a previous part of the discussion, we debated how and why foodparticle size could impact, positively or negatively, on fish growth andfood conversion. The observation that food particle sizes larger thanSopt tend to enhance size heterogeneity (Fig. 4), suggests an additionalmechanism, which can be summarized as follows. In this study, thefeeding level was maintained as close as possible to Ropt so as tooptimise food conversion. It can be reasonably proposed that growthheterogeneity in this study essentially originated from variable foodintake among individuals, i.e. some fish presumably ate more thanRopt, while others ate less than Ropt. By definition, food conversion isless efficient if the food ration departs from Ropt, so the mean foodconversion efficiency is inversely proportional to the heterogeneity offood intake. When no food is wasted, as was the case during thisstudy, growth is directly proportional to food conversion efficiency,and thus inversely proportional to growth heterogeneity. If differen-tial food intake originates from feeding hierarchies, the GCE is likely tobe further decreased because the exercise of hierarchies generallyinvolves additional energy expenditures. This explanation mightaccount, at least in part for why growth was slower among fish thatwere offered food particles larger than Sopt. At present, the relativeimportance of this mechanism in comparison to the other causativefactors cannot be determined. This would require testing similarranges of food particle sizes, but with different feeding levels betweenRopt and Rmax.

On the practical side, the finding that the increase in sizeheterogeneity in O. niloticus is proportional to food particle sizesuggests that distributing food particles slightly smaller than Soptmight contribute to minimizing growth heterogeneity, which is amajor problem in tilapia culture. However, the implementation of thisfeeding strategy should be restricted in time; otherwise the particleswould rapidly fall below a relative size that compromises growth andfood conversion. All in all, the balance between the respective benefitsand drawbacks of small and large food particles suggests that feedingschedules should track Sopt as closely as possible.

Acknowledgements

This study benefited from the bilateral collaboration betweenTunisia and France under the auspices of the French Ministry ofForeign Affairs. The authors wish to thank Prof. P. Kestemont (FacultésUniversitaires Notre-Dame de la Paix, Namur, Belgium), for providingthe ballotini; Prof. S. Dhaoui (National School of Veterinary Medicine,Sidi Thabet, Tunis, Tunisia) for photoradiography; and, Dr. M.Legendre (IRD, UR 175, Montpellier, France) for a constructivediscussion on the manuscript. The assistance of Mrs. F. Hamzaoui-Azaza with the analysis of X-ray photographs was greatly appreciated.Many thanks to Mr. S. Kalboussi and K. Elebdelli for their mostefficient technical assistance throughout the study, and to the otherstaff of the Béchima fish-culture research station. Mrs. DominiqueCaseau contributed to improve the English style of the manuscript.

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