J. Anim Sci. 2009. 87:571-582. doi:10.2527/jas.2008-0951
© 2009 American Society of Animal Science
Feed preference in pigs: Relationship with feed particle size and texture1
D. Solà-Oriol*,
E. Roura
and
D. Torrallardona*,2
* Animal Nutrition-Institut de Recerca i Tecnologia Agroalimentàries (IRTA), E-43120 Constantí, Tarragona, Spain; and
R&D Feed Additives, Lucta SA, E-08170 Montornés del Vallès, Barcelona, Spain
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Abstract
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In previous studies, we observed important differences in the feed preferences of pigs resulting from changes in only 1 dietary ingredient. The present experiment was conducted to study the relationship between the feed preference values of feeds reported previously and their particle size and texture characteristics. The effect of individual feed ingredients was studied when added to a common basal diet. In addition to the basal diet, which included rice, a soybean meal product containing 56% CP, sunflower oil, and wheat bran, a total of 126 diets were studied. Of these, 63 were prepared by replacing the rice in the basal diet with another cereal, 29 by replacing the soybean product with different protein sources, 19 by replacing the sunflower oil with different lipid sources, and 6 by replacing the wheat bran with different fiber sources. Cereals were studied at inclusion rates of 150, 300, and 600 g·kg–1; protein sources were studied at 50, 100, and 200 g·kg–1; lipids were studied at 15, 30, and 100 g·kg–1; and fiber sources were studied at 65 and 130 g·kg–1. The particle size profile of all the diets was determined by using a 9-screen sieve shaker. The geometric mean particle size, particle size uniformity, number of particles per gram, surface area (cm2·g–1), and percentage of fine (passing through a 250-µm sieve) and coarse particles (remaining in a 2,000-µm sieve) were calculated. The texture properties (hardness, fragility, chewing work, and adhesiveness) of the feeds were also determined by using a texture analyzer. The Pearson correlation coefficients of these variables with feed preference were as follows: geometric mean particle size (r = 0.07; P = 0.45), particle size uniformity (r = 0.16; P = 0.07), number of particles per gram (r = –0.05; P = 0.61), surface area (r = –0.07; P = 0.46), percentage of coarse particles (r = 0.04; P = 0.65), percentage of fine particles (r = –0.12; P = 0.19), hardness (r = –0.21; P = 0.02), fragility (r = –0.20; P = 0.03), chewing work (r = –0.33; P < 0.001), and adhesiveness (r = 0.02; P = 0.78). It was concluded that the texture properties of the feed could explain in part the feed preferences observed in pigs, whereas particle size characteristics had less impact.
Key Words: cereal • particle size • pig • preference • texture
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INTRODUCTION
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Feed palatability to pigs is clearly affected by the nature of the feedstuffs included in a diet, as shown by our group in a series of double-choice preference experiments (Solà-Oriol, 2008
). Among the orosensory characteristics of the feedstuffs, odor and taste undoubtedly play a very important role, because these senses have evolved in animals to trigger a preference for nutritious compounds or an aversion to toxic ones (Goff and Klee, 2006). As reported in humans, somatosensory activity may also play an important role in food palatability (Blossfeld et al., 2007).
Some textural characteristics are felt when the feed is first placed in the mouth, but most are perceived when the feed is deformed by chewing, or while it is manipulated and moved around the oral cavity by the tongue and mixed with saliva (Szczesniak, 2002). It is not possible to evaluate the sensations experienced by the pigs when eating different feeds. However, this can be done with texture-testing instruments that quantify certain physical traits, which can be interpreted in terms of sensory perception (Szczesniak, 2002).
Changing the ingredient composition of the feeds may result in changes in their particle size and texture characteristics, which at the same time may affect their acceptability to pigs (preference). For example, in our previous studies (Solà-Oriol, 2008), we have observed that replacing white rice only with unhulled rice reduced feed preference by 39%. Although this could be due to changes in nutrient composition, an effect of the particle size and textural traits could have been involved. In piglets, reducing the particle size reduced feed intake of sorghum and corn diets (Healy et al., 1994) and wheat diets (Mavromichalis et al., 2000). Similarly, Szczesniak (2002) reported that babies and young children reject food with texture traits associated with a more difficult manipulation in the mouth. The present study was conducted to study the relationship between previously reported ingredient-related feed preferences in pigs (Solà-Oriol, 2008) and their corresponding feed particle size profile and texture traits.
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MATERIALS AND METHODS
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The experimental procedures with animals described in this study were approved by the Ethical Committee on Animal Experimentation of IRTA.
Diets
The diets used in the present work were the same as those used previously for the determination of double-choice preference in pigs, as reported by Solà-Oriol (2008). All diets were prepared from a basal diet containing 600 g of white rice, 200 g of soybean meal protein product [soybean meal-56, containing 56% CP (HP-300, Hamlet Protein, Horsens, Denmark)], 130 g of wheat bran, and 30 g of sunflower oil per kilogram, and AA, vitamins, and minerals.
A total of 127 different diets (including the basal diet), previously used to determine feed preference (Solà-Oriol, 2008), were tested. Diets were prepared by replacing (completely or partially) 1 of the main ingredients in the basal diet with the feedstuff under evaluation. Sixty-three cereal diets were prepared by replacing rice with 300 and 600 g of barley, corn (2 sources), wheat, cassava meal, biscuit meal, rye, sorghum, and oats per kilogram, or 150, 300, and 600 g of short-grain rice (unhulled, brown, and white extruded), long-grain white rice (raw and cooked), extruded barley, extruded corn, extruded wheat, oats (unhulled thick rolled, cooked, and 2 additional raw sources), and naked oats (raw, extruded, and micronized) per kilogram. Similarly, 38 protein diets were prepared by replacing the soybean meal protein product with 200 g of soybean meal (44% CP) per kilogram, 100 and 200 g of lupines, full-fat extruded soybeans, soybean meal (48% CP), sunflower meal, and rapeseed meal per kilogram, or 50, 100, and 200 g of concentrated soybean protein (Soycomil, Archer Daniels Midland, Decatur, GA), potato protein (Protastar, Avebe Group Veendam, the Netherlands), wheat gluten (Amytex 100, Amylum Group Aalst, Belgium), fishmeal (999 Prime Quality Fish Meal, TripleNine Fish Protein a.m.b.a., Esbjerg, Denmark), dried skimmed milk, sweet milk whey, acid milk whey, spray-dried porcine plasma (AP 820, APC Europe, Granollers, Spain), and spray-dried porcine solubles (Palbio 62 SP, Bioiberica, Palafolls, Spain) per kilogram. Lipid diets (19 in total) were prepared by replacing 15 or 30 g of sunflower oil per kilogram of basal diet with coconut oil, fish oil, soybean oil, palm oil, lard, and linseed oil. Diets containing 100 g·kg–1 of all the lipid sources (including sunflower oil) were also prepared by the additional replacement of 70 g of white rice per kilogram of basal diet with the corresponding lipid source. Finally, 6 fiber diets were prepared by replacing wheat bran in the basal diet with 65 and 130 g of alfalfa, sugar beet pulp, and carob bean pulp per kilogram. All the feedstuffs tested, except those already in the finely ground form, were ground with the same hammer mill (3-mm mesh).
Particle Size Determination
The particle size profile of two 50-g aliquots of each of the 127 different diets was determined (Microcomputer Screener FT-97 sieve shaker, Filtra Vibrations SL, Barcelona, Spain) essentially as described by Wondra et al. (1995b). Briefly, feed samples were placed on the top screen of the sieve shaker, which was equipped with 9 screens with 3,600-, 2,500-, 2,000-, 1,000-, 710-, 500-, 250-, 180-, and 160-µm openings and a solid pan at the bottom. The samples were sieved at maximum speed for 5 min, and the weights of feed remaining in each screen and in the pan were used to calculate the geometric mean particle size, particle size uniformity, number of particles per gram, and surface area (cm2·g–1) of each feed sample according to Pfost and Headley (1976). Additionally, the contents of fine and coarse particles were estimated as the percentage of particles passing through the 250-µm and the percentage remaining in the 2,000-µm screen, respectively.
Texture Analysis
The texture characteristics of the feeds were also analyzed (TA-XT2 Texture Analyzer, Stable MicroSystems, Surrey, UK). For each diet, 5 aliquots of 30 g were taken and mixed with distilled water at a proportion of 1:1 (wt/wt). The mixture was immediately placed in a cylindrical recipient (60 mm in diameter and 100 mm in height), in which 5 simple compressions with a 30-mm (diameter) cylinder were performed (maximum penetration of 15 mm at a speed of 1 mm·s–1). The time frame of the force required to penetrate the sample and to withdraw the 30-mm cylinder were registered (Figure 1). From this, the texture traits of hardness, fragility, chewing work, and adhesiveness were calculated (XT. RA Dimension version 3.7A, Stable MicroSystems, Surrey, UK) essentially as described by Szczesniak (2002).
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Figure 1. Texture profile analysis of the reference rice-based diet using a single compression. Hardness (kg) is defined as the maximum force achieved during the compression phase; fragility is defined as the slope of the line between zero force at the x-axis and the maximum force point; chewing work is the calculated area under the positive force curve (A1), and adhesiveness is the calculated area under the negative force curve (A2).
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Hardness (maximum force achieved; kg) provides an indication of the force required to compress the feed during chewing. Fragility (slope between zero force at the x-axis and point of maximum force) is an indication of the speed at which the maximum force is achieved during mastication; fragility is greater for hard, crispy feeds than for elastic, chewy feeds. Chewing work (resulting from the integration of the positive area of the force curve; kg·s) provides an estimation of the overall effort required to masticate the feed. Finally, adhesiveness (integration of the negative area of the force curve; kg·s) measures the adherence of the feed to the teeth and palate.
Statistical Analysis
Particle size and texture profile variables for each group of ingredients were analyzed by inclusion rate with ANOVA, using the GLM procedure (SAS Inst. Inc., Cary, NC). The model used was Yi = µ + 
i + 
i, where Yi is the value for the observation of ingredient (i), µ is the general mean of all observations, i is the effect of the ingredient, and i is the unexplained random error. Pearson correlation coefficients between feed preference and the particle size and texture variables were obtained by using the CORR procedure of SAS.
The effect of extrusion on the texture characteristics of 5 cereal-based diets (at 600 g·kg–1 of inclusion) was also analyzed by ANOVA according to a 5 x 2 factorial arrangement of treatments, with cereal source (barley, corn, naked oats, white rice, or wheat) and extrusion (yes or no) as the main factors, by using the GLM procedure of SAS. The model used was Yij = µ + i + βj + βij + ij, where Yij is the value for the observation of cereal source (i), raw or extruded (j); µ is the general mean of all observations; i is the effect of cereal source; βj is the effect of extrusion; βij is the interaction between cereal source and the extrusion; and ij is the unexplained random error.
The level used for the determination of significance for all the analyses was 0.05. Differences among means were compared by using the Tukey’s Studentized range (honestly significant differences) test.
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RESULTS
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The particle size and texture characteristics of feeds differing in only 1 ingredient are shown in Tables 1 to 8. The reported values correspond to the measurements obtained for the diets, in which cereal, protein, lipid, and fiber sources were added at inclusion rates of 600, 200, 30, and 130 g·kg–1, respectively.
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Table 1. Average feed particle size (dgw), particle size SD (sgw), number of particles per gram of feed, surface area, and proportions of coarse (>2,000 µm) and fine (<250 µm) particles of diets containing 60% of different cereals
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Table 2. Hardness, fragility, chewing work, and adhesiveness of diets containing 60% of different cereal ingredients
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Table 3. Average feed particle size (dgw), particle size SD (sgw), number of particles per gram of feed, surface area, and proportions of coarse (>2,000 µm) and fine (<250 µm) particles of diets containing 20% of different protein sources
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Table 4. Hardness, fragility, chewing work, and adhesiveness of diets containing 20% of different protein sources
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Table 5. Average feed particle size (dgw), particle size SD (sgw), number of particles per gram of feed, surface area, and proportions of coarse (>2,000 µm) and fine (<250 µm) particles of diets containing 3% of different lipid sources
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Table 7. Average feed particle size (dgw), particle size SD (sgw), number of particles per gram of feed, surface area, and proportions of coarse (>2,000 µm) and fine (<250 µm) particles of diets containing 13% of different fiber sources
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Among the cereals, the diet with micronized naked oats had a greater number of particles (163 per mg) than any other, except for the extruded barley diet (Table 1
). It also had the greatest proportion of fine particles (44%), the greatest surface area (187 cm2·g–1), and the smallest average feed particle size (293 µm). In contrast, the barley-based diet had the greatest average feed particle size (531 µm) and a large proportion of coarse particles, together with the smallest number of particles (1.8%), the smallest surface area (102 cm2·g–1), and the smallest proportion of fine particles (23%). Regarding the texture measurements, the diets containing naked oats, extruded naked oats, or thick rolled (dehulled) oats had the smallest hardness (1.0 to 1.4 kg), fragility (0.06 to 0.09), and chewing work (11 to 14 kg·s) values. These values were, however, greatest for the diets based on unhulled rice, extruded white rice, corn (source 1), and extruded barley (4.9 to 5.7 kg, 0.32 to 0.38, and 34 to 54 kg·s, respectively). The greatest adhesiveness (–11 kg·s) was also observed in the diets containing extruded white rice and extruded barley (Table 2).
The effect of extrusion on the texture characteristics of different cereals is shown in Figure 2. Significant effects (P < 0.01) were observed for both cereal source and extrusion, as well as for their interaction. Although extrusion increased (P < 0.05) the values for hardness, fragility, and chewing work in barley, rice, and wheat, for corn it decreased (P < 0.05) the hardness and fragility. Extrusion increased the adhesiveness in all the cereals, with values ranging between –2.5 and –10.8 kg·s for treated cereals compared with –0.6 and –3.1 kg·s for nontreated cereals.
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Figure 2. Hardness, fragility, chewing work, and adhesiveness of diets containing 600 g·kg–1 of different cereal ingredients in either raw or extruded form. a–dBars with different letters are different: P < 0.05. Effects of cereal source, extrusion, and their interaction for all 4 variables: P < 0.01. Pooled SE represented by vertical bars.
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Of the protein-source diets studied, the diet with dried porcine solubles had a greater average feed particle size and a smaller proportion of fine particles than any other diet (Table 3). This diet had a large particle size SD (2.0 µm), a large proportion of coarse particles (1.9%), the smallest number of particles (11 per mg), and the smallest surface area (69 cm2·g–1). However, the diet with spray-dried porcine plasma had the smallest average feed particle size (353 µm), particle size SD (1.8 µm), and proportion of coarse particles (0.3%), along with the largest surface area (151 cm2·g–1) and the largest proportion of fine particles (36%). Despite their decreased rate of inclusion, protein sources had a greater impact on texture traits than did cereals (Figures 3, 4, and 5). The sweet milk whey diet had a resistance force to compression that was too large (>25 kg) to be measured in our apparatus. Therefore, it had the greatest hardness, fragility, and chewing work values, although these values could not be measured. Dried porcine solubles, potato protein, acid milk whey, and soybean protein-based diets had the greatest hardness (15 to 25 kg), fragility (1.1 to 1.7), and chewing work (49 to 88 kg·s) values. In contrast, spray-dried porcine plasma and dry-skimmed milk had the least hardness (0.4 kg), fragility (<0.03), chewing work (<1.7 kg·s), and adhesiveness (>–0.3 kg·s) values (Table 4).
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Figure 3. Correlation between feed preference and hardness. Cereals: white short-grain rice (A), unhulled rice (B), brown rice (C), extruded white rice (D), white long-grain rice (E), cooked white long-grain rice (F), barley (G), extruded barley (H), corn (I), extruded corn (J), wheat (K), extruded wheat (L), oats (M), flaked rolled oats (N), cooked oats (O), naked oats (P), extruded naked oats (Q), micronized naked oats (R), cassava pellets (S), biscuit meal (T), rye (U), and sorghum (V) tested at 150, 300, and 600 g·kg–1 of inclusion. Protein sources: soybean meal-56 [a; soybean meal protein product containing 56% CP (HP-300, Hamlet Protein, Horsens, Denmark)], lupines (b), full-fat extruded soybeans (c), soybean meal (44% CP; d), soybean meal (48% CP; e), hulled sunflower meal (f), rapeseed meal (g), soybean protein (h), wheat gluten (i), potato protein (j), fishmeal (k), spray-dried porcine solubles (l), spray-dried porcine plasma (m), dried skimmed milk (n), sweet milk whey (o), and acid milk whey (p) tested at 50, 100, and 200 g·kg–1 of inclusion. Lipid sources: sunflower oil (q), coconut oil (r), fish oil (s), soybean oil (t), palm oil (u), lard (v), and linseed oil (w) tested at 15, 30, and 100 g·kg–1 of inclusion. Fiber sources: wheat bran (W), dehydrated alfalfa (X), sugar beet pulp (Y), and carob bean pulp (Z) tested at 65 and 130 g·kg–1 of inclusion. Pearson correlations: cereals, r = –0.54, P < 0.001; protein sources, r = –0.40, P = 0.013; and lipid sources and fiber sources, P > 0.1.
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Figure 4. Correlation between feed preference and fragility. Cereals: white short-grain rice (A), unhulled rice (B), brown rice (C), extruded white rice (D), white long-grain rice (E), cooked white long-grain rice (F), barley (G), extruded barley (H), corn (I), extruded corn (J), wheat (K), extruded wheat (L), oats (M), flaked rolled oats (N), cooked oats (O), naked oats (P), extruded naked oats (Q), micronized naked oats (R), cassava pellets (S), biscuit meal (T), rye (U), and sorghum (V) tested at 150, 300, and 600 g·kg–1 of inclusion. Protein sources: soybean meal-56 [a; soybean meal protein product containing 56% CP (HP-300, Hamlet Protein, Horsens, Denmark)], lupines (b), full-fat extruded soybeans (c), soybean meal (44% CP; d), soybean meal (48% CP; e), hulled sunflower meal (f), rapeseed meal (g), soybean protein (h), wheat gluten (i), potato protein (j), fishmeal (k), spray-dried porcine solubles (l), spray-dried porcine plasma (m), dried skimmed milk (n), sweet milk whey (o), and acid milk whey (p) tested at 50, 100, and 200 g·kg–1 of inclusion. Lipid sources: sunflower oil (q), coconut oil (r), fish oil (s), soybean oil (t), palm oil (u), lard (v), and linseed oil (w) tested at 15, 30, and 100 g·kg–1 of inclusion. Fiber sources: wheat bran (W), dehydrated alfalfa (X), sugar beet pulp (Y), and carob bean pulp (Z) tested at 65 and 130 g·kg–1 of inclusion. Pearson correlations: cereals, r = –0.54, P < 0.001; protein sources, r = –0.39, P = 0.016; and lipid sources and fiber sources, P > 0.1.
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Figure 5. Correlation between feed preference and chewing work. Cereals: white short-grain rice (A), unhulled rice (B), brown rice (C), extruded white rice (D), white long-grain rice (E), cooked white long-grain rice (F), barley (G), extruded barley (H), corn (I), extruded corn (J), wheat (K), extruded wheat (L), oats (M), flaked rolled oats (N), cooked oats (O), naked oats (P), extruded naked oats (Q), micronized naked oats (R), cassava pellets (S), biscuit meal (T), rye (U), and sorghum (V) tested at 150, 300, and 600 g·kg–1 of inclusion. Protein sources: soybean meal-56 [a; soybean meal protein product containing 56% CP (HP-300, Hamlet Protein, Horsens, Denmark)], lupines (b), full-fat extruded soybeans (c), soybean meal (44% CP; d), soybean meal (48% CP; e), hulled sunflower meal (f), rapeseed meal (g), soybean protein (h), wheat gluten (i), potato protein (j), fishmeal (k), spray-dried porcine solubles (l), spray-dried porcine plasma (m), dried skimmed milk (n), sweet milk whey (o), and acid milk whey (p) tested at 50, 100, and 200 g·kg–1 of inclusion. Lipid sources: sunflower oil (q), coconut oil (r), fish oil (s), soybean oil (t), palm oil (u), lard (v), and linseed oil (w) tested at 15, 30, and 100 g·kg–1 of inclusion. Fiber sources: wheat bran (W), dehydrated alfalfa (X), sugar beet pulp (Y), and carob bean pulp (Z) tested at 65 and 130 g·kg–1 of inclusion. Pearson correlations: cereals, r = –0.43, P < 0.001; protein sources, r = –0.41, P = 0.011; and lipid sources and fiber sources, P > 0.1.
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No differences among lipid sources were observed for most particle size traits, except for average feed particle size, which was significantly greater in lard (447 µm) than in coconut oil (353 µm) diets, and the proportion of fine particles was greater in coconut oil diets (36%) than in soybean oil, palm oil, and lard diets (28 to 30%; Table 5). Diets containing soybean oil and lard had greater values for hardness (2.9 kg), fragility (1.2), and chewing work (21 to 22 kg·s) than those containing fish and coconut oils (<1.8 kg, 0.1, and <14 kg·s, respectively; Table 6).
For the fiber-source diets, sugar beet pulp had the largest average feed particle size (466 µm) and the largest proportion of coarse particles (2.9%) combined with the least number of particles (53 per mg) and the smallest surface area (121 cm2·g–1; Table 7). Wheat bran had the smallest average feed particle size (398 µm), particle size SD (1.8 µm), and proportion of coarse particles (1.1%), and the greatest surface area (137 cm2·g–1) and proportion of fine particles (32%). Dehydrated alfalfa had the greatest particle size SD (2.0 µm), the greatest number of particles (67 per mg), and the smallest proportion of fine particles (28%). Sugar beet pulp also had the smallest hardness, fragility, and chewing work values, whereas these were the greatest for carob bean pulp. Sugar beet pulp and dehydrated alfalfa had greater adhesiveness than wheat bran (Table 8).
In the overall analysis and for most of the ingredient categories studied, the variables of particle size did not correlate with the preference values (Table 9). Only the proteins of vegetable origin, average particle size (r = 0.42; P = 0.06), particle size SD (r = 0.39; P = 0.08), and percentage of coarse particles (r = 0.50; P = 0.06) showed a positive correlation, whereas the number of particles (r = –0.45; P = 0.04) and the surface area (r = –0.43; P = 0.05) correlated negatively. In addition, for fiber sources, particle size SD (r = –0.83; P = 0.02) and percentage of coarse particles (r = –0.85; P = 0.06) showed a negative correlation, whereas the percentage of coarse particles (r = 0.72; P = 0.07) correlated positively.
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Table 9. Pearson correlation coefficients between the preference of feeds containing different ingredients and the average feed particle size (dgw), particle size SD (sgw), number of particles per gram of feed, surface area per gram of feed, percentage of coarse (>2,000 µm) particles, and percentage of fine (<250 µm) particles
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Overall, the texture variables of hardness (r = –0.21; P = 0.02), fragility (r = –0.20; P = 0.03), and chewing work (r = –0.33; P < 0.001) showed a negative correlation with preference values (Table 10). Considering separately the diets in which the different cereals or the different protein sources were studied, stronger correlations were obtained, particularly for hardness and fragility. For cereals, these correlations were hardness (r = –0.49; P < 0.001), fragility (r = –0.49; P < 0.001), and chewing work (r = –0.36; P = 0.003). For the protein sources, the correlations were hardness (r = –0.40; P = 0.013), fragility (r = –0.39; P = 0.015), and chewing work (r = –0.41; P = 0.011). Figures 3 to 5 show the relationship between the preference values and the texture traits of the different diets. Adhesiveness did not correlate with the preference values for any of the different feed ingredient categories studied (Table 10).
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Table 10. Pearson correlation coefficients between the preference of feeds containing different ingredients and the texture variables of hardness, fragility, chewing work, and adhesiveness
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DISCUSSION
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Although palatability is often described as a combination of taste and smell, somatosensory activity may also play a major role in perception (Blossfeld et al., 2007), indicating that multiple distinct sensory inputs are processed to generate the overall sensation (Goff and Klee, 2006). The current work studied the correlation between feed preferences and feed particle size and texture. Although particle size characteristics showed only marginal correlations with preference values, the texture characteristics of hardness, fragility, and chewing work showed a statistically significant negative correlation.
As expected, changing the ingredient composition of the feeds modified their particle size characteristics. Apparently, the relative impact of cereals and fiber sources was less important than the relative impact of protein and lipid sources. For cereals, the changes in mean particle size per percentage unit of ingredient ranged between –1.8 and 2.2 µm, and for fiber sources these ranged between 0 and 5.2 µm, whereas they ranged between –2.3 and 21.6 µm for protein sources and between –15 and 16 µm for lipid sources.
In general, unprocessed, raw cereals had a larger mean particle size (437 vs. 329 µm), fewer particles per gram of feed (51,838 vs. 95,858), a smaller surface area (127 vs. 163 cm2·g–1), and less fine particles (30 vs. 37%) than the technologically treated cereals. This is probably related to the technological process itself because it usually includes fine grinding as part of the treatment. Among the protein sources, dried porcine solubles had a large mean particle size, along with large and small percentages of coarse and fine particles, respectively. This is probably due to a "balling" effect of the product because of its high hygroscopicity. A similar effect may explain the larger particle size in diets containing lard and palm oil because of their greater contents of solid, saturated fats.
The poor correlation between feed particle size and feed preference value indicates that reducing the particle size will not improve feed intake, except for vegetable proteins and fibers. This is in agreement with previous observations in piglets, in which reducing the particle size reduced the feed intake of sorghum and corn diets (Healy et al., 1994) and wheat diets (Mavromichalis et al., 2000). Reductions in feed intake with smaller particle sizes have also been observed in growing-finishing pigs fed corn-based diets (Wondra et al., 1995a) and wheat-based diets (Mavromichalis et al., 2000). In contrast, Wondra et al. (1995b) also reported that lactating sows increased their feed intake of a corn-based diet as particle size was with decreased. However, it must be considered that in those studies, the particle size ranged from 300 to 400 µm up to 900 to 1,300 µm. In our study, the particle size ranged only from 293 to 531 µm (micronized naked oats and barley, respectively) because all the ingredients were ground under the same conditions (unless already in a ground form). Therefore, in our study the differences in particle size may be related to the physical characteristics of the grains. For example, Healy et al. (1994) reported that particle size increased with endosperm hardness.
A particle size between 500 and 600 µm has been recommended for piglets (Healy et al., 1994; Mavromichalis et al., 2000). However, factors other than feed intake, such as the decreased predisposition to gastric ulceration (Wondra et al., 1995a) and the greater resistance to gastrointestinal infections (Brunsgaard, 1998) with coarsely ground diets, have been considered when making these recommendations. Somatosensory activity is used to evaluate the physicomechanical and structural properties of feed (e.g., texture, temperature, and pungency).
Somatosensory evaluation takes place predominantly in the mouth and results from the combination of multiple characteristics of the food. Although texture properties can be perceived by animals, they cannot describe them, unlike humans. Therefore, we rely on the texture-testing instruments to detect and quantify certain physical traits, which can be related and interpreted in terms of sensory perception (Szczesniak, 2002). In humans, excellent correlations have been described between instrumental and sensory rating textural profile analyses (Szczesniak, 1963). Hardness may provide an indication of the maximum force that the pigs must have to compress the feed during chewing. Fragility measures the speed at which this maximum force is achieved, and it is greater for hard, crispy feeds than for elastic, chewy feeds. Chewing work provides an estimation of the overall effort required to perform the whole biting process. Finally, adhesiveness is used as an indication of the stickiness of the feed to the teeth and palate of the pig.
Because of the greater DM content, we added water to the piglet feed to be able to perform the texture profile analysis. A 1:1 water:feed ratio was chosen because this coincides with the rate of saliva production by the pig (Corring, 1979); therefore, conditions similar to those occurring in the mouths of the pigs could be simulated. However, saliva has a high mucus content to lubricate the feed bolus. The use of water to simulate the effect of saliva does not provide this lubricating effect, and this should be considered when interpreting the results.
Among the feedstuffs tested, protein sources (compared with cereals) showed a more important impact on texture characteristics, despite their reduced rate of inclusion. In particular, sweet milk whey, potato protein, and dried porcine solubles resulted in the greatest hardness, fragility, and chewing work values. This is possibly related to the hygroscopic properties of these proteins. For those, a greater amount of saliva may be needed for the feed bolus to achieve the texture required to be able to be swallowed. However, spray-dried animal plasma had the least values for hardness, fragility, and chewing work, which may be due to its water-holding capacity, foaming, and emulsifying properties (Polo et al., 2007).
We have observed that texture properties of cereals can be affected by the different technological treatments. However, it must be considered that in some cases, the technological treatment implies physical changes in the raw cereal caused by hull removal or finer grinding. In any case, although the extrusion of cereals was always accompanied by a reduction in particle size, the effect of extrusion on hardness, fragility, and chewing work depended on the nature of the cereal, with corn being different from the other cereals studied. However, adhesiveness for all the cereals was clearly increased by extrusion, but that did not correlate with their preference values.
In our study, the texture variables of hardness, fragility, and chewing work, as measured by a texture analyzer, correlated negatively with the preferences shown by the pigs. Similar correlations between the textural profile analysis and the texture sensations experienced by pigs, and those described in humans (Szczesniak, 1963) can be assumed for piglets, supporting the view that textural profile analysis may be a useful tool to obtain information about piglet feed acceptance.
The study of the correlation between texture traits and feed preference, using diets containing ingredients with common characteristics (i.e., different presentations of barley, dairy proteins, etc.), resulted in stronger correlations than the overall use of feeds. This is probably due to a less pronounced effect of other factors such as taste, odor, or nutritional value on feed preference when similar ingredients are studied together.
In humans, Szczesniak (2002) reported that babies and young children reject foods with textures that are difficult to manipulate in the mouth. Gisel (1991) showed that the texture characteristics of a particular food determine how long it needs to be chewed before it can be swallowed. Presumably, feeds requiring shorter chewing times are likely to be best preferred, particularly in piglets at weaning. Our observation that feed preference in pigs is negatively correlated with hardness and chewing work supports this.
As shown previously (Solà-Oriol, 2008), the palatability of feed for piglets varies, depending on the feedstuffs used. Our data showed that changing only 1 ingredient modified the particle size and texture properties of the feed. Particle size did not seem to be responsible for the changes in feed preference, because a poor correlation was observed between preference and particle size values. In contrast, feed preference values in pigs were correlated with the texture traits of the feed, indicating that texture explains, at least in part, feed palatability for pigs. Although statistically significant, the low correlation indices suggest that other factors, such as taste, odor, or nutritional value, may also be important in the overall feed preference. Further work needs to be conducted to assess possible interactions among ingredients and ways to improve feed intake through technological processes that affect texture.
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Footnotes
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1 This study was supported by CDTI (Spanish Innovation Agency, Ministry of Industry Tourism, and Trade, Madrid, Spain), project 050369. The authors thank A. Romero and L. Guerrero for the technical support received. The assistance of the IRTA laboratory and farm staff in conducting the trials is also acknowledged. 
2 Corresponding author: David.Torrallardona{at}irta.es
Received for publication February 12, 2008.
Accepted for publication October 13, 2008.
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LITERATURE CITED
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Abstract
INTRODUCTION
