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RESEARCH ARTICLE (Open Access)

Additivity and associative effects of metabolisable energy and ileal amino acid digestibility in broiler diets combining sorghum with different protein sources

A. Sultan A B , X. Li https://orcid.org/0000-0003-3109-5789 A , D. Zhang A and W. L. Bryden https://orcid.org/0000-0002-7187-4464 A C *
+ Author Affiliations
- Author Affiliations

A School of Agriculture and Food Sustainability, The University of Queensland, Gatton, Qld 4343, Australia.

B Department of Poultry Science, The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan.

C Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Qld 4072, Australia.

* Correspondence to: w.bryden@uq.edu.au

Handling Editor: Kris Angkanaporn

Animal Production Science 64, AN24159 https://doi.org/10.1071/AN24159
Submitted: 11 May 2024  Accepted: 9 July 2024  Published: 30 July 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

Poultry diets consist of several ingredients contributing specific amounts of nutrients and it is assumed that the supply from each ingredient is additive when diets are formulated. However, the additivity of apparent metabolisable energy (AME) and ileal amino acid digestibility in broiler diets combining sorghum with different protein sources has not been examined.

Aims

To determine the additivity of AME along with ileal digestibility values for protein and amino acids in diets combining sorghum with different protein sources.

Methods

The digestibility assays, based on semi-purified diets containing sorghum, sunflower meal (SFM), meat and bone meal (MBM), soybean meal (SBM), canola meal (CM), and cottonseed meal (CSM), were fed individually, or sorghum was combined with the different protein sources. Each diet was fed to three cages of 12 17-day-old broilers for 7 days. Excreta was collected for the final 3 days and at the end of the assay, digesta was collected from the terminal ileum for digestibility determination.

Key results

When sorghum was mixed with the different protein sources, all predicted values for protein digestibility were additive, but for AME only the value for sorghum + SFM was additive. All other predicted AME values for sorghum combinations were different (P < 0.05) from the determined value. There were significant (P < 0.05) differences between predicted and determined amino acid digestibility coefficients, but amino acids showing associative effects varied among the different sorghum protein source combinations.

Conclusions

Overall, the present results indicated that caution should be exercised when predicting the AME and apparent ileal amino acid digestibility values for sorghum-based diets from values determined with individual feed ingredients.

Implications

The study indicated that positive and negative interactions are likely to occur among dietary ingredients in mixed diets, which has implications for both energy and protein utilisation.

Keywords: additivity, amino acids, associate effects, broilers, canola meal, cottonseed meal, meat and bone meal, sorghum, soybean meal, sunflower meal.

Introduction

Nutrient availability is an important index for measuring the quality of any feed ingredient (Ravindran and Bryden 1999; Lemme et al. 2004; Bryden and Li 2010). In a complete poultry diet, the content of available or digestible nutrients is considered rather than the concentration of nutrients per se, for accurate feed formulation. Poultry diets consist of a number of ingredients contributing specific amounts of nutrients and it is assumed that the supply from each ingredient is additive when diets are formulated (Bryden and Li 2010). A number of studies with poultry (Angkanaporn et al. 1996; Cowieson et al. 2019; Osho et al. 2019) and pigs (Fan et al. 1993; Stein et al. 2005; Wang et al. 2018) have shown that digestibilities of nutrients in complete diets can be predicted from values of digestibilities determined with individual ingredients, but no studies have examined sorghum. Associative effects occur when the dietary supply of nutrients is not equal to the sum of predicted values determined for individual ingredients (Pond et al. 2005). In both ruminants (Mould et al. 1983; Dixon and Stockdale 1999; Niderkorn and Baumont 2009) and non-ruminants (Laplace et al. 1989; Palmgren Karlsson et al. 2000; Hong et al. 2001), associative effects have been reported. Feed ingredients with low amino acid concentrations and containing anti-nutritional factors may have lower ileal digestibility, thus masking additivity in a complete diet (Laplace et al. 1989). Such feedstuffs often vary greatly in composition and digestibility, which affects digestion and absorption of protein (Bryden 1996). Moreover, anti-nutritional factors may also perturb protein utilisation in complete diets by increasing endogenous amino acid losses (Imbeah et al. 1988; Angkanaporn et al. 1994).

Sorghum is used widely in Australian poultry diets, primarily as an energy component (Bryden et al. 2009a; Selle et al. 2018). It is usually fed in diets that contain wheat but may be the only cereal in diets when wheat prices are high (Bryden et al. 2009a; Selle et al. 2010). The composition of sorghum can be variable and the presence of anti-nutritive factors (phytate, kafirin, and non-tannin phenolics and polyphenols) affects protein digestibility (Bryden et al. 2009a; Selle et al. 2018; Hodges et al. 2021). In complete diets, sorghum is fed with a range of protein meals. There are no studies indicating the impact of sorghum anti-nutritional factors on the additivity of ileal amino acid digestibility with different protein sources; many of which also contain anti-nutritional factors. Thus, the objective of this study was to determine whether apparent metabolisable energy (AME) content, ileal crude protein and amino acid digestibility coefficients of mixed diets containing sorghum with different protein sources can be predicted from the values determined with individual feed ingredients.

Materials and methods

Ethical considerations

The experimental procedures involving birds were approved by the Animal Care and Ethics Committee of the University of Queensland and complied with the Australia Code of Practice for the Care and Use of Animals for Scientific Purposes (NHMRC 2013).

Birds and housing

In total, 396 male, broiler chicks (Ross 308) were collected from a local commercial hatchery and placed in cages in an environmentally controlled room. Temperature, lighting, humidity and ventilation were maintained inside the room as recommended by the breeding company (Aviagen 2018). Chicks were maintained on a commercial starter diet (220 g protein/kg diet; Better Blend Stock Feeds, Toowoomba, Queensland, Australia) till the commencement of the experiment. Birds always had free access to diets and water and were monitored twice daily, both before and during the experiment.

Dietary treatments and experimental procedures

Sorghum (Sorghum bicolor), sunflower meal (SFM, Helianthus annuus), meat and bone meal (MBM), soybean meal (SBM, Glycine max), cottonseed meal (CSM, Gossypium sp) and canola meal (CM, Brassica napus) were obtained from a local commercial feed-ingredient supplier in Toowoomba, Queensland. In total, 11 semi-purified assay diets (Table 1) were prepared as described by Ravindran et al. (2005) and fed as a mash. Celite® (Celite Corporation, Lompoc, CA, USA), a source of acid-insoluble ash (AIA), was incorporated (20 g/kg) into all diets as an indigestible marker. The fibre component of the diets containing MBM was satisfied by adding cellulose (Solkafloc®, James River Co., New Jersey, USA).

Table 1.Composition (g/kg ‘as is’) of assay diets.

IngredientSorghumSunflower mealMeat and bone mealSoybean mealCanola mealCottonseed mealSorghum + SFMSorghum + MBMSorghum + SBMSorghum + CMSorghum + CSM
Sorghum918571408417526513600600600600600
Protein source279279279279279
Dextrose308471462353366
Canola oil2060606060606060606060
Celite2020202020202020202020
Dicalcium P171919191919191919
Limestone131010101010101010
Choline CL33333333333
Salt22222222222
Broiler premix A77777777777
Solkafloc2929
Total10001000100010001000100010001000100010001000

SFM, sunflower meal; MBM, meat and bone meal; SBM, soybean meal; CM, canola meal; CSM, cottonseed meal.

A Each kilogram of premix contained: trans-retinol, 0.66 mg; cholecalciferol, 0.018 mg; dI-α-tocopherol acetate; 4 mg; menadione, 0.4 mg; thiamine, 0.3 mg; riboflavin, 1.6 mg; calcium pantothenate, 3 mg; niacin, 6 mg; pyridoxine, 1 mg; folic acid, 0.4 mg; cyanocobalamin, 3 μg; biotin, 0.02 mg; manganese, 15 mg; zinc, 10 mg; iron, 4 mg; copper, 1 mg; iodine, 0.2 mg; cobalt, 0.06 mg; selenium, 0.02 mg; molybdenum, 0.32 mg; choline chloride, 60 mg, ethoxyquin, 25 mg.

On Day 17 post-hatch, all birds were weighed individually and allocated to cages, each containing 12 birds, by random stratification so that each cage of chickens had similar initial mean and range of liveweights. Experimental diets were randomly allocated to three cages of birds and fed for 7 days. For the last 3 days of feeding, total excreta were collected and weighed daily after removal of feathers, scales and debris, pooled from each cage and subsamples were stored at −20°C for AME determination (Li et al. 2006a). After 7 days, all birds were euthanised with an intra-cardial injection of sodium pentobarbitone and the contents of the lower half of ileum were collected by gentle flushing with distilled water into plastic containers. The ileum was taken from the Meckel’s diverticulum to a point 40 mm proximal to the ileo–caecal junction. Samples from all birds within a pen were pooled, frozen and stored at −20°C.

Digesta and excreta samples were lyophilised (Christ®, Quantum Scientific, Australia) and ground using a Retsch grinder (Retsch RM-200, Retsch GmbH, Retsch-Allee, Germany) to pass through a 0.5 mm sieve.

Chemical analyses

Dry matter was measured by drying 3 g of each sample in an oven (Axyos Technologies Clayson, Australia) for 24 h at 105°C.

An adiabatic bomb calorimeter (IKA® Werke, USA), standardised with benzoic acid, was used to determine the gross energy of feed ingredients, canola oil, dextrose, diets and excreta samples. Gross energy from canola oil and dextrose was assumed 100% utilised by the bird and diet values were corrected accordingly.

The nitrogen (N) content of feed ingredients, diets and ileal digesta was determined by the Dumas combustion method using a FP-428 nitrogen determinator (LECO® Corporation, St Joseph, Michigan, USA), according to Sweeney (1989). The N value was multiplied by 6.25 to obtain the crude-protein content of the samples.

The AIA content of diet and ileal digesta samples was determined by ashing in an electric furnace (ModuTemp, Australia) for 8 h at 500°C and then boiling with 4 N HCl (Li et al. 2006a).

Amino acids were determined as described by Li et al. (2006a). Briefly, diet and digesta samples were hydrolysed with 8 M HCl under pressure of 100 kPa at 121°C for 16 h. Amino acids in the hydrolysate were separated using cation-exchange column chromatography with post-column derivatisation and fluorometric detection with O-phthaldialdehyde. There was usually insufficient ileal sample to determine cystine and methionine after oxidation. Hence no values for cystine are reported and the values determined for methionine are likely to be underestimated due to losses during acid hydrolysis.

Calculations

The AME (MJ/kg DM) values of the feed ingredients and diets were calculated using the following formula:

AME diet=(Feed intake × GE diet )  (Excreta output × GE excreta )Feed intake

where AMEdiet is AMEingredient; GEdiet is diet gross energy corrected for oil or dextrose energy; GEexcreta is the gross energy from excreta

The apparent amino acid digestibility coefficients for feed ingredients were calculated using the following formula:

Apparent ileal amino acid digestibility coefficients=(AA/AIA)d  (AA/AIA)i(AA/AIA)d

where (AA/AIA)d is the ratio of amino acid to acid-insoluble ash in diet and (AA/AIA)i is the ratio of amino acid to acid-insoluble ash in ileal digesta.

Digestibility coefficients of protein and amino acids of mixed diets were determined (measured or observed) and predicted (calculated) on the basis of the digestibility value of individual ingredients. Individual amino acid digestibility coefficient and level contributed by each ingredient were used to calculate and predict digestibility coefficients of protein and amino acids in the mixed diet. Calculated protein and amino acid digestibility coefficients were subtracted from the respective measured values of each mixed diet and were tested for significance. The same procedure was adopted for predicting the AME content of mixed diets.

Statistical analyses

Minitab (MINITAB 1996) was used to analyse experimental data using one-way ANOVA and means were separated with l.s.d. test. The Tukey’s test was used to compare the observed and predicted values of protein, AME, and amino acid digestibility coefficients of diets.

Results

The determined values of dry matter, AME, crude protein and amino acid contents of the feedstuffs used in this study are given in Table 2. The AME value of SBM was higher than the values for MBM, CM, CSM and SFM. The content of crude protein was highest in MBM followed by SBM, CSM, CM and SFM. The concentrations of all the essential amino acids were higher in SBM, followed by MBM, CSM, CM and SFM.

Table 2.Apparent metabolisable energy (AME), crude-protein (CP) and amino acid contents of the feed ingredients (g/kg ‘as is’ basis).

ParameterSorghumSFMMBMSBMCMCSM
DM880898944893891915
AME (MJ/kg)14.6212.7814.7515.1114.0513.33
CP (N × 6.25)113350529480372410
Indispensable amino acids
 Threonine4.113.720.422.213.322.8
 Valine5.817.823.225.216.624.6
 Methionine1.54.27.96.65.26.9
 Isoleucine4.714.315.623.912.019.0
 Leucine17.123.436.241.222.936.1
 Phenylalanine6.215.618.425.919.418.9
 Histidine3.010.312.015.712.215.1
 Lysine3.014.033.637.219.132.6
 Arginine4.329.739.039.443.529.4
Dispensable amino acids
 Aspartic acid7.831.340.057.933.934.4
 Serine5.916.323.929.618.523.4
 Glutamic acid26.774.270.096.675.590.1
 Glycine3.419.164.421.215.423.7
 Alanine10.914.738.622.514.721.4
 Tyrosine3.58.513.718.410.413.6

SFM, sunflower meal; MBM, meat and bone meal; SBM, soybean meal; CM, canola meal, CSM, cottonseed meal.

Values are the means of the analysis of duplicate samples.

Protein and amino acid digestibility

The apparent ileal protein and amino acid digestibility coefficients of the feed ingredients used in experiment are presented in Table 3. Apparent ileal digestibility coefficient of protein was significantly (P < 0.05) higher for SBM (0.85), followed by SFM (0.83), with no significant difference between these ingredients. Sorghum (0.81) had significantly (P < 0.05) higher protein digestibility than did CSM (0.72), CM (0.74) and MBM (0.72) and these three were not significantly different from each other. As shown in Table 3, among the different feed ingredients, SBM had the highest average apparent ileal amino acid digestibility coefficient (0.88), followed by SFM (0.84). The lowest amino acid digestibility coefficients were in CM (0.71) and MBM (0.72). Digestibility coefficients for most of the essential and non-essential amino acids were greater in SMB and SFM diets. Meat and bone and CM had the lowest digestibility coefficients for all the amino acids.

Table 3.Amino acid digestibility coefficients of feed ingredients.

FeedstuffCPThrValMetIleLeuPheHisLysArgAspSerGluGlyAlaTyrMean
Sorghum0.81b0.74bc0.83ab0.83b0.84b0.87a0.87ab0.74c0.86b0.85b0.84ab0.81b0.87c0.74bc0.88a0.82b0.83b
SFM0.83ab0.77b0.85a0.89b0.86b0.85a0.90a0.81b0.86b0.93a0.83b0.77b0.92a0.71c0.86a0.85b0.84b
MBM0.72c0.66d0.72c0.76c0.69d0.72c0.75d0.71d0.72d0.79c0.59e0.65e0.72e0.79b0.78c0.71e0.72d
SBM0.85a0.83a0.87a0.92a0.88a0.87a0.88a0.88a0.90a0.92a0.86a0.86a0.90b0.84a0.87a0.90a0.88a
CM0.74c0.61e0.69d0.74d0.65e0.68d0.79c0.75c0.58e0.86b0.72d0.70d0.82d0.68d0.66d0.75d0.71d
CSM0.72c0.72c0.78b0.89b0.78c0.82b0.83b0.81b0.81c0.86b0.75c0.75c0.87c0.77b0.81b0.80c0.80c
Pooled s.e.m.0.0080.0070.0060.0050.0050.0060.0050.0060.0070.0040.0060.0060.0040.0080.0060.0040.005
P-Value0.020.030.010.020.010.010.030.020.020.030.010.010.020.010.010.030.02

Each value is a mean of three replicates (12 birds/replicate).

SFM, sunflower meal; MBM, meat and bone meal; SBM, soybean meal; CM, canola meal; CSM, cottonseed meal; CP, ileal crude-protein digestibility coefficients.

Means within a column with no common letters differ significantly (at P = 0.05).

Table 4 contains protein and amino acid digestibility coefficients of diets combining sorghum and different protein sources. Diets with either sorghum combined with SBM (0.84) or SFM (0.84) had significantly (P < 0.05) higher apparent ileal protein digestibility coefficients than did the rest of the diets. There was no significant difference in the apparent ileal protein digestibility coefficients of sorghum with CM or CSM. The combination of sorghum with MBM had a significantly (P < 0.05) lower protein digestibility coefficient than did all other combinations. Sorghum + SBM had the highest mean amino acid digestibility coefficient (0.87), followed by sorghum combinations with SFM (0.85), CM (0.82), CSM (0.80) and MBM (0.76). These mean amino acid digestibility coefficients were all significantly (P < 0.05) different from each other.

Table 4.Amino acid digestibility coefficients of diets with sorghum in combination with different protein sources.

GroupCPThrValMetIleLeuPheHisLysArgAspSerGluGlyAlaTyrMean
Sorghum + SFM0.84a0.78b0.86a0.88a0.87a0.87a0.89a0.81b0.89b0.91b0.85a0.81b0.91a0.76b0.87a0.85b0.85b
Sorghum + MBM0.73c0.69c0.77c0.80d0.77c0.81c0.81c0.72d0.79e0.81d0.59d0.69e0.79d0.74c0.82c0.78d0.76e
Sorghum + SBM0.84a0.82a0.86a0.88a0.87a0.84b0.88ab0.85a0.94a0.93a0.87a0.86a0.88b0.84a0.84b0.87a0.87a
Sorghum + CM0.79b0.70c0.79b0.87b0.79b0.82c0.87b0.81b0.86c0.93a0.83b0.79d0.87b0.76b0.82bc0.81c0.82c
Sorghum + CSM0.78b0.76b0.79b0.82c0.80b0.82c0.81c0.78c0.82d0.82c0.75c0.78c0.85c0.77b0.81c0.81c0.80d
Pooled s.e.m.0.0080.0070.0040.0030.0050.0060.0050.0060.0020.0030.0040.0070.0040.0060.0060.0050.005
P-Value0.030.0020.010.020.010.020.020.010.010.020.0010.010.010.020.010.020.01

Each value is a mean of three replicates (12 birds/replicate).

SFM, sunflower meal; MBM, meat and bone meal; SBM, soybean meal; CM, canola meal; CSM, cottonseed meal; CP, iIeal crude-protein digestibility coefficients.

Means within a column with no common letters differ significantly (at P = 0.05).

Additivity of AME, protein and amino acid digestibility values

Determined and predicted AME values and ileal protein and amino acid digestibility coefficients of sorghum with different protein sources are presented in Table 5. Predicted values of AME and the digestibility coefficients are based on nutrient values determined for single ingredients and the proportion of these included in the mixed diets. Except for sorghum + SFM, the determined value was greater (P < 0.05) than the predicted value for the other mixed diets. In contrast, no significant (P > 0.05) difference was seen in the measured and predicted ileal digestibility coefficients of protein in any of the mixed diet. Differences between determined and predicted ileal digestibility coefficients of the amino acids were not significant in the sorghum + SFM diet, except for lysine and glycine that were higher (P < 0.05) than predicted. In the diet containing sorghum + SBM, threonine, histidine, lysine, arginine and glycine all had significantly (P < 0.05) higher determined than predicted coefficients. In contrast, leucine and alanine had significantly (P < 0.05) lower digestibility coefficients. In the sorghum + MBM diet, the determined values were greater (P < 0.05) for methionine, isoleucine, lysine, and tyrosine and lower (P < 0.05) for aspartate and glycine than their predicted digestibility coefficients. The determined digestibility coefficient of all the amino acids was greater (P < 0.05) in the sorghum + CM diet except for leucine. Interestingly, the determined digestibility coefficients of most amino acids in the sorghum + CSM diet were lower than predicted, except for threonine, valine, histidine, serine, glycine and tyrosine.

Table 5.Determined (D) and predicted (P) apparent metabolisable energy (AME) values and ileal amino acid digestibility coefficients of sorghum in combination with different protein sources.

Amino acidSorghum + sunflower mealSorghum + meat bone mealSorghum + soybean mealSorghum + canola mealSorghum + cottonseed meal
DPDifferenceDPDifferenceDPDifferenceDPDifferenceDPDifference
Thr0.780.760.020.690.680.000.820.800.02*0.700.660.04*0.760.720.03*
Val0.860.840.020.770.760.010.860.850.000.790.750.05*0.790.790.00
Met0.880.870.010.800.780.02*0.880.89−0.010.870.770.09*0.820.87−0.06*
Ile0.870.850.020.770.750.02*0.870.870.000.790.740.05*0.800.80−0.01
Leu0.870.870.000.810.800.010.840.87−0.03*0.820.800.020.820.85−0.03*
Phe0.890.890.000.810.800.010.880.880.000.870.820.05*0.810.85−0.03*
His0.810.780.030.720.720.010.850.840.02*0.810.750.07*0.780.790.00
Lys0.890.860.03*0.790.740.05*0.940.900.04*0.860.650.21*0.820.82−0.01
Arg0.910.910.000.810.800.010.930.910.02*0.930.860.08*0.820.86−0.04*
Asp0.850.840.020.590.67−0.07*0.870.850.010.830.760.07*0.750.78−0.03*
Ser0.810.790.020.690.70−0.010.860.850.010.790.740.05*0.780.770.01
Glu0.910.900.010.790.790.000.880.89−0.010.870.840.03*0.850.87−0.02*
Gly0.760.720.05*0.740.78−0.04*0.840.810.03*0.760.700.07*0.770.760.01
Ala0.870.870.000.820.820.000.840.87−0.03*0.820.790.03*0.810.84−0.04*
Tyr0.850.840.020.780.750.03*0.870.880.000.810.780.04*0.810.810.00
Mean0.850.830.020.760.77−0.010.870.860.02*0.820.770.05*0.800.81−0.02*
Protein0.840.820.020.730.75−0.010.840.840.000.790.770.020.780.760.02
AME (MJ/kg)14.2414.090.1515.7114.660.90*15.6414.780.66*14.8614.440.42*14.8214.230.58*

Each value is the mean of three replicates (12 birds/replicate).

Predicted values for AME and amino acids were calculated from the respective contributions from each feed ingredient to the mixture.

*Determined versus predicted values are significantly different (at P = 0.05).

Discussion

The performance of broilers fed sorghum-based diets is inferior to birds fed wheat- or maize-based diets and has been attributed to low nutrient availability, especially energy, and the presence of anti-nutritional factors (Selle et al. 2010, 2021). These anti-nutritional factors (phytate, kafirin, and non-tannin phenolics and polyphenols) are thought to reduce nutrient utilisation, including nutrients from other feed ingredients in mixed diets. This may compromise the additivity of nutrients in mixed poultry diets, thus decreasing the overall performance of broilers fed sorghum-based diets. The present study examined the additivity of AME and amino acid digestibility coefficients in sorghum-based diets containing different protein sources. The dry matter, AME, protein and amino acid composition of sorghum and protein sources (SFM, SBM, CSM, CM and MBM) determined in this study are within the range of values reported for Australian poultry feed ingredients (Ravindran et al. 2005; Bryden et al. 2009b) and internationally (Wiltafsky et al. 2016; Li and Wu 2020). The variations in the nutrient composition of feed ingredients among different reports reflect the effect of different cultivars, agronomic practices, growing season, and processing (Ravindran et al. 2005). For example, amino acid concentrations in sorghum increase with an increasing protein content (Ravindran et al. 2005; Li et al. 2006b) and this also has implications for digestibility (Selle et al. 2010).

Apparent ileal protein and amino acid digestibility coefficients of the sorghum and protein sources (SBM, SFM, CM and CSM) used in this study fall within the range of digestibility coefficients for Australian poultry feedstuffs (Bryden et al. 2009b). Lower digestibility coefficients of protein and amino acids in CM and CSM may reflect the presence of anti-nutritive factors (Bell 1993; Świątkiewicz et al. 2016). Moreover, processing conditions during oil extraction from oilseed meals may affect digestibility of amino acids (Dale 1996). The overall digestibility of amino acids was lower in MBM than in the other protein feedstuffs, except CM. Meat and bone meal has a variable raw ingredient composition and contains varying amounts of collagen, cartilage, tendons and bone and is subject to significant heat during rendering (Skurray 1974; Wang and Parsons 1998; Ravindran et al. 2002). Collagen has an imbalance in amino acids because it is deficient in essential amino acids and is poorly digested (Ravindran et al. 2005).

Mixed diets of sorghum with either SFM, MBM, SBM, CM or CSM were tested for the additivity of AME content and amino acid digestibility coefficients determined with the individual ingredients (Table 5). Except for sorghum + SFM, the determined AME values for the other dietary combinations were significantly greater than predicted. Despite the wide use of AME values in feed formulation, there are few studies that have compared the additivity of different feed ingredients. Imbeah et al. (1988) and Hong et al. (2001) compared values in pigs and ducks respectively, but only observed numerically different values. The reasons for the differences in the current study are unclear but may relate to species or more probably the anti-nutritional factors present in the different ingredients (Mateos et al. 2019). Moreover, Wu et al. (2020), after their extensive review, questioned the assumption that AME values of individual feed ingredients are usually additive.

Apparent ileal digestibility coefficients of protein for all diets were additive and similar to those reported previously (Imbeah et al. 1988; Furuya and Kaji 1991; Angkanaporn et al. 1996), except for sorghum + cottonseed meal. However, significant differences were found (Table 5) between the determined and the predicted digestibilities for amino acids in the mixed diets, indicating associative effects. In most instances, determined values were greater than predicted, indicating that a surplus of amino acids would not occur in a formulated feed. For the combinations of sorghum with SFM, MBM and SBM, 2, 4 and 6 amino acids respectively, were under-predicted. However, in the case of sorghum + CM, all determined amino acid digestibility coefficients were more than predicted. In contrast with sorghum + CSM, values for eight amino acids were over-predicted. It was of concern to note that lysine was usually the amino acid most adversely effected. The anti-nutritional factors described above for sorghum would have contributed to the associative effects observed in this study. However, it is important to note that all the plant-protein sources used in the study also contain deleterious anti-nutritional factors (see SFM, Senkoylu and Dale 1999; Waititu et al. 2018; CM, Bell 1993; Khajali and Slominski 2012); CSM, Świątkiewicz et al. 2016; Abdallh et al. 2020), whereas MBM has a variable raw ingredient composition and high ash content (Shirley and Parsons 2000, 2001). Although SBM is the protein source of choice in poultry diets it can vary in quality and contain anti-nutritional factors (Ravindran et al. 2014; Dunmire et al. 2023). Associative effects have also been reported for some amino acids in pigs and ducks when fed a mixture of barley, canola and soybean meal (Imbeah et al. 1988; Hong et al. 2001). Importantly, the mechanisms of how most anti-nutritional factors perturb nutrient utilisation is well described, but possible interactions resulting in either positive or negative associate effects on nutrient utilisation have not been delineated.

Finally, it can be deduced from the present findings that positive and negative interactions are likely to occur among dietary ingredients, and these will have implications for both energy and protein utilisation. Nevertheless, AME and amino acid digestibility values determined for single ingredients can be used with caution to predict values in mixed diets. To increase the accuracy of predictions, a number of studies have shown that correcting values for both energy (Dale and Fuller 1980; Wu et al. 2020) and amino acids (Kong and Adeola 2013; Xue et al. 2014; Cowieson et al. 2019; Osho et al. 2019) for endogenous losses will mitigate these interactions or make values ‘more additive’ (Parsons 2020).

Data availability

Data will be made available upon reasonable request to the corresponding author.

Conflicts of interest

WLB is a member of the Editorial Board of Animal Production Science but was not involved in the review and editorial process for this paper. The authors have no further conflicts of interest to declare.

Declaration of funding

The study reported in this paper received no specific funding.

Acknowledgements

We thank the postgraduate students who assisted with the conduct of the digestibility assays.

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