Effects of dietary fibre level and body weight of pigs on nutrient digestibility and available energy in high-fibre diet based on wheat bran or sunflower meal.

The objectives of this study were (a) to investigate the effect of body weight (BW) on available energy in fibre-rich diets containing two NDF levels; and (b) to evaluate the effect of fibre type and NDF level on AA digestibility. In Exp. 1, barrows (24 at 33.4 ± 1.1 kg; 24 at 86.8 ± 3.3 kg) were randomly allotted to 4 diets containing a high protein basal (HPB), a low protein basal (LPB), 70% HPB + 30% wheat bran (WB) (HPB-WB) and 70% LPB + 30% sunflower meal (SFM) (LPB-SFM). In Exp. 2, barrows (24 at 33.5 ± 1.8 kg; 24 at 87.0 ± 3.8 kg) were randomly allotted to 4 diets containing no SFM with 12% NDF (SFM0LF), no SFM with 16% NDF (SFM0HF), 24% SFM with 12% NDF (SFM24LF) and 24% SFM with 16% NDF (SFM24HF). In Exp. 3, twelve barrows (35.5 ± 3.4 kg) fitted with T-cannulas were allotted to two 6 × 4 Youden square design with 6 diets (4 same diets as in Exp. 2 and 2 nitrogen-free diets). The concentration of DE, ME and ATTD of GE, CP, NDF and ADF in diets was greater (p < .01) when fed to 90 kg pigs compared with 30 kg pigs. The ME in ingredients was not affected by BW. The ATTD of NDF was negatively correlated with the CF (r = -.98; p < .01), ADF (r = -.99; p < .01) and ADL content (r = -.96; p < .01). The ME of diets was negatively correlated with the ATTD of CF (r = -.98; p < .01). The addition of SFM increased the standardized ileal digestibility (SID) of Met (p < .05). In conclusion, diets rich in fibre had different nutritional values at different pig weight stages. The AA digestibility depends mainly on chemical composition of diets.

Metabolizable energy requirement for maintenance estimated by regression analysis of body weight gain or metabolizable energy intake in growing pigs

Objective: Feed energy required for pigs is first prioritized to meet maintenance costs. Additional energy intake in excess of the energy requirement for maintenance is retained as protein and fat in the body, leading to weight gain. The objective of this study was to estimate the ME requirements for maintenance (MEm) by regressing body weight gain against ME intake (MEI) in growing pigs. Methods: Thirty-six growing pigs (26.3 ± 1.7 kg) were allotted to 1 of 6 treatments with 6 replicates per treatment in a randomized complete block design. Treatments were 6 feeding levels which were calculated as 50, 60, 70, 80, 90 or 100% of the estimated ad libitum MEI (2,400 kJ/kg BW0.60·d). All pigs were individually housed in metabolism crates for 30 d and weighed every 5 d. Moreover, each pig from each treatment was placed in the open-circuit respiration chambers to measure heat production (HP) and energy retained as protein (REp) and fat (REf) every 5 d. Serum biochemical parameters of pigs were analyzed at the end of the experiment. Results: The ADG and HP as well as the REp and REf linearly increased with increasing feed intake (p < 0.010). ß-hydroxybutyrate (BHBA) concentration of serum tended to increase with increasing feed intake (p = 0.080). The regression equations of MEI on ADG were MEI, kJ/kg BW0.60·d = 1.88 × ADG, g/d + 782 (R2=0.86) and MEm was estimated at 782 kJ/kg BW0.60·d. Protein retention of growing pigs would be positive while REf would be negative at this feeding level via regression equations of REp and REf on MEI. Conclusion: The MEm was estimated at 782 kJ/kg BW0.60·d in current experiment. Furthermore, growing pigs will deposit protein and oxidize fat if provided feed at the estimated maintenance level.

Effect of inclusion level and adaptation duration on digestible energy and nutrient digestibility in palm kernel meal fed to growing-finishing pigs.

OBJECTIVE: An experiment was conducted to evaluate effects of inclusion level of palm kernel meal (PKM) and adaptation duration on the digestible energy (DE) and apparent total tract digestibility (ATTD) of chemical constituents in diets fed to growing-finishing pigs. METHODS: Thirty crossbred barrows (Duroc×Landrace×Large White) with an average initial body weight of 85.0±2.1 kg were fed 5 diets in a completely randomized design. The diets included a corn-soybean meal basal diet and 4 additional diets in which corn and soybean meal were partly replaced by 10%, 20%, 30%, or 40% PKM. After 7 d of adaptation to the experimental diets, feces were collected from d 8 to 12, d 15 to 19, d 22 to 26, and d 29 to 33, respectively. RESULTS: The DE and ATTD of gross energy (GE), dry matter (DM), ash, organic matter (OM), neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) in diets decreased linearly as the dietary PKM increased within each adaptation duration (p< 0.01). Diet containing 19.5% PKM had less DE value and ATTD of all detected items compared with other diets when fed to pigs for 14 days (p<0.05). The ATTD of CP in PKM calculated by 19.5% and 39.0% linearly increased as adaptation duration prolonged from 7 to 28 days (p<0 .01). CONCLUSION: Inclusion level of PKM and adaptation duration had an interactive effect on DE and the ATTD of GE, DM, OM, and CP (p<0.01 or 0.05) but ash, NDF, and ADF in diet (p> 0.05). Considering a stable determination, 21 days of adaptation to a diet containing 19.5% PKM is needed in pigs and a longer adaptation time is recommended as dietary PKM increases.

Comparative digestibility of nutrients and amino acids in high-fiber diets fed to crossbred barrows of Duroc boars crossed with Berkshire×Jiaxing and Landrace×Yorkshire.

OBJECTIVE: This experiment was conducted to determine the differences in the apparent ileal (AID) and total tract digestibility (ATTD) of nutrients and indispensable amino acids (IAA) in high-fiber diets with wheat middlings, rice bran or alfalfa meal fed to Duroc×(Landrace× Yorkshire) (DLY) and Duroc× (Berkshire×Jiaxing) (DBJ) growing barrows. METHODS: Eighteen DLY and 18 DBJ growing barrows were randomly allotted to a 2×3 factorial arrangement involving 2 crossbreeds and 3 high-fiber diets. The experiment lasted 15 d with 10 d for diets adaptation, 3 d for feces collection and 2 d for digesta collection. Three diets were based on corn and soybean meal with 25% wheat middlings, rice bran and alfalfa meal respectively. RESULTS: DBJ had a greater (p<0.05) AID of isoleucine, leucine, lysine, phenylalanine and valine and a lower (p<0.05) AID of methionine than DLY. The hindgut disappearance of acid detergent fiber for DBJ was greater (p<0.05) than DLY. The ATTD of gross energy, dry matter, organic matter, neutral detergent fiber and acid detergent fiber in wheat middlings diet were greater (p<0.05) than in rice bran and alfalfa meal diets. The hindgut disappearance of neutral detergent fiber and acid detergent fiber in wheat middlings diet or rice bran diet were the highest or lowest (p<0.05), and those of alfalfa meal diet were the middle. Barrows fed rice bran diet had a greater (p<0.05) hindgut disappearance of gross energy, dry matter and organic matter and lower hindgut disappearance of neutral detergent fiber and acid detergent fiber than barrows fed alfalfa meal diet. CONCLUSION: DBJ growing barrows showed a significant higher digestibility of fiber in the hindgut and most IAA in the small intestine compared with DLY barrows. The digestibilities of chemical constituents and IAA were affected by the diets formulated with different fiber sources.

Methodology effects on determining the energy concentration and the apparent total tract digestibility of components in diets fed to growing pigs.

OBJECTIVE: An experiment was conducted to investigate the effects of different diet formulations: F1 (Two complicated basal diets containing different crude protein levels plus tested feedstuff) vs F2 (A simple corn soybean meal [SBM] basal diet plus tested feedstuff) combined with total collection (TC) or chromic oxide (Cr2O3) marker or acid-insoluble ash (AIA) marker method, and freeze-dry or oven-dry (OD) technique on estimation of nutrient digestibility in diets fed to growing pigs. METHODS: In F1, twelve barrows were allocated to two 6×4 Youden Squares. The treatment diets included a high protein basal (HPB) diet, a low protein basal (LPB) diet, a corn diet and a wheat bran (WB) diet formulated based on the HPB diet, and a SBM diet and a rapeseed meal (RSM) diet formulated based on the LPB diet. In F2, eight barrows were allocated to two 4×4 Latin Squares. The treatment diets included a corn basal diet, a SBM basal diet formulated based on the corn diet, and a WB diet and a RSM diet formulated based on the SBM diet. RESULTS: Concentration of digestible (DE) and metabolizable energy (ME), and the apparent total tract digestibility of gross energy, ash, neutral detergent fibre, and acid detergent fibre determined by Cr2O3 marker method were greater than those determined by TC and AIA marker methods in HPB, LPB, and RSM diets formulated by F1 and in corn diet formulated by F2 (p<0.05). The DE values in WB and both DE and ME values in SBM and RSM estimated using F1 were greater than those estimated using F2 (p<0.05). CONCLUSION: From the accuracy aspect, the AIA marker or TC method combined with OD technique is recommended for determining the energy concentration and nutrient digestibility of components in diets fed to growing pigs.

Net energy content of rice bran, corn germ meal, corn gluten feed, peanut meal, and sunflower meal in growing pigs.

OBJECTIVE: The objective of this experiment was to determine the net energy (NE) content of full-fat rice bran (FFRB), corn germ meal (CGM), corn gluten feed (CGF), solvent-extracted peanut meal (PNM), and dehulled sunflower meal (SFM) fed to growing pigs using indirect calorimetry or published prediction equations. METHODS: Twelve growing barrows with an average initial body weight (BW) of 32.4±3.3 kg were allotted to a replicated 3×6 Youden square design with 3 successive periods and 6 diets. During each period, pigs were individually housed in metabolism crates for 16 d, which included 7 days for adaptation. On d 8, the pigs were transferred to the respiration chambers and fed one of the 6 diets at 2.0 MJ metabolizable energy (ME)/kg BW0.6/d. Total feces and urine were collected and daily heat production was measured from d 9 to d 13. On d 14 and d15, pigs were fed at their maintenance energy requirement level. On the last day pigs were fasted and fasting heat production was measured. RESULTS: The NE of FFRB, CGM, CGF, PNM, and SFM measured by indirect calorimetry method was 12.33, 8.75, 7.51, 10.79, and 6.49 MJ/kg dry matter (DM), respectively. The NE/ME ratios ranged from 67.2% (SFM) to 78.5% (CGF). The NE values for the 5 ingredients calculated according to the prediction equations were 12.22, 8.55, 6.79, 10.51, and 6.17 MJ/kg DM, respectively. CONCLUSION: The NE values were the highest for FFRB and PNM and the lowest in the corn co-products and SFM. The average NE of the 5 ingredients measured by indirect calorimetry method in the current study was greater than values predicted from NE prediction equations (0.32 MJ/kg DM).

Effects of variety and storage duration on the nutrient digestibility and the digestible and metabolisable energy content of maize fed to growing pigs.

The objective of this research was to determine the effects of variety and storage duration on the nutrient digestibility and the digestible (DE) and metabolisable (ME) energy content in maize when fed to growing pigs. Four maize varieties (LS1, LS2, LS3 and LS4) were hand-harvested from the same growing area in China in early October of 2012. The samples were sun dried to about 14% moisture content and then stored in the warehouse of the Fengning Pig Experiment Base at China Agricultural University for 0, 3 or 10 months. Twenty-four barrows of about 33 kg body weight were used and allotted to a completely randomised block design with four diets and six replicate pigs per diet. Pigs were individually housed in metabolic crates. The four experimental diets were formulated by mixing 96.8% of each variety of maize with 3.2% vitamins and minerals. A 5-day collection period followed a 7-day diet acclimation period. The results indicated that the DE and ME contents of maize and the apparent total tract digestibility (ATTD) of organic matter (OM), dry matter, gross energy (GE), neutral detergent fibre, acid detergent fibre (ADF), crude protein (CP) and ether extract (EE) were significantly (p < 0.05) influenced by maize variety and storage duration. With an extension of storage duration from 0 to 10 months, the DE and ME of maize and the ATTD of OM, GE, ADF, CP and EE changed in a quadratic manner (p < 0.05), and 3 months of storage exceeded 0 months of storage by 1.84%, 1.43%, 0.31%, 0.32%, 15.37%, 2.11% and 5.02%, respectively. The DE, ME of maize and the ATTD of OM, GE, ADF, CP and EE decreased by 3.67%, 6.00%, 0.97%, 1.40%, 30.54%, 3.92% and 20.93%, respectively, at 10 months of storage compared to 3 months of storage. No interaction was observed between maize variety and storage duration in DE and ME contents in maize. In conclusion, under the conditions of this study, most of the nutrient digestibility and the DE and ME contents of maize increased from 0 to 3 months and decreased from 3 to 10 months.

Oligosaccharides are a key factor in prediction of amino acid digestibility in soybean meal of different origins when fed to growing pigs.

OBJECTIVE: The objective of this experiment was to determine apparent ileal digestibility (AID) and standardized ileal digestibility (SID) of crude protein (CP) and amino acid (AA) in 15 sources of soybean meal (SBM) produced from soybeans from different countries and subsequently to establish equations for predicting the AID and SID in SBM based on their chemical composition. METHODS: Eighteen barrows (57.9±6.1 kg) fitted with a simple T-cannula were allotted into three 6×6 Latin square designs. Each period comprised a 6-d adaption period followed by a 2-d collection of ileal digesta. The 15 test diets included SBM as a sole source of AA in the diet. Another nitrogen-free diet was used to measure basal endogenous losses of CP and AA. Chromic oxide (0.3%) was used as an inert marker in each diet. RESULTS: The AID of lysine in SBM from China and USA tended to be greater than in SBM from Brazil (p<0.10). The SID of valine and proline in SBM from China was greater than in SBM from Brazil (p<0.05). The SID of lysine, threonine, cysteine and glycine in SBM from China tended to be greater than in SBM from Brazil (p<0.10). From a stepwise regression analysis, a series of AID and SID prediction equations were generated. The best fit equations for lysine in SBM were: AID lysine = 1.16 sucrose-1.81 raffinose+82.10 (R2 = 0.69, p<0.01) and SID lysine = 1.14 sucrose-1.93 raffinose-0.99 ether extract (EE)+85.26 (R2 = 0.77, p<0.01). CONCLUSION: It was concluded that under the conditions of this experiment, the oligosaccharides (such as sucrose and raffinose) can be used to predict the AID and SID of AA in SBM with reasonable accuracy.

Prediction of digestible and metabolisable energy in soybean meals produced from soybeans of different origins fed to growing pigs.

The objective of this experiment was to determine the digestible energy (DE) and metabolisable energy (ME) in 22 sources of soybean meal (SBM) produced from soybeans from different countries and subsequently to establish equations for predicting the DE and ME in SBM based on their chemical composition. The 22 sources of SBM were all processed in Chinese crushing plants, but the soybeans used originated from China (n=6), the US (n=6), Brazil (n=7) or Argentina (n=3). The basal diet was a corn-based diet and 22 additional diets were formulated by mixing corn and 24.3% of each source of SBM. The average DE and ME in SBM from China, the US, Brazil and Argentina were 15.73, 15.93, 15.64 and 15.90 MJ/kg and 15.10, 15.31, 14.97 and 15.42 MJ/kg, respectively, and no differences among countries were observed. From a stepwise regression analysis, a series of DE and ME prediction equations were generated. The best-fit equations for SBM were DE=38.44-0.43 crude fibre -0.98 gross energy +0.11 acid detergent fibre (R2=0.67, p<0.01) and ME=2.74+0.97 DE -0.06 crude protein (R2=0.79, p<0.01). In conclusion, there were no differences in the DE and ME of SBM among the different soybean sources used in this experiment. The DE and ME of SBM of different origin can be predicted based on their chemical composition when fed to growing pigs.

Oils with different degree of saturation: effects on ileal digestibility of fat and corresponding additivity and bacterial community in growing pigs.

BACKGROUND: Oils are important sources of energy in pig diets. The combination of oils with different degree of saturation contributes to improve the utilization efficiency of the mixed oils and may reduce the cost of oil supplemented. An experiment was conducted to evaluate the effects of oils with different degree of saturation on the fat digestibility and corresponding additivity and bacterial community in growing pigs. METHODS: Eighteen crossbred (Duroc × Landrace × Yorkshire) barrows (initial body weight: 29.3 ± 2.8 kg) were surgically fitted with a T-cannula in the distal ileum. The experimental diets included a fat-free basal diet and 5 oil-added diets. The 5 oil-added diets were formulated by adding 6% oil with different ratio of unsaturated to saturated fatty acids (U:S) to the basal diet. The 5 oils were palm oil (U:S = 1.2), canola oil (U:S = 12.0), and palm oil and canola oil were mixed in different proportions to prepare a combination of U:S of 2.5, 3.5 and 4.5, respectively. RESULTS: The apparent and standardized ileal digestibility (AID and SID) of fat and fatty acids increased linearly (P < 0.05) as the U:S of dietary oils increased except for SID of fat and C18:2. The AID and SID of fat and fatty acids differed among the dietary treatments (P < 0.05) except for SID of unsaturated fatty acids (UFA) and C18:2. Fitted one-slope broken-line analyses for the SID of fat, saturated fatty acids (SFA) and UFA indicated that the breakpoint for U:S of oil was 4.14 (R2 = 0.89, P < 0.01), 2.91 (R2 = 0.98, P < 0.01) and 3.84 (R2 = 0.85, P < 0.01), respectively. The determined SID of fat, C18:1, C18:2 and UFA in the mixtures was not different from the calculated SID of fat, C18:1, C18:2 and UFA. However, the determined SID of C16:0, C18:0 and SFA in the mixtures were greater than the calculated SID values (P < 0.05). The abundance of Romboutsia and Turicibacter in pigs fed diet containing palm oil was greater than that in rapeseed oil treatment group, and the two bacteria were negatively correlated with SID of C16:0, C18:0 and SFA (P < 0.05). CONCLUSIONS: The optimal U:S for improving the utilization efficiency of mixed oil was 4.14. The SID of fat and UFA for palm oil and canola oil were additive in growing pigs, whereas the SID of SFA in the mixture of two oils was greater than the sum of the values of pure oils. Differences in fat digestibility caused by oils differing in degree of saturation has a significant impact on bacterial community in the foregut.

T Cells Development Is Different between Thymus from Normal and Intrauterine Growth Restricted Pig Fetus at Different Gestational Stage.

This experiment was conducted to evaluate the development of T cells in intrauterine growth retarded (IUGR) piglets at different gestational stages, and tentatively explore the relationship between T cells development and the Notch signaling pathway. A total of 18 crossbred (Landrace×Large white) primiparous sows were mated at similar weights and estruses and euthanized at d 60, 90 and 110 of gestation with six replicates for each time point. One IUGR and one normal fetus were picked from each litter. The T-cell subsets, mRNA expression of Delta-like1, Delta-like4, Jagged1, and Notch2 genes in the thymus were investigated. Compared to normal piglets, CD3(+)CD4(-)CD8(+) cells in IUGR fetuses at d 90 was 0.13% lower (p<0.05). At d 110 of gestation CD8(+) T cells in IUGR fetuses was 0.19% lower (p<0.05). The percentage of CD8(+) T cells was 3.14% lower (p<0.05) of the total T cells in IUGR pigs at d 60. The abundance of Notch2 and Delta-like4 mRNA at d 110 was 20.93% higher and 0.77% (p<0.05) lower, and Delta-like1 mRNA at d 90 was 0.19% (p<0.05) higher compared to normal pigs. These results suggested that normal fetuses had a greater proportion of T-cell subsets at earlier gestation periods, and the Notch signaling pathway was likely partially responsible for these differences to some degree.

Net energy and its establishment of prediction equations for wheat bran in growing pigs.

OBJECTIVE: The objective of this experiment was to determine the net energy (NE) value of 6 wheat bran and 1 wheat shorts by indirect calorimetry and establish the NE prediction equations of wheat bran fed to growing barrows. METHODS: Forty-eight growing barrows (28.5±2.4 kg body weight) were allotted in a completely randomized design to 8 dietary treatments that included a corn-soybean meal basal diet, 6 wheat bran diets and 1 wheat shorts diet. The inclusion level of wheat bran or wheat shorts in diets is 30%. RESULTS: The addition of wheat bran reduced the apparent total tract digestibility (ATTD) of nutrients (p<0.05). The ATTD of gross energy, crude protein (CP) and dry matter (DM) in the wheat shorts were greater than that in the wheat bran. Addition of wheat bran or wheat shorts had no effect on total heat production and fasting heat production. The NE of wheat bran was negatively correlated with neutral detergent fiber (r = -0.84; p<0.05) and acid detergent fiber (r = -0.83; p<0.05), while it was positively correlated with CP (r = 0.92; p<0.01). The NE values of wheat bran ranged from 6.79 to 8.15 MJ/kg DM, and the NE value of wheat shorts was 12.47 MJ/kg DM. The ratio of NE to metabolizable energy for wheat bran fed to growing pigs was from 66.0% to 71.7%, whereas the value for wheat shorts was 83.7%. CONCLUSION: The NE values of wheat bran ranged from 6.79 to 8.15 MJ/kg DM, and the NE value of wheat shorts was 12.47 MJ/kg DM. The NE value of wheat bran can be well predicted based on energy content and proximate analysis.

Modeling net energy partition patterns of growing-finishing pigs using nonlinear regression and artificial neural networks.

The objectives of this study were to evaluate the net energy (NE) partition patterns of growing-finishing pigs at different growing stages and to develop the corresponding prediction models using nonlinear regression (NLR) and artificial neural networks (ANN). Twenty-four pigs with an initial body weight (BW) of ~30 kg were kept in metabolic cages and fed ad libitum and were moved into six respiration chambers in turns until ~90 kg. The NE partition patterns, i.e., NE for maintenance (NEm), NE retained as protein (NEp), and NE retained as lipid (NEl), were calculated based on indirect calorimetry and nitrogen balance techniques. The energy balance data collected through the animal trial was then randomly split into a training data set containing 75% of the samples and a testing data set containing the remaining 25% of the samples. The NLR models and a series of ANN models were established on the training data set to predict the metabolizable energy intake, NE intake, NEm, NEp, and NEl of pigs. The best-fitted ANN models were selected by 5-fold cross-validation in the training data set. The prediction performance of the best-fitted NLR and ANN models were compared on the testing data set. The results showed that the average NE intakes of pigs were 17.71, 23.25, 24.56, and 28.96 MJ/d in 30 to 45 kg, 45 to 60 kg, 60 to 75 kg, and 75 to 90 kg, respectively. The NEm and NEl (MJ/d) kept increasing as BW increased from 30 kg to 90 kg, while the NEp increased to its maximum value and then kept in a certain range of 4.64 to 4.88 MJ/d. The proportion of NEm for pigs at 30 to 90 kg stayed within the range of 42.0% to 48.6%, while the proportion of NEl kept increasing. For the prediction models built based on the animal trial, ANN models exhibited better performance than NLR models for all the target outputs. In conclusion, NE partition patterns changed in different growth stages of pigs, and ANN models are more flexible and powerful than NLR models in predicting the NE partition patterns of growing-finishing pigs.

Net energy (NE) is the most refined energy system in animal nutrition, and understanding the NE partition patterns of pigs can help us to develop suitable feeding strategies to improve the growth performance and carcass traits of pigs. However, it is time-consuming, laborious, and expensive to directly measure the NE; thus, establishing a predicted model is more efficient. In research on the energy nutrition of pigs, regression is the most used tool to develop models, but little literature has focused on the application of artificial neural networks (ANN) models. In this study, we measured the NE partition patterns of pigs, and our results show that the proportion of NE for maintenance stayed within the range of 42.0% to 48.6%, while the proportion of NE retained as a lipid kept increasing as pig grows (pigs body weight: 30 to 90 kg). The value of NE retained as protein increased to its maximum value and then stayed in a certain range of 4.64 to 4.88 MJ/d, but with a decreased proportion of NE intake. Additionally, we applied the corresponding nonlinear regression (NLR) and ANN models and made comparisons between them. The ANN models exhibited better performance than NLR models for all the target outputs.

Determination and prediction of the available energy and amino acids digestibility of full-fat soybean fed to growing pigs.

Two experiments were conducted to determine the digestible energy and metabolizable energy contents, as well as the apparent ileal digestibility and standardized ileal digestibility of amino acids in full-fat soybean fed to growing pigs. Ten full-fat soybean samples were collected from different areas in China and used in two experiments in this study. In Exp. 1, 66 growing pigs (initial body weight = 18.48 ± 1.2 kg) were randomly allotted to 1 of 11 diets (n = 6) including a corn basal diet and 10 experimental diets formulated by replacing the corn with 30% full-fat soybean. In Exp. 2, 11 growing pigs (initial body weight = 50.45 ± 3.2 kg) were surgically equipped with a T-cannula in the distal ileum and arranged in a 6 × 11 Youden square design with 11 diets and 6 periods. The diets included an N-free diet based on cornstarch and sucrose and 10 experimental diets formulated with full-fat soybeans as the sole source of amino acids. Chromic oxide was added into the diets as an indigestible maker to calculate the digestibility of the amino acids. Results showed that there was considerable variation in neutral detergent fiber, acid detergent fiber, and trypsin inhibitor contents in the 10 full-fat soybean samples with a coefficient of variation greater than 10%. On a dry matter basis, the averaged digestible energy and metabolizable energy values in the 10 full-fat soybean samples were 4,855 and 4,555 kcal/kg, respectively, both were positively correlated with the ether extract content. The best-fitted prediction equations for digestible energy and metabolizable energy of full-fat soybean were: digestible energy, kcal/kg = 3,472 + 94.87 × ether extract - 97.63 × ash (R2 = 0.91); metabolizable energy, kcal/kg = 3,443 + 65.11 × ether extract - 36.84 × trypsin inhibitor (R2 = 0.91). In addition, all full-fat soybean samples showed high apparent ileal digestibility and standardized ileal digestibility values in amino acids and were all within the range of previously published values. Those values significantly varied among different samples (P < 0.05) for most amino acids, except for glycine and proline. In conclusion, full-fat soybean is a high-quality protein ingredient with high ileal digestibility of amino acids when fed to growing pigs, and the metabolizable energy value of full-fat soybean could be predicted based on its ether extract and trypsin inhibitor contents.

Full-fat soybean is an excellent protein source supplied in swine diets, especially in weaned and growing stages. However, the high price limits its utilization in practice, so it is vital to accurately evaluate the available energy and digestible amino acids contents in full-fat soybean to better formulate a least-cost diet. Ten full-fat soybean samples were collected from different areas in China, and two experiments were conducted to evaluate the energy concentration and amino acids digestibility of full-fat soybean and to establish the corresponding prediction equations. The averaged digestible and metabolizable energy of FFSB were 4,855 and 4,555 kcal/kg (dry matter basis), and the best-fitted prediction equations for digestible energy and metabolizable energy of full-fat soybean were: digestible energy, kcal/kg = 3,472 + 94.87 × ether extract − 97.63 × ash; metabolizable energy, kcal/kg = 3,443 + 65.11 × ether extract − 36.84 × trypsin inhibitor. Except for glycine and proline, the digestibility of other amino acids significantly varied among 10 full-fat soybean samples but all were within the range of previously published values. In addition, all the amino acids exhibited high digestibility, indicating that full-fat soybean is a protein ingredient with high quality.

Mitigating environmental impacts using net energy system in feed formulation in China's pig production.

As the world's largest pork producer, China is facing substantial environmental pressures caused by pig production and the relevant feed production. The net energy (NE) system is promoted as a new evaluation method to evaluate energy content in feed and energy requirements of pigs, but its application lacks of comprehensive and comparative evaluation from the environmental perspective. To identify influence factors and to develop mitigation strategies, the carbon and nitrogen footprints and land use (LU) of pigs (25-120 kg) in China were explored through scenario analysis and cradle-to-farm gate life cycle assessment (LCA). Functional unit (FU) was defined as 1 kg of live weight increase in pig. Among all the procedures of pig production, feed crop production and manure management were the principal contributors to the greenhouse gas (GHG) and nitrogen emissions. As for the carbon footprint, the GHG emissions ranged from 2.37 to 2.55 kg CO2-eq. FU-1 for scenarios using the NE system, 2 % lower than that of the metabolizable energy (ME) system. Cottonseed meal-based scenario generated the lowest GHG emissions, and anaerobic digestion achieved the same effects as other manure management methods. As for the nitrogen footprint, reactive nitrogen (Nr) emissions ranged from 53.4 to 66.2 g Nr FU-1 for scenarios using the NE system, 4 % lower than that of the ME system. Peanut-based scenario won the lowest Nr losses. Moreover, arable LU ranged from 4.63 to 5.85 m2 FU-1 for scenarios using the NE system, 4 % lower than that of the ME system, and economic advantage by using the NE system was also proved. Sensitivity analysis and data quality assessment were conducted to quantify the uncertainties of the above models. In conclusion, the application of the NE system in feed formulation was an effective strategy to improve the environmental sustainability of China's pig production.

Metabolomic analysis reveals differences in umbilical vein plasma metabolites between normal and growth-restricted fetal pigs during late gestation.

Intrauterine growth restriction (IUGR) remains a major problem for both human health and animal production due to its association with high rates of neonatal morbidity and mortality, low efficiency of food utilization, permanent adverse effects on postnatal growth and development, and long-term health and productivity of the offspring. However, the underlying mechanisms for IUGR are largely unknown. In this study, one IUGR fetus and one normal body weight (NBW) fetus were obtained from each of 9 gilts at each of 2 gestational ages (d 90 and 110). Metabolomes of umbilical vein plasma in IUGR and NBW fetuses were determined by MS, while hormones, amino acids, and related metabolites in maternal and fetal plasma were measured using assay kits and chromatographic methods. Metabolites (including glucose, urea, ammonia, amino acids, and lipids) in umbilical vein plasma exhibited a cluster of differences between IUGR and NBW fetuses on d 90 and 110 of gestation. These changes in the IUGR group are associated with disorders of nutrient and energy metabolism as well as endocrine imbalances, which may contribute to the retardation of fetal growth and development. The findings help provide information regarding potential mechanisms responsible for IUGR in swine and also have important implications for the design of effective strategies to prevent, diagnose, and treat IUGR in other mammalian species, including humans.

Effects of Replacing Fishmeal and Soybean Protein Concentrate with Degossypolized Cottonseed Protein in Diets on Growth Performance, Nutrient Digestibility, Intestinal Morphology, Cecum Microbiome and Fermentation of Weaned Piglets.

The inclusion of high-quality proteins is commonly used in swine production, especially in weaned pigs. Our research investigated the effects of replacing fishmeal (FM) and soybean protein concentrate (SPC) with degossypolized cottonseed protein (DCP) on the growth performance, nutrient digestibility, intestinal morphology, cecum microbiota and fermentation in weaned pigs. A total of 90 pigs were used in a 4-week trial. Pigs were randomly assigned to three dietary treatments (initial BW 8.06 ± 0.26 kg; six pigs per pen; five pens per treatment), including a basal diet group (CON) with a 6% SPC and 6% FM; two experimental diets group (SPCr and FMr) were formulated by replacing SPC or FM with 6% DCP, respectively. There were no differences in growth performance and diarrhea rate among three treatments except for the ADFI during day 14 to day 28. Using the DCP to replace FM would weaken the jejunum morphology and decrease the nutrient digestibility of pigs during day 0 to day 14. However, replacing FM with DCP can improve the community structure of cecum microbiota, and may relieve these negative effects. In conclusion, DCP can be used as a cost-effective alternative protein supplement.

Predicting the growth performance of growing-finishing pigs based on net energy and digestible lysine intake using multiple regression and artificial neural networks models.

BACKGROUNDS: Evaluating the growth performance of pigs in real-time is laborious and expensive, thus mathematical models based on easily accessible variables are developed. Multiple regression (MR) is the most widely used tool to build prediction models in swine nutrition, while the artificial neural networks (ANN) model is reported to be more accurate than MR model in prediction performance. Therefore, the potential of ANN models in predicting the growth performance of pigs was evaluated and compared with MR models in this study. RESULTS: Body weight (BW), net energy (NE) intake, standardized ileal digestible lysine (SID Lys) intake, and their quadratic terms were selected as input variables to predict ADG and F/G among 10 candidate variables. In the training phase, MR models showed high accuracy in both ADG and F/G prediction (R2ADG = 0.929, R2F/G = 0.886) while ANN models with 4, 6 neurons and radial basis activation function yielded the best performance in ADG and F/G prediction (R2ADG = 0.964, R2F/G = 0.932). In the testing phase, these ANN models showed better accuracy in ADG prediction (CCC: 0.976 vs. 0.861, R2: 0.951 vs. 0.584), and F/G prediction (CCC: 0.952 vs. 0.900, R2: 0.905 vs. 0.821) compared with the MR models. Meanwhile, the "over-fitting" occurred in MR models but not in ANN models. On validation data from the animal trial, ANN models exhibited superiority over MR models in both ADG and F/G prediction (P < 0.01). Moreover, the growth stages have a significant effect on the prediction accuracy of the models. CONCLUSION: Body weight, NE intake and SID Lys intake can be used as input variables to predict the growth performance of growing-finishing pigs, with trained ANN models are more flexible and accurate than MR models. Therefore, it is promising to use ANN models in related swine nutrition studies in the future.

Effects of dietary oil sources and fat extraction methods on apparent and standardized ileal digestibility of fat and fatty acids in growing pigs.

BACKGROUND: There is a lack of data for the standardized ileal digestibility (SID) of fat and fatty acids in national feed databases. In addition, it is important to specify the procedures used for fat analyses. Therefore, an experiment was conducted to 1) determine the apparent ileal digestibility (AID) and SID of fat and fatty acids in ten different oil sources for growing pigs and to develop prediction equations for SID of fat based on fatty acid composition; and 2) compare the effect of the fat extraction methods on the calculated values for endogenous loss and digestibility of fat. METHODS: Twenty-two barrows (initial body weight: 32.1 ± 2.3 kg) were surgically fitted with a T-cannula in the distal ileum, and allotted to 1 of 11 experimental diets in a 4-period Youden Square design. A fat-free diet was formulated using cornstarch, soy protein isolate and sucrose. Ten oil-added diets were formulated by adding 6% of dietary oil sources to the fat-free diet at the expense of cornstarch. All diets contained 26% sugar beet pulp and 0.40% chromic oxide. RESULTS: The endogenous loss of ether extract (EE) was lower than that of acid-hydrolyzed fat (AEE; P < 0.01). There were significant differences in the AID and SID of fat and saturated fatty acids across the dietary oil sources (P < 0.05). The SID of AEE for palm oil was lower than that of sunflower oil, corn oil, canola oil, rice oil and flaxseed oil (P < 0.01). The AID and SID of fat ranged from 79.65% to 86.97% and from 91.14% to 99.18%. Although the AID of EE was greater than that of AEE (P < 0.01), there was no significant difference in SID of EE and AEE except for palm oil. The ratio of unsaturated to saturated fatty acids (U/S) had a positive correlation with SID of fat (P < 0.05), whereas C16:0 and long chain saturated fatty acids (LSFA) were significant negatively correlated with SID of fat (P < 0.01). The best-fit equation to predict SID of fat was SID AEE = 102.75 - 0.15 × LSFA - 0.74 × C18:0 - 0.03 × C18:1 (Adjusted coefficient of determination = 0.88, P < 0.01). CONCLUSIONS: When calculating the SID of fat, the EE content of the samples can be analyzed using the direct extraction method, whereas the acid hydrolysis procedure should be used to determine the AID of fat. Fat digestibility of dietary oils was affected by their fatty acid composition, especially by the contents of C16:0, LSFA and U/S.

Prediction of net energy values in expeller-pressed and solvent-extracted rapeseed meal for growing pigs.

OBJECTIVE: The objective of this study was to determine net energy (NE) of expeller-press (EP-RSM) and solvent-extracted rapeseed meal (SE-RSM) and to establish equations for predicting the NE in rapeseed meal (RSM) fed to growing pigs. METHODS: Thirty-six barrows (initial body weight [BW], 41.1±2.2 kg) were allotted into 6 diets comprising a corn-soybean meal basal diet and 5 diets containing 19.50% RSM added at the expense of corn and soybean meal. The experiment had 6 periods and 6 replicate pigs per diet. During each period, the pigs were individually housed in metabolism crates for 16 days which included 7 days for adaption to diets. On day 8, pigs were transferred to respiration chambers and fed their respective diet at 2,000 kJ metabolizable energy (ME)/kg BW0.6/d. Feces and urine were collected, and daily heat production was measured from day 9 to 13. On days 14 and 15, the pigs were fed at 890 kJ ME/kg BW0.6/d and fasted on day 16 for evaluation of fasting heat production (FHP). RESULTS: The FHP of pigs averaged 790 kJ/kg BW0.6/d and was not affected by the diet composition. The NE values were 10.80 and 8.45 MJ/kg DM for EP-RSM and SE-RSM, respectively. The NE value was positively correlated with gross energy (GE), digestible energy (DE), ME, and ether extract (EE). The best fit equation for NE of RSM was NE (MJ/kg DM) = 1.14×DE (MJ/kg DM)+0.46×crude protein (% of DM)-25.24 (n = 8, R2 = 0.96, p<0.01). The equation NE (MJ/kg DM) = 0.22×EE (% of DM)-0.79×ash (% of DM)+14.36 (n = 8, R2 = 0.77, p = 0.018) may be utilized to quickly determine the NE in RSM when DE or ME values are unavailable. CONCLUSION: The NE values of EP-RSM and SE-RSM were 10.80 and 8.45 MJ/kg DM. The NE value of RSM can be well predicted based on energy content (GE, DE, and ME) and proximate analysis.