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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 NElof 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 NEpincreased 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 NElkept 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.This study provides a clear understanding of net energy (NE) utilization in pigs and finds that the NE intake and NE partition patterns were greater compared with those reported previously, indicating the increased NE requirements of modern pig breeds. This study has also applied and compared the corresponding nonlinear regression models and artificial neural networks models.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.

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.This study determined the digestible energy, metabolizable energy, and digestible amino acids contents of full-fat soybean fed to growing pigs, and established the corresponding prediction equations. The results showed that full-fat soybean is a high-quality protein ingredient.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.

This study was conducted to determine the chemical composition, DE, ME, and NE contents, and the apparent and standardized ileal digestibility (AID and SID) of AA in Cyperus esculentusco-products fed to growing pigs. The five C. esculentusco-products included expeller-pressed C. esculentuscake (EPCC), cold-pressed C. esculentuscake (CPCC), solvent-extracted C. esculentusmeal (SECM), C. esculentusdistillers’s dried grains with solubles (CE DDGS), and C. esculentusmeal (CEM). In Exp. 1, a total of 36 crossbred growing pigs (Duroc × Landrace × Yorkshire; BW: 50.12 ± 2.91 kg) were fed one of six diets in a completely randomized design. The diets included a corn-soybean meal basal diet and five experimental diets containing 24.31% C. esculentusco-products. In Exp. 2, 12 same breed of growing pigs (BW: 47.12 ± 3.2 kg), surgically fitted with a T-cannula in the distal ileum, were allotted to one of four experimental diets in a 2-period Youden Square design. The diets included one N-free diet and three experimental diets containing 50% C. esculentusco-products (including EPCC, SECM, and CE DDGS). Results indicated that the SECM and CE DDGS had the greatest contents of starch and CP, respectively. The contents of CF, NDF, and ADF were the greatest in CEM and the lowest in SECM. On a DM basis, the DE, ME, predicted NE, and apparent total tract digestibility (ATTD) of GE values of the 5 C. esculentusco-products ranged from 1,203 to 3,897 kcal/kg, 1,127 to 3,621 kcal/kg, 536 to 2,871 kcal/kg, and 28% to 79%, respectively. The EPCC and CPCC had the greatest DE, ME, and predicted NE values, and CPCC, EPCC, and SECM had the greatest ATTD of GE, whereas CEM had the lowest DE, ME, NE, and ATTD of GE (P< 0.001). The NDF and ADF were negatively correlated with DE, ME, and NE (P< 0.05). The AID and SID of CP varied from 53.57 % to 57.86% and from 69.99% to 87.85%, respectively. The EPCC and SECM had greater SID of CP, Ile, Met, Val, Asp, Cys, and Tyr compared to those of CE DDGS (P< 0.05). These results indicated that the chemical composition, DE, ME, and NE as well as the most AA digestibility of C. esculentusco-products obtained from different processing techniques varied greatly. Based on the energy contents and AA digestibility, the EPCC is a better feedstuff for growing pigs compared with the other 4 C. esculentusco-products.

The objective of this study was to evaluate the effects of different defatted rice bran (DFRB) sources and processing technologies on nutrient digestibility in different intestinal segments of pigs. Nine barrows with T-cannula in the distal ileum were randomly allotted to nine different sources in which oil was pressed extracted for seven sources and was solvent extracted for two sources. The experiment contained 6 periods of 12 d, including 8 d for diet adaptation, 2 d for fecal collection, and 2 d for digesta collection. The apparent ileal digestibility (AID) of dry matter (DM), ash, total dietary fiber (TDF), insoluble dietary fiber (IDF), neutral detergent fiber (NDF), acid detergent fiber (ADF), and hemicellulose in different sources of DFRB was quite variable. There were no differences in the AID of dietary gross energy (GE), organic matter (OM), ether extract (EE), crude protein (CP), and soluble dietary fiber (SDF) between different sources of DFRB. There were no differences in the AID of dietary EE, TDF, IDF, and hemicellulose between different processing technologies. Pressed DFRBs have greater (P< 0.05) average AID of dietary GE, DM, ash, OM, CP, SDF, and NDF and lower (P< 0.01) ADF compared with solvent-extracted DFRBs. The apparent total tract digestibility (ATTD) of most of the dietary nutrients, except for the ATTD of dietary EE, SDF, and hemicellulose, significantly varied in different sources of DFRB (P< 0.05). In addition, pressed DFRB had greater (P< 0.05) ATTD of dietary SDF, NDF, ADF, and hemicellulose compared with solvent-extracted DFRB. The apparent hindgut digestibility (AHD) of dietary DM, SDF, NDF, and ADF significantly varied (P<0.05) in different sources of DFRB. Exception with DM, there are no differences in the AHD of nutrients digestibility between pressed DFRB and solvent-extracted DFRB. In conclusion, DFRB in different sources and processing technologies with different physicochemical properties had different effects on nutrient digestibility in the foregut and hindgut of pigs.