ABSTRACT
The present study aimed to compare NIRS results using freeze-dried ground or not ground (FDG or FDNG) faeces to predict faecal chemical composition and apparent total tract digestibility (ATTD) coefficients. Two different batches of pigs were used (n = 20 mixed sex pens/batch; 11 pigs/pen; Duroc × (Large White × Landrace)). The first batch of pigs (B1; 50.1 ± 3.44 kg body weight (BW)) was used at 13 wks of age and the second batch (B2; 87.0 ± 4.10 kg BW) was used at 18 wks of age. For both B1 and B2, pens were assigned to five diets formulated to obtain a control [10.03 MJ of net energy (NE), 160.0 g of crude protein (CP), and 9.5 g of standardized ileal digestive (SID) lysine (Lys) per kg of feed], low protein (132.0 g CP and 7.5 g SID Lys), high protein (188.0 g CP and 11.5 g SID Lys), low energy (9.61 MJ NE/kg), and high energy (10.45 MJ NE/kg) diets. After a 10-day adaptation period, one faecal sample was collected daily from each pen floor during 6 days in both B1 and B2 (n = 120/batch). Faecal samples were freeze-dried and analysed via NIRS as FDNG and FDG faeces. Dry matter (DM), organic matter (OM), CP, gross energy (GE), fat, and ATTD coefficients were analysed/calculated. The NIRS calibrations were evaluated by cross-validation, splitting the data in four random groups, or using the leave-one-out method. For both FDNG and FDG faeces, coefficients of determination for calibration (R2cv) and residual predictive deviation (RPD) values were: close to 0.9 and 3 for DM and CP, 0.7-0.8 and ≥2 for OM and GE, 0.6 and <2 for fat, and 0.54-0.75 and ≤2 for ATTD coefficients, respectively. CP was better predicted using FDG faeces (p < 0.05), while DM and OM ATTD were better predicted using FDNG faeces (p < 0.05). In conclusion, NIRS successfully predicts faeces' chemical components and ATTD coefficients of nutrients using FDNG or FDG faeces.
ABSTRACT
BACKGROUND: Diet evaluation and optimization is a slow and expensive process and it is not possible to do it at a farm level. This study aimed to use the blood serum metabolite (BSM) and faecal volatile fatty acid (VFA) profiles as potential biomarkers to identify changes in protein, amino acid and energy dietary content in growing and finishing pig diets at farm level. RESULTS: Two studies were conducted. The first study (S1) included 20 pens of 11 pigs (87.0 ± 4.10 kg; 18 weeks old) assigned to 5 diets: control (C1), high or low crude protein (HP1 and LP1, respectively), and high or low net energy (HE1 and LE1, respectively). The second study (S2) included 28 pens of 11 pigs (41.3 ± 2.60 kg; 12 weeks old) assigned to 7 diets: control (C2), high or low crude protein (HP2 and LP2, respectively), high or low amino acid (HA2 and LA2, respectively), and high or low net energy (HE2 and LE2, respectively). Pigs were followed for 10 (S1) and 20 (S2) days, and blood and faecal samples were collected at 20 (S1) and 14 (S2) weeks of age. Data were analysed using general linear models and receiver operating characteristic curve analysis. Urea nitrogen showed the best results as a biomarker. Urea nitrogen was higher in pigs fed high protein diets, HP1 (13.6 ± 0.95 mg/dL) and HP2 (11.6 ± 0.61), compared to those fed low protein diets, LP1 (6.0 ± 0.95) and LP2 (5.2 ± 0.61; P < 0.001), showing good discrimination ability (Area under the curve (AUC) = 98.4 and 100%, respectively). These differences were not observed between diets LA2 (6.5 ± 0.61) and HA2 (8.7 ± 0.61; P > 0.05; AUC = 71.9%), which were formulated based on the ideal protein profile but with no excess of protein. Creatinine, triglycerides, branched-chain fatty acids, albumin, propionic acid, and cholesterol showed differences between at least 2 diets but only in one of the studies. CONCLUSIONS: Urea nitrogen showed high accuracy to detect excess of crude protein in growing and finishing pig diets. Other biomarkers like BCFA showed promising results and need to be further studied.
ABSTRACT
Slow-growing pigs negatively affect production efficiency in conventional pig farms by increasing the occupation time of the facilities and being a limiting factor for the All-In/All-Out swine production systems. This subset of pigs is usually managed with the rest of the pigs, and their nutrient requirements may not be fulfilled. The purpose of the present study was to compare the productive performance of slow- and fast-growing pigs to different standardized ileal digestible (SID) amino acids (AA) dietary levels at late grower-finisher stage. A total of 84 pigs were weighed, tagged, and classified as slow-growing (SG; n = 48; 24.1 ± 1.38 kg) or fast-growing pigs (FG; n = 36; 42.7 ± 1.63 kg) at 11 weeks of age. Pigs were housed in mixed sex pens (n = 8 SG+6 FG/pen) equipped with feeding stations to record daily feed intake per individual pig. Pigs were assigned to three dietary treatments resulting in a 2 × 3 factorial arrangement at 15 weeks of age. Isoenergetic diets were formulated by increasing the ideal protein profile based on the following SID lysine (Lys) levels: 0.92%, 1.18% and 1.45%. Pigs were weighed bi-weekly until 21 weeks of age. Fast-growing pigs were 33.7 kg heavier, gained 255 g/day and consumed 625.5 g/day more than SG pigs (p < 0.001). No interaction or diet effects were observed for final body weight, average daily gain and average daily feed intake (p > 0.05). However, feed conversion ratio was 0.3 lower for SG pigs fed 1.45% SID Lys/AA compared to SG pigs fed 0.92% SID Lys/AA (p = 0.002). Feed conversion ratio was not different within the FG pigs' dietary treatments (p > 0.05). The efficiency of SG pigs may be improved when dietary SID AA levels are increased from 0.92 up to 1.45% SID Lys/AA. Thus, nutrient requirements may vary depending on growth rate at the same age, and SG pigs may require higher dietary SID AA levels than FG pigs to achieve similar productive performance.