Abstract
The identification of an inexpensive, indirect measure of feed efficiency in swine could be a useful tool to help identify animals with improved phenotypes to supplement expensive phenotypes including individual feed intakes. The purpose of this study was to determine whether hematology parameters in pigs at the beginning and end of a feed efficiency study, or changes in those values over the study, were associated with average daily gain (ADG), average daily feed intake (ADFI), or gain-to-feed (G:F). Whole blood samples were taken at days 0 and 42 from pigs (n = 178) that were monitored for individual feed intakes and body weight gain during a 6-week study. Blood samples were analyzed for blood cell parameters including white blood cell (WBC), neutrophil, lymphocyte, monocyte, eosinophil and basophil counts, red blood cell (RBC) counts, hemoglobin, hematocrit, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC), platelet count, and mean platelet volume (MPV). Feed efficiency parameters were predicted using an ANOVA model including fixed effects of farrowing group and pen (sex constant) and individual hematology parameters at day 0, day 42 or their change as covariates. At day 0, platelet count was positively associated with ADFI (P < 0.05) and negatively associated with G:F (P < 0.1), and lymphocyte count was positively associated with ADFI (P < 0.05). At day 42, neutrophil, RBC counts, hemoglobin and hematocrit were associated with ADFI (P < 10−3). Over the course of the study, changes in RBC measurements including RBC, hemoglobin, MCV, MCH, and MCHC (P < 10−4) which may improve oxygen carrying capacity, were associated with ADG and ADFI. The change in hematocrit over the course of the study was the only parameter that was associated with all three measures of feed efficiency (P < 0.05). Changes in RBC parameters, especially hematocrit, may be useful measurements to supplement feed efficiency phenotypes in swine.
Keywords: complete blood count, feed efficiency, pigs, red blood cells
INTRODUCTION
Selecting animals with improved feed efficiency phenotypes is one way to reduce producer costs associated with feed. However, methods to identify feed efficient animals require individual feed intake measurements, which is time consuming and the equipment for these measurements can be expensive. Moreover, feed efficiency phenotypes require the integration of multiple feed intake and body weight gain data points for each animal and various calculations. An indirect measure that represents a proxy for feed efficiency that is inexpensive, easy to measure, and easy to collect could alleviate these issues.
Some previously studied proxies for feed efficiency in production animals include SNPs (Ramayo-Caldas et al., 2019; Keel et al., 2020), backfat depth (Knap and Kause, 2018), feeding behavior (Reyer et al., 2017), microbial populations or communities (McCormack et al., 2019a, 2019b), and methane or carbon dioxide emissions (Arthur et al., 2018; Renand et al., 2019). Other studies have evaluated the use of blood parameters for association with feed efficiency traits (Foote et al., 2016; Crane et al., 2016; Consolo et al., 2018). Although genomic markers are widely used now in seedstock evaluation, the cost of measuring feed intake precludes their full utilization in all areas of swine production; thus, measurements or data that can help replace the loss of phenotypic recording are useful. While there appears to be much promise in the areas of feeding behavior, microbiome, and emissions as proxies for feed efficiency, these measures require assays, equipment, and/or labor.
Genes involved in immune function have been associated with livestock feed efficiency in tissues, including adipose, rumen, and the small intestine. There is likely communication between the circulating cells and these tissues making it possible to identify differences in white blood cell populations and counts. The circulating red blood cells (RBCs) are responsible for carrying oxygen to the tissues, and hemoglobin is involved in the buffering capacity of blood and contributes to vasodilation and improved blood flow to working muscle (Mairbäurl, 2013). We hypothesized that differences in the populations of circulating cells may have a role in livestock feed efficiency. The objective of this study was to determine whether hematology parameters at the beginning and end of a feed efficiency study, or the changes in parameters between those timepoints were associated with ADG, ADFI, or gain:feed (G:F) in pigs. A whole blood sample is relatively easy to obtain, and in some settings, is routinely collected. These samples are inexpensive and can be tested on an in-house instrument, such as the Element HT5 (Heska, Loveland, CO) or transported to a commercial laboratory for veterinary hematology analysis, which is a routine assay.
MATERIALS AND METHODS
Animal Care and Use
The U.S. Meat Animal Research Center (USMARC) Animal Care and Use Committee reviewed and approved all animal procedures. The procedures for handling pigs complied with the Guide for the Care and Use of Agricultural Animals in Agricultural Research and Teaching (FASS, 2010).
Population, Phenotypes, and Sampling
Feed intake and body weight gain were measured on growing pigs (n = 178; 81 barrows and 97 gilts, penned by sex) from the USMARC population (maternal Landrace × Yorkshire and Landrace sire line). Pigs entered the barn at 95 ± 3 d of age at the beginning of the feeding trial and had ad libitum access to water and a standard corn/soybean meal-based diet that met or exceeded NRC recommendations (NRC, 2012) for 42 d. Diets for days 0 to 21 were: 76.48% corn, 20.08% soybean meal (465 g/kg), 2.25% vitamin/mineral premix, 1% soybean oil, 0.092% l-Lysine MHC (980 g/kg), 0.047% l-Threonine (980 g/kg), and dl-Methionine (985 g/kg). Metabolizable energy was 13.73 MJ/kg and crude protein was 159 g/kg. For days 22 to 42, diets included: 82.17% corn, 14.72% soybean meal (465 g/kg), 2% vitamin/mineral premix, 1% soybean oil, 0.07% l-Lysine MHC (980 g/kg), and 0.04% l-Threonine (980 g/kg). Metabolizable energy was 13.77 MJ/kg and crude protein was 137.4 g/kg. Pigs were housed in one of 14 single sex pens (14 pigs per pen) containing a single Feed Intake Recording System (FIRE) feeder (Osborne Industries, Inc., Osborne, KS). A total of 192 animals entered the study; however, two blood samples were only collected on a total of 178 animals. Of these, 81 were male and 97 were female. After a one-week adjustment period, daily feed intakes for each pig were recorded via the FIRE feeders and pigs were weighed at the beginning (d 0) and end (d 42) of the feeding trial. Average daily body weight gain (ADG) was divided by average daily feed intake (ADFI) for each pig to determine the feed efficiency phenotype for each pig (gain:feed). On days 0 and 42 of the feed efficiency study, whole blood (1 to 2 mL) was collected via jugular venipuncture into tubes containing EDTA. Blood samples were inverted to mix and prevent coagulation. After all animals were collected, samples were transported to the laboratory for hematology analysis. Samples were placed on gentle rotation on a tube rocker at room temperature until analysis. Samples were tested for 14 WBC and RBC hematology parameters on a Heska Element HT5 Veterinary analyzer. Hematology parameters included white blood cell (WBC), neutrophil, lymphocyte, monocyte, eosinophil and basophil counts, RBC counts, hemoglobin, hematocrit, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC), platelet count, and mean platelet volume (MPV). The averages of the values fell within the reference values for pigs described by Radostits et al. (2000), except for platelet or MPV which are not described with reference values.
Statistical Analysis
Day 0, day 42 and changes in hematology parameters from day 0 to day 42 were for significant effects on ADG, ADFI, and G:F using individual ANOVA models that included farrowing group and pen as fixed effects and the hematology parameter as a fixed covariate. Sex was not included implicitly in the model as it was a component of the effect of pen since all pens contained single sex. Model R2 were compared to based models for ADG, ADFI, and G:F to determine the amount of additional variation explained from the addition of the hematology covariates. Correction for multiple testing was performed by multiplying the P-value by the number of hematology parameters (14) times the three time points/intervals (3; day 0, day 42, and change); thus, nominal P-values were multiplied by 42 to correct for multiple testing.
RESULTS
Feed Efficiency Phenotypes and Whole Blood Parameters
Feed efficiency phenotypes for the cohort of 178 pigs (n = 81 males and 97 females) are presented in Table 1. Average weights increased in these animals from 48.9 kg (SEM, ±0.541 kg) on day 0 to 89.7 kg (SEM, ±0.812 kg) on day 42. Variation in ADG, ADFI, and G:F was identified in the animals in this group and is shown in Table 1 with average values with standard deviations, minimum and maximum values obtained. Whole blood samples were analyzed on a veterinary hematology instrument. Average values and standard deviations, along with minimum and maximum values obtained for animals at days 0 and 42 are presented in Table 2.
Table 1.
Feed efficiency phenotypic information from all pigs (n = 178)
| Phenotype1 | Average (SD) | Minimum | Maximum |
|---|---|---|---|
| Weight (day 0) | 48.9 (7.22) | 33.2 | 63.4 |
| Weight (day 42) | 89.7 (10.83) | 63.1 | 116.2 |
| ADG | 0.97 (0.148) | 0.47 | 1.38 |
| ADFI | 3.69 (0.796) | 2.17 | 6.63 |
| G:F | 0.273 (0.0572) | 0.12 | 0.40 |
1Day 0 and day 42 weights are in kg. The units for average daily gain (ADG) and average daily feed intake (ADFI) are kg/d. G:F is the ratio of ADG to ADFI.
Table 2.
Hematology parameters for all pigs (n = 178) at days 0 and 42
| Day 0 | Day 42 | ||||||
|---|---|---|---|---|---|---|---|
| Hematology parameter1 | Average (SD)2 | Min | Max | Average (SD) | Min | Max | Average difference (delta) |
| WBC, 109/L | 18.35 (3.295) | 11.15 | 28.74 | 17.32 (2.880) | 10.53 | 36.95 | −1.03 |
| NEU, 109/L | 6.05 (1.784) | 2.15 | 12.95 | 5.15 (1.330) | 1.56 | 11.54 | −1.1 |
| LYM, 109/L | 10.68 (2.316) | 6.25 | 19.83 | 10.59 (2.153) | 6.6 | 24.06 | −0.09 |
| MONO, 109/L | 0.94 (0.412) | 0.2 | 3.24 | 0.85 (0.317) | 0.18 | 3.63 | −0.09 |
| EOS, 109/L | 0.47 (0.235) | 0.04 | 2.25 | 0.54 (0.258) | 0.1 | 2.0 | 0.07 |
| BAS, 109/L | 0.22 (0.073) | 0.08 | 0.61 | 0.19 (0.087) | 0.07 | 0.88 | −0.03 |
| RBC, 1012/L | 7.12 (0.479) | 5.86 | 8.27 | 7.17 (0.515) | 5.98 | 9.61 | 0.05 |
| HGB, g/dL | 12.72 (0.625) | 10.0 | 14.8 | 12.97 (0.735) | 10.6 | 17.1 | 0.25 |
| HCT, % | 40.60 (2.062) | 32.5 | 47.5 | 39.86 (2.401) | 32.2 | 52.8 | −0.74 |
| MCV, fL | 57.19 (3.439) | 48.5 | 65.7 | 55.71 (3.260) | 48.1 | 64.2 | −1.48 |
| MCH, pg | 17.91 (1.102) | 15.1 | 20.8 | 18.13 (1.039) | 15.4 | 21.0 | 0.22 |
| MCHC, g/dL | 31.33 (0.587) | 29.9 | 32.9 | 32.54 (0.712) | 29.1 | 34.0 | 1.21 |
| PLT, 109/L | 366.79 (94.993) | 45.0 | 661.0 | 313.45 (85.194) | 48 | 506 | −53.34 |
| MPV, fL | 8.78 (0.635) | 7.4 | 10.8 | 8.92 (0.702) | 6.8 | 10.8 | 0.14 |
1WBC = white blood cell count, NEU = neutrophil count (109/L), LYM = lymphocyte count (109/L), MONO = monocyte count (109/L), EOS = eosinophil count (109/L), BAS = basophil count (109/L). RBC = red blood cell count (1012/L), PLT = platelet count (109/L), HGB = hemoglobin, HCT = hematocrit, MCV = mean corpuscular volume, MCH = mean corpuscular hemoglobin, MCHC = mean corpuscular hemoglobin concentration, RDW = red cell distribution width, PLT = platelets, MPV = mean platelet volume.
Timepoint Associations with Hematology Parameters
Baseline R2 variation from models including only pen and farrowing group was 0.220, 0.420, and 0.474 for ADG, ADFI, and G:F. Lymphocyte and platelet counts were positively associated with ADFI at day 0, but only accounted for 1.5 to 1.7% more variation in these animals (P < 0.05; Table 3). At day 42, neutrophil count was negatively associated with ADFI and explained an additional 8.4% of variation in ADFI, while RBC count, hemoglobin and hematocrit were positively associated with ADFI (P < 0.05; Table 3) and explained an additional 7.8% to 10% of the variation. Hemoglobin also displayed a tendency toward a negative association with G:F (P = 0.054), but only accounted for an additional 1.6% of the variation. None of the hematology parameters obtained at day 0 or day 42 were associated with ADG. After adjustment for multiple testing, lymphocycte, platelet, and neutrophil counts were no longer significant; however, the associations between hemoglobin and hematocrit with ADFI maintained significance (P < 0.05).
Table 3.
Associations between feed efficiency phenotypes and hematology parameters at day 0 and day 42
| Hematology parameter1 | ADG | ADFI | G:F | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Day 0 | Reg2 | SE | R 2 | P 3 | Reg | SE | R 2 | P | Reg | SE | R 2 | P |
| WBC | 0.0029 | 0.00331 | 0.224 | 0.387 | 0.027 | 0.0149 | 0.432 | 0.068 | −0.0011 | 0.00102 | 0.478 | 0.303 |
| NEU | −0.0049 | 0.00657 | 0.223 | 0.453 | 0.0080 | 0.0291 | 0.420 | 0.783 | −0.0014 | 0.00201 | 0.476 | 0.480 |
| LYM | 0.0071 | 0.00464 | 0.231 | 0.127 | 0.047 | 0.0211 | 0.437 | 0.027 | −0.0014 | 0.00143 | 0.477 | 0.337 |
| MONO | 0.014 | 0.0282 | 0.221 | 0.618 | 0.063 | 0.128 | 0.420 | 0.622 | −0.00072 | 0.00865 | 0.474 | 0.934 |
| EOS | 0.070 | 0.0502 | 0.229 | 0.167 | 0.18 | 0.230 | 0.422 | 0.443 | 0.0063 | 0.0154 | 0.475 | 0.682 |
| BAS | 0.11 | 0.162 | 0.223 | 0.493 | 0.64 | 0.740 | 0.422 | 0.385 | −0.021 | 0.0497 | 0.475 | 0.670 |
| RBC | −0.019 | 0.0229 | 0.223 | 0.419 | −0.027 | 0.104 | 0.420 | 0.796 | −0.0028 | 0.00700 | 0.475 | 0.692 |
| HGB | −0.024 | 0.0177 | 0.229 | 0.174 | −0.055 | 0.0813 | 0.421 | 0.497 | −0.0014 | 0.00546 | 0.474 | 0.800 |
| HCT | −0.0060 | 0.00539 | 0.226 | 0.267 | −0.011 | 0.0247 | 0.420 | 0.671 | −0.00060 | 0.00166 | 0.474 | 0.720 |
| MCV | 0.00015 | 0.00353 | 0.220 | 0.966 | 0.00051 | 0.0161 | 0.420 | 0.975 | 0.00016 | 0.00108 | 0.474 | 0.884 |
| MCH | −0.0012 | 0.0106 | 0.220 | 0.910 | −0.0078 | 0.0484 | 0.420 | 0.872 | 0.00094 | 0.00325 | 0.474 | 0.772 |
| MCHC | −0.010 | 0.0195 | 0.222 | 0.609 | −0.049 | 0.0892 | 0.421 | 0.586 | 0.0023 | 0.00604 | 0.475 | 0.710 |
| PLT | −6.7E−06 | 0.000121 | 0.220 | 0.956 | 0.0012 | 0.000546 | 0.436 | 0.034 | −7.2E−05 | 3.68E−05 | 0.486 | 0.053 |
| MPV | −0.013 | 0.0189 | 0.223 | 0.487 | −0.061 | 0.0861 | 0.421 | 0.482 | −0.0026 | 0.00578 | 0.475 | 0.653 |
| Day 42 | ||||||||||||
| WBC | −0.00070 | 0.00369 | 0.247 | 0.851 | −0.012 | 0.01639 | 0.487 | 0.465 | 0.00033 | 0.00119 | 0.478 | 0.785 |
| NEU | −0.0041 | 0.00918 | 0.248 | 0.652 | −0.099 | 0.0401 | 0.504 | 0.015 | 0.0054 | 0.00293 | 0.489 | 0.067 |
| LYM | 0.00099 | 0.00487 | 0.247 | 0.839 | 0.013 | 0.0216 | 0.487 | 0.557 | −0.0011 | 0.00157 | 0.479 | 0.496 |
| MONO | −0.040 | 0.0339 | 0.254 | 0.239 | −0.16 | 0.151 | 0.489 | 0.279 | −2.9E−07 | 0.0110 | 0.478 | 0.999 |
| EOS | −0.0096 | 0.0449 | 0.247 | 0.831 | −0.20 | 0.200 | 0.489 | 0.310 | 0.012 | 0.0145 | 0.480 | 0.422 |
| BAS | −0.063 | 0.120 | 0.248 | 0.600 | −0.14 | 0.536 | 0.486 | 0.792 | −0.014 | 0.0388 | 0.478 | 0.721 |
| RBC | 0.0098 | 0.0229 | 0.248 | 0.669 | 0.20 | 0.101 | 0.498 | 0.048 | −0.012 | 0.00732 | 0.486 | 0.111 |
| HGB | 0.016 | 0.0146 | 0.253 | 0.278 | 0.21 | 0.0629 | 0.520 | 0.001 | −0.0091 | 0.00467 | 0.490 | 0.054 |
| HCT | 0.0030 | 0.00458 | 0.249 | 0.516 | 0.067 | 0.0197 | 0.520 | 0.001 | −0.0035 | 0.00145 | 0.497 | 0.016 |
| MCV | 0.00090 | 0.00361 | 0.247 | 0.804 | 0.020 | 0.0160 | 0.490 | 0.220 | −0.00080 | 0.00116 | 0.479 | 0.492 |
| MCH | 0.0072 | 0.0108 | 0.249 | 0.504 | 0.055 | 0.0478 | 0.490 | 0.250 | −0.00058 | 0.00349 | 0.478 | 0.868 |
| MCHC | 0.024 | 0.0178 | 0.256 | 0.178 | −0.0055 | 0.0791 | 0.485 | 0.945 | 0.0090 | 0.00572 | 0.486 | 0.120 |
| PLT | 6.9E−05 | 0.000129 | 0.248 | 0.592 | 0.00046 | 0.000570 | 0.488 | 0.425 | 9.6E−06 | 4.17E−05 | 0.478 | 0.818 |
| MPV | 0.011 | 0.0166 | 0.249 | 0.501 | −0.0056 | 0.0739 | 0.485 | 0.940 | 0.0017 | 0.00535 | 0.478 | 0.747 |
1WBC = white blood cell count (109/L), NEU = neutrophil count (109/L), LYM = lymphocyte count (109/L), MONO = monocyte count (109/L), EOS = eosinophil count (109/L), BAS = basophil count (109/L). NEU% = neutrophil percent, LYM% = lymphocyte percent, MONO% = monocyte percent, EOS% = eosinophil percent, BAS% = basophil percent, RBC = red blood cell count (1012/L), PLT = platelet count (109/L), HGB = hemoglobin, HCT = hematocrit, MCV = mean corpuscular volume, MCH = mean corpuscular hemoglobin, MCHC = mean corpuscular hemoglobin concentration, RDW = red cell distribution width, PLT = platelets, MPV = mean platelet volume.
2Reg is the estimated increase in ADG, ADFI, or G:F per unit increase or decrease in the change in hematology parameter.
3Nominal P-value is presented as P. P-values in bold represent those that were P < 0.05.
Associations with Changes in Hematology Parameters Over the Study
The change in hematocrit values from days 0 to 42 was the only hematology value in this study that was associated with all of the feed efficiency parameters (ADG, ADFI, and G:F) tested (P < 0.05; Table 4), and explained an additional 8.7%, 12.7%, and 1.4% of the variation of each trait, respectively. The change in hematocrit over the study was positively associated with ADG and ADFI, and negatively associated with G:F. The strongest associations detected in this study (P < 0.0001) were with changes in RBC parameters (RBC, hemoglobin, MCV, MCH, MCHC) over the course of the study, which were positively associated with ADG and ADFI. These parameters explained an additional 8.1% to 10.7% of the variation of ADG, and 8% to 13.8% of the variation of ADFI. Change in MPV was also positively associated with ADG and ADFI; however, this parameter explained no additional variation for ADFI and only 1.5% of ADG. After correction for multiple testing, the changes in RBC, hemoglobin, hematocrit, MCV, MCH, MCHC, and MPV values from day 0 to day 42 over the study maintained significant associations with ADG and ADFI (P < 0.05).
Table 4.
Associations between feed efficiency phenotypes and the change in hematology parameters over days 0 to 42
| Hematology parameters1 | Average daily gain (kg/d) | Average daily feed intake (kg/d) | Gain:Feed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Reg2 | SE | R 2 | P | P adjusted 3 | Reg2 | SE | R 2 | P | P adjusted | Reg2 | SE | R 2 | P | P adjusted | |
| WBC_Δ | 0.0018 | 0.00325 | 0.222 | 0.58 | NS | −0.0075 | 0.0148 | 0.420 | 0.61 | NS | 0.00083 | 0.001 | 0.476 | 0.41 | NS |
| NEU_Δ | 0.0092 | 0.00642 | 0.230 | 0.16 | NS | −0.017 | 0.0286 | 0.421 | 0.55 | NS | 0.0033 | 0.00196 | 0.483 | 0.096 | NS |
| LYM_Δ | −0.00014 | 0.00523 | 0.220 | 0.98 | NS | −0.0033 | 0.0240 | 0.420 | 0.89 | NS | −2.9E−05 | 0.00161 | 0.474 | 0.99 | NS |
| MONO_Δ | −0.012 | 0.0239 | 0.221 | 0.61 | NS | −0.032 | 0.109 | 0.420 | 0.77 | NS | −0.00077 | 0.00731 | 0.474 | 0.92 | NS |
| EOS_Δ | −0.063 | 0.0573 | 0.226 | 0.27 | NS | −0.30 | 0.261 | 0.424 | 0.25 | NS | 0.0055 | 0.0176 | 0.474 | 0.75 | NS |
| BAS_Δ | −0.048 | 0.117 | 0.221 | 0.68 | NS | −0.11 | 0.534 | 0.420 | 0.83 | NS | −0.0059 | 0.0358 | 0.474 | 0.87 | NS |
| RBC_Δ | 0.065 | 0.0150 | 0.301 | 2.69E−05 | 0.001 | 0.38 | 0.0658 | 0.519 | 3.79E−08 | 1.6E−06 | −0.0079 | 0.00481 | 0.483 | 0.10 | NS |
| HGB_Δ | 0.043 | 0.00847 | 0.327 | 1.13E−06 | 4.75E−5 | 0.26 | 0.0363 | 0.558 | 4.04E−11 | 1.7E−09 | −0.0053 | 0.00276 | 0.486 | 0.056 | NS |
| HCT_Δ | 0.012 | 0.00271 | 0.307 | 1.28E−05 | 0.00052 | 0.078 | 0.0116 | 0.547 | 3.06E−10 | 1.3E−08 | −0.0018 | 0.000867 | 0.489 | 0.035 | NS |
| MCV_Δ | 0.011 | 0.00249 | 0.307 | 1.31E−05 | 0.00055 | 0.068 | 0.0108 | 0.535 | 2.65E−09 | 1.1E−07 | −0.0014 | 0.000802 | 0.483 | 0.093 | NS |
| MCH_Δ | 0.036 | 0.00742 | 0.320 | 2.7E−06 | 0.00011 | 0.20 | 0.0325 | 0.534 | 2.74E−09 | 1.2E−07 | −0.0034 | 0.00242 | 0.480 | 0.16 | NS |
| MCHC_Δ | 0.018 | 0.00404 | 0.309 | 1.01E−05 | 0.00042 | 0.093 | 0.0182 | 0.500 | 9.56E−07 | 4E−05 | −0.001 | 0.00131 | 0.476 | 0.45 | NS |
| PLT_Δ | 0.00022 | 0.000124 | 0.235 | 0.083 | NS | −3.5E−05 | 0.000571 | 0.420 | 0.95 | NS | 7.2E−05 | 3.79E−05 | 0.486 | 0.060 | NS |
| MPV_Δ | 0.067 | 0.0136 | 0.322 | 2.22E−06 | 9.3E−5 | 0.31 | 0.062 | 0.498 | 1.47E−06 | 6.2E−05 | −0.0014 | 0.00446 | 0.474 | 0.75 | NS |
1Delta (Δ) is the change in these values calculated by subtracting the value obtained at day 0 from the value obtained a day 42 of the study. WBC = white blood cell count (109/L), NEU = neutrophil count (109/L), LYM = lymphocyte count (109/L), MONO = monocyte count (109/L), EOS = eosinophil count (109/L), BAS = basophil count (109/L). NEU% = neutrophil percent, LYM% = lymphocyte percent, MONO% = monocyte percent, EOS% = eosinophil percent, BAS% = basophil percent, RBC = red blood cell count (1012/L), PLT = platelet count (109/L), HGB = hemoglobin, HCT = hematocrit, MCV = mean corpuscular volume, MCH = mean corpuscular hemoglobin, MCHC = mean corpuscular hemoglobin concentration, RDW = red cell distribution width, PLT = platelets, MPV = mean platelet volume. Bold values were significant after correction for multiple testing.
2Reg is the estimated increase in ADG, ADFI, or G:F per unit increase or decrease in the change in hematology parameters from day 0 to day 42 (delta).
3NS, the calculated value of Padjusted is not significant.
DISCUSSION
The purpose of this study was to evaluate blood cell profiles to determine whether they could be useful to predict or identify animals with feed efficiency phenotypes. The phenotypes evaluated here were ADG, ADFI, and G:F. Measuring actual feed intake is expensive and not an option for all production settings. Since individual feed intake phenotyping is not possible for all animals in commercial or research settings, the ability to use an easy to obtain, inexpensive measurement where smaller numbers of animals have individual feed intake data could provide a desirable alternative or additional measure to supplement animals that do not get individual feed intake data.
In this study, we evaluated hematology parameters for association with feed efficiency phenotypes in pigs. Change in hematocrit was the only parameter associated with all three phenotypes (ADG, ADFI, and G:F). Hematocrit was positively associated with ADG and ADFI, and negatively associated with G:F. Hematocrit, which is the packed RBC volume, is the proportion of whole blood made up of RBCs. The function of RBCs is to transport oxygen to the cells in the body and carbon dioxide to the lungs. Hemoglobin is the iron-containing oxygen-transport protein in RBCs and has high oxygen binding capacity. Hemoglobin carries oxygen from the lungs to the body’s tissues and carbon dioxide from the tissues to the lungs; thus, we might expect to see complementarity in this study between hemoglobin and RBC parameters. Indeed, we did also identify changes in RBC parameters associated with ADG and ADFI. Higher numbers of RBC and increased hemoglobin may deliver more oxygen to tissues to meet the higher metabolic demands of animals with higher gain and higher feed intake.
The strongest associations detected in this study were between changes in RBC hematology parameters between days 0 and 42 over the course of the study with ADG or ADFI. Although this may be the first study to describe the relationship of hematology values over time with feed efficiency phenotypes, it is not the first study to identify relationships between RBC parameters and feed efficiency phenotypes at a specific time point (Richardson et al., 2002; Mpetile et al., 2015; Crane et al., 2016; Foote et al., 2016; Jégou et al., 2016; Consolo et al., 2018). However, these studies are limited in pigs (Mpetile et al., 2015; Jégou et al., 2016). In the study by Mpetile et al. (2015), higher hemoglobin, hematocrit, MCV, MCH, and MCHC values were identified among low RFI selection line Yorkshire pigs. Jégou et al. (2016) detected higher RBC, hemoglobin and hematocrit among efficient French Large White pigs selected for RFI. Our data contradicts the studies by Mpetile et al. (2015) and Jégou et al. (2016), that detected higher hemoglobin and RBC parameters associated with animals with lower than expected feed intakes (low RFI). Notable differences were that in Mpetile et al. (2015), samples were collected between 35 and 42 d of age but the feed efficiency study was not performed until 90 d of age, and Jegou et al. (2016) collected blood samples at the end of the feed efficiency study. Furthermore, the low RFI selection line pigs used in Mpetile et al. (2015) study had reduced ADG, ADFI, and less backfat thickness in comparison to the high RFI selection line pigs, as reported in Mauch et al. (2018), indicating growth trajectory, metabolic activity, and performance were dramatically different between the two lines. Estienne et al. (2019) reported greater levels of hemoglobin, MCV, and MCH in smaller at weaning pigs in contrast to larger at weaning pigs. Similar to the pig performance in Mpetile et al. (2015) and Mauch et al. (2018), the smaller at weaning pigs grew slower and had greater G:F during the nursery phase as compared to the larger at weaning pigs. The current study measured blood parameters of a general population at approximately 95 d of age, just prior to feed efficiency evaluation.
Studies in cattle and rams have produced similar results as this study (Richardson et al., 2002; Rincon-Delgado et al., 2011). RBC count was higher in inefficient rams; however, MCV and MCH tended to be lower in these animals. In cattle, RBC parameters have been associated with more efficient steers and heifers (Richardson et al., 2002; Crane et al., 2016; Consolo et al., 2018). Specifically, hemoglobin concentrations were higher in inefficient heifers (Crane et al., 2016; Consolo et al., 2018), and sire EBVs for high RFI (Richardson et al., 2002). Animals in the previous studies with high RFI have higher than expected feed intakes, suggesting that these data may correspond with the results of our study.
On day 0, we identified two parameters, lymphocyte and platelet counts, that were associated with ADFI (P < 0.05). Both were positively correlated with feed intake. Higher lymphocyte counts have been previously associated with efficient pregnant heifers and cows (Consolo et al., 2018). Foote et al. (2016) also identified relationships between lymphocyte counts and feed efficiency phenotypes in beef cattle from blood samples obtained at the end of a feed efficiency study. In that study, lymphocytes were negatively associated with dry matter intake in steers; and in heifers, lymphocyte count was positively associated with gain and G:F. In this study, higher lymphocyte counts were associated with higher feed intakes, and not with gain or G:F suggesting no advantage for feed efficiency at day 0. To the best of our knowledge, there have been no other reports of association of platelets with feed efficiency phenotypes. The only other association between WBC parameters and feed efficiency phenotypes was neutrophil count which was negatively associated with ADFI at day 42. Neutrophils increase in response to illness, injury, and stress. In this study, neutrophil levels were higher in animals with lower feed intakes. While it is unlikely that illness would be responsible for lower feed intakes in these animals as they are monitored on a regular basis, it is possible that animals more susceptible to stress may consume less feed, or that there may have been a sub-clinical infection or an early exposure to a pathogen.
CONCLUSION
To the best of our knowledge, this is the first report of associations between changes in RBC parameters and feed efficiency phenotypes in finishing pigs. These data were based on whole blood collections from 178 animals at the beginning and the end of a feed efficiency study. These measures help to explain between 1.4% and 13.8% of the variation of the phenotypes presented here and may be a useful data to supplement studies or commercial applications where some animals have feed intake and gain measurements.
ACKNOWLEDGMENTS
Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the USDA and does not imply approval to the exclusion of other products that may be suitable. USDA is an equal opportunity provider and employer.
Conflict of interest statement. J. E. Wells is currently a Section Editor for the Journal of Animal Science. All of the other authors declare no conflicts of interest.
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