Equations generated to predict iodine value of pork carcass back, belly, and jowl fat1,2

Abstract

Data from existing literature were used to generate equations to predict finishing pig back, belly, and jowl fat iodine values (IV) and an experiment was conducted to evaluate these equations. The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For experiments that changed dietary fatty acid composition, initial (INT) diets were defined as those fed before the change in diet composition and final (FIN) diets were those fed after. The predictor variables tested were divided into 5 groups: 1) diet fat composition (dietary percent C16:1, C18:1, C18:2, C18:3, EFA, unsaturated fatty acids, and IV product) for both INT and FIN diets, 2) day feeding the INT and FIN diets, 3) ME or NE of the INT and FIN diet, 4) live performance criteria (initial BW, final BW, ADG, ADFI, and G:F), and 5) carcass criteria (HCW and backfat thickness). The PROC MIXED procedure of SAS (SAS Inst., Inc., Cary, NC) was used to develop regression equations. Evaluation of models with significant terms was then conducted based on the Bayesian information criterion. The optimum equations to predict back, belly, and jowl fat IV were backfat IV = 84.83 + (6.87 × INT EFA) - (3.90 × FIN EFA) - (0.12 × INT days) - (1.30 × FIN days) - (0.11 × INT EFA × FIN days) + (0.048 × FIN EFA × INT days) + (0.12 × FIN EFA × FIN days) - (0.0060 × FIN NE) + (0.0005 × FIN NE × FIN days) - (0.26 × backfat depth); belly fat IV = 106.16 + (6.21 × INT EFA) - (1.50 × FIN days) - (0.11 × INT EFA × FIN days) - (0.012 × INT NE) + (0.00069 × INT NE × FIN days) - (0.18 × HCW) - (0.25 × backfat depth); and jowl fat IV = 85.50 + (1.08 × INT EFA) + (0.87 × FIN EFA) - (0.014 × INT days) - (0.050 × FIN days) + (0.038 × INT EFA × INT days) + (0.054 × FIN EFA × FIN days) - (0.0066 × INT NE) + (0.071 × INT BW) - (2.19 × ADFI) - (0.29 × backfat depth). Dietary treatments from the evaluation experiment consisted of a corn-soybean meal control diet with no added fat or a 3 × 3 factorial arrangement with main effects of fat source (4% tallow, 4% soybean oil, or a blend of 2% tallow and 2% soybean oil) and feeding duration (d 0 to 42, 42 to 84, or 0 to 84). The back, belly, and jowl fat IV equations tended to overestimate IV when observed IV were less than approximately 65 g/100 g and underestimate belly fat IV when actual IV are greater than approximately 74 g/100 g or when the fat blend was fed from d 0 to 84 or 42 to 84. Overall, with the exceptions noted, the regression equations were an accurate tool for predicting carcass fat quality based on dietary and pig performance factors.

Development of equations to predict the influence of floor space on average daily gain, average daily feed intake and gain : feed ratio of finishing pigs

“…A literature review was conducted to compile studies that examined the effects of floor space allowance on ADG, ADFI and G : F of finishing pigs. The literature review and database development used similar techniques as described previously for predicting the effects of net energy on ADG and G : F by Nitikanchana et al (2015) and the effects of dietary composition on pork fat iodine value by Paulk et al (2015). Briefly, the literature search was conducted via the Kansas State University Libraries, utilizing the CABI search engine, and using the keywords 'space requirement' or 'floor space allowance' with 'finishing pig' or 'growing pig.'…”

Influence of dietary fat source and feeding duration on finishing pig growth performance, carcass composition, and fat quality1,2

“…Recently, Paulk et al (2015) performed a literature review to create predictive equations for back, belly, and jowl IV based on many different variables such as EFA, ADFI, and initial BW. The current study was used to vali date the predictive equations and they were found to be moderately accurate for estimated backfat IV values, but they overestimate most backfat values, especially for pigs with backfat IV under 65 g/100 g. Belly fat IV was un der predicted for most treatments, with only 34% of the variation explained by the model.…”

“…This study was used to validate those equa tions. A portion of the data from this study was reported by Paulk et al (2015) with the remainder being reported herein. This study was conducted to determine the effects of feeding soybean oil, beef tallow, or a blend of the 2, as well as feeding duration, on finishing pig growth perfor mance, carcass characteristics, and IV of belly and jowl fat and backfat.…”

“…Limiting the duration of feeding unsaturated fats and substi tuting a saturated fat, such as beef tallow, in late fin ishing has shown promise for positively affecting IV (Browne et al, 2013a;Kellner et al, 2014). Paulk et al (2015) performed a metaanalysis to generate predictive IV equations for various fat depots in swine. This study was used to validate those equa tions.…”

Pork fat quality of pigs fed distillers dried grains with solubles with variable oil content and evaluation of iodine value prediction equations1

“…However, using dietary C18:2 or IVP as a single predictor variable resulted in highly variable PE ranging from 3.43 to 8.36 g/100 g and bias ranging from −5.05 to 5.66 g/100 g. In contrast, Eq. [8], [13], and [16] were developed from a meta-analysis by Paulk et al (2015) and included multiple predictive factors involving diet lipid composition, feeding days, NE content of diets, live growth performance criteria, and carcass composition. Therefore, it is reasonable to expect that adding these additional predictors may improve the prediction of IV because they more broadly account for the variation in dietary energy concentration as well as changes in diet composition that affect the intake and metabolic utilization of dietary lipids by pigs.…”