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

Citation: Flohr, J. R., Woodworth, J. C., Tokach, M. D., Dritz, S. S., DeRouchey, J. M., & Goodband, R. D. (2016). Development of equations to predict the influence of floor space on average daily gain, average daily feed intake, and gain-to-feed ratio of finishing. Journal of Animal Science, 94, 7-7. doi:10.2527/msasas2016-015Data from existing literature examining the influence of floor space allowance on the growth of finishing pigs was used to develop prediction equations for ADG, ADFI, and G:F. Two databases were used: the first included information from studies examining the influence of floor space allowance, and the second included the aforementioned papers along with papers examining the impact of floor space after pigs were removed from the pen. The first database included 27, 25, and 25 papers for ADG, ADFI, and G:F, respectively, and the second database contained 30, 28, and 28 papers for ADG, ADFI, and G:F, respectively. The predictor variables tested were floor space (m2/pig), k (floor space/final BW0.67), initial BW, final BW, feed space (pigs per feeder hole), water space (pigs per waterer), group size (pigs per pen), gender, floor type, and study length (d). Floor space treatments within each experiment were the experimental unit and random effects of decade, paper within decade, and experiment within paper × decade interactions were included in the statistical model. A weighted variance term was included in the statistical model to account for heterogeneity of experimental designs and replication across the existing literature. The statistical significance for inclusion of terms in the model was determined at P < 0.10. Further evaluation of models with significant terms was then conducted based on the Bayesian information criterion (BIC). Once the ADG and ADFI models for each respective database were determined, then the G:F model was evaluated as the predicted ADG/predicted ADFI. The optimum equations to predict finishing ADG, ADFI, and G:F for the first database were ADG, g = 395.57 + (15,727 × k) ? (221,705 × k2) ? (3.6478 × initial BW, kg) + (2.209 × final BW, kg) + (67.6294 × k × initial BW, kg); ADFI, g = 802.07 + (20,121 × k) ? (301,210 × k2) ? (1.5985 × initial BW, kg) + (11.8907 × final BW, kg) + (159.79 × k × initial BW, kg); and G:F = predicted ADG/predicted ADFI. The optimum equations to predict ADG, ADFI, and G:F for the second database were ADG, g = 337.57 + (16,468 × k) ? (237,350 × k2) ? (3.1209 × initial BW, kg) + (2.569 × final BW, kg) + (71.6918 × k × initial BW, kg); ADFI, g = 833.41 + (24,785 × k) ? (388,998 × k2) ? (3.0027 × initial BW, kg) + (11.246 × final BW, kg) + (187.61 × k × initial BW, kg); and G:F = predicted ADG/predicted ADFI. All multiterm models improved BIC values compared with single-term predictor models, signifying that multiterm models proved to better fit their respective databases