Feed efficiency represents the cumulative efficiency with which the pig utilizes dietary nutrients for maintenance, lean gain and lipid accretion. It is closely linked with energy metabolism, as the oxidation of carbon-containing components in the feed drive all metabolic processes. While much is known about nutrient utilization and tissue metabolism, blending these subjects into a discussion on feed efficiency has proven to be difficult. For example, while increasing dietary energy concentration will almost certainly increase feed efficiency, the correlation between dietary energy concentration and feed efficiency is surprisingly low. This is likely due to the plethora of non-dietary factors that impact feed efficiency, such as the environment and health as well as individual variation in maintenance requirements, body composition and body weight.Nonetheless, a deeper understanding of feed efficiency is critical at many levels. To individual farms, it impacts profitability. To the pork industry, it represents its competitive position against other protein sources. To food economists, it means less demand on global feed resources. There are environmental and other societal implications as well.Interestingly, feed efficiency is not always reported simply as a ratio of body weight gain to feed consumed. This review will explain why this arithmetic calculation, as simple as it initially seems, and as universally applied as it is in science and commerce, can often be misleading due to errors inherent in recording of both weight gain and feed intake.This review discusses the importance of feed efficiency, the manner in which it can be measured and reported, its basis in biology and approaches to its improvement. It concludes with a summary of findings and recommendations for future efforts.

Induction of remission is easily achieved with dietary treatment in dogs diagnosed with Food Responsive Chronic Diarrhea (FRD). Administration of prebiotics and glycosaminoglycans (GAGs) may improve epithelial cell integrity and therefore be useful as adjunct treatment. This study evaluated whether the relapse rate of FRD dogs that are switched back to a normal diet can be influenced using supplemental treatment with prebiotics and GAGs. A randomized, controlled clinical trial (RCCT) was performed in dogs diagnosed with FRD. Dogs were diagnosed based on clinical exclusion diagnosis, endoscopic biopsies showing predominantly lymphoplasmacytic infiltration, and response to dietary treatment. Dogs were randomized to be fed a combination of prebiotics and GAGs (group 1) or placebo (group 2) in addition to a hydrolyzed diet. At week 10, a second endoscopy was performed and dogs were switched back to normal diet. Relapse rate was monitored every 2 weeks after that until week 18. Statistical analysis was performed for each outcome (Canine Chronic Enteropathy Clinical Activity Index (CCECAI), clinicopathological data, endoscopic scoring, mWSAVA histological scoring index (mWSAVA), and number of relapses following switch to normal diet) using a linear mixed effects model for group comparison. Time, group, and their interactions were included as a fixed effect, whereas each dog was treated as a random effect. Of the 35 dogs enrolled into the clinical trial, 10 in each group reached the point of second endoscopy. A total of 13 dogs (n = 8 in group 1 and n = 5 in group 2) reached the trial endpoint of 18 weeks. After switching back to normal diet, none of the dogs in either group relapsed. No significant differences were found over time or between groups for CCECAI, endoscopy scoring and histological scoring. Although there was a clinical worsening in the placebo group after switching back to the original diet, this was not statistically significant (CCECAI p = 0.58). Post-hoc power calculation revealed that 63 dogs per group would have been needed to detect statistically significant differences in CIBDAI between treatment groups. Standard dietary treatment induced rapid clinical response in all cases, however, additional supplementation with prebiotics and GAGs did not significantly improve clinical outcome within 4 months after switching back to normal diet. Since there are very few RCCT published in CE in dogs, this pilot study provides important power analyses for planning of further studies.

Statistical analysis of data and understanding of experimental design are critical skills needed by Animal Science Graduate Students (ASGS). These skills are even more valuable with the increased development of high-throughput technologies. The objective of this study was to evaluate the perceived statistical training of US ASGS. A survey with 38 questions was shared across US universities, and 416 eligible ASGS from 43 universities participated in this study. The survey included questions on the demographics and overall training, graduate education on statistics, and self-assessment on statistics and career path of ASGS. Several analyses were performed: relationship between perceived received education (PRE; i.e., how ASGS evaluated their graduate education in statistics) and perceived knowledge (PK; i.e., how ASGS evaluated their knowledge in statistics from their education), ranking of statistical topics based on PRE, PK, and confidence in performing statistical analyses (CPSA), cluster analysis of statistical topics for PRE, PK, and CPSA, and factors (demographic, overall training, interest in statistics, and field of study) associated with overall scores for PRE, PK, and CPSA. Students had greater (P < 0.05) PRE than PK for most of the statistical topics included in this study. The moderate to high repeatability of answers within statistical topics, indicate substantial correlations in ASGS answers between PRE and PK. The cluster analysis resulted in distinct groups of “Traditional” and “Non-Traditional” statistical topics. ASGS showed lower (P < 0.05) scores of PRE, PK, and CPSA in “Non-Traditional” compared with “Traditional” statistical methods. Several factors were associated (P < 0.05) with the overall scores of PRE, PK, and CSPA. In general, factors related to greater training and interest in statistics of ASGS were associated with greater overall scores, such as taking more credits in statistics courses, having additional training in statistics outside the classroom, knowing more than one statistics software, and more. This study provided comprehensive information on the perceived level of education, knowledge, and confidence in statistics in ASGS in the US. Although objective measurements of their training in statistics are needed, the current study suggests that ASGS have limited statistical training on topics of major importance for the current and future trends of data-driven research in animal sciences.

Induction of remission is easily achieved with dietary treatment in dogs diagnosed with Food Responsive Chronic Enteropathy (FRD). Administration of prebiotics and glycosaminoglycans (GAGs) may improve epithelial cell integrity and therefore be useful as adjunct treatment. This study evaluated whether the relapse rate of FRD dogs that are switched back to a normal diet can be influenced using supplemental treatment with prebiotics and GAGs. A randomized, controlled clinical trial (RCCT) was performed in dogs diagnosed with FRD. Dogs were diagnosed based on clinical exclusion diagnosis, endoscopic biopsies showing predominantly lymphoplasmacytic infiltration, and response to dietary treatment. Dogs were randomized to be fed a combination of prebiotics and GAGs (group 1) or placebo (group 2) in addition to a hydrolyzed diet. At week 10, a second endoscopy was performed and dogs were switched back to normal diet. Relapse rate was monitored every 2 weeks after that until week 18. Statistical analysis was performed for each outcome (Canine Chronic Enteropathy Clinical Activity Index (CCECAI), clinicopathological data, endoscopic scoring, mWSAVA histological scoring index (mWSAVA), and number of relapses following switch to normal diet) using a linear mixed effects model for group comparison. Time, group, and their interactions were included as a fixed effect, whereas each dog was treated as a random effect.  Of the 35 dogs enrolled into the clinical trial, 10 in each group reached the point of second endoscopy. A total of 13 dogs (n=8 in group 1 and n=5 in group 2) reached the trial endpoint of 18 weeks. After switching back to normal diet, none of the dogs in either group relapsed. No significant differences were found over time or between groups for CCECAI, endoscopy scoring and histological scoring. Although there was a clinical worsening in the placebo group after switching back to the original diet, this was not statistically significant (CCECAI p=0.58). Post-hoc power calculation revealed that 63 dogs per group would have been needed to detect statistically significant differences in CIBDAI between treatment groups.  Standard dietary treatment induced rapid clinical response in all cases, however, additional supplementation with prebiotics and GAGs did not significantly improve clinical outcome within 4 months after switching back to normal diet. Since there are very few RCCT published in CE in dogs, this pilot study provides important power analyses for planning of further studies.

Statistical training is a major component in the education of animal science graduate students (ASGS). Although most graduate courses in animal science require ASGS to take credits in statistics courses, ASGS differ on their educational and professional interest in statistics. Thus, the aim of this study was to identify associations between the overall graduate and statistical training of ASGS with the statistical interest related to their professional career path. Data from a nationwide statistical training survey was used and included information on 381 ASGS from 42 universities. Analyses focused on identifying overall graduate and statistical training factors associated with ASGS’s answers to the following questions: “Gives statistical advices to lab peers” (No/Yes), “Gives statistical advices to others outside the lab” (No/Yes), “Desired career path after graduation” (Academia/Industry/Other), and “Desire to be involved in statistical analysis in desired career path” (No/Somewhat/Yes). Data were analyzed using logistic regression model including 11 fixed effects, such as degree being pursued (MS/PhD), years of graduate education (covariate), previous professional experience (No/Yes), preferred stats software (SAS/R/SAS and R/Other), etc. There were significant associations (P < 0.05) for all four analyses. ASGS were more likely to give statistical advice to lab peers as they had more years of graduate education [odds-ratio (OR)=1.33], had additional training in statistics (OR=1.92), and had analyzed their own dataset (OR=4.46). ASGS with and without previous professional experience had greater desire to go to industry (OR=1.3) and academia (OR=1.23), respectively. ASGS interested in being involved in statistics in their future career had greater years of graduate education (OR=1.31) and credits in stats courses (OR=1.31), had previously completed a graduate degree (OR=1.49), had previous research experience (OR=1.5), and had additional training in statistics (OR=1.54). These results indicate that a variety of experiences prior to and during graduate ASGS education are associated with their interest in statistics.