Accurate predictions of chemical composition of pigs for a wide range of body weights: no longer a myth!
Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry
Assessing body or carcass composition in growing pigs is essential to refine nutritional models, select for specific traits and evaluate pork products. The gold standard methods are dissection and chemical measurements, which are time-consuming and invasive ways to obtain the data. Different teams have tested dual-energy x-ray absorptiometry (DEXA), especially for determining total and regional body composition of fat, soft lean tissues and bone minerals [1-3]. The DEXA measurements are quick, non-invasive, precise, and operator independent. However, the instruments from different manufacturers are unique in implementation so that it is difficult to obtain and share generalized equations. In addition, the validity and accuracy of the measures when applied to pigs having very different composition have been scarcely addressed.
The present manuscript shows that carcass analysis by DEXA can be used to predict empty body chemical composition, and it provides accuracy values for the content in single nutrients (protein, lipids, Ca, P). The body weight range used to generate differences in body composition is very large (20 to 100 kg), which is important when studying pigs along growth. Moreover, regression equations within weight classes (20, 60 and 100 kg) show no important biases, with the exception for body fat especially at the earliest growth stages. Limitations of the technique are the needs of anesthesia when applied to living pigs, and of standardizing the positions of body, carcass and cuts when applied to living or dissected pigs. Another originality of the manuscript is the comparison of the obtained calibrations with previously published prediction models, showing that the differences do not preclude the possibility to use a single model when built from a meta-analysis of the different data. Taken together, this work offers good perspectives to refine nutritional models by inputs from rapidly analyzed body chemical composition and to monitor body and carcass composition in several pigs for genetics applications.
 Mitchell AD., Scholz AM., Pursel VG., and Evock-Clover CM. (1998). Composition analysis of pork carcasses by dual-energy x-ray absorptiometry. Journal of Animal Science. 76(8), 2104-14. https://doi.org/10.2527/1998.7682104x
 Marcoux M., Bernier JF., and Pomar C. (2003). Estimation of Canadian and European lean yields and composition of pig carcasses by dual-energy X-ray absorptiometry. Meat Science. 63(3), 359-65. https://doi.org/10.1016/S0309-1740(02)00094-3
 Kipper M., Marcoux M., Andretta I., and Pomar C. (2018). Repeatability and reproducibility of measurements obtained by dual-energy X-ray absorptiometry on pig carcasses. Journal of Animal Science, 96(5), 2027-2037. https://doi.org/10.1093/jas/skx046 "
Florence Gondret (2020) Accurate predictions of chemical composition of pigs for a wide range of body weights: no longer a myth! . Peer Community in Animal Science, 100005. 10.24072/pci.animsci.100005
Revision round #210 Dec 2020
Decision round #2
Dear authors, After the careful reading of this second version of the manuscript, I think that Rewiewers’ comments have been properly addressed in this revised version of the preprint. However, I still have some comments that must be addressed before I can render a decision and recommend the preprint. Comments are listed below.
I hope that you will be able to make the modifications and provide a clean version incorporating the modifications (without any track changed), so that the process could continue to its term.
I thank you for choosing PCI in Animal Science in order to give a large exposure to your work and to support Open Science.
Section L20-L29 should be shortened, since here this sounds as a repetition of the introduction section.
L33 “we present the accuracy of those predictions”. please give details about the accuracy obtained for a subset of studied traits. This will be more informative for the readers.
L34: provide the values used to estimate the accuracy (RMSE, etc.)
L35-36: “This should be deleted, since the conclusion of the abstract already states this.
L55: delete unappropriated bracket
L132: spell the abbreviation EB
L485: verb and words are missing in the sentence (fits well ?)
L614: provide a reference number or link in Zenodo, so that data could be easily found by the readers
Revision round #105 Nov 2020
Decision round #1
The manuscript quoted in reference has been examined by two expert scientists in body composition evaluation in pigs. Although the two reviewers found merit in this study and recognized the quality of the associated paper, they raised a number of concerns that should be addressed before any decision could be rendered. I enclosed below detailed evaluation points. If you think you are able to provide a detailed answer to the different points, I encourage you to respond point by point and submit a new version of the preprint.
Anyway, thanks you for submission to PCI Animal Science Community.