Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry

Kasper, Claudia; Schlegel, Patrick; Ruiz-Ascacibar, I.; Stoll, Peter; Bee, Giuseppe

doi:10.1101/2020.09.15.286153

Cited by 5 publications

(7 citation statements)

References 25 publications

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“…The idea underlying the depletion–repletion strategy is therefore to trigger regulatory mechanisms during the depletion phase to induce an increase in P utilization efficiency without affecting growth performance ( 1 ). In the case of P and Ca, the mineral content of the body or of a specific bone is monitored using X-ray absorptiometry [DXA, ( 135 )]. During depletion in growing pigs, body bone mineral content continues to increase, but bone accretion is decreased compared to control pigs, leading to reduced bone mineral content.…”

Section: Strategies To Reduce Phosphorus Excretionmentioning

confidence: 99%

Dietary Phosphorus and Calcium Utilization in Growing Pigs: Requirements and Improvements

et al. 2021

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The sustainability of animal production relies on the judicious use of phosphorus (P). Phosphate, the mined source of agricultural phosphorus supplements, is a non-renewable resource, but phosphorus is essential for animal growth, health, and well-being. P must be provided by efficient and sustainable means that minimize the phosphorus footprint of livestock production by developing precise assessment of the bioavailability of dietary P using robust models. About 60% of the phosphorus in an animal's body occurs in bone at a fixed ratio with calcium (Ca) and the rest is found in muscle. The P and Ca requirements must be estimated together; they cannot be dissociated. While precise assessment of P and Ca requirements is important for animal well-being, it can also help to mitigate the environmental effects of pig farming. These strategies refer to multicriteria approaches of modeling, efficient use of the new generations of phytase, depletion and repletion strategies to prime the animal to be more efficient, and finally combining these strategies into a precision feeding model that provides daily tailored diets for individuals. The industry will need to use strategies such as these to ensure a sustainable plant–animal–soil system and an efficient P cycle.

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Section: Strategies To Reduce Phosphorus Excretionmentioning

confidence: 99%

Dietary Phosphorus and Calcium Utilization in Growing Pigs: Requirements and Improvements

et al. 2021

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“…An inherent limitation of using DXA is that although based on basic principles and hence intrinsically accurate, the software used to analyse the data is proprietary. Animal cadaver studies have shown that both the Prodigy and iDXA have good correlation with chemical analysis results, though many body composition parameters were over- or underestimated 24 , 25 , which may in part be due to differences in animal tissue thickness 26 , 27 and FFM hydration 24 , 26 . The proprietary nature of the software means that we are unable to fully elucidate where differences between the devices may stem from, though our results suggest a larger role of software than instrumentation.…”

Section: Discussionmentioning

confidence: 99%

Cross-calibration of two dual-energy X-ray absorptiometry devices for the measurement of body composition in young children

Lyons-Reid

Kenealy

Albert

et al. 2022

Sci Rep

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This study aimed to cross-calibrate body composition measures from the GE Lunar Prodigy and GE Lunar iDXA in a cohort of young children. 28 children (mean age 3.4 years) were measured on the iDXA followed by the Prodigy. Prodigy scans were subsequently reanalysed using enCORE v17 enhanced analysis (“Prodigy enhanced”). Body composition parameters were compared across three evaluation methods (Prodigy, Prodigy enhanced, iDXA), and adjustment equations were developed. There were differences in the three evaluation methods for all body composition parameters. Body fat percentage (%BF) from the iDXA was approximately 1.5-fold greater than the Prodigy, whereas bone mineral density (BMD) was approximately 20% lower. Reanalysis of Prodigy scans with enhanced software attenuated these differences (%BF: − 5.2% [95% CI − 3.5, − 6.8]; and BMD: 1.0% [95% CI 0.0, 1.9]), although significant differences remained for all parameters except total body less head (TBLH) total mass and TBLH BMD, and some regional estimates. There were large differences between the Prodigy and iDXA, with these differences related both to scan resolution and software. Reanalysis of Prodigy scans with enhanced analysis resulted in body composition values much closer to those obtained on the iDXA, although differences remained. As manufacturers update models and software, researchers and clinicians need to be aware of the impact this may have on the longitudinal assessment of body composition, as results may not be comparable across devices and software versions.

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“…Pigs were slaughtered at a BW of approximately 106 ± kg and the left carcass including the whole head was scanned with dual-energy X-ray absorptiometry (DXA; GE Lunar i-DXA, GE Medical Systems, Glattbrugg, Switzerland), which determines, among other things, the lean tissue and fat content. The lean tissue and the fat content obtained from i-DXA was used in the following prediction equations to estimate the protein content, energy content and fat content retained in the carcass (Kasper et al, 2020b (Ruiz-Ascacibar et al, 2017). The protein and digestible energy content per kg carcass of these piglets were chemically determined and the average of each sex was used as the baseline protein and energy content of piglets at 20 kg BW.…”

Section: Feeding Behaviours and Efficiency Traitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…PE can be measured chemically, which is laborious and costly. An alternative is the use of modern imaging technology, such as DXA (dual-energy X-ray absorptiometry) (Kasper et al, 2020b), which has, after the initial investment, lower operating costs, but still requires a considerable amount of human resources for image acquisition and processing. Preferably, a proxy can be used as a high-throughput phenotyping method for the selection of protein-efficient pigs, which is ideally recorded automatically, in a non-destructive fashion and/or in the course of standard rearing conditions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

Ewaoluwagbemiga¹,

Bee²,

Kasper³

2020

Preprint

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The objective of this study was to explore the potential of using automatically recorded feeding behaviour as a proxy for protein efficiency (PE) by investigating the relationship between feeding behaviour and PE. A total of 402 Swiss Large White pigs were used in this experiment (204 females and 198 castrated males). Pigs were fed ad libitum on a reduced protein diet (80% of standard) from 20kg to 100kg BW. Individual daily feed intake was monitored and carcass composition at slaughter was determined by dual-energy X-ray absorptiometry (DXA). The PE was calculated as the ratio of protein in the carcass (estimated by DXA) to the total protein consumed. Feeding behaviour traits monitored were daily feed intake (DFI; g/day), feed intake per visit (FIV; g/visit), number of daily visits (NDV; visits/day), duration of visits (DUV; min/visit), feeding rate (FR; g/min), and feeder occupation (FO; min/day). Regression analysis was used to estimate the relationship between PE and feeding behaviour, while correcting for the effects of sex, experimental series and age. Weak Pearson’s correlations (−0.25 to 0.12) were found between PE and feeding behaviour traits. Beta (β) estimates from this analysis for feeding behaviours were also very low (0.0093% to 0.087%). An increase in FR (g/min) will increase PE by 0.087% and an increase in DFI (g/day) will decrease PE by 0.0093%. In conclusion, feeding behaviours are not suitable for the identification of protein-efficient pigs, as estimates are negligible.ImplicationsThis study suggests that feeding behaviour traits recorded via automatic feeder are not reliable predictors of protein efficiency in Swiss Large White pigs receiving a protein-reduced diet. Despite the large differences in protein efficiency, only negligible changes in a range of feeding behaviours were observed. Hence, feeding behaviours are not suitable proxies for the high-throughput phenotyping of protein efficiency and the selection of live animals for use in nutrition experiments or for breeding.

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Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry

Cited by 5 publications

References 25 publications

Dietary Phosphorus and Calcium Utilization in Growing Pigs: Requirements and Improvements

Dietary Phosphorus and Calcium Utilization in Growing Pigs: Requirements and Improvements

Cross-calibration of two dual-energy X-ray absorptiometry devices for the measurement of body composition in young children

Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

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