body weight and body composition of broilers Galyna Dukhta, Gyrgy - - PowerPoint PPT Presentation

A growth model to predict body weight and body composition of broilers

Galyna Dukhta, György Kövér, Veronika Halas

Kaposvár University, Guba S. 40, 7400 Kaposvár, Hungary

Introduction

Growth models have been developed for decades Static table values vs dynamic model values

Aim

 To introduce a broiler growth model predicting BW and chemical body composition from digestible nutrients  To show some application of the model

Flow chart

Feather FFBP

Feather loss

PD FI digProtein/AAs digFat digStarch digSugar digResidue ME intake LD PD-free NE available Empty body lipid

Cost of PD Maintenance & physical activity

genetics Endogenous losses

Empty body protein BW

InraPorc Broiler model c 0.75 0.8 d 0.6 0.7

Feed Intake

Values

Carré et al., 2014 Coef ME Coef AMEn Coef NE kJ/g CrudeFat 38.38 37.77 32.43 CrudeProt 20.60 18.36 14.32 Starch 17.00 16.67 13.28 Sugars 13.02 12.52 7.932 Residue 9.93 9.30 12.71

Factors for energy conversion

 Gamma function NEI (MJ/d) = (a·b·BW·exp(-b·BW)+1)·c·BWd

a & b – depending on FI at 1 and 2 kg BW

Pt = Pm · exp [-exp ((ln (-ln (Pi/Pm)) – (Bprot · t)))]

Sophisticated Gompertz function for daily body protein deposition (PD)

Wt = Wm · exp [-exp ((ln (-ln (Wi/Wm)) – (B · t)))]

0,000 0,200 0,400 0,600 0,800 1,000 1,200 1,400 20 40 60 80 100 Protein mass, kg Age ,d

Pt = Pm · exp [-exp ((ln (-ln (Pi/Pm)) – (Bprot · t)))] Potential PD = precocity · prot_init·ln(Pm/prot_init)

Sophisticated Gompertz function for daily body protein deposition (PD)

Wt = Wm · exp [-exp ((ln (-ln (Wi/Wm)) – (B · t)))]

0,0 5,0 10,0 15,0 20,0 0,000 0,200 0,400 0,600 0,800 1,000 1,200 1,400 20 40 60 80 100 PD, g/d Protein mass, kg Age, d Protein mass, kg potPD, g/d

0,5 1 1,5 2 2,5 3 3,5 10 20 30 40 BW, kg Age, d

The effect of meanPD on dynamics of BW

9 11 13,5 0,5 1 1,5 2 2,5 3 3,5 10 20 30 40 BW, kg Age, d

The effect of precocity on dynamics of BW

0,03 0,039 0,055

Model output

Body weight (BW) prediction for fixed mean PD (11 g/d) and different precocity parameter (left) and for fixed precocity (0.040) and different mean PD with (right)

3 phases feeding 0-14 d 15-28 d 29-42 d AMEn 13.00 13.00 13.00 CP 24 22 19 dig Lys 1.56 1.33 1.14 dig Met 0.55 0.47 0.40 dig Thr 0.90 0.80 0.71 5 phases feeding 0-10 d 11-20 d 21-28 d 29-35 d 36-42 d AMEn 13.00 12.99 12.84 12.56 12.36 CP 24 22 21 20 19 dig Lys 1.56 1.33 1.14 1.18 1.14 dig Met 0.55 0.47 0.40 0.42 0.40 dig Thr 0.90 0.80 0.75 0.72 0.71

Nutritional composition of the diets

Model application

0,0 5,0 10,0 15,0 20,0 10 20 30 40 daily deposition, g/d Age, d

3 phases

PD potPD Lipids 0,0 5,0 10,0 15,0 20,0 10 20 30 40 daily deposition, g/d Age, d

5 phases

Comparison of FCR and BW with different phase feeding

Input parameters:

• FI at 1 kg BW – 1.2; at 2 kg BW – 1.9 kg
• precocity: 0.040; meanPD = 11 g/d; initial BW = 44 g; duration: 42 d

1,0 1,2 1,4 1,6 1,8 2,0 10 20 30 40 FCR, kg/kg Age, d 3 Phases 5 Phases 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 20 40 BW, kg Age, d 5 % difference in BW at 35 days of age

Body composition

0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,0 0,5 1,0 1,5 2,0 2,5 3,0 20 40 kg Age, d 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,0 0,5 1,0 1,5 2,0 2,5 3,0 20 40 kg Age, d BW protein lipids

Input parameters I:

• FI at 1kg BW – 1.2; 2kg BW – 1.8 kg
• precocity: 0.040; meanPD = 11 g/d;

initial BW = 44 g; duration: 42 d Input parameters II:

• FI at 1kg BW – 1.3; 2kg BW – 2 kg
• precocity: 0.055; meanPD = 9 g/d;

initial BW = 44 g; duration: 42 d

Conclusion

The examples provided in this presentation show the benefit of using mathematical models and their applicability in precision nutrition. It can be concluded that the growth model helps to apply “from desired feed to desired food” concept.

Thank You for your attention!

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 633531. The publication is supported by the EFOP-3.6.3-VEKOP-16-2017-00008 project. The project is co-financed by the European Union and the European Social Fund.