CompoCow: a predictive model to estimate variations in body composition and the energy requirements of cull cows during finishing

García, F. Javier Giráldez; Agabriel, Jacques

doi:10.1017/s002185960800779x

Cited by 12 publications

(13 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Estimation of body composition, energy retained in tissues and calculated E resid EBW was calculated from BW according to the allometric equation proposed by Robelin and Daenicke (1980): EBW¼c 0 Â BW C1 where c 0 ¼0.8284 and c 1 ¼0.8384. These values for coefficients c 0 and c 1 correspond to large frame size beef cows (height at withers in the range 140-150 cm, Garcia and Agabriel, 2008). Total adipose tissue weight (TAD, % EBW) and empty body lipid weight (LIP, kg) were calculated from adipose cell diameter (ACD, mm) using equations proposed by Garcia and Agabriel (2008) based on a Charolais dissection: TAD ¼5.211 Â exp (0.0114 Â ACD) and LIP ¼1.134 Â TAD 0.992 .…”

Section: Adipose Cell Diameter and Plasma Nefa Concentrationsmentioning

confidence: 99%

“…These values for coefficients c 0 and c 1 correspond to large frame size beef cows (height at withers in the range 140-150 cm, Garcia and Agabriel, 2008). Total adipose tissue weight (TAD, % EBW) and empty body lipid weight (LIP, kg) were calculated from adipose cell diameter (ACD, mm) using equations proposed by Garcia and Agabriel (2008) based on a Charolais dissection: TAD ¼5.211 Â exp (0.0114 Â ACD) and LIP ¼1.134 Â TAD 0.992 . Empty body protein weight (PROT) was deduced from EBW and LIP by PROT¼(EBW ÀLIP) Â 0.20, it being assumed that the composition of fat-free mass was 20% protein and 80% water (Hoch and Agabriel, 2004).…”

Section: Adipose Cell Diameter and Plasma Nefa Concentrationsmentioning

confidence: 99%

See 1 more Smart Citation

Changes in calculated residual energy in variable nutritional environments: An indirect approach to apprehend suckling beef cows’ robustness

et al. 2015

Self Cite

View full text Add to dashboard Cite

a b s t r a c tThe major perturbation that beef cows have to face in extensive livestock systems is changes in feed resource availability. The ability of beef cows to face variable nutritional environments (robustness) involves adaptive processes that drive adjustments in the energy allocation toward life functions. This study proposes an indirect approach to quantify the modulation of energy allocation over a changing nutritional environment. The concept of residual energy (E resid ), defined as the net energy intake minus the energy secreted in milk and deposited in tissues, was used to investigate the variation in energy allocation priority for maintaining productive traits. In this study robustness was assessed by the difference in E resid between cows experiencing either variable or non limiting nutritional trajectories and differing in body reserves at calving. Forty multiparous Charolais suckling cows, differing in their body condition at calving (moderate (M, n¼ 19): BCS c ¼ 2.070.04 (scale 0-5)) vs fat (F, n¼ 18): BCS c ¼ 2.870.08) were used. They were submitted to two energy levels during the first 120 days post-partum (P1): Control (MC (n¼9) and FC (n¼ 9)) vs Low (ML (n¼10) and FL (n¼ 9)). The average energy intake, expressed in net energy for lactation (NE L ), was 90.7 and 54.7 MJ/d/ cow for C and L cows, respectively. Subsequently (P2, 120-196 days post-partum) all the cows were turned out to a permanent pasture. BW, body condition and milk production were regularly measured in P1 and P2. Body lipid reserves were assessed at calving, end of P1 and end of P2 by measuring adipose cell diameter. The overall milk production was similar between groups of cows over the 2 phases of the changing nutritional trajectories highlighting the robustness of beef cows to achieve this function. During P1, L cows lost BW and body lipid reserves. During P2, BW and BCS gains were similar in FL and ML cows. At the end of P2, FL and ML cows weighed 20 and 10 kg less than FC and MC cows, respectively. Considering both experimental periods (P1þ P2), E resid was 23% lower in L than in C cows (Po0.05). This difference was observed regardless of BCS c , showing that thin beef cows withstood the change in nutritional trajectory after calving similarly to the fatter ones. E resid changes reflect the ability of beef cows to preserve energy allocation toward life functions in changing nutritional environments and may be viewed as indirect criteria of robustness.

show abstract

Section: Adipose Cell Diameter and Plasma Nefa Concentrationsmentioning

confidence: 99%

Section: Adipose Cell Diameter and Plasma Nefa Concentrationsmentioning

confidence: 99%

Changes in calculated residual energy in variable nutritional environments: An indirect approach to apprehend suckling beef cows’ robustness

et al. 2015

Self Cite

View full text Add to dashboard Cite

show abstract

“…Les valeurs des coefficients c 0 et c 1 sont respectivement égales à 0,8284 et 0,8384 et correspondent à une vache de grand format du modèle de composition corporelle des vaches « CompoCow » (Garcia et Agabriel 2008).…”

Section: / Données Disponibles Et Hypothèses De Calculs Pour La Quantunclassified

“…Les mesures de diamètre des adipocytes (diam) ont été transformées en proportions de tissu adipeux dans le PVV (TAD en % PVV) en reprenant l'équation du modèle « Compo-Cow » : TAD (% PVV) = 5,211 x exp (0,0114xdiam) puis exprimés en kilos. Les lipides corporels (LIP, kg) ont ensuite été calculés par l'équation d'allométrie : (INRA 1978) La quantité de protéines corporelles (PROT, kg) a été calculée en considérant que la masse délipidée était constituée de 20% de protéines et de 80% d'eau (Garcia et Agabriel 2008) :…”

Section: / Données Disponibles Et Hypothèses De Calculs Pour La Quantunclassified

Prendre en compte l’efficience alimentaire des vaches allaitantes dans les recommandations alimentaires à travers la quantification de leurs dépenses non productives

Torre

Agabriel

2018

INRA Prod. Anim.

Self Cite

View full text Add to dashboard Cite

La vache allaitante utilise près de 70% de l’énergie qu’elle ingère pour son besoin d’entretien. L’importance de cette dépense non productive détermine fortement son efficience d’utilisation de l’énergie. Les nouvelles recommandations alimentaires de l’INRA permettent de mieux quantifier cette dépense non productive afin d’en maîtriser les principaux facteurs de variation. Une base de données a été constituée en regroupant 30 expérimentations, présentant notamment des niveaux alimentaires contrastés (soit au final 101 traitements expérimentaux), menées en stations expérimentales avec des vaches allaitantes. L’Énergie des dépenses non productives (EDNP) exprimée en énergie nette (UFL) a été calculée pour chaque traitement comme la différence entre l’énergie nette ingérée et celles des besoins de lactation, de gestation, et des variations de la masse corporelle par estimation de sa composition chimique. La production de lait moyenne est de 8 kg/jour et prioritaire, quel que soit le niveau alimentaire subit. Estimée par sa composition chimique (respectivement 37 et 21% de lipides), la valeur énergétique de la variation de poids s’élève en moyenne à 2,4 UFL/kg pour les multipares et 1,8 UFL/kg pour les primipares. Les dépenses non productives peuvent s’estimer à partir d’une seule équation dont les variables sont le besoin d’entretien (Eentretien), les conditions d’activité (Iact), la variation de poids (ΔPV) et l’état initial au vêlage (NEC) : EDNP = (Eentretien x Iact) + (0,0073 x ΔPVc x NEC). Le terme interférant (ΔPVc x NEC) traduit les adaptations du métabolisme en situation nutritionnelle contraignante ou pléthorique. Cette quantification nouvelle de l’épargne énergétique associée à la baisse des apports (ou l’inverse) permettra aux éleveurs de mieux gérer l’alimentation de leurs vaches. Les variations de dépenses non productives et leurs nombreux facteurs de variation devront devenir la cible des recherches dans les années à venir.

show abstract

“…Theoretical live weight and theoretical weight gain are calculated with a sub model which draws standard growth curves according to animal sex, age and production objective. These growth curves are based on equations exposed in Garcia and Agabriel (2008) for females (cows and three year old heifers) at fattening and for other animal classes on Gompertz functions defined in INRA (2007). In order to give flexibility to the model to adjust…”

Section: Animal Productionmentioning

confidence: 99%

On-Farm Weather Risk Management in Suckler Cow Farms: A Recursive Discrete Stochastic Programming Approach

Mosnier

Agabriel

Lherm

et al. 2011

Bio-Economic Models Applied to Agricultural Systems

Self Cite

View full text Add to dashboard Cite

Currently France wants to introduce a weather risk management framework into its agricultural policy for livestock farming. The aim of this paper is to better understand how on-farm risk reducing strategies modify the production system and profit distribution of French suckler cow enterprises. We present in this paper an original bioeconomic model that takes into account both risk anticipation and risk adjustments and that details biotechnical relationships between the different components of the beef cattle production system and their dynamics. On-farm risk management strategies are endogeneized under weather uncertainty and tested on real observed weather sequences. We simulate four scenarios characterized by different risk aversions and feed prices. Results emphasized that production adjustments, particularly the adjustments of area of grassland harvested and the possibility to purchase substitutes to on-farm forage production, improve farmers profit under weather variability. However, limiting the amplitude of these adjustments helps decreasing profit variability. All simulated long term decisions associated to risk reducing strategies encompass a reduction of long term stocking rate and the constitution of feed stocks. The impact of hay feed price on the market has similar effects on the long term strategy.

show abstract

CompoCow: a predictive model to estimate variations in body composition and the energy requirements of cull cows during finishing

Cited by 12 publications

References 28 publications

Changes in calculated residual energy in variable nutritional environments: An indirect approach to apprehend suckling beef cows’ robustness

Changes in calculated residual energy in variable nutritional environments: An indirect approach to apprehend suckling beef cows’ robustness

Prendre en compte l’efficience alimentaire des vaches allaitantes dans les recommandations alimentaires à travers la quantification de leurs dépenses non productives

On-Farm Weather Risk Management in Suckler Cow Farms: A Recursive Discrete Stochastic Programming Approach

Contact Info

Product

Resources

About