RESUMO
The aims of this work were to study on dairy farm conditions: i) the repeatability of long-term enteric CH4 emissions measurement from lactating dairy cows using GreenFeed (GF); ii) the ranking of dairy cows according to their CH4 emissions across diets. Forty-five Holstein lactating dairy cows were randomly assigned to 3 equivalent groups at the beginning of their lactation. The experiment was composed of 3 successive periods: i) pre-experimental period (weeks 1 to 5) in which all cows received a common diet; ii) a dietary treatment transition period (weeks 6 to 10); and iii) an experimental period (weeks 11 to 26) in which each group was fed a different diet. Experimental diets were formulated to generate more or less CH4 production: i) a diet based on ryegrass silage and concentrates, low in starch and lipid, designed to induce high CH4 emissions (CH4+); ii) a diet based on maize silage and concentrates, rich in starch, designed to induce intermediate CH4 emissions (CH4int); iii) a diet based on maize silage and concentrates, rich in starch and lipid, designed to induce low CH4 emissions (CH4-). Gas emissions were individually measured using GF systems. Repeatability of gas emissions, dry matter intake (DMI) and dairy performances measurements was calculated from data averaged over 1, 2, 4, and 8 weeks for each animal. Hierarchical cluster analysis was performed to rank individual animals according to their CH4 emissions. No significant differences were observed for daily CH4 emissions (g/day) among diets, because of lower DMI of CH4+ cows. When CH4 emissions were referred to units of DMI or milk, the differences among diets emerged as significant and persistent over the observed period of lactation. Repeatability values of gas emissions measurements were higher than 0.7 averaged over 8 weeks of measurement, but still higher than 0.6 for CH4 g/day, CO2 g/day, CH4 g/kg milk, and CH4/CO2 even averaging only 2 weeks of measurement. The repeatability of CH4 emissions measurement was systematically lower than those of DMI or dairy performance parameters, like milk and FPCM yield, irrespective of the averaged measurement period. The dairy cow ranking was not stable over time between all individuals or within any of the diets. In our experimental conditions, the GF performance in the long term can be considered reliable in differentiating dairy herds by their CH4 emissions according to diets with different methanogenic potential, but did not allow the ranking of individual dairy cows within a same diet. Our data highlight the importance of phenotyping animals across environment in which they will be expected to perform.
Assuntos
Monitorização de Parâmetros Ecológicos/métodos , Microbioma Gastrointestinal/fisiologia , Efeito Estufa/prevenção & controle , Metano/biossíntese , Silagem , Animais , Variação Biológica da População , Bovinos , Monitorização de Parâmetros Ecológicos/estatística & dados numéricos , Fazendas/estatística & dados numéricos , Feminino , Lactação/metabolismo , Rúmen/metabolismo , Rúmen/microbiologiaRESUMO
Considerable technological advances have been made in the automated detection of estrus in dairy cattle, but few studies have evaluated their relative performance on the same animals or assessed cow-related factors that affect their performance. Our objective was to assess the performance and reliability of three devices commercially available in France for cow estrus detection. The devices were a pedometer (PM; Afitag) and two activity meters (AM1; Heatime-RuminAct, and AM2; HeatPhone). Two algorithms were tested for AM2. We fitted 63 lactating Holstein cows with the three detectors from calving to 90 days after calving. The onset and pattern of cyclicity were monitored from 7 to 90 days postpartum measuring progesterone concentration in milk twice weekly. A total of 211 ovulations were identified. Cyclicity was classified as normal in 60% of cows (38/63). Calculated over the operating period of all the devices (179 periods of estrus), the sensitivities and positive predictive values were, respectively, 71% and 71% for PM, 62% and 84% for AM1, 61% and 67% for the first algorithm of AM2, and 62% and 87% for the second algorithm of AM2. Both activity meters had a lower sensitivity but a higher positive predictive value than the PM (P < 0.05). For all devices, the performance in estrus detection was much poorer at the first postpartum ovulation than at subsequent ovulations (P < 0.05). Lactation rank and milk production affected some devices (P < 0.05). These devices could be used to reinforce visual observations, especially after 50 days postpartum, the minimum recommended delay to insemination. However, their full benefit remains to be verified in different farming systems and taking into account the specific objectives of the dairy farmer.