RESUMO
Hormone-based reproductive management programs can be beneficial to improve dairy cow's reproductive performance. This study aimed to compare the economic impact of reproductive management programs using systematic hormonal treatments to individual cows with a specific DIM range with a reproductive management program using cow-specific hormonal treatment based on a veterinary diagnosis of ovarian dysfunction during a fertility check. An existing individual cow-based, dynamic, and stochastic bio-economic simulation model, mimicking the production dynamics of a 200 cow-herd in daily time steps, was extended with ovarian dysfunction and fertility inputs. Four hormone-based reproductive management programs were modeled. In the default reproductive management program, reflecting the current reproductive management of Dutch herds, lactating dairy cows are inseminated based on detection of estrus and non-cyclic dairy cows are treated with hormones based on a veterinary diagnosis of ovarian dysfunction during a fertility check. Hormone treatments prescribed by the veterinarian for anestrus, cystic, and sub-estrus cows were an 8-d progesterone-releasing intravaginal device (PRID)-Synch protocol (PRIDsynch), an Ovsynch protocol, and a PGF2⺠treatment, respectively. The 3 other reproductive management programs reflected systematic hormonal treatments to cows at specific DIM and included a 1) Double-Ovsynch protocol for TAI with nonpregnant cows submitted to a resynchronization protocol (FTAI), 2) Double-Ovsynch protocol for TAI with nonpregnant cows detected in estrus or submitted to a resynchronization protocol (FTAI+ED), and 3) detection of estrus with cows not detected submitted to a PRIDsynch protocol (ED+TAI). All nonpregnant cows were submitted to a resynchronization protocol based on the absence (PRIDsynch) or presence (Ovsynch protocol) of a corpus luteum (CL). The annual mean net economic return (NER) was calculated for all reproductive management programs. Compared with the default reproductive management program, the highest NER was observed for the FTAI+ED reproductive management program with 23,764 higher net revenues, followed by the FTAI and the ED+TAI reproductive management programs with 19,550 and 14,314 higher net revenues, respectively. Overall, systematic hormone-based reproductive management programs gave higher costs due to more hormones administered and higher calving and feed costs due to more pregnant cows. Nevertheless, the additional revenues of milk and calves in the systematic hormone-based reproductive management programs outweighed the total cost. For instance, the FTAI+ED reproductive management program gave 8,953 higher total cost per year compared with the default but with 32,654 higher revenues. In summary, reproductive management programs where hormones were systematically used gave economic advantages over the current default reproductive management program in which hormones are administered to individual cows based on a veterinary diagnosis of ovarian dysfunction during a fertility check.
RESUMO
Animal welfare is becoming an important consideration in animal health-related decision-making. Integrating considerations of animal welfare into the decision-making process of farmers involves recognising the significance of health disorder impacts in relation to animal welfare. Yet little research quantifies the impact, making it difficult to include animal welfare in the animal health decision-making process. Quantifying the impact of health disorders on animal welfare is incredibly challenging due to empirical animal-based data collection constraints. An approach to circumvent these constraints is to rely on expert knowledge whereby perceived welfare impairment weights are indicative of the negative welfare effect. In this research, we propose an expertise-based method to quantify the perceived impact of sub-optimal mobility (SOM) on the welfare of dairy cows, because of its welfare importance. We first quantified perceived welfare impairment weights of SOM by eliciting expert knowledge using adaptive conjoint analysis (ACA). Second, using the perceived welfare impairment weights, we derived the perceived welfare disutility (i.e., perceived negative welfare effect) of mobility scores 1-5 (1 = optimal mobility, 5 = severely impaired mobility). Third, using the perceived welfare disutility per mobility score, we quantified the perceived welfare impact at case- and herd-level of SOM for different SOM severity. Results showed that perceived welfare disutility increased with each increase in mobility score. However, the perceived welfare impact of SOM cases with lower mobility scores was higher compared to SOM cases with higher mobility scores. This was because of the longer-lasting duration of the SOM cases with lower mobility scores. Moreover, the perceived herd-level welfare impact was largely due to SOM cases with lower mobility scores because of the longer duration and more frequent incidence compared to the SOM cases with higher mobility scores. These results entail that better welfare of dairy cows with respect to SOM can be achieved if lower mobility scores are detected and treated sooner. Our research demonstrates a novel approach that quantifies the perceived impact of health disorders on animal welfare when empirical evidence is limited.