The magnitude of public concerns about agricultural innovations has often been underestimated, as past examples, such as pesticides, nanotechnology, and cloning, demonstrate. Indeed, studies have proven that the agricultural sector presents an area of tension and often attracts skepticism concerning new technologies. Digital technologies have become increasingly popular in agriculture. Yet there are almost no investigations on the public acceptance of digitalization in agriculture so far. Our online survey provides initial insights to reduce this knowledge gap. The sample (n = 2012) represents the German population in terms of gender, age (minimum 18 years), education and size of place of residence. Results showed that if the potential of digital farming technologies (DFT) regarding animal welfare and environmental protection was described, respondents reacted positively. Thus, the general attitudes of respondents toward the benefits of DFT were mostly positive. The approval to increasing adoption rates of particular DFT by providing subsidies was also high. Linear regression models showed that the dominant positive influences on respondents' attitudes toward the benefits of DFT were a generally positive attitude toward farming and a strong trust in farmers in Germany. Confronting respondents with pictures showing DFT resulted in many spontaneous negative associations and general criticism of agricultural production. The latter holds true for DFT in animal husbandry in particular. However, as agriculture as a whole is criticized by many groups in Germany, it is unlikely that benefits from digitalization will significantly increase the public acceptance of agriculture as a whole.
Although estrus detection makes a relevant contribution to the reproductive performance of dairy cattle, studies on the economic evaluation of automatic estrus detection systems are rare. The objective of the present study is to provide an economic evaluation of activity meters used for estrus detection. The effect of different estrus detection rates on gross margins was modeled with SimHerd (SimHerd A/S, Viborg, Denmark). The analysis considers all costs associated with the investment in activity meters. The economic evaluation was carried out through simulation of Simmental herds with yearly milk yields of 7,000 or 9,000 kg and Holstein Friesian herds with yearly milk yields of 9,000 or 11,000 kg, each with herd sizes of 70 or 210 cows. Furthermore, we distinguished between 2 investment scenarios. In scenario 1, only cows are equipped with activity meters for estrus detection, whereas scenario 2 assumes that cows and heifers are equipped with activity meters. Because existing empirical information for some variables shows significant variability (estrus detection rates, time for estrus detection), they were modeled with distributions using the Monte Carlo method in @ RISK (Palisade Corporation, Ithaca, NY), allowing us to model a probability distribution of net returns (NR) of investment in activity meters for estrus detection. The simulation results show that the average NR of investment in activity meters for estrus detection over all scenarios ranges from +€7 to +€40 per cow per year for the Simmental breed, and from +€19 to +€46 per cow per year for the Holstein Friesian breed. Generally, the NR depends on the milk production level assumed. For the Simmental breed, depending on the scenario, the simulation results show a 54 to 200% larger average NR of investment in activity meters for estrus detection with a milk yield of 9,000 kg/yr compared with 7,000 kg/yr. For the Holstein Friesian breed, the effect of the modeled milk yield on the NR is much less pronounced. Average NR of investment in activity meters are greater for larger herd sizes because of cost degression effects. An additional equipping of heifers has, on average, a positive effect on the economics of activity meters for estrus detection because of the resulting reduction in the age at first calving. Considering all scenarios, the probability of a positive NR of investment in activity meters ranges between 74 and 98% for the Simmental breed and between 85 and 99% for the Holstein Friesian breed.
Studies evaluating calving sensors provided evidence that attaching the sensor to the tail may lead to changes in the cows’ behavior. Two different calving sensors were attached to 18 cows, all of which were equipped with a rumen bolus to record their activity. Two methodological approaches were applied to detect potential behavioral changes: analysis of homogeneity of variance in cow activity (5 days pre-sensor and 24 h post-sensor) and analysis of video-recorded behavior (12 h pre- and post-sensor, respectively) in a subgroup. The average results across the sample showed no significant changes in the variability of activity and no statistically significant mean differences in most visually analyzed behaviors, namely walking, eating, drinking, social interaction, tail raising, rubbing the tail, and the number of standing and lying bouts after calving sensor attachment. In addition to considering mean values across all cows, individual cow investigations revealed an increased number of time slots showing a significant increase in the variability of activity and an increased frequency of tail raising and rubbing the tail on objects after calving sensor attachment in some cows, which should be investigated in more detail on a larger scale.
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