Improving lameness detection in cows: A machine learning algorithm application.

The deployment of diverse data-generating technologies in livestock farming holds the promise of early disease detection and improved animal well-being. In this paper, we combine routinely collected dairy farm and herd data with weather and high-frequency sensor data from 6 farms to predict new lameness events in various future periods, spanning from the following day to 3 wk. A Random Forest classifier, using input features selected by the Boruta algorithm, was used for the prediction task; effects of individual features were further assessed using partial dependence plots.

Exploiting the pH-Cross Sensitivity of Ion-Selective Optodes to Broaden Their Response Range.

While the pH cross-sensitivity of chromoionophore-based ion-selective optodes (ISOs) has often been regarded as a significant limitation, this paper demonstrates how this apparent drawback can be transformed into a beneficial feature. The response range of chromoionophore-based ISOs shifts proportionally with changes in the sample pH. Thus, integrating them with a stable pH gradient across the optode surface, such as those provided by immobilized pH gradient (IPG) gels, allows for significant enhancement of the effective measuring range of chromoionophore-based ISOs while preserving their maximum sensitivity.

Timing matters: the overlooked issue of response time mismatch in pH-dependent analyte sensing using multiple sensors.

Accurate measurement of pH-dependent analytes is crucial for a wide range of applications, including environmental monitoring, industrial processes, and healthcare diagnostics. In multi-sensor systems, combining data from multiple sensors offers the potential for more comprehensive analysis, yet it is important to be aware of the limitations of this approach. In this paper, we investigate the often-overlooked issue of response time mismatch among sensors, which can introduce significant errors in calculated sum parameters.

A 2-year study reveals implications of feeding management and exposure to mycotoxins on udder health, performance, and fertility in dairy herds.

We recently reported the ubiquitous occurrence of mycotoxins and their secondary metabolites in dairy rations and a substantial variation in the feeding management among Austrian dairy farms. The present study aimed to characterize to which extent these factors contribute to the fertility, udder health traits, and performance of dairy herds. During 2019 and 2020, we surveyed 100 dairy farms, visiting each farm 2 times and collecting data and feed samples.

Imaging of CO and Dissolved Inorganic Carbon via Electrochemical Acidification-Optode Tandem.

Dissolved inorganic carbon (DIC) is a key component of the global carbon cycle and plays a critical role in ocean acidification and proliferation of phototrophs. Its quantification at a high spatial resolution is essential for understanding various biogeochemical processes. We present an analytical method for 2D chemical imaging of DIC by combining a conventional CO optode with localized electrochemical acidification from a polyaniline (PANI)-coated stainless-steel mesh electrode.