Evaluating machine learning algorithms to predict lameness in dairy cattle.

Dairy cattle lameness represents one of the common concerns in intensive and commercial dairy farms. Lameness is characterized by gait-related behavioral changes in cows and multiple approaches are being utilized to associate these changes with lameness conditions including data from accelerometers, and other precision technologies. The objective was to evaluate the use of machine learning algorithms for the identification of lameness conditions in dairy cattle.

InsectSound1000 An insect sound dataset for deep learning based acoustic insect recognition.

InsectSound1000 is a dataset comprising more than 169000 labelled sound samples of 12 insects. The insect sound level spans from very loud (Bombus terrestris) to inaudible to human ears (Aphidoletes aphidimyza). The samples were extracted from more than 1000 h of recordings made in an anechoic box with a four-channel low-noise measurement microphone array.

Influence of the urease inhibitor suspension (Atmowell) on the fluorescent dye pyranine and its spray and drift behavior in wind tunnel measurements.

Too many ammonia emissions are released into the environment from cattle farming. These damage the environment and have an impact on animal and human health. Ammonia Emissions could be reduce by urease inhibitors.

Amount and variation of strip yields collected by a defined hand-milking method after machine milking of Holstein dairy cows.

Hand-milking methods to assess the completeness of milking in dairy cows need to be reliable as well as quick to apply in order to avoid delays in group milking parlours. A previous study comparing different methods demonstrated that a defined milking handgrip with a strip frequency of 1 Hz was most suitable to assess the completeness of milk-out in dairy cows. In a first step, the present study aimed to investigate how much milk can be hand-milked by the defined handgrip, strip frequency and within a time limit of 15 s per quarter.

Transcriptome analysis of North American sweet birch (Betula lenta) revealed a higher expression of genes involved in the biosynthesis of secondary metabolites than European silver birch (B. pendula).

The North American Betula lenta L. (sweet birch) has been used for medicinal reasons for centuries by native Americans. Although sophisticated technologies have rapidly been developed, a large information gap has been observed regarding genetic regulators of medicinally important compounds in sweet birch.

Identification and analysis of key genes involved in methyl salicylate biosynthesis in different birch species.

Species of the perennial woody plant genus Betula dominate subalpine forests and play a significant role in preserving biological diversity. In addition to their conventional benefits, birches synthesize a wide range of secondary metabolites having pharmacological significance. Methyl salicylate (MeSA) is one of these naturally occurring compounds constitutively produced by different birch species.

Low-Input Estimation of Site-Specific Lime Demand Based on Apparent Soil Electrical Conductivity and In Situ Determined Topsoil pH.

Site-specific liming helps increase efficiency in agricultural production. For adequate determination of the lime demand, a combination of apparent soil electrical conductivity (EC) and topsoil pH can be used. Here, it was hypothesized that this can also be done at low-input level.

Accuracy and application of milk fatty acid estimation with diffuse reflectance near-infrared spectroscopy.

Near infrared spectroscopy (NIRS) has the potential to estimate contents of fatty acids (FA) in milk frequently at-farm or during daily milking routine. In this study, a total of 738 raw milk spectra collected from 33 Holstein cows over a period of 30 weeks were recorded. Reference data on FA composition in milk and in milk fat were analysed in laboratory.

Effect of a multi-sided concave liner barrel design on thickness and roughness of teat-end hyperkeratosis.

In a round liner barrel, the force of the closing liner is transferred by the two opposite sides of the liner wall to the teat apex. Liners with a multi-sided barrel shape close at three or more planes and distribute their force to a larger area of the teat apex. The objective of the study was to investigate effects of a liner with a multi-sided concave barrel design on the degree of teat-end hyperkeratosis, thickness and roughness, and on the time delay until thickness or roughness of teat-end hyperkeratosis responded to the experimental liner.

Rumination activity of dairy cows in the 24 hours before and after calving.

Monitoring rumination behavior serves multiple purposes in feeding and herd management of dairy cows. The process of calving is a major event for cows, and a detailed understanding of alterations in behavioral patterns of animals in the time around calving is important in calving detection. The objective of this study was to describe the short-term changes in rumination patterns in dairy cows immediately before and after parturition.

Robustness of near-infrared calibration models for the prediction of milk constituents during the milking process.

The robustness of in-line raw milk analysis with near-infrared spectroscopy (NIRS) was tested with respect to the prediction of the raw milk contents fat, protein and lactose. Near-infrared (NIR) spectra of raw milk (n = 3119) were acquired on three different farms during the milking process of 354 milkings over a period of six months. Calibration models were calculated for: a random data set of each farm (fully random internal calibration); first two thirds of the visits per farm (internal calibration); whole datasets of two of the three farms (external calibration), and combinations of external and internal datasets.

NIRS-aided monitoring and prediction of biogas yields from maize silage at a full-scale biogas plant applying lumped kinetics.

The aim of this study was to apply near-infrared spectroscopy (NIRS), available biogas plant data and lumped degradation kinetics to predict biogas production (BPr) of maize silage. A full-scale agricultural biogas plant was equipped with NIRS-metrology at the feeding station. Continuously NIR-spectra were collected for 520 d.

Use of near infrared spectroscopy in online-monitoring of feeding substrate quality in anaerobic digestion.

In order to keep the anaerobic process stably and uniformly producing biogas it needs to be supplied with either an even amount of substrate of stable quality or varying amounts according to variations in quality. Feeding amounts are usually adjusted manually as a reaction to changing rates of biogas production. Continuous information about the actual substrate quality is not available and feedstuff analyses are costly.

Use of near infrared spectroscopy in monitoring of volatile fatty acids in anaerobic digestion.

Recently biogas production from agricultural sources has rapidly developed. Therefore the demands on biogas plants to optimise the efficiency of the anaerobic digestion (AD) process have grown immensely. At present there is no online-supervision tool available to monitor the AD process, but costly and time-consuming chemical analyses are necessary.

Development of a dynamic model to predict PM10 emissions from swine houses.

Influences on dust emissions from livestock operations are number, weight, and kind of animals and characteristics of the housing system. Differences between facilities cannot be explained solely by mechanistic input variables. The objective of this study was to characterize the main input variables for modeling emissions of particulate matter with a mass median diameter < or = 10 microm (PM10) from swine facilities using a data-based model.