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Vibration emissions during the transport of boar semen for artificial insemination (AI) affect sperm quality. In the present study, the common influence of the following factors was investigated: vibrations (displacement index (Di) = 0.5 to 6.0), duration of transport (0 to 12 h) and storage time (days 1 to 4). Normospermic ejaculates were collected from 39 fertile Pietrain boars (aged 18.6 ± 4.5 months) and diluted in a one-step procedure with an isothermic (32 °C) BTS (Minitüb) extender (n = 546 samples). Sperm concentration was adjusted to 22 × 106 sperm·mL−1. Extended semen (85 ± 1 mL) was filled into 95 mL QuickTip Flexitubes (Minitüb). For transport simulation on day 0, a laboratory shaker IKA MTS 4 was used. Total sperm motility (TSM) was evaluated on days 1 to 4. Thermo-resistance test (TRT), mitochondrial activity (MITO) and plasma membrane integrity (PMI) were assessed on day 4. Sperm quality dropped with increasing vibration intensity and transport duration, and the effect was enhanced by a longer storage time. A linear regression was performed using a mixed model, accounting for the boar as a random effect. The interaction between Di and transport duration significantly (p < 0.001) explained data for TSM (−0.30 ± 0.03%), TRT (−0.39 ± 0.06%), MITO (−0.45 ± 0.06%) and PMI (−0.43 ± 0.05%). Additionally, TSM decreased by 0.66 ± 0.08% with each day of storage (p < 0.001). It can be concluded that boar semen extended in BTS should be transported carefully. If this is not possible or the semen doses are transported a long way, the storage time should be reduced to a minimum.

In the modern pig reproduction system, artificial insemination (AI) doses are delivered from AI centers to sow farms via logistics vehicles. In this study, six breeding companies in three countries (Brazil, Germany, and the USA) were interviewed about their delivery process. It was found that there is currently no comprehensive monitoring system for the delivery of semen. The entire process “shipping of boar semen” was documented using Business Process Model and Notation (BPMN). Although it is not currently known which vibrations occur at all, it is suspected that vibration emissions affect the quality of boar semen. For this reason, a prototype of a measuring system was developed to calculate a displacement index (Di), representing vibration intensities. Vibrations were analyzed in standardized road trials (n = 120) on several road types (A: smooth asphalt pavement, B: rough asphalt pavement, C: cobblestone, and D: dirt road) with different speeds (30, 60, 90, 120, and 150 km/h). A two-way ANOVA showed significant differences in mean Di, depending on road surface and speed as well as an interaction of both factors (p < 0.001). A field study on a reference delivery from a German AI center to several sow farms indicated that 33% of the observed roads are in good quality and generate only a few vibrations (Di ≤ 1), while 40% are of a moderate quality with interrupted surfaces (Di = 1–1.5). However, 25% of the roads show markedly increased vibrations (Di ≥ 1.5), as a consequence of bad conditions on cobblestones or unpaved roads. Overall, more attention should be paid to factors affecting sperm quality during transport. In the future, an Internet of Things (IoT) based solution could enable complete monitoring of the entire transport process in real time, which could influence the courier’s driving behavior based on road conditions in order to maintain the quality of the transported AI doses.

Recent technologies allowed a major growth of geographical datasets with different levels of detail, different point of views, and different specifications, but on the same geographical extent. These datasets need to be integrated in order to benefit from their diversity. Conflation is one of the solutions to provide integration. Conflation aims at combining data that represent same entities from several datasets, into a richer new dataset. This paper proposes a framework that provides a geometrical conflation that preserves the characteristic shapes of geographic data. The framework is based on least squares adjustment, inspired from least squares based generalization techniques. It does not require very precise pre-matching, which is interesting as automatic matching remains a challenging task. Several constraints are proposed to preserve different kind of shape and relations between features, while conflating data. The framework is applied to a real land use parcels conflation problem with excellent results. The least squares based conflation is evaluated, notably with comparisons with existing techniques like rubber sheeting. The paper also describes how the framework can be extended to other geometrical optimization problems.

External-cavity quantum cascade lasers (EC-QCL) are now established as versatile wavelength-tunable light sources for analytical spectroscopy in the mid-infrared (MIR) spectral range. We report on the realization of rapid broadband spectral tuning with kHz scan rates by combining a QCL chip with a broad gain spectrum and a resonantly driven micro-opto-electro-mechanical (MOEMS) scanner with an integrated diffraction grating in Littrow configuration. The capability for real-time spectroscopic sensing based on MOEMS EC-QCLs is demonstrated by transmission measurements performed on polystyrene reference absorber sheets, as well as on hazardous substances, such as explosives. Furthermore, different applications for the EC-QCL technology in spectroscopic sensing are presented. These include the fields of process analysis with on- or even inline capability and imaging backscattering spectroscopy for contactless identification of solid and liquid contaminations on surfaces. Recent progress in trace detection of explosives and related precursors in relevant environments as well as advances in food quality monitoring by discriminating fresh and mold contaminated peanuts based on their MIR backscattering spectrum is shown.