Evaluation of a Cost-Effective Ammonia Monitoring System for Continuous Real-Time Concentration Measurements in a Fattening Pig Barn.

Ammonia (NH3) emission is one of the major environmental issues in livestock farming. Gas measurements are required to study the emission process, to establish emission factors, and to assess the efficiency of emission reduction techniques. However, the current methods for acquiring reference measurements of NH3 are either high in cost or labor intensive. In this study, a cost-effective ammonia monitoring system (AMS) was constructed from a commercially-available gas analyzing module based on tunable diode laser absorption (TDLA) spectroscopy. To cope with the negative measurement biases caused by differing inlet pressures, a set of correction equations was formulated. Field validation of the AMS on NH3 measurement was conducted in a fattening pig barn, where the system was compared to a Fourier-transform infrared (FTIR) spectroscopy analyzer. Under two test conditions in a fattening pig barn, the absolute error of the AMS measurements with respect to the average obtained values between the AMS and the FTIR was respectively 0.66 and 0.08 ppmv, corresponding to 5.9% and 0.5% relative error. Potential sources of the measurement uncertainties in both the AMS and FTIR were discussed. The test results demonstrated that the AMS was capable of performing high-quality measurement with sub-ppm accuracy, making it a promising cost-effective tool for establishing NH3 emission factors and studying NH3 emission processes in pig houses.

On-Farm Claw Scoring in Sows Using a Novel Mobile Device.

Claw lesions and lameness in sows are important problems in the industry as they impair sow welfare and result in economic losses. Available scoring techniques to detect claw lesions are all limited in terms of collecting data during all reproductive phases and recording all claws. The Mobile Claw Scoring Device (MCSD) was designed to address these limitations. After considering different practical situations and a design phase, two prototypes were constructed and tested. Improvements were incorporated into a final aluminium apparatus, consisting of two cameras with light-emitting diode (LED) lights mounted in a two-segment aluminium box and covered with laminated tempered glass plates. The operating system slides underneath the claws and takes video images. This final prototype was optimised and validated in an experiment with 20 hybrid sows, comparing scores for soiled claws using the MCSD against scores for clean claws using the Feet First© sow chute (as gold standard). Fifty percent of the scores differed between both scoring tools, with mainly medial claw digits deviating, but this seemed biologically irrelevant. The MCSD seems to be an appropriate alternative for on-farm claw scoring and is distinguishable from other claw scoring techniques; however, it needs further optimisation to improve the similarity between the two techniques.

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments.

Temporal Dynamics of Bacterial and Fungal Colonization on Plastic Debris in the North Sea.

Despite growing evidence that biofilm formation on plastic debris in the marine environment may be essential for its biodegradation, the underlying processes have yet to be fully understood. Thus, far, bacterial biofilm formation had only been studied after short-term exposure or on floating plastic, yet a prominent share of plastic litter accumulates on the seafloor. In this study, we explored the taxonomic composition of bacterial and fungal communities on polyethylene plastic sheets and dolly ropes during long-term exposure on the seafloor, both at a harbor and an offshore location in the Belgian part of the North Sea. We reconstructed the sequence of events during biofilm formation on plastic in the harbor environment and identified a core bacteriome and subsets of bacterial indicator species for early, intermediate, and late stages of biofilm formation. Additionally, by implementing ITS2 metabarcoding on plastic debris, we identified and characterized for the first time fungal genera on plastic debris. Surprisingly, none of the plastics exposed to offshore conditions displayed the typical signature of a late stage biofilm, suggesting that biofilm formation is severely hampered in the natural environment where most plastic debris accumulates.

Development of a Stereovision-Based Technique to Measure the Spread Patterns of Granular Fertilizer Spreaders.

Centrifugal fertilizer spreaders are by far the most commonly used granular fertilizer spreader type in Europe. Their spread pattern however is error-prone, potentially leading to an undesired distribution of particles in the field and losses out of the field, which is often caused by poor calibration of the spreader for the specific fertilizer used. Due to the large environmental impact of fertilizer use, it is important to optimize the spreading process and minimize these errors. Spreader calibrations can be performed by using collection trays to determine the (field) spread pattern, but this is very time-consuming and expensive for the farmer and hence not common practice. Therefore, we developed an innovative multi-camera system to predict the spread pattern in a fast and accurate way, independent of the spreader configuration. Using high-speed stereovision, ejection parameters of particles leaving the spreader vanes were determined relative to a coordinate system associated with the spreader. The landing positions and subsequent spread patterns were determined using a ballistic model incorporating the effect of tractor motion and wind. Experiments were conducted with a commercial spreader and showed a high repeatability. The results were transformed to one spatial dimension to enable comparison with transverse spread patterns determined in the field and showed similar results.

Spray Droplet Characterization from a Single Nozzle by High Speed Image Analysis Using an In-Focus Droplet Criterion.

Accurate spray characterization helps to better understand the pesticide spray application process. The goal of this research was to present the proof of principle of a droplet size and velocity measuring technique for different types of hydraulic spray nozzles using a high speed backlight image acquisition and analysis system. As only part of the drops of an agricultural spray can be in focus at any given moment, an in-focus criterion based on the gray level gradient was proposed to decide whether a given droplet is in focus or not. In a first experiment, differently sized droplets were generated with a piezoelectric generator and studied to establish the relationship between size and in-focus characteristics. In a second experiment, it was demonstrated that droplet sizes and velocities from a real sprayer could be measured reliably in a non-intrusive way using the newly developed image acquisition set-up and image processing. Measured droplet sizes ranged from 24 µm to 543 µm, depending on the nozzle type and size. Droplet velocities ranged from around 0.5 m/s to 12 m/s. The droplet size and velocity results were compared and related well with the results obtained with a Phase Doppler Particle Analyzer (PDPA).

Development of a High Irradiance LED Configuration for Small Field of View Motion Estimation of Fertilizer Particles.

Better characterization of the fertilizer spreading process, especially the fertilizer pattern distribution on the ground, requires an accurate measurement of individual particle properties and dynamics. Both 2D and 3D high speed imaging techniques have been developed for this purpose. To maximize the accuracy of the predictions, a specific illumination level is required. This paper describes the development of a high irradiance LED system for high speed motion estimation of fertilizer particles. A spectral sensitivity factor was used to select the optimal LED in relation to the used camera from a range of commercially available high power LEDs. A multiple objective genetic algorithm was used to find the optimal configuration of LEDs resulting in the most homogeneous irradiance in the target area. Simulations were carried out for different lenses and number of LEDs. The chosen configuration resulted in an average irradiance level of 452 W/m² with coefficient of variation less than 2%. The algorithm proved superior and more flexible to other approaches reported in the literature and can be used for various other applications.

High speed stereovision setup for position and motion estimation of fertilizer particles leaving a centrifugal spreader.

A 3D imaging technique using a high speed binocular stereovision system was developed in combination with corresponding image processing algorithms for accurate determination of the parameters of particles leaving the spinning disks of centrifugal fertilizer spreaders. Validation of the stereo-matching algorithm using a virtual 3D stereovision simulator indicated an error of less than 2 pixels for 90% of the particles. The setup was validated using the cylindrical spread pattern of an experimental spreader. A 2D correlation coefficient of 90% and a Relative Error of 27% was found between the experimental results and the (simulated) spread pattern obtained with the developed setup. In combination with a ballistic flight model, the developed image acquisition and processing algorithms can enable fast determination and evaluation of the spread pattern which can be used as a tool for spreader design and precise machine calibration.

Factors influencing claw lesion scoring in sows.

Claw lesions have a multifactorial origin and may affect sow welfare and farm profitability. However, estimating the precise impact is hampered by several factors that interfere with the accuracy of claw lesion assessment. The objective of this study was to determine the impact of observer, scoring condition and claw cleanliness on claw lesion scoring in sows. The first experiment evaluated the impact of observer by calculating the inter- and intra-observer reliability during three test sessions using photographs. The second experiment evaluated the impact of observer, scoring condition (Feet First© chute of Zinpro Corp., "sow chute" vs. Mobile Claw Scoring Device, "MCSD"), and claw cleanliness (clean or soiled claws) on claw lesion scoring. For this experiment, 20 hybrid mid-gestating sows were hoisted up using the sow chute in which the MCSD was positioned. Lateral and medial claw digits of both hind claws were scored for heel horn erosion and separations along the heel/sole junction and white line. Scores were given by drawing a vertical bar on a 160 mm tagged visual analogue scale (tVAS); the severity of a claw lesion type was determined by measuring the distance from 0 mm. Four scores per sow were collected and analysed: clean claws × MCSD video recordings, soiled claws × MCSD video recordings, clean claws × visual scoring in a sow chute, and soiled claws × visual scoring in a sow chute. In both experiments, observer had an impact on the claw lesion scores. The inter-observer reliability was highest for overgrown dewclaws and lowest for the horizontal wall cracks (0.84 and 0.35, resp.). The highest intra-observer reliability was found for overgrown dewclaws and heel horn erosion (0.89) and lowest for vertical wall cracks (0.64). Furthermore, scoring condition and claw cleanliness influenced the scores in the second experiment and the limits of agreements were high (23.5-58.9 mm). The improved concordance correlation coefficient (iCCC) was highest for the heel horn erosion scores. In conclusion, the impact of observer seemed less relevant for claw lesion scoring; however, claw cleanliness and scoring condition were important and cannot be used interchangeably.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares.

Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate.

Daily lying time, motion index and step frequency in dairy cows change throughout lactation.

Lying behaviour in dairy cows has the potential to be used for welfare assessment or problem detection, but knowledge about variation in normal lying behaviour is scarce. Accelerometer data were collected at four Danish farms from 366 Holstein dairy cows in loose-housing systems in 2008 and 2009. Daily lying time decreased steeply during early lactation to a minimum around four weeks after calving, followed by a steady increase towards the end of lactation. Motion index and step frequency during walking exhibited a similar pattern. An adapted version of Wilmink's function for lactation curves was used to model these behaviours in relation to days in milk. The results demonstrate the importance of including information about days in milk when interpreting data on lying behaviour and activity.