Spatial Variability of Ammonia Concentrations in an Open-Sided Dairy Barn

D’Urso, Provvidenza Rita; Arcidiacono, Claudia; Cascone, Giovanni

doi:10.1007/978-3-030-98092-4_9

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…The diurnal pattern for CO 2 and CH 4 with maxima at nighttime was also reported by [27,29]. The diurnal pattern for NH 3 with maximum concentrations around noon was also reported by [30] and can be explained by the higher ammonia evaporation rates with higher temperatures, as reported, e.g., by [31], with higher temperatures at daytime, and also by the activity pattern of the animals, resulting in higher urination activity in the daytime and thus a higher NH 3 evaporation potential. The low-cost system was able to capture these diurnal patterns.…”

Section: Discussionsupporting

confidence: 69%

A Low-Cost Wireless Sensor Network for Barn Climate and Emission Monitoring—Intermediate Results

Janke,

Bornwin,

Coorevits

et al. 2023

Atmosphere

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A barn’s climate is vital for animal welfare and emissions control, including greenhouse gases like methane (CH4) and carbon dioxide (CO2) and environmental gases like ammonia (NH3). The goal of this study was to investigate a developed low-cost online tool for monitoring barn climate and air pollutant emissions (OTICE) in naturally ventilated barns. OTICE employed a wireless sensor network with low-cost sensors for gases and climate variables, allowing scalable use across multiple barns. We evaluated the sensors for CO2, NH3, and CH4 for accuracy, both in controlled lab conditions and in a dairy barn in Germany, where measurements were carried out continuously for a duration of 12 days. For the averaged concentration levels over the measurement period, the low-cost sensors agreed well with the reference system, with relative deviations lower than 7% for all three gases, with maximum peak deviations up to 32% for CO2, 67% for NH3, and 65% for CH4, with strong Spearman correlations for CO2 and NH3 (ρCO2 = 0.8, ρNH3 = 0.68) and a rather weak correlation for CH4 with ρCH4 = 0.24. Further calibration and stability investigations are required, especially for CH4 sensing. However, the overall good results for NH3 and especially CO2 measurements indicate a huge potential of the low-cost system as a valuable tool for monitoring relative NH3 emission levels and the measurement of air exchange rates in naturally ventilated barns.

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Section: Discussionsupporting

confidence: 69%

A Low-Cost Wireless Sensor Network for Barn Climate and Emission Monitoring—Intermediate Results

Janke,

Bornwin,

Coorevits

et al. 2023

Atmosphere

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“…Moreover, a further evaluation should consider a dairy barn equipped with sprinklers or fogging systems, especially in Mediterranean areas where these systems provide cooling to the animals to reduce their heat stress [ 40 , 41 ]. The presence of the cooling system may increase the negative effects on the accuracy of the measurements.…”

Section: Discussionmentioning

confidence: 99%

Assessment of a UWB Real Time Location System for Dairy Cows’ Monitoring

D’Urso

Arcidiacono

Pastell

et al. 2023

Sensors

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In the field of precision livestock farming, many systems have been developed to identify the position of each cow of the herd individually in a specific environment. Challenges still exist in assessing the adequacy of the available systems to monitor individual animals in specific environments, and in the design of new systems. The main purpose of this research was to evaluate the performance of the SEWIO ultrawide-band (UWB) real time location system for the identification and localisation of cows during their activity in the barn through preliminary analyses in laboratory conditions. The objectives included the quantification of the errors performed by the system in laboratory conditions, and the assessment of the suitability of the system for real time monitoring of cows in dairy barns. The position of static and dynamic points was monitored in different experimental set-ups in the laboratory by the use of six anchors. Then, the errors related to a specific movement of the points were computed and statistical analyses were carried out. In detail, the one-way analysis of variance (ANOVA) was applied in order to assess the equality of the errors for each group of points in relation to their positions or typology, i.e., static or dynamic. In the post-hoc analysis, the errors were separated by Tukey’s honestly significant difference at p > 0.05. The results of the research quantify the errors related to a specific movement (i.e., static and dynamic points) and the position of the points (i.e., central area, perimeter of the investigated area). Based on the results, specific information is provided for the installation of the SEWIO in dairy barns as well as the monitoring of the animal behaviour in the resting area and the feeding area of the breeding environment. The SEWIO system could be a valuable support for farmers in herd management and for researchers in the analysis of animal behavioural activities.

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