This paper reviews the environmental impact of current livestock practices and discusses the advantages offered by Precision Livestock Farming (PLF), as a potential strategy to mitigate environmental ...risks.
PLF is defined as: “the application of process engineering principles and techniques to livestock farming to automatically monitor, model and manage animal production”. The primary goal of PLF is to make livestock farming more economically, socially and environmentally sustainable and this can be obtained through the observation, interpretation of behaviours and, if possible, individual control of animals. Furthermore, adopting PLF to support management strategies, may lead to the reduction of the environmental impact of farms. Currently, few studies reported PLF efficacy in reducing the environmental impact, however further studies are necessary to better analyze the actual potential of PLF as a mitigation strategy.
Literature shows the potentiality of the application of PLF, as the introduction of PLF in farms can lead to a reduction of Greenhouse gases (GHG) and ammonia (NH3) emission in air, nitrates and antibiotics pollution in water bodies, phosphorus, antibiotics and heavy metals in the soil.
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•PLF allows to monitor, model and control continuously animal bio-responses.•PLF, optimizing livestock performance, indirectly reduces environmental impact.•More positive effects of PLF on air, water and soil should be further investigated.•PLF could enter fully-fledged among BATs, if its potential will be confirmed.
Biotrickling filter (BTF) is often used for purification of waste gas from swine houses, with vital information still needed regarding interaction effects among multiple gas pollutants removal and ...also the formation of byproducts especially nitrous oxide (N2O, a strong greenhouse gas) due to the relative high NH3 concentration level compared to other gases. In this study, gas removal and N2O production were compared between two BTFs, where the inlet gas of BTF-1 contained NH3 and H2S while p-cresol was additionally supplied to BTF-2. At inlet load (IL) between 3.67 and 18.91 g m−3 h−1, removal efficiencies of NH3 exceeded 95% for both BTFs. As alternative strategy, adding thiosulfate improved H2S removal. Interestingly, presence of p-cresol to some extent promoted H2S removal at IL of 0.56 g m−3 h−1possibly due to effect on pH value of circulating solution. Similar to NH3, removal efficiencies of p-cresol were higher than 95% at an average IL of 2.98 g m−3 h−1. Gas residence time, pH of circulating solution and inlet loading were identified as key factors affecting BTF performance, but the response of individual gas compound to these factors was not consistent. Overall, p-cresol enhanced N2O generation although the effects were not always significant. High-throughput sequencing results showed that Proteobacteria accounted for the largest proportion of relative abundance and BTF-2 had much richer microbial diversity compared to BTF-1. Thermomonas, Comamonas, Rhodanobacter and other bacterial genus capable of denitrification were detected in both BTFs, and their corresponding abundances in BTF-2 (10.9%, 8.7% and 5.2%) were all greater than those in BTF-1 (0.4%, 0.3% and 2.0%), indicating that more denitrification may occur within BTF-2 and higher N2O could have been generated. This study provided evidence that organic gas components, served as carbon source, may increase the N2O production from BTF when treating waste gases containing NH3.
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•Interactions among NH3, H2S and p-cresol removal were investigated in BTF.•The presence of p-cresol promoted H2S removal, with no clear effects on NH3.•N2O was inevitably generated along with the removal of NH3, H2S and p-cresol.•p-cresol may serve as carbon source to microbes, further increasing the N2O production.•Relative abundance of microbial genus towards denitrification increased when p-cresol presented.
Lameness in dairy cattle is a clinical sign of impaired locomotion, mainly caused by painful foot lesions, compromising the US dairy industry's economic, environmental, and social sustainability ...goals. Combining technology and on farm data may be a more precise and less labor-intensive lameness detection tool, particularly for early detection. The objective of this observational study was to describe the association between average weekly autonomous camera-based (AUTO) locomotion scores and hoof trimming (HT) data. The AUTO data were collected from 3 farms from April 2022 to March 2023. Historical farm HT data were collected from March 2016 to March 2023 and used to determine cow lesion history and date of HT event. The HT events were categorized as a regular HT (TRIM; n = 2290) or a HT with a lesion recorded (LESION; n = 670). Events with LESION were sub-categorized based on lesion category: digital dermatitis (DD; n = 276), sole ulcer (SU; n = 79), white line disease (WLD; n = 141), and other (n = 174). The data also contained the leg of the LESION, classified as front left (FL; n = 54), front right (FR; n = 146), rear left (RL; n = 281), or rear right (RR; n = 183) leg with 6 events missing the leg. Cows' HT histories were classified as follows: cows with no previous recorded instance of any lesion were classified as TRIM0 (n = 1554). The first instance of any hoof lesion was classified as LESION1 (n = 238). This classification was retained until a subsequent TRIM occurred - recorded as TRIM1 (n = 632). The next unique instance of any lesion following a TRIM1 was classified as LESION2 (n = 86). Any LESION events occurring after LESION1 or LESION2 without a subsequent TRIM were considered a hoof lesion recurrence and classified as LESIONRE1 (n = 164) and LESIONRE2 (n = 22), respectively. TRIM events after LESION2 or LESION2RE (n = 104) or LESION events after LESIONRE1 or LESIONRE2 were classified as LESION_OTHER (n = 160). The AUTO scores from −28 to −1 days prior to the HT event were summarized into weekly scores and included if cows had at least 1 observation per week in the 4 weeks before the event. For all weeks, LESION cows had a higher median AUTO score than TRIM cows. Cows with TRIM0 had the lowest and most consistent median weekly score compared to LESION and other TRIM classifications. Before HT cows with TRIM0 and TRIM1, both had median score increases of 1 across the 4 weeks, while the LESION categories had an increase of 4 to 8. Scores increased with each subsequent LESION event compared to the previous LESION event. Cows with SU lesions had the highest median score across the 4 weeks, WLD had the largest score increase, and DD had the lowest median score and score increase. When grouping a LESION event by leg the hoof lesion was found on, the AUTO scores for four groups displayed comparable median values. Due to the difference between TRIM and LESION events, this technology shows potential for the early detection of hoof lesions.
Digitalisation is an integral part of modern agriculture. Several digital technologies are available for different animal species and form the basis for precision livestock farming. However, there is ...a lack of clarity as to which digital technologies are currently used in agricultural practice. Thus, this work aims to present for the first time the status quo in Swiss livestock farming as an example of a highly developed, small-scale and diverse structured agriculture. In this context, the article focuses on the adoption of electronic sensors and measuring devices, electronic controls and electronic data-processing options and the usage of robotics in ruminant farming, namely, for dairy cattle, dairy goats, suckler cows, beef cattle and meat-sheep. Furthermore, the use of electronic ear tags for pigs and the smartphone usage for barn monitoring on poultry farms was assessed. To better understand the adoption process, farm and farmer’s characteristics associated with the adoption of (1) implemented and (2) new digital technologies in ruminant farming were assessed using regression analyses, which is classified at a 10% adoption hurdle. The results showed clear differences in the adoption rates between different agricultural enterprises, with both types of digital technologies tending to be used the most in dairy farming. Easy-to-use sensors and measuring devices such as those integrated in the milking parlour were more widespread than data processing technologies such as those used for disease detection. The husbandry system further determined the use of digital technologies, with the result that farmers with tie stall barns were less likely to use digital technologies than farmers with loose housing systems. Additional studies of farmers’ determinants and prospects of implementation can help identify barriers in the adoption of digital technologies.
•Bluetooth Low Energy (BLE) presents opportunities for animal monitoring.•Purpose−built devices were calibrated alongside commercial BLE beacons.•Distance using BLE signal strength was estimated with ...prediction equations.•Device height and animal behaviour will impact on Bluetooth Low Energy range.•Two methods of sheep localisation were trialled successfully using BLE beacons.
Monitoring animal location and proximity can provide useful information on behaviour and activity, which can act as a health and welfare indicator. However, tools such as global navigation satellite systems (GNSS) can be costly, power−hungry and often heavy, thus not viable for commercial uptake in small ruminant systems. However, developments in Bluetooth Low Energy (BLE) could offer another option for animal monitoring, BLE signal strength can be variable, and further information is needed to understand the relationship between signal strength and distance in an outdoor environment and assess factors which might affect its interpretation in on-animal scenarios. A calibration of a purpose-built device containing a BLE reader, alongside commercial BLE beacons, was conducted in a field environment to explore how signal strength changed with distance and investigate whether this was affected by device height, and thus animal behaviour. From this calibration, distance prediction equations were developed whereby beacon distance from a reader could be estimated based on signal strength. BLE as a means of localisation was then trialled, firstly using a multilateration approach to locate 16 static beacons within an ∼5 400 m2 section of paddock using 6 BLE readers, followed by an on-sheep validation where two localisation approaches were trialled in the localisation of a weaned lamb within ∼1.4 ha of adjoining paddocks, surrounded by nine BLE readers. Validation was conducted using 1 days’ worth of data from a lamb fitted with both a BLE beacon and separate GNSS device. The calibration showed a decline in signal strength with increasing beacon distance from a reader, with a reduced range and earlier decline in the proportion of beacons reported at lower reader and beacon heights. The distance prediction equations indicated a mean underestimation of 12.13 m within the static study, and mean underestimation of 1.59 m within the on-sheep validation. In the static beacon localisation study, the multilateration method produced a mean localisation error of 22.02 m, whilst in the on-sheep validation, similar mean localisation errors were produced by both methods – 19.00 m using the midpoint and 23.77 m using the multilateration method. Our studies demonstrate the technical feasibility of localising sheep in an outdoor environment using BLE technology; however, potential commercial application of such a system would require improvements in BLE range and accuracy.
The study aimed to identify the implementation of extension program planning on cattle farmers in Padang City, West Sumatra. It conducted with a survey method. The respondent was the cattle farmers ...who had already received transfer innovation related to raising cattle by Extension Officers. It determined sixty farmers from six districts in Padang City. The data obtained with the questionnaire then analysed descriptive quantitatively and presented in percentages. The result showed the implementation of extension program planning of data collecting 11.67% implemented, state analysis 61.67% implemented, problems identification 61.67% implemented, goal formalisations 36.67% implemented, plan formation 50.00% implemented, activities conducted 100% implemented, activities progress evaluation 95.00% implemented, and reconsideration 36.67% implemented. It concluded that the implementation extension program planning on cattle farmers in Padang City are not implemented well.
The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
Milk yield dynamics and production performance reflect ...how dairy cows cope with their environment. To optimize farm management, time series of individual cow milk yield have been studied in the context of precision livestock farming, and many mathematical models have been proposed to translate raw data into useful information for the stakeholders of the dairy chain. To gain better insights on the topic, this study aimed at comparing 3 recent methods that allow one to estimate individual cow potential lactation performance, using daily data recorded by the automatic milking systems of 14 dairy farms (7 Holstein, 7 Italian Simmental) from Belgium, the Netherlands, and Italy. An iterative Wood model (IW), a perturbed lactation model (PLM), and a quantile regression (QR) were compared in terms of estimated total unperturbed (i.e., expected) milk production and estimated total milk loss (relative to unperturbed yield). The IW and PLM can also be used to identify perturbations of the lactation curve and were thus compared in this regard. The outcome of this study may help a given end-user in choosing the most appropriate method according to their specific requirements. If there is a specific interest in the post–peak lactation phase, IW can be the best option. If one wants to accurately describe the perturbations of the lactation curve, PLM can be the most suitable method. If there is need for a fast and easy approach on a very large dataset, QR can be the choice. Finally, as an example of application, PLM was used to analyze the effect of cow parity, calving season, and breed on their estimated lactation performance.
Respiratory rate (RR) is an important indicator of the health and welfare status of dairy cows. In recent years, progress has been made in monitoring the RR of dairy cows using video data and ...learning methods. However, existing approaches often involve multiple processing modules, such as region of interest (ROI) detection and tracking, which can introduce errors that propagate through successive steps. The objective of this study was to develop an end-to-end computer vision method to predict RR of dairy cows continuously and automatically. The method leverages the capabilities of a state-of-the-art Transformer model, VideoMAE, which divides video frames into patches as input tokens, enabling the automated selection and featurization of relevant regions, such as a cow's abdomen, for predicting RR. The original encoder of VideoMAE was retained, and a classification head was added on top of it. Further, the weights of the first 11 layers of the pre-trained model were kept, while the weights of the final layer and classifier were fine-tuned using video data collected in a tie-stall barn from 6 dairy cows. Respiratory rates measured using a respiratory belt for individual cows were serving as the ground truth (GT). The evaluation of the developed model was conducted using multiple metrics, including mean absolute error (MAE) of 2.58 breaths per minute (bpm), root mean squared error (RMSE) of 3.52 bpm, root mean squared prediction error (RMSPE; as a proportion of observed mean) of 15.03%, and Pearson correlation (r) of 0.86. Compared with a conventional method involving multiple processing modules, the end-to-end approach performed better in terms of MAE, RMSE and RMSPE. These results suggest the potential to implement the developed computer vision method for an end-to-end solution, for monitoring RR of dairy cows automatically in a tie-stall setting. Future research on integrating this method with other behavioral detection and animal identification algorithms for animal monitoring in a free-stall dairy barn can be beneficial for a broader application.
Intensive livestock farming has raised issues about environmental impacts and food security during the past 20 years. As a consequence, there is a strong social demand for sustainable livestock ...systems. Sustainable livestock systems should indeed be environmentally friendly, economically viable for farmers, and socially acceptable, notably for animal welfare. For that goal, many sustainability indicators and methods have been developed at the farm level. The main challenge is using a transparent selection process to avoid assessment subjectivity. Here, we review typologies of sustainability indicators. We set guidelines for selecting indicators in a data-driven context, by reviewing selection criteria and discussing methodological issues. A case study is presented. The selected set of indicators mainly includes (1) environmental indicators focusing on farmer practices; (2) quantitative economic indicators; and (3) quantitative social indicators with a low degree of aggregation. The selection of indicators should consider (1) contextualization to determine purpose, scales, and stakeholders involved in the assessment; (2) the comparison of indicators based on various criteria, mainly data availability; and (3) the selection of a minimal, consistent, and sufficient set of indicators. Finally, we discuss the following issues: topics for which no indicators are measurable from available data should explicitly be mentioned in the results. A combination of means-based indicators could be used to assess a theme, but redundancy must be avoided. The unit used to express indicators influences the results and has therefore to be taken into account during interpretation. To compare farms from indicators, the influence of the structure on indicator values has to be carefully studied.
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