On-farm Use Research Articles

On-farm compost and parsley residues extract use on organic fennel crop to improve agronomic performance and environmental sustainability

ABSTRACT Recycling agricultural residues to obtain production factors directly in the farm could be crucial to improve sustainability. The aim of this study was to use plant residues to produce both organic amendments (on-farm compost) and plant biostimulants (liquid extracts). They were applied on a 2-year organic fennel crop, both alone (compost on-farm – OC) and combined (compost on-farm plus parsley extract – OCex) and compared with two commercial organic fertilizers (of vegetal origin – ORG-V; and of animal origin – ORG-A) and an unfertilized control, alone (NF) and combined with the extract (NFex). On average, the agronomic performance of compost treatments was higher than the unfertilized control and comparable to ORG-V. The use of the plant extract induced a synergistic effect with the on-farm compost, likely due to the P, K, Ca, Fe, and Mg supplementation by the extract to fennel crop. This is a relevant result, particularly in the perspective of widening the number of fertilizers produced inside the farm in organic farming, thus avoiding both synthetic fertilizers and commercial organic fertilizers. Finally, on-farm compost use reduced GWP emissions, since an average value of −12.44%, compared to the commercial fertilized treatments, was found, thus suggesting environmental sustainability.

Innovations in animal health: artificial intelligence-enhanced hematocrit analysis for rapid anemia detection in small ruminants.

Due to their value as a food source, fiber, and other products globally, there has been a growing focus on the wellbeing and health of small ruminants, particularly in relation to anemia induced by blood-feeding gastrointestinal parasites like Haemonchus contortus. The objective of this study was to assess the packed cell volume (PCV) levels in blood samples from small ruminants, specifically goats, and create an efficient biosensor for more convenient, yet accurate detection of anemia for on-farm use in agricultural environments for animal production optimization. The study encompassed 75 adult male Spanish goats, which underwent PCV testing to ascertain their PCV ranges and their association with anemic conditions. Using artificial intelligence-powered machine learning algorithms, an advanced, easy-to-use sensor was developed for rapidly alerting farmers as to low red blood cell count of their animals in this way to enable timely medical intervention. The developed sensor utilizes a semi-invasive technique that requires only a small blood sample. More precisely, a volume of 30 μL of blood was placed onto Whatman filter paper No. 1, previously soaked with anhydrous glycerol. The blood dispersion pattern on the glycerol-infused paper was then recorded using a smartphone after 180 s. Subsequently, these images were examined in correlation with established PCV values obtained from conventional PCV analysis. Four separate machine learning models (ML) supported models, namely support vector machine (SVM), K-nearest neighbors (KNN), backpropagation neural network (BPNN), and image classification-based Keras model, were created and assessed using the image dataset. The dataset consisted of 1,054 images that were divided into training, testing, and validation sets in a 70:20:10 ratio. The initial findings indicated a detection accuracy of 76.06% after only 10 epochs for recognizing different levels of PCV in relation to anemia, ranging from healthy to severely anemic. This testing accuracy increased markedly, to 95.8% after 100 epochs and other model parameter optimization. Results for SVM had an overall F1 score of 74-100% in identifying the PCV range for blood pattern images representing healthy to severely anemic animals, and BPNN showed 91-100% accuracy in identifying the PCV range for anemia detection. This work demonstrates that AI-driven biosensors can be used for on-site rapid anemia detection. Optimized machine learning models maximize detection accuracy, proving the sensor's validity and rapidity in assessing anemia levels. This breakthrough will allow farmers, with rapid results, to increase animal wellbeing and agricultural productivity.

Predicting future climate scenarios: a machine learning perspective on greenhouse gas emissions in agrifood systems

Global climate change is an extensive phenomenon characterized by alterations in weather patterns, temperature trends, and precipitation levels. These variations substantially impact agrifood systems, encompassing the interconnected components of farming, food production, and distribution. This article analyzes 8,100 data points with 27 input features that quantify diverse aspects of the agrifood system’s contribution to predicted Greenhouse Gas Emissions (GHGE). The study uses two machine learning algorithms, Long-Short Term Memory (LSTM) and Random Forest (RF), as well as a hybrid approach (LSTM-RF). The LSTM-RF model integrates the strengths of LSTM and RF. LSTMs are adept at capturing long-term dependencies in sequential data through memory cells, addressing the vanishing gradient problem. Meanwhile, with its ensemble learning approach, RF improves overall model performance and generalization by combining multiple weak learners. Additionally, RF provides insights into the importance of features, helping to understand the significant contributors to the model’s predictions. The results demonstrate that the LSTM-RF algorithm outperforms other algorithms (for the test subset, RMSE = 2.977 and R2 = 0.9990). These findings highlight the superior accuracy of the LSTM-RF algorithm compared to the individual LSTM and RF algorithms, with the RF algorithm being less accurate in comparison. As determined by Pearson correlation analysis, key variables such as on-farm energy use, pesticide manufacturing, and land use factors significantly influence GHGE outputs. Furthermore, this study uses a heat map to visually represent the correlation coefficient between the input variables and GHGE, enhancing our understanding of the complex interactions within the agrifood system. Understanding the intricate connection between climate change and agrifood systems is crucial for developing practices addressing food security and environmental challenges.

Improving On-farm Energy Use Efficiency by Optimizing Machinery Operations and Management: A Review

AbstractThe energy use and emissions from direct fossil fuel combustion on-farms to power farm machinery was critically reviewed. Approximately, 15% of agricultural production costs on-farm are energy-related. A potential solution to more sustainable energy use is a shift toward biofuels from renewable resources. The reduction of greenhouse gas emissions through the substitution of diesel oil with biodiesel depends on the feedstock, the inter-esterification process, the storage period, and ambient conditions. In modern tractors, increased fuel use efficiency (or reduced fuel consumption) has been achieved by power/load matching and the use of variable transmission. Engine management systems that are capable of continuously communicating with the engine and transmission to make appropriate adjustments based on inputs received from the tractor allow for quick and precise responses to changing conditions. As a result, maximum efficiency and productivity can be obtained from the tractor operating similarly to the traditional ‘gear-up and throttle-back’ methods of a proficient operator. The future for autonomous tractors is promising, though not new. Electric-powered tractors are near to commercialization or are already commercially available. Hybrid electric driven tractors present some advantages in terms of increased energy use efficiency and functionalities. Increased efficiency can lead to a reduction in diesel fuel consumption and hence, a concurrent decrease in CO2 emission. Where the local electricity supply has a low-carbon emission factor, this can also result in significant emission reductions. Small light-weight robotic equipment can potentially perform functions currently undertaken by tractor-drawn and other heavy equipment with high-fuel consumption, provided field operating capacity was not compromised. However, the size and weight limitations inherent in current harvesting and transport technology mean that soil compaction will still be a problem with robotic units. The robotic operation of medium-scale equipment within a precision-controlled traffic farming environment should offer more feasible and energy-efficient alternatives.

Evaluation of a Temperature/Humidity Data Logger for the Usage in Cattle Barns.

Climate change is a worldwide problem that is manifested in livestock farming with a decrease in animal health and welfare and economic losses due to heat stress. Therefore, a precise and continuous recording of the barn climate is essential to be able to implement actions at a certain threshold. The aim of this study was to evaluate a logger for temperature and humidity (Kestrel Drop D2) marketed for on-farm use in comparison to various other temperature/humidity data loggers under field conditions. Four different sensors were used and placed in different settings in cattle barns to correlate temperature and humidity measurements. Data were recorded for over a year in total. The data were very highly correlated. Furthermore, the area under the curve for the evaluated logger in comparison to the other ones was 0.99 to 1.0, using a temperature-humidity index cut-off of 72, often set to define heat stress. In conclusion, the evaluated logger performed equally well as the other used devices. For on-farm use, it is suitable.

Manure contribution to rural livelihoods at farm and landscape levels: a systemic approach in semi-arid Central Tunisia

ABSTRACT Manure valorization through on-farm use or market transactions is an ancient and widespread practice in the mixed crop-livestock systems of the semi-arid areas of North Africa. While research has long focused on the manure contribution to soil fertility at the plot level, little has been done concerning livelihood conditions. The present paper aims to assess the contribution of manure use and exchange on the livelihoods of rural communities using an original dataset collected in 2021 among 150 farmers in Central Tunisia. This analysis is carried out within the analytical agroecology framework combined with factor analysis methods. Results showed that manure use and valorization differ along the watershed, from a socioeconomic perspective in small farms operating under rainfed tree-pastoral systems, to an environmental and agronomic perspective in the mixed rainfed-irrigated systems downstream. Manure flow analysis confirmed that on-farm manure balance is positively correlated to economic wealth. However, the manure fluxes questioned the environmental sustainability of the vulnerable zones. Its use and management could significantly impact livelihood discrepancies in the future, with the increasing of demand and use of manure in more favorable zones such as irrigated lands at the detriment of the rainfed zones.

Designing precision livestock farming system innovations: A farmer perspective

Precision livestock farming (PLF) is increasingly being suggested as a promising tool for contributing to the sustainable transition of livestock farming as a market system innovation for farm-animal value chains. The innovations of PLF systems are over and above applications aimed at achieving on-farm goals (e.g. improving efficiency and monitoring farm animals), which are well recognised in the existing literature. This paper specifies the new dimensions of PLF systems, including data-sharing with retailers in the chain, with certifiers/control organisations, with other farmers and with market innovators, as well as data governance. Because farmers approach PLF applications that extend beyond on-farm use with reluctance, it is crucial to take farmer preferences into account when designing multi-actor PLF-system innovations. Proceeding from a mixed-method design, this study begins with a literature review and expert interviews, followed by an examination of farmer preferences regarding the architectural-design attributes of a PLF-system innovation. The latter takes the form of a conjoint study based on data obtained from 367 pig and dairy farmers in Finland, the Netherlands and Spain. Results indicate that farmers attach the greatest importance to the governing structure that manages their data, followed by the opportunity to use an on-farm early-warning system to monitor farm animals, and the possibility of sharing the collected data with value-chain actors mainly for purposes of optimising business innovation and certification. A cluster analysis further highlights the importance of finding customised solutions, considering the heterogenous preferences of farmers for PLF-system innovations beyond European borders. These preferences should be considered in the design of multi-actor PLF-system innovations.

Functionalized Graphene-Based Biosensors for Early Detection of Subclinical Ketosis in Dairy Cows

Precision livestock farming is one method of improving the productivity, health, and well-being of animals. Advanced diagnostic tools including biosensors can play a key role in the management of livestock operations. Detection of ketosis, a metabolic disease that occurs in early lactation dairy cows due to the negative energy balance, is one potential on-farm use of biosensors. Beta–hydroxybutyrate (βHB) is an excellent biomarker for ketosis monitoring in dairy cows because βHB is one of the main ketones produced during this metabolic state. In this report, we develop a low-cost, Keto-sensor (graphene-based sensor) for the detection and quantification of βHB concentrations in less than a minute. In this device, graphene nanosheets were layered onto a screen–printed electrode (SPE), and then a stabilized enzyme (Beta–hydroxybutyrate dehydrogenase, NADH, and glycerol) was used to functionalize the graphene surface enabled by EDC–NHS conjugation chemistry. The Keto-sensor offers an analytical sensitivity of 10 nM and a limit-of-detection (LoD) of 0.24 nM within a detection range of 0.00001-3.0 mM. Spike testing indicates that the Keto-sensor can detect βHB in serum samples from bovines with subclinical ketosis. The Keto-sensor developed in this study shows promising results for early detection of subclinical ketosis on farms.

Comparison of radial immunodiffusion, turbidimetric immunoassay, and Brix refractometry for determining bovine colostrum quality

Determining the concentration of IgG in colostrum is critical for assessment of colostrum quality. On-farm use of a Brix refractometer to estimate colostrum IgG concentration is widespread, whereas radial immunodiffusion (RID) is the laboratory reference method. Turbidimetric immunoassay (TIA) might offer an alternative method to quantify IgG in colostrum, but the agreement with RID, as well as critical thresholds to determine high-quality colostrum, remain uncertain. The objective of this study was to determine the level of agreement between RID, Brix %, and TIA for evaluation of colostrum quality. Composite colostrum samples (n = 58) from Holstein cows were evaluated using a digital Brix refractometer at the time of collection and stored at −20°C until analysis. The concentration of IgG was determined using RID and TIA. Data were analyzed using Passing-Bablok regression and Bland-Altman plots. Critical thresholds for TIA and Brix measurements to identify colostrum with an IgG concentration ≥50 and ≥100 g/L based on the reference method were determined using logistic regression and receiver operating characteristic curves. Results revealed that both TIA (Kendall's τ = 0.91) and Brix % (τ = 0.78) had a strong correlation with RID. Passing-Bablok regression identified a systematic (6.91 [4.33 to 8.98] g/L) and proportional (0.69 [0.67 to 0.72] g/L) bias between RID and TIA. The optimum thresholds to identify samples with an IgG concentration ≥50 and ≥100 g/L were 40.6 g/L (area under the curve [AUC]: 1.0; sensitivity (Se): 100; specificity [Sp]: 100) and 85.8 g/L (AUC: 0.99; Se: 96.6; Sp: 96.6) for TIA and 18.4% (AUC: 1.0; Se: 100; Sp: 100) and 25.8% (AUC: 0.99; Se: 82.8; Sp: 93.1) for Brix %, respectively. Using the identified thresholds, our results show that both Brix and TIA were highly accurate for identifying high-quality colostrum, but because of a proportional bias, direct comparison of IgG concentration results obtained by RID and TIA are cautioned.

Comparison of two methods for collecting antimicrobial usage in large dairy farms in Ohio and California

Quantification of on-farm antimicrobial use (AMU) is critical to correlate with patterns of antimicrobial resistance, surveil­lance programs and formulate interventions to optimize its use. Prior studies have used the empty drug container (EDC) method to quantify AMU; however, the method is labor-intensive and time-consuming. Therefore, this study aimed to compare it against farm treatment records (FTR) as a reliable method to collect on-farm AMU. We hypothesized a low level of agreement in on-farm treatment incidence (TI) obtained between these 2 different collection methods.

Nutrient imbalances of smallholder dairy farming systems in Indonesia: The relevance of manure management

CONTEXTNitrogen (N) and phosphorus (P) imbalances from dairy farming systems (DFSs) lead to environmental problems, such as eutrophication. OBJECTIVEThis study aimed to quantify nutrient deficits and losses from DFSs with different manure management systems (MMSs) at the farm level and at the levels of its sub-systems. METHODSWe compared NP balances of 30 farms with four different MMSs: applying manure directly on forage land, without treatment (ADL), selling or exporting manure (SEL), using manure for anaerobic digestion (ADI), and discharging manure (DIS). NP balances were calculated based on differences between in- and outflows. RESULTS AND CONCLUSIONSResults showed that N balances at DFS averaged 222 kg N farm−1 yr−1 and did not differ between MMSs. Average P balances at DFS differed between MMSs; balances were highest for DIS (83 kg P farm−1 yr−1), and lowest for SEL (−25 kg P farm−1 yr−1). Soil P balances did not differ between MMSs and were mostly negative, except for four ADL farms. Annually, all dairy farms in Lembang region are estimated to cause a nutrient loss of ∼1061 tons of N and ∼ 290 tons of P, and extract 8 tons of P from soils. Overall, high NP imbalances are caused by discharging manure into the environment. SIGNIFICANCETo reduce imbalances, collection and on-farm use of manure must be improved, and excess manure needs to be sold to crop farms. The carrying capacity for high-input high-output dairy farming is determined by the capacity of arable farms to apply the manure surpluses.

Assessing the difference in contamination of retail meat with multidrug-resistant bacteria using for-consumer package label claims that indicate on-farm antibiotic use practices- United States, 2016-2019.

Antibiotic use in food-producing animals can select for antibiotic resistance in bacteria that can be transmitted to people through contamination of food products during meat processing. Contamination resulting in foodborne illness contributes to adverse health outcomes. Some livestock producers have implemented antibiotic use reduction strategies marketed to consumers on regulated retail meat packaging labels ("label claims"). We investigated whether retail meat label claims were associated with isolation of multidrug-resistant organisms (MDROs, resistant to ≥3 classes of antibiotics) from U.S. meat samples. We utilized retail meat data from the U.S. Food and Drug Administration National Antimicrobial Resistance Monitoring System (NARMS) collectedduring 2016-2019 for bacterial contamination of chicken breast, ground turkey, ground beef, and pork chops. We used modified Poisson regression models to compare the prevalence of MDRO contamination among meat samples with any antibiotic restriction label claims versus those without such claims (i.e., conventionally produced). In NARMS, 62,338 meat samples were evaluated for bacterial growth from 2016-2019. Of these, 24,446 (39%) samples had label claims that indicated antibiotic use was restricted during animal production. MDROs were isolated from 2252 (4%) meat samples, of which 71% (n = 1591) were conventionally produced, and 29% (n = 661) had antibiotic restriction label claims. Compared with conventional samples, meat with antibiotic restriction label claims had a statistically lower prevalence of MDROs (adjusted prevalence ratio: 0.66; 95% CI: 0.61, 0.73). This relationship was consistent for the outcome of any bacterial growth. This repeated cross-sectional analysis of a nationally representative retail meat surveillance database in the United States supports that retail meats labeled with antibiotic restriction claims were less likely to be contaminated with MDROs compared with retail meat without such claims during 2016-2019. These findings indicate the potential for the public to become exposed to bacterial pathogens via retail meat and emphasizes a possibility that consumers could reduce their exposure to environmental reservoirs of foodborne pathogensthat are resistant to antibiotics.

Reducing pest pressure and insecticide use by increasing hedgerows in the landscape

Reducing pesticide use while maintaining agricultural production is a key challenge. Ecological theory predicts that landscape simplification is likely to increase insect pest outbreaks and limit their control by natural enemies, and this situation could boost insecticide use. Some studies have indeed detected that simpler landscapes were associated with higher insecticide use, but very few have demonstrated that this association is caused by landscape effects on pest abundance. Here, we analysed insecticide use and pest pressure in response to landscape simplification across 557 arable farms across France. Accounting for potentially confounding covariates, we found that lower cover of hedgerows in the landscape, but not semi natural areas, were associated with higher on-farm insecticide use. We also found that greater hedgerow coverage was associated with lower aphid pest pressure. Specifically, increasing the landscape-scale cover of hedgerows from 1 % to 3 % meant that insecticide use was halved. These findings suggest that restoring hedgerow cover at the landscape scale should be targeted in order to speed-up the ecological intensification of agriculture.

Efficacy of a novel cervical dislocation tool for humane euthanasia of broilers and broiler breeders

Euthanasia is an essential task performed daily on commercial poultry farms around the world to safeguard animal welfare. Manual cervical dislocation (MCD) is the most common euthanasia method but can be challenging to perform given the physical strength required to implement this technique. Therefore, the objective of this study was to evaluate the efficacy of a Novel Cervical Dislocation Tool (NCDT) compared to MCD. A total of 60 Ross 308 chickens (6-weeks old) and 60 Ross 706 parent stock breeders (21-weeks old) were enrolled in the study. Birds were sexed, blocked by body weight, and allocated to one of two treatments: 1) MCD and 2) NCDT. Immediately following euthanasia application, insensibility and death was monitored. Once death was confirmed, gross evaluation, radiograph and macroscopic/microscopic scoring was performed. Both euthanasia methods were 100% effective in achieving insensibility followed by cardiac and respiratory arrest in both age groups. In six-week-old broilers, there were no differences in insensibility measures or location and severity of the dislocation site by treatment. The NCDT treatment group showed an increased frequency of fractures located at the tooth-like process that projects from the cranial aspect of the centrum of the axis (dens) but had no impact on bird insensibility. For parent stock, differences in Nictitating Membrane Reflex (NMR) and laceration scores for birds euthanized with NCDT were found and likely associated with additional force exerted with the tool. The NCDT is a promising replacement for manual cervical dislocation (MCD) and future work should address the development of free and accessible training materials for on-farm use.

A coaching approach to strengthen farm management teams to reduce antimicrobial use in Dutch high usage pig farms: a 2 year intervention study.

The use of antimicrobials in the pig sector in the Netherlands has been reduced by more than 70% over the last decade. However, there is still a considerable number of pig farms that have not been able to lower their antimicrobial usage (AMU) to a sufficiently low level, comparable to the majority of the other pig farms. Therefore, an intervention study was initiated to lower on-farm antimicrobial use in which 45 pig farms with high AMU were recruited. These farms were coached over a period of 2 years whereby different management interventions were introduced. During the 2-year study period a significant reduction of 13 and 17% in total AMU was seen in weaned piglets and fattening pigs respectively. The introduction of coaching as well as multiple management interventions were (univariably) associated with the decrease in AMU. After mutual adjustment of coaching and individual interventions, the association between coaching and AMU became substantially weaker, indicating that coaching and interventions were interrelated and specific interventions explained the reduction in AMU. In conclusion, a coaching effect was observed in this study, with an effect on AMU through specific interventions. More insights are needed regarding the role and effects of coaching on the influence on the management team comprising the farmer, veterinarian and (feed) advisor, and interventions implemented.

Multi-criteria decision analysis for supporting the selection of subclinical mastitis screening tests to use in large- and small-scale dairy farms in Türkiye.

The production of high-quality and safe milk is closely associated with the udder health of dairy cows. While there are many mastitis diagnostic tests/methods available, choosing the most appropriate diagnostic test for a sustainable udder health control program could be a challenge. This study was aimed at selecting tests for the screening of subclinical mastitis on small- and large-scale dairy farms in Türkiye, using multi-criteria decision-making methods. An integrated approach employing the analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) together was used to select subclinical mastitis screening tests for on-farm use. While the AHP determines the weights of the evaluation criteria, the TOPSIS provides a final ranking. Nine different subclinical mastitis screening (SCM) methods (DeLaval somatic cell counter, PortaSCC test, California mastitis test (CMT), rapid culture, portable/hand-held electrical conductivity meter, infrared thermography, leukocyte esterase strip test, milk pH, UdderCheck test) were analyzed on the basis of five selection criteria (the market availability of the test, the diagnostic accuracy of the test, the cost of the test, the cow-side use of the test, and the practicality of the test). The selection criteria were determined based on literature review and stakeholder input. The weighting of the criteria with the AHP was based on the pairwise comparison of the criteria by stakeholders. The criteria were weighted from 1 to 9 according to their relative importance as follows: "1: equally important," "3: moderately important," "5: strongly important," "7: very strongly important," "9: extremely important," and "2, 4, 6, 8: intermediate values." Final ranking of SCM tests with the TOPSIS was based on the stakeholder evaluations of fulfillment of the criteria by the alternatives. The most appropriate screening test for both large- and small-scale dairy farms was determined to be the CMT. The CMT is a very useful, easy to perform, and low-cost tool for detecting subclinical mastitis. Being a major element of udder health control programs, the CMT, if regularly used on dairy farms in Türkiye, would enable the culling of chronically infected animals and the reduction of mastitis-associated economic losses. Furthermore, regular CMTs would contribute to reducing milk SCC and improving milk quality. In conclusion, multi-criteria decision-making methods not only provide a systematic approach that may assist both veterinarians and farmers in deciding on the best choice among the different tests available for the screening of subclinical mastitis but also offer potential benefits to policymakers, researchers, and other industry stakeholders.

Effect of a dairy farmworker stewardship training program on antimicrobial drug usage in dairy cows

Antimicrobial use (AMU) is critical to preserving animal health and welfare. However, the development of antimicrobial resistance (AMR) represents a public health threat. Although most antimicrobials used on the farm require a veterinarian prescription, farmworkers make daily on-farm treatment decisions. Therefore, farmworker training is vital to promote responsible AMU. This research project aimed to evaluate the effect of farmworker antimicrobial stewardship (AMS) training on the quantity of AMU on dairy farms in Ohio and California. We hypothesized that farms receiving AMS training would have reduced AMU in dairy cattle compared with farms where training wasn't administered. We designed a quasiexperimental study with 18 conventional dairy farms enrolled in Ohio and California. Twelve farms received AMS training, and 6 farms did not. The AMS program included a 12-wk training focused on accurate identification of cows requiring antimicrobial treatment. We quantified AMU by collecting used drug containers, manually counted by researchers during farm visits. Treatment incidence (TI) was calculated using animal daily doses (ADD), and Poisson regression models were used to analyze the TI data. Disease incidence rate (DIR) in lactating cows was 2.2, 1.5, 1.0, 0.4, 0.3, 0.2, and 0.03/1,000 cow-days for mastitis, lameness, metritis, pneumonia, retained placenta, diarrheas, and other diseases (e.g., conjunctivitis, injuries), respectively. The highest TI by antimicrobial class (provided in ADD/1,000 cow-days) was cephalosporin (5.9), penicillin (5.2), tetracyclines (0.4), lincosamides (0.2), and sulfonamides (0.1). Among the trained farms using a within-treatment group analysis, no significant differences were observed in TI pre-intervention (10.9 ADD/1,000 cow-days) compared with TI postintervention (10.3 ADD/1,000 cow-days). Treatment incidence from the training group was 10.8 ADD/1,000 cow-days and although numerically lower, it was not significantly different compared with TI in the control groups at 13.9 ADD/1,000 cow-days (rate ratio = 0.77, CI = 0.25-2.38). Future research on AMS should incorporate farmworker training with social science approaches to overcome barriers and promote on-farm responsible use.

On-farm use of recycled liquid ammonium sulphate in Southwest Germany using a participatory approach

For political and environmental reasons, there is an urgent need for alternatives to energy-intensive synthetic fertilizers. One solution is the targeted recycling of nutrients within agriculture. In this study, liquid ammonium sulphate (LAS) as a recycling product derived from digestate treatment was compared to calcium ammonium nitrate, manure and original digestates in an on-farm experiment using a participatory approach. Based on regular meetings with the farmers involved, a flexible experimental design was developed which integrated the fertilization legislation and the farmers’ operational structures already in place, such as crop rotation, available application techniques and manure management demands. The aim was to achieve both implementation practicability and acceptance of the study results by the farmers. Results from the year 2020 showed that LAS applied with three-jet nozzles in barley and wheat had significantly lower yields than the other fertilizers. Applied with a slurry tanker trailing shoe applicator in 2021, LAS had comparable yields to the other fertilizers in maize (51.2 t ha−1) and comparable yields to digestate in rapeseed (4.4 t ha−1). Application techniques that minimize environmental impacts and lower the LAS pH could potentially increase the effectiveness of the fertilizer. We recommend that farmers use this fertilizer not as a single solution but as a mineral compensatory fertilizer in addition to organic fertilizers following local fertilizer legislation. In this case, LAS could potentially substitute calcium ammonium nitrate (CAN).

Parasiticides: perspectives and prospects

For over 50 years, anthelmintics, insecticides and acaricides have played a central role in the treatment and control of ruminant parasites, but over the same time-frame, their effectiveness has gradually diminished through the emergence of resistance. Currently, in parallel with initiatives to reduce on-farm use of antibiotics, the routine use of anthelmintics and ectoparasiticides is actively discouraged by several organisations and individuals. For these reasons, there is little incentive for the animal health industry to discover and develop new products for farm animals. While the removal of parasites in clinical disease must inevitably rest on effective therapeutics, longer term control of parasitism can be facilitated through complementary practices that enhance host resistance and resilience and reduce parasite challenge. When parasiticides are used, preservation and maintenance of refugia are key to reducing selection pressure for resistance and mitigating any untoward side-effects in the environment. Adoption of such approaches requires adaptability, more attention to detail and extra effort by farmers. Veterinarians can play an important role in encouraging the adoption of proven diagnostic and monitoring technologies and providing advice to farmers as they transition away from parasiticide-dependence.

Dilution Reduces Sample Matrix Effects for Rapid, Direct, and Miniaturised Phenotypic Antibiotic Susceptibility Tests for Bovine Mastitis.

The time-consuming nature of current methods for detecting antimicrobial resistance (AMR) to guide mastitis treatment and for surveillance, drives innovation towards faster, easier, and more portable technology. Rapid on-farm testing could guide antibiotic selection, reducing misuse that contributes to resistance. We identify challenges that arise when developing miniaturized antibiotic susceptibility tests (AST) for rapid on-farm use directly in milk. We experimentally studied three factors: sample matrix (specifically milk or spoiled milk); the commensal bacteria found in fresh bovine milk; and result time on the performance of miniaturised AST. Microfluidic "dip-and-test" devices made from microcapillary film (MCF) were able to monitor Gram-negative bacterial growth colourimetrically even in the presence of milk and yoghurt (used to simulate spoiled milk samples), as long as this sample matrix was diluted 1:5 or more in growth medium. Growth detection kinetics using resazurin was not changed by milk at final concentrations of 20% or lower, but a significant delay was seen with yoghurt above 10%. The minimum inhibitory concentration (MIC) for ciprofloxacin and gentamicin was increased in the presence of higher concentrations of milk and yoghurt. When diluted to 1% all observed MIC were within range, indicating dilution may be sufficient to avoid milk matrix interfering with microfluidic AST. We found a median commensal cell count of 6 × 105 CFU/mL across 40 healthy milk samples and tested if these bacteria could alter microfluidic AST. We found that false susceptibility may be observed at early endpoint times if testing some pathogen and commensal mixtures. However, such errors are only expected to occur when a susceptible commensal organism is present at higher cell density relative to the resistant pathogen, and this can be avoided by reading at later endpoints, leading to a trade-off between accuracy and time-to-result. We conclude that with further optimisation, and additional studies of Gram-positive organisms, it should be possible to obtain rapid results for microfluidic AST, but a trade-off is needed between time-to-result, sample dilution, and accuracy.