Challenges and Tendencies of Automatic Milking Systems (AMS): A 20-Years Systematic Review of Literature and Patents

Farmers' Perceptions on Implementing Automatic Milking Systems in Large USA Dairies: Decision-Making Process, Management Practices, Labor, and Herd Performance

Automatic Milking System (AMS) installations are increasing in the USA despite the higher investment cost than conventional systems. Surveys on AMSs conducted outside the USA focused on small-medium herds, specific regions, or aspects of AMS milking. This study described farmers' perceptions about the decision-making process of adopting an AMS in the USA's large dairies (≥7 AMS boxes) regarding changes in technology, housing, management practices, labor, herd performance, and health. After being contacted, 27 of 55 farmers from large AMS herds completed the survey. The main reasons for adopting an AMS were labor costs, cows' welfare, and herd performance. Most farms constructed new barns, used a free-flow traffic system, and changed their feed management. Increases in water and energy use were perceived by 42% and 62% of farmers, respectively. Farmers estimated decreases in labor costs of over 21%, and AMS employees worked 40-60 h/week. Milk production increases were reported by 58%, with 32% observing higher milk fat and protein content. Easier sick cow detection, better mastitis management, and improvements in pregnancy rates were reported. Thus, farmers transitioning to AMSs perceived altered resource utilization, labor cost savings, and improvements in employee quality of life, animal welfare, and farm management. While 54% of respondents would recommend an AMS to other farms, 38% suggested considering additional aspects prior to adoption.

Unlocking insights: text mining analysis on the health, welfare, and behavior of cows in automated milking systems

Automated Milking Systems (AMS) have undergone significant evolution over the past 30 yr, and their adoption continues to increase, as evidenced by the growing scientific literature. These systems offer advantages such as a reduced milking workload and increased milk yield per cow. However, given concerns about the welfare of farmed animals, studying the effects of AMS on the health and welfare of animals becomes crucial for the overall sustainability of the dairy sector. In the last few years, some analysis conducted through text mining (TM) and topic analysis (TA) approaches have become increasingly widespread in the livestock sector. The aim of the study was to analyze the scientific literature on the impact of AMS on dairy cow health, welfare, and behavior: the paper aimed to produce a comprehensive analysis on this topic using TM and TA approaches. After a preprocessing phase, a dataset of 427 documents was analyzed. The abstracts of the selected papers were analyzed by TM and a TA using Software R 4.3.1. A Term Frequency-Inverse Document Frequency (TFIDF) technique was used to assign a relative weight to each term. According to the results of the TM, the ten most important terms, both words and roots, were feed, farm, teat, concentr, mastiti, group, SCC (somatic cell count), herd, lame and pasture. The 10 most important terms showed TFIDF values greater than 3.5, with feed showing a value of TFIDF of 5.43 and pasture of 3.66. Eight topics were selected with TA, namely: 1) Cow traffic and time budget, 2) Farm management, 3) Udder health, 4) Comparison with conventional milking, 5) Milk production, 6) Analysis of AMS data, 7) Disease detection, 8) Feeding management. Over the years, the focus of documents has shifted from cow traffic, udder health and cow feeding to the analysis of data recorded by the robot to monitor animal conditions and welfare and promptly identify the onset of stress or diseases. The analysis reveals the complex nature of the relationship between AMS and animal welfare, health, and behavior: on one hand, the robot offers interesting opportunities to safeguard animal welfare and health, especially for the possibility of early identification of anomalous conditions using sensors and data; on the other hand, it poses potential risks, which requires further investigations. TM offers an alternative approach to information retrieval in livestock science, especially when dealing with a substantial volume of documents.

Geographical trends for automatic milking systems research in non-pasture-based dairy farms: A scoping review

Automatic milking system (AMS) adoption in the United States is trending upward, with issues such as lower availability and increased cost of labor being factors frequently listed as motives for AMS implementation. In addition, more interest in precision dairy farming by the new generation of farmers may also help increase AMS adoption. The objective of this scoping review was to characterize the nature of the literature investigating non-pasture-based AMS and the opportunities and challenges for future research. The eligibility criteria included studies published in or after the year 2000, with full text in English, of at least 500 words, examining various outcomes related to AMS in non-pasture-based dairy farms. Six electronic databases were searched: Biosis (Web of Science), CAB Abstracts (CAB Direct), Medline (PubMed), PubAg, AGRIS (FAO), and Scopus (Elsevier). The review focused on studies with objectives, characteristics, farms, and AMS information. A total of 4,292 titles and abstracts were screened, and 536 studies were finally included. Most of the studies were conducted in Europe (73.5%), among commercial herds (67.9%), comprising Holstein cows (57.7%), using Lely and DeLaval brands (45.4% vs. 39.7%), with free-flow traffic (52.7%). The main research topics investigated were milk production, milk composition, and AMS efficiency, followed by behavior and welfare, health disorders (especially mastitis), and nutrition in Europe and other regions. At the same time, in the United States, trends were similar, except for nutrition. Since 2016, there has been an increased interest in studies on energy and water consumption, technological development, environment (enteric emissions), reproduction, genetics, and longevity or culling. However, the small number of studies and unclear characterization of what is optimum for reproductive management, other health disorders, economics, and water and energy consumption suggest a need for future research.

A scoping review of the testing of bulk milk to detect infectious diseases of dairy cattle: Diseases caused by bacteria

Testing of bulk milk (BM) samples is a convenient, cost-effective strategy that can easily be implemented as part of disease surveillance programs on dairy farms. Here, we performed a scoping review to summarize the literature reporting on the testing of BM samples to detect infectious diseases of dairy cattle caused by bacteria. We also provide a non-exhaustive, albeit significant, list of diagnostic tests that are marketed for BM samples, as well as a list of disease surveillance activities that included testing of BM samples. A literature search was carried out in 5 databases, yielding 8,829 records from which 474 were retained. Overall, 575 eligible bacterial pathogens were screened for using BM samples, ranging from 1 to 6 individual pathogens per study. Staphylococcus aureus, including methicillin-resistant Staph. aureus, were the most studied bacteria (n = 179 studies), followed by Streptococcus agalactiae (86), Mycobacterium avium ssp. paratuberculosis (79), Coxiella burnetii (79), and Mycoplasma spp. (67). Overall, culture-based protocols, ELISA, real-time PCR, and PCR were the most commonly adopted methodologies to screen BM samples. Sensitivity of BM testing for bovine paratuberculosis was generally low and varied greatly according to the ELISA cut-offs adopted and herd-level definition of disease. In general, protocols had low to moderate sensitivities (<50%), which increased for herds with high within-herd seroprevalence. Specificity of BM testing for paratuberculosis was generally high. With respect to mastitis pathogens, BM testing demonstrated high sensitivity and specificity for Strep. agalactiae, in general. However, we observed inconsistency among studies with respect to the sensitivity of BM culture to detect infected herds, which was notably higher if enrolled herds were heavily infected or had history of clinical disease. Among Salmonella spp. pathogens, Salmonella Dublin was the most frequently studied bacterium for which BM testing has been validated. Specificity of BM ELISA was high, ranging from 89.0 to 99.4. In contrast, sensitivity varied greatly among studies, ranging from 50.6% to 100%. Our findings support that one of most important factors affecting sensitivity of BM ELISA for Salmonella Dublin is whether nonlactating cattle are considered in the definition of herd infection status. In general, protocols analyzed in this review suffered from very low sensitivities, which hardly justifies their use as part of disease surveillance as single testing. Nevertheless, test sensitivity can be increased by the adoption of more inclusive definitions of disease-free herds. Further, low-sensitivity and high-specificity methods can be valuable tools for surveillance when used repeatedly over time.

Genomic-based genetic parameters for milkability traits derived from automatic milking systems in North American Holstein cattle

The number of dairy farms adopting automatic milking systems (AMS) has considerably increased around the world aiming to reduce labor costs, improve cow welfare, increase overall performance, and generate a large amount of daily data, including production, behavior, health, and milk quality records. In this context, this study aimed to (1) estimate genomic-based variance components for milkability traits derived from AMS in North American Holstein cattle based on random regression models; and (2) derive and estimate genetic parameters for novel behavioral indicators based on AMS-derived data. A total of 1,752,713 daily records collected using 36 milking robot stations and 70,958 test-day records from 4,118 genotyped Holstein cows were used in this study. A total of 57,600 SNP remained after quality control. The daily-measured traits evaluated were milk yield (MY, kg), somatic cell score (SCS, score unit), milk electrical conductivity (EC, mS), milking efficiency (ME, kg/min), average milk flow rate (FR, kg/min), maximum milk flow rate (FRM, kg/min), milking time (MT, min), milking failures (MFAIL), and milking refusals (MREF). Variance components and genetic parameters for MY, SCS, ME, FR, FRM, MT, and EC were estimated using the AIREMLF90 software under a random regression model fitting a third-order Legendre orthogonal polynomial. A threshold Bayesian model using the THRGIBBS1F90 software was used for genetically evaluating MFAIL and MREF. The daily heritability estimates across days in milk (DIM) ranged from 0.07 to 0.28 for MY, 0.02 to 0.08 for SCS, 0.38 to 0.49 for EC, 0.45 to 0.56 for ME, 0.43 to 0.52 for FR, 0.47 to 0.58 for FRM, and 0.22 to 0.28 for MT. The estimates of heritability (± SD) for MFAIL and MREF were 0.02 ± 0.01 and 0.09 ± 0.01, respectively. Slight differences in the genetic correlations were observed across DIM for each trait. Strong and positive genetic correlations were observed among ME, FR, and FRM, with estimates ranging from 0.94 to 0.99. Also, moderate to high and negative genetic correlations (ranging from -0.48 to -0.86) were observed between MT and other traits such as SCS, ME, FR, and FRM. The genetic correlation (± SD) between MFAIL and MREF was 0.25 ± 0.02, indicating that both traits are influenced by different sets of genes. High and negative genetic correlations were observed between MFAIL and FR (-0.58 ± 0.02) and MFAIL and FRM (-0.56 ± 0.02), indicating that cows with more MFAIL are those with lower FR. The use of random regression models is a useful alternative for genetically evaluating AMS-derived traits measured throughout the lactation. All the milkability traits evaluated in this study are heritable and have demonstrated selective potential, suggesting that their use in dairy cattle breeding programs can improve dairy production efficiency in AMS.

Comparison of Cattle Housing Systems Based on the Criterion of Damage to Barn Equipment and Construction Errors

Simple Summary

As a result of many years of use, dairy cattle barns are subject to gradual wear and degradation. Damage to technical equipment can be identified in many areas in the barn. These areas are used by dairy cattle, so it is important to recognize the problem of damage and the associated health risks for animals. The problem of damage to internal equipment (e.g., damage to the floor, partitions between lying stalls, feed ladders, drinking bowls) applies to both tie-stall and freestall barns, which are the most common in dairy farms. Such premises became an inspiration to compare barns with a tie-stall system, a freestall system and their individual areas (lying, feeding, milking and social) in terms of the amount of damage but also construction errors. Most damage per one barn was found in the feeding area of objects with a tie-stall housing system. More cow health problems (e.g., laminitis, hoof problems) were identified in the barns with the freestall housing system. Equipment failures and construction errors may disrupt efficient and animal-safe dairy production in the barn. The results of the research study may be an incentive for farmers to check the barns in terms of their technical wear.

Abstract

Dairy cattle housing systems are the subject of numerous studies, in which a strong emphasis is placed on the comparison of animal welfare, animal behavior, production indicators and labor inputs. Dairy cattle housing systems are linked to specific livestock buildings, which is a prerequisite for undertaking studies comparing barns and their technical equipment. The aim of the study was to compare barns with two types of housing systems, i.e., tie-stall and freestall, including the identification of technical wear in various areas used by animals. This objective was linked to the assessment of animal health problems in livestock facilities. The research covered 38 dairy farms, 19 of which kept cows in the tie-stall system and 19 in the freestall system. The barns in these farms were examined for technical damage and construction errors, assessed in four areas: lying, feeding, milking and social. The research results confirmed significant differences in the degree of damage to technical equipment in individual areas of barns and between barns with tie-stall and freestall housing systems. The conclusions indicate the need to link the degradation of barns and their technical equipment, as well as design errors with the evaluation of dairy cattle welfare in future studies.

Evaluation of Heat Stress Effects in Different Geographical Areas on Milk and Rumen Characteristics in Holstein Dairy Cows Using Robot Milking and Rumen Sensors: A Survey in South Korea

This survey investigated, using robotic milking and rumen sensors, the effects of an adjusted temperature−humidity index (THI) in different geographical areas on milk yield, fat and protein, rumen temperature, and activity in lactating Holstein cows. We additionally explored the effect of parity on milk and rumen temperature and activity under different THI levels during the summer. From January to September 2020, four farms (276 dairy cows) were subjected to the use of robot milking machines, and two farms (162 dairy cows) to the use of rumen sensors. For the temperature and humidity data, the THI was calculated on the basis of the data from the Korea Meteorological Administration (KMA). The data were analyzed using the GLM procedure of SAS. Milk yield and milk protein decreased (p < 0.05), and milk fat increased (p < 0.05) at all farms during the summer, from July to August, when the temperature and humidity were high (THI = 72−79). Milk yields were the highest in the fifth, sixth, seventh, and eighth parities, and the lowest in the fourth (p < 0.05). Milk fat concentration was the highest in the fourth parity and the lowest in the first parity (p < 0.05). In the first parity, the highest levels of milk protein and lactose were seen (5.24% and 4.90%, respectively). However, milk protein concentration was the lowest in the third parity, and the lactose concentration was the lowest in the fifth, sixth, seventh, and eighth parities. According to the rumen sensor, the rumen temperature of the dairy cows at the two farms also continued to increase (p < 0.05) from July to August, and then decreased (p < 0.05) in September. However, the activity in the rumen was increased (p < 0.05) from July to September. In the second parity, the highest rumen temperature (39.02 °C) was observed, while the lowest value (38.28 °C) was observed in the third parity. The highest value of rumen activity (12.26 mg) was observed in the second parity and the lowest value (11.31 mg) in the fourth parity. These data, taken together, confirm that a high THI during summer conditions negatively affects milk yield, milk protein content, and rumen temperature and activity in lactating Holstein cows. It is also demonstrated that various parities affect milk characteristics and the rumen environment in the summer season.

Assessment of technical-productive aspects in Italian dairy farms equipped with automatic milking systems: A multivariate statistical analysis approach

The aim of this study was to assess technical-productive aspects of dairy farms equipped with automatic milking system (AMS) in Northern and Central Italy. A survey was carried out on 62 dairy farms selected through convenience sampling with the following inclusion criteria: adoption of robotic milking for at least 1 yr and ability to provide farm data. Data were collected using a structured questionnaire to obtain a general description of farm characteristics and overall management practices. Through the combination of principal component analysis and k-means cluster analysis, the farms were allocated in 3 clusters. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main observed differences between clusters were the average number of lactating cows and AMS installed, average annual milk production, average AMS loading, average annual milk yield per full-time employee, average daily milk yield per cow and AMS, and the average annual veterinary costs per cow. cluster 1 (n = 24) included small-to-medium-sized semi-intensive farms with low AMS loading and low average daily milk yield per cow. In this farm typology, the AMS is not fully used and is likely perceived as a means to improve quality of life rather than profitability. Clusters 2 (n = 31) and 3 (n = 7) included, respectively, small-medium-sized and large intensive farms. These 2 farm typologies are characterized by an intensive approach to dairy cattle breeding, with average higher AMS loading, labor efficiency, and milk yield compared with the farms of cluster 1, likely due to better farm management. This classification could help dairy technicians give farmers customized management advice for the function of the cluster they belong to, and farmers falling in a specific cluster could evaluate whether they are reaching their objectives.

Graduate Student Literature Review: Farm management practices: Potential microbial sources that determine the microbiota of raw bovine milk

Environmental and herd-associated factors such as geographical location, climatic conditions, forage types, bedding, soil, animal genetics, herd size, housing, lactation stage, and udder health are exploited by farmers to dictate specific management strategies that ensure dairy operation profitability and enhance the sustainability of milk production. Along with milking routines, milking systems, and storage conditions, these farming practices greatly influence the microbiota of raw milk, as evidenced by several recent studies. During the past few years, the increased interest in high-throughput sequencing technologies combined with culture-dependent methods to investigate dairy microbial ecology has improved our understanding of raw milk community dynamics throughout storage and processing. However, knowledge is still lacking on the niche-specific communities in the farm environment, and on the factors that determine bacteria transfer to the raw milk. This review summarizes findings from the past 2 decades regarding the effects of farm management practices on the diversity of bacterial species that determine the microbiological quality of raw cow milk.

Effect of Minimum Milking Interval on Traffic and Milk Production of Cows Milked by a Pasture Based Automatic Milking System

Simple Summary

Several studies have demonstrated that combining grazing and robotic milking is possible. However, there is often a decrease in milking frequency, which leads to a decrease in milk production. The objective of this study was to investigate the effect of two strategies to improve traffic in a pasture-based automatic milking system. Therefore we formed four groups differing based on concentrate allocation and based on minimum milking interval (MMI) necessary to access the robot for milking. Therefore four groups (high concentrate–short MMI, high concentrate–long MMI, low concentrate–short MMI, low concentrate–long MMI) were constituted. We compared these four groups with regard to traffic parameters (milkings, refused milkings) and animal production. The study highlighted the positive effect of high concentrate–short MMI on traffic to the robot by reducing the number of refused milkings. High concentrate allocation allowed to maintain high milk production over the experiment duration.

Abstract

In dairy farms automatic milking systems and grazing, traffic to the robot is the cornerstone of profitability as higher milking frequency enhances milk yield. In this study, we investigated whether shortening the minimum milking interval (MMI), i.e., the required time between two milkings for an animal to get access to the milking unit, coupled with high concentrate allocation, could increase the daily milking frequency (MF, milking/cow/day) and consequently the milk yield of grazing cows. Two groups of cows (n = 19 and n = 20) belonging to the same herd were discriminated based on concentrate supply (high vs. low: 4 vs. 2 kg/cow/day) and then further divided on the basis of MMI (4 h vs. 6 h) so that four groups were formed (HC4 h–HC6 h–LC4 h and finally LC6 h). Higher concentrate allocation induced a rise in milk yield (MY, kg/cow/day) and allowed to stabilize it in periods of grass shortage but did not influence milking frequency, while shorter MMI (4 h) was correlated with higher MF without effect on MY. A combination of both strategies (4 h and high concentrate) improved the traffic globally to the robot. This result was linked to a reduction of refused milking and, therefore, the decrease in returns to the robot. This strategy could be advised to maximize the system’s efficiency during periods of high milk sales. When the economic conditions do not favour the increase in concentrate supply, short MMI could facilitate the traffic and increase the efficiency of returns.

Historical Evolution of Cattle Management and Herd Health of Dairy Farms in OECD Countries

This work aimed to review the important aspects of the dairy industry evolution at herd level, interrelating production with health management systems. Since the beginning of the industrialization of the dairy cattle sector (1950s), driven by the need to feed the rapidly growing urban areas, this industry has experienced several improvements, evolving in management and technology. These changes have been felt above all in the terms of milking, rearing, nutrition, reproductive management, and design of facilities. Shortage of labor, emphasis on increasing farm efficiency, and quality of life of the farmers were the driving factors for these changes. To achieve it, in many areas of the world, pasture production has been abandoned, moving to indoor production, which allows for greater nutritional and reproductive control of the animals. To keep pace with this paradigm in milk production, animal health management has also been improved. Prevention and biosecurity have become essential to control and prevent pathologies that cause great economic losses. As such, veterinary herd health management programs were created, allowing the management of health of the herd as a whole, through the common work of veterinarians and farmers. These programs address the farms holistically, from breeding to nutrition, from prevention to consultancy. In addition, farmers are now faced with a consumer more concerned on animal production, valuing certified products that respect animal health and welfare, as well as environmental sustainability.

The prevalence of Campylobacter spp., Listeria monocytogenes and Shiga toxin-producing Escherichia coli in Norwegian dairy cattle farms; a comparison between free stall and tie stall housing systems

Aims

This study explored how dairy farm operating systems with free‐stall or tie‐stall housing and cow hygiene score influence the occurrence of zoonotic bacteria in raw milk.

Methods and Results

Samples from bulk tank milk (BTM), milk filters, faeces, feed, teats and teat milk were collected from 11 farms with loose housing and seven farms with tie‐stall housing every second month over a period of 11 months and analysed for the presence of STEC by culturing combined with polymerase chain reaction and for Campylobacter spp. and L. monocytogenes by culturing only. Campylobacter spp., L. monocytogenes and STEC were present in samples from the farm environment and were also detected in 4%, 13% and 7% of the milk filters, respectively, and in 3%, 0% and 1% of BTM samples. Four STEC isolates carried the eae gene, which is linked to the capacity to cause severe human disease. L. monocytogenes were detected more frequently in loose housing herds compared with tie‐stalled herds in faeces (p = 0.02) and feed (p = 0.03), and Campylobacter spp. were detected more frequently in loose housing herds in faeces (p < 0.01) and teat swabs (p = 0.03). An association between cow hygiene score and detection of Campylobacter spp. in teat milk was observed (p = 0.03).

Conclusion

Since some samples collected from loose housing systems revealed a significantly higher (p < 0.05) content of L. monocytogenes and Campylobacter spp. than samples collected from tie‐stalled herds, the current study suggests that the type of housing system may influence the food safety of raw milk.

Significance and Impact of the Study

This study highlights that zoonotic bacteria can be present in raw milk independent of hygienic conditions at the farm and what housing system is used. Altogether, this study provides important knowledge for evaluating the risk of drinking unpasteurized milk.