Sequential Behavior of Broiler Chickens in Enriched Environments under Varying Thermal Conditions Using the Generalized Sequential Pattern Algorithm: A Proof of Concept.

Behavior analysis is a widely used non-invasive tool in the practical production routine, as the animal acts as a biosensor capable of reflecting its degree of adaptation and discomfort to some environmental challenge. Conventional statistics use occurrence data for behavioral evaluation and well-being estimation, disregarding the temporal sequence of events. The Generalized Sequential Pattern (GSP) algorithm is a data mining method that identifies recurrent sequences that exceed a user-specified support threshold, the potential of which has not yet been investigated for broiler chickens in enriched environments. Enrichment aims to increase environmental complexity with promising effects on animal welfare, stimulating priority behaviors and potentially reducing the deleterious effects of heat stress. The objective here was to validate the application of the GSP algorithm to identify temporal correlations between heat stress and the behavior of broiler chickens in enriched environments through a proof of concept. Video image collection was carried out automatically for 48 continuous hours, analyzing a continuous period of seven hours, from 12:00 PM to 6:00 PM, during two consecutive days of tests for chickens housed in enriched and non-enriched environments under comfort and stress temperatures. Chickens at the comfort temperature showed high motivation to perform the behaviors of preening (P), foraging (F), lying down (Ld), eating (E), and walking (W); the sequences <{Ld,P}>; <{Ld,F}>; <{P,F,P}>; <{Ld,P,F}>; and <{E,W,F}> were the only ones observed in both treatments. All other sequential patterns (comfort and stress) were distinct, suggesting that environmental enrichment alters the behavioral pattern of broiler chickens. Heat stress drastically reduced the sequential patterns found at the 20% threshold level in the tested environments. The behavior of lying laterally "Ll" is a strong indicator of heat stress in broilers and was only frequent in the non-enriched environment, which may suggest that environmental enrichment provides the animal with better opportunities to adapt to stress-inducing challenges, such as heat.

Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis.

The advancement of technology has significantly transformed the livestock landscape, particularly in the management of dairy cattle, through the incorporation of digital and precision approaches. This study presents a bibliometric analysis focused on these technologies involving dairy farming to explore and map the extent of research in the scientific literature. Through this review, it was possible to investigate academic production related to digital and precision livestock farming and identify emerging patterns, main research themes, and author collaborations. To carry out this investigation in the literature, the entire timeline was considered, finding works from 2008 to November 2023 in the scientific databases Scopus and Web of Science. Next, the Bibliometrix (version 4.1.3) package in R (version 4.3.1) and its Biblioshiny software extension (version 4.1.3) were used as a graphical interface, in addition to the VOSviewer (version 1.6.19) software, focusing on filtering and creating graphs and thematic maps to analyze the temporal evolution of 198 works identified and classified for this research. The results indicate that the main journals of interest for publications with identified affiliations are "Computers and Electronics in Agriculture" and "Journal of Dairy Science". It has been observed that the authors focus on emerging technologies such as machine learning, deep learning, and computer vision for behavioral monitoring, dairy cattle identification, and management of thermal stress in these animals. These technologies are crucial for making decisions that enhance health and efficiency in milk production, contributing to more sustainable practices. This work highlights the evolution of precision livestock farming and introduces the concept of digital livestock farming, demonstrating how the adoption of advanced digital tools can transform dairy herd management. Digital livestock farming not only boosts productivity but also redefines cattle management through technological innovations, emphasizing the significant impact of these trends on the sustainability and efficiency of dairy production.

Differences in the Behavioral Parameters of Young Zebu and Composite Bulls Kept on Non-Forested or in Integrated Crop-Livestock-Forestry Systems.

The behavior of ruminants can influence their productive efficiency. The aim of this study was to evaluate the behavior of young zebu and composite bulls kept in pasture production systems, either in a crop-livestock-forest integration or without afforestation. The work was carried out in São Carlos, Brazil (21°57'42″ S, 47°50'28″ W), in a high-altitude tropical climate, from March to July, 2022. Forty young bulls were evaluated, being 20 Nelore (Bos indicus) (342.5 ± 36.6 kg BW; 16.9 ± 1.8 months) and 20 Canchim (5/8 Bos taurus × 3/8 Bos indicus) (338.4 ± 39.8 kg BW; 19.1 ± 1.9 months), equally distributed in full-sun (FS) and integrated crop-livestock-forestry (ICLF) production systems. Behavior was monitored uninterruptedly by an acoustic sensor and accelerometer attached to a collar, and complemented by direct visual assessment, in two one-day campaigns per month. Serum cortisol concentration was assessed monthly. Statistical analyses were conducted using a general linear model at a 5% significance level (SAS, version 9.4). The ICLF system had a milder microclimate and favored thermal comfort. Natural shading influenced grazing, resting, and rumination time. The Canchim bulls were more active when moving and grazing (p < 0.05), even at the hottest times of the day. In turn, the Nelore bulls spent more time resting at all times (p < 0.001), which was shown to be an adaptive strategy in response to environmental stimuli. The Canchim bulls had a longer rumination time than the Nelore bulls (p < 0.001), due to their longer grazing time. The frequency of water and mineral mixture intake did not differ between genotypes, regardless of the production system (p > 0.05). There was no difference in the serum cortisol concentrations of the Nelore and Canchim bulls kept in FS or ICLF (p = 0.082). Thus, young bulls of the different genotypes showed different behaviors, regardless of whether they were kept on pasture without afforestation or in an integrated crop-livestock-forestry system.

Applications of livestock monitoring devices and machine learning algorithms in animal production and reproduction: an overview.

Some sectors of animal production and reproduction have shown great technological advances due to the development of research areas such as Precision Livestock Farming (PLF). PLF is an innovative approach that allows animals to be monitored, through the adoption of cutting-edge technologies that continuously collect real-time data by combining the use of sensors with advanced algorithms to provide decision tools for farmers. Artificial Intelligence (AI) is a field that merges computer science and large datasets to create expert systems that are able to generate predictions and classifications similarly to human intelligence. In a simplified manner, Machine Learning (ML) is a branch of AI, and can be considered as a broader field that encompasses Deep Learning (DL, a Neural Network formed by at least three layers), generating a hierarchy of subsets formed by AI, ML and DL, respectively. Both ML and DL provide innovative methods for analyzing data, especially beneficial for large datasets commonly found in livestock-related activities. These approaches enable the extraction of valuable insights to address issues related to behavior, health, reproduction, production, and the environment, facilitating informed decision-making. In order to create the referred technologies, studies generally go through five steps involving data processing: acquisition, transferring, storage, analysis and delivery of results. Although the data collection and analysis steps are usually thoroughly reported by the scientific community, a good execution of each step is essential to achieve good and credible results, which impacts the degree of acceptance of the proposed technologies in real life practical circumstances. In this context, the present work aims to describe an overview of the current implementations of ML/DL in livestock reproduction and production, as well to identify potential challenges and critical points in each of the five steps mentioned, which can affect results and application of AI techniques by farmers in practical situations.

Decision support system to classify the vulnerability of broiler production system to heat stress based on fuzzy logic.

In this study, we develop an artificial intelligence model to predict the vulnerability of broiler production systems (broilers and facilities) to heat conditions using a fuzzy model approach. The model was designed with a multiple-input and a single-output (MISO) approach (input: physical environment and broilers age; output: degree of vulnerability of broilers system). For the validation of the fuzzy model, two approaches were used: (1) records from the scientific literature and (2) meteorological forecasts. First, we validated the model fuzzy with data from the scientific literature; second, we validate the model with data from meteorological forecasts. Both validation approaches were performed in different scenarios of the thermal environment (comfort, discomfort, and discomfort + low heat exchange), broilers' age (21-35 days, 25-39 days, and 28-42 days), and relative cooling efficiency (0% inefficient; and 80% efficient). Then, we applied the model to predict the degree of vulnerability of the broiler system with the help of weather forecasts. The recall and precision of the fuzzy model were high (> 0.9) for the thermal comfort and thermal discomfort + low heat exchange scenarios. In contrast, the fuzzy model was moderate agreement (recall 0.45; precision 0.64) for the thermal discomfort scenario compared to the scientific literature. The application of the model with the weather forecast showed the interaction between the physical and biological systems when submitted to a thermal environment challenge. Regardless of the broilers' age, a high degree of vulnerability was observed in facilities with inefficient cooling system. The fuzzy model developed in this study was efficient to predict the vulnerability of the broiler production system to heat conditions, further, to identify the uncertain conditions associated with broilers' age, relative humidity, and the relative cooling efficiency of the facilities.

Applications of livestock monitoring devices and machine learning algorithms in animal production and reproduction: an overview

Some sectors of animal production and reproduction have shown great technological advances due to the development of research areas such as Precision Livestock Farming (PLF). PLF is an innovative approach that allows animals to be monitored, through the adoption of cutting-edge technologies that continuously collect real-time data by combining the use of sensors with advanced algorithms to provide decision tools for farmers. Artificial Intelligence (AI) is a field that merges computer science and large datasets to create expert systems that are able to generate predictions and classifications similarly to human intelligence. In a simplified manner, Machine Learning (ML) is a branch of AI, and can be considered as a broader field that encompasses Deep Learning (DL, a Neural Network formed by at least three layers), generating a hierarchy of subsets formed by AI, ML and DL, respectively. Both ML and DL provide innovative methods for analyzing data, especially beneficial for large datasets commonly found in livestock-related activities. These approaches enable the extraction of valuable insights to address issues related to behavior, health, reproduction, production, and the environment, facilitating informed decision-making. In order to create the referred technologies, studies generally go through five steps involving data processing: acquisition, transferring, storage, analysis and delivery of results. Although the data collection and analysis steps are usually thoroughly reported by the scientific community, a good execution of each step is essential to achieve good and credible results, which impacts the degree of acceptance of the proposed technologies in real life practical circumstances. In this context, the present work aims to describe an overview of the current implementations of ML/DL in livestock reproduction and production, as well to identify potential challenges and critical points in each of the five steps mentioned, which can affect results and application of AI techniques by farmers in practical situations.(AU)

Major differences between single or twin hair lambs in the immediate postpartum period: Metabolic and thermodynamic patterns detected by infrared thermography.

The objective was to evaluate the differences between hair lambs, born from single or twin births, regarding the latency periods for standing up and suckling, the vitality, glycemic, cortisol, and triiodothyronine concentrations, as well as the phenotypic characteristics related to the maintenance of homeothermy in the immediate postpartum. Single (n = 10) or twin (n = 12) Morada Nova lambs were evaluated after birth, during the first successful suckling (M0 = Timepoint 0), and at regular intervals of 20 min (M20, M40, M60). Lambs from single births had higher birth weight (3.09 vs 2.58 kg; P ≤ 0.05) and higher serum triiodothyronine concentration (267 vs 209 ng/dL; P ≤ 0.05) compared to twin lambs. There was a positive correlation between weight and blood glucose (0.57; P ≤ 0.05) for both single and twin lambs. The type of birth did not affect vitality, which was negatively associated with cortisol concentration (-0.53; P ≤ 0.05). Twin lambs had higher internal and ocular temperatures (39.29 vs 38.67 °C and 38.84 vs 38.13 °C; P ≤ 0.05, respectively). Body surface temperatures increased over time in both groups (P ≤ 0.05). An increase in the temperature of the hips region (ysingle = 27.88 + 0.019*time; R2 = 0.96; P = 0.019 and ytwin = 28.74 + 0.019*time; R2 = 0.94; P = 0.029) was observed for both single and twin lambs, which coincides with the region of brown adipose tissue deposition. The lowest absolute thermal variabilities between twin and single lambs in M0 and M60 were recorded in the midloin and integral dorsal area. The parturition type did not influence the latencies to stand up (P = 0.908) and for the first suckling (P = 0.888), and the vitality score (P = 0.353). Thus, single and twin lambs do not differ in neonatal behavior, but they presented specific metabolic strategies to regulate body temperature over time. Midloin and integral dorsal areas are anatomical regions suggested for use in serial thermographic monitoring. Infrared thermography may be an important complementary resource in neonatal care.

Dynamics of Thermolysis and Skin Microstructure in Water Buffaloes Reared in Humid Tropical Climate-A Microscopic and Thermographic Study.

The thermolytic capacity test is used to assess the adaptability of animals to existing environmental conditions. However, there is insufficient information on the relationship between histomorphometry and adaptability of buffaloes. Thus, this study aimed to assess the use of thermolysis pathways by buffaloes reared in a hot and humid environment so as to understand the relationships between environment, skin morphological characteristics, and heat storage, as well as the intensity and proportionality of use of its ways of dissipating heat to maintain homeothermy. The heat tolerance test, associated with the evaluations via infrared thermography, was applied to 10 female Murrah buffaloes and tegument histomorphometry was carried out. The animals exhibited very high heat tolerance with an average of 9.66 ± 0.21 and used thermal polypnea as the main heat dissipation pathway. Their mean skin thickness was 6.03 ± 1.16 mm and the active sweat and sebaceous gland tissue were 1.57 ± 0.38% and 1.08 ± 0.39%, respectively. The buffaloes exhibited a positive correlation between eyeball temperature and internal body temperature (r = 0.84523, p < 0.0001) and a negative correlation between respiratory rate and skin thickness (r = -0.73371, p = 0.0157). The high thermolytic capacity in shade conditions confirms the importance of access to shade in buffalo rearing systems in tropical regions.

Prandial Correlations and Structure of the Ingestive Behavior of Pigs in Precision Feeding Programs.

The feeding behavior of growing-finishing pigs was analyzed to study prandial correlations and the probability of starting a new feeding event. The data were collected in real-time based on 157,632 visits by a group of 70 growing-finishing pigs (from 30.4 to 115.5 kg body weight, BW) to automatic feeders. The data were collected over 84 days, during which period the pigs were kept in conventional (by phase and by group) or precision (with daily and individual adjustments) feeding programs. A criterion to delimit each meal was then defined based on the probability of an animal starting a new feeding event within the next minute since the last visit. Prandial correlations were established between meal size and interval before meal (pre-prandial) or interval after meal (post-prandial) using Pearson correlation analysis. Post-prandial correlations (which can be interpreted as hunger-regulating mechanisms) were slightly stronger than pre-prandial correlations (which can be interpreted as satiety regulation mechanisms). Both correlations decreased as the animals' age increased but were little influenced by the feeding programs. The information generated in this study allows a better understanding of pigs' feeding behavior regulation mechanisms and could be used in the future to improve precision feeding programs.

Classification of environmental factors potentially motivating for dairy cows to access shade.

The aim of this Research Communication was to apply the data mining technique to classify which environmental factors have the potential to motivate dairy cows to access natural shade. We defined two different areas at the silvopastoral system: shaded and sunny. Environmental factors and the frequency that dairy cows used each area were measured during four days, for 8 h each day. The shaded areas were the most used by dairy cows and presented the lowest mean values of all environmental factors. Solar radiation was the environmental factor with most potential to classify the dairy cow's decision to access shaded areas. Data mining is a machine learning technique with great potential to characterize the influence of the thermal environment in the cows' decision at the pasture.

Environmental variables responsible for Zebu cattle thermal comfort acquisition.

The aim of this study was to estimate, using data mining, which microclimate and behavioral variables affect the behavior of animals to seek shaded or sunny areas. The experiment was carried out between January and May 2016 in an integrated crop-livestock-forest system. In this system, we defined two different areas: shaded and sunny. Microclimatic variables (At, BGt, RH, and WS) were measured in each area on 4 consecutive days per month. With these variables, we determined the bioclimatic indicators (THI, BGHI, HLI, MRT, RTL, and ETI). In addition, we calculated the absolute difference (Δ) by subtracting the value recorded in shaded areas from the value recorded in sunny areas for all microclimatic variables and bioclimatic indicators, except for WS. The behaviors (grazing, ruminating, and other activities), posture (standing or lying), and use of areas (shaded or sunny) of 38 Zebu cattle were recorded on 2 consecutive days per month. The data mining technique was applied for analysis in a classification task. The model correctly classified 76% of the instances with a Kappa statistic of 0.51 after features selection from the database. The ΔBGt was the most important feature in the model to classify the decision of Zebu cattle to seek another area or remain in a determined area. The model was built with seven classification rules, being one simple rule, composed of the interaction between ΔBGt and rumination; and other more complex rules, composed of the interactions among the ΔBGt, WS, and rumination. The preference of Zebu cattle to seek or remain in shaded or sunny areas was influenced by eight features: rumination, drinking water, WS, ΔBGt, MRT in shade, BGHI in sun, ΔBGHI, and HLI in sun.

Smart Feeding Unit for Measuring the Pecking Force in Farmed Broilers.

Feeding is one of the most critical processes in the broiler production cycle. A feeder can collect data of force signals and continuously transform it into information about birds' feed intake and quickly permit more agile and more precise decision-making concerning the broiler farm's production process. A smart feeding unit (SFU) prototype was developed to evaluate the broiler pecking force and average feed intake per pecking (g/min). The prototype consisted of a power supply unit with a data acquisition module, management software connected to a computer for data storage, and a video camera to verify the pecking force during signal processing. In the present study, seven male Cobb-500 broilers were raised in an experimental chamber to test and commission the prototype. The prototype consisted of a feeding unit (feeder) with a data acquisition module (amplifier), with real-time integration for testing and intuitive operation with Catman Easy software connected to a computer to obtain and store data from signals. The sampling of average feed intake per pecking per broiler (g) was conducted during the first minute of feeding, subtracting the amount of feed provided per the amount of feed consumed, including the count of pecking in the first minute of feeding. An equation was used for estimating the average feed intake per pecking per broiler (g). The results showed that the average broiler pecking force was 1.39 N, with a minimum value of 0.04 N and a maximum value of 7.29 N. The average feed intake per pecking (FIP) was 0.13 g, with an average of 173 peckings per minute. The acquisition, processing, and classification of signals in the pecking force information were valuable during broilers' feeding. The smart feeding unit prototype for broilers was efficient in the continuous assessment of feed intake and can generate information for estimating broiler performance.

Estresse calórico e reprodução em ovinos: fundamentos e perspectivas tecnológicas / Heat stress on sheep reproduction: fundamentals and technological perspectives

A ovinocultura é uma importante atividade que produz proteínas de alto valor biológico, mas seus ganhos podem ser reduzidos em função do estresse ambiental. Isso reforça a importância de se estudar a relação entre o ambiente térmico e o animal, identificando animais mais adaptados e férteis, e melhores práticas de manejo. O ovino (Ovis aries) é um animal homeotérmico, que mantem sua temperatura corporal em equilíbrio dinâmico. Quando em estresse calórico, os ovinos usam mecanismos sensíveis e latentes para dissipar o calor acumulado, com destaque para o redirecionamento do fluxo sanguíneo, a ofegação e a sudorese. O escroto desempenha importante crucial na termorregulação dos testículos, os quais precisam funcionar sob em até 6,0oC abaixo da temperatura interna corpórea. A hipertermia testicular compromete a espermatogênese, reduz a concentração seminal, a motilidade progressiva e a viabilidade espermática. Ainda, leva a aumento dos defeitos morfológicos espermáticos, na produção de espécies reativas de oxigênio e na fragmentação do DNA espermático, diminuindo a capacidade fecundante. Tecnologias disruptivas para monitoramento do ambiente de produção, da termorregulação e do bem-estar dos animais já são realidade e se encontram em expansão, favorecendo a tomada de decisões em tempo real e o desempenho reprodutivo dos ovinos.

Sheep farming is a relevant activity that provides proteins of high biological value, but its gains can be reduced due to environmental stress. This reinforces the importance of studying the relationship between the thermal environment and the animal, identifying more adapted and fertile animals, and better management practices. Sheep (Ovis aries) are homeothermic animals and thus maintain their body temperature in a state of dynamic balance. Under heat stress, sheep dissipate accumulated heat through sensitive and latent mechanisms, primarily using redirection of blood flow, panting and sweating. The scrotum plays a crucial role in the thermoregulation of the testicles, which need to be maintained up to 6.0oC below the body core temperature. Testicular hyperthermia impairs spermatogenesis, reduces seminal concentration, progressive motility and sperm viability. Furthermore, it leads to an increase in sperm morphological defects, in the production of reactive oxygen species, and in sperm DNA fragmentation, reducing the fertilizing capacity. Disruptive technologies for monitoring the production systems, animal thermoregulation and welfare are already a reality and are expanding, favoring realtime decision making and the reproductive performance of sheep.

Robotic milking of dairy cows: a review / Ordenha robotizada de vacas leiteiras: uma revisão

Automatic milking systems (AMS) have aroused worldwide interest recently. The first installation was by the company Lely in a project in the Netherlands (its homeland) in 1992. But nowadays, AMS represents a growing reality due to lobby for labor issues, rising costs, difficulty finding well-trained workers, and/ or difficulty keeping people on farms. This work aimed to present a review of the literature on AMS, beginning with a brief history of the evolution of the technology, showing advantages and limitations of its use, and ultimately giving some suggestions. The understanding of the technical functioning and operational running can help farmers and technicians in decision making on the adoption of the new technology. Besides workforce reduction and labor quality promotion, AMS has potential to improve feed conversion to milk, milk quality (with lower SCC), and cow productivity, as well as providing useful data and parameters for better farm management. Potential limitations include high investment costs, changes in milk composition (solids, free fatty acids), and increased risk of ketosis in cows.(AU)

Robôs ordenhadores são uma novidade razoavelmente recente no mundo. O primeiro foi instalado em 1992, pela empresa Lely, em um projeto experimental em seu país de origem, a Holanda. Entretanto, trata-se de uma realidade presente e cada vez maior, pois o problema da mão de obra, em diversos locais do mundo, cada vez mais cara, pouco capacitada e/ou difícil de manter na fazenda, é inexorável. Objetivou-se apresentar uma revisão da literatura sobre a utilização da robótica na ordenha de vacas leiteiras, abordando o funcionamento técnico e operacional, bem como vantagens e limitações de sua utilização, visando auxiliar pecuaristas e técnicos na tomada de decisões em adotar, ou não, essa tecnologia. Apresentou-se, ainda, um breve histórico da evolução dos robôs ordenhadores, bem como algumas considerações finais. Constatou-se que os robôs, além de substituírem mão de obra, possuem o potencial de melhorarem a conversão alimentar para leite, a qualidade do leite (baixar CCS), aumentar a produtividade das vacas e proporcionar dados e parâmetros para uma gestão mais adequada dos números da atividade dentro da fazenda. Dentre as possíveis limitações estão o alto valor de investimento, alterações em sólidos do leite, presença de ácidos graxos livres no leite e aumento nos riscos de cetose nas vacas.(AU)

Feeding behavior of growing and finishing pigs fed different dietary threonine levels in a group-phase feeding and individual precision feeding system.

Feeding behavior is an important aspect of pig husbandry as it can affect protein deposition (PD) in pigs. A decrease in plasma threonine (Thr) levels may influence feed intake (FI) due to amino acid imbalance. We set out to study whether different Thr inclusion rates of 70%, 85%, 100%, 115%, and 130% of the ideal Thr:lysine (Lys) ratio of 0.65 in two different feeding programs (individual precision feeding and group-phase feeding could affect pig feeding behavior and consequently PD. Two 21-d trials were performed in a 2 × 5 factorial setup (feeding systems × Thr levels) with 110 pigs in the growing phase [25.0 ± 0.8 kg of body weight (BW)] and 110 pigs in the finishing phase (110.0 ± 7.0 kg BW), which correspond to 11 pigs per treatment in each trial. Pigs were housed in the same room and fed using computerized feeding stations. The total lean content was estimated by dual x-ray absorptiometry at the beginning (day 1) and the end (day 21) of the trial. Multivariate exploratory factor analysis was performed to identify related variables. Confirmatory analysis was performed by orthogonal contrasts and Pearson correlation analysis. Graphical analysis showed no difference in feeding patterns between feeding systems during the growing or finishing phase. Pigs exhibited a predominant diurnal feeding, with most meals (73% on average) consumed between 0600 and 1800 h. Exploratory factor analysis indicated that feeding behavior was not related to growth performance or PD in growing or finishing pigs. Changes in feeding behavior were observed during the growing phase, where increasing dietary Thr resulted in a linear increase in the FI rate (P < 0.05). During the finishing phase, the duration of the meal and FI rate increased linearly as dietary Thr increased in the diet (P < 0.05). These changes in feeding behavior are, however, correlated to BW. In conclusion, the exploratory factor analysis indicated that feeding behavior had no correlation with growth performance or protein and lipid deposition in growing or finishing pigs. Dietary Thr levels and feeding systems had no direct effect on FI.

Robotic milking of dairy cows: a review / Ordenha robotizada de vacas leiteiras: uma revisão

Automatic milking systems (AMS) have aroused worldwide interest recently. The first installation was by the company Lely in a project in the Netherlands (its homeland) in 1992. But nowadays, AMS represents a growing reality due to lobby for labor issues, rising costs, difficulty finding well-trained workers, and/ or difficulty keeping people on farms. This work aimed to present a review of the literature on AMS, beginning with a brief history of the evolution of the technology, showing advantages and limitations of its use, and ultimately giving some suggestions. The understanding of the technical functioning and operational running can help farmers and technicians in decision making on the adoption of the new technology. Besides workforce reduction and labor quality promotion, AMS has potential to improve feed conversion to milk, milk quality (with lower SCC), and cow productivity, as well as providing useful data and parameters for better farm management. Potential limitations include high investment costs, changes in milk composition (solids, free fatty acids), and increased risk of ketosis in cows.

Robôs ordenhadores são uma novidade razoavelmente recente no mundo. O primeiro foi instalado em 1992, pela empresa Lely, em um projeto experimental em seu país de origem, a Holanda. Entretanto, trata-se de uma realidade presente e cada vez maior, pois o problema da mão de obra, em diversos locais do mundo, cada vez mais cara, pouco capacitada e/ou difícil de manter na fazenda, é inexorável. Objetivou-se apresentar uma revisão da literatura sobre a utilização da robótica na ordenha de vacas leiteiras, abordando o funcionamento técnico e operacional, bem como vantagens e limitações de sua utilização, visando auxiliar pecuaristas e técnicos na tomada de decisões em adotar, ou não, essa tecnologia. Apresentou-se, ainda, um breve histórico da evolução dos robôs ordenhadores, bem como algumas considerações finais. Constatou-se que os robôs, além de substituírem mão de obra, possuem o potencial de melhorarem a conversão alimentar para leite, a qualidade do leite (baixar CCS), aumentar a produtividade das vacas e proporcionar dados e parâmetros para uma gestão mais adequada dos números da atividade dentro da fazenda. Dentre as possíveis limitações estão o alto valor de investimento, alterações em sólidos do leite, presença de ácidos graxos livres no leite e aumento nos riscos de cetose nas vacas.

Robotic milking of dairy cows: a review / Ordenha robotizada de vacas leiteiras: uma revisão

Automatic milking systems (AMS) have aroused worldwide interest recently. The first installation was by the company Lely in a project in the Netherlands (its homeland) in 1992. But nowadays, AMS represents a growing reality due to lobby for labor issues, rising costs, difficulty finding well-trained workers, and/ or difficulty keeping people on farms. This work aimed to present a review of the literature on AMS, beginning with a brief history of the evolution of the technology, showing advantages and limitations of its use, and ultimately giving some suggestions. The understanding of the technical functioning and operational running can help farmers and technicians in decision making on the adoption of the new technology. Besides workforce reduction and labor quality promotion, AMS has potential to improve feed conversion to milk, milk quality (with lower SCC), and cow productivity, as well as providing useful data and parameters for better farm management. Potential limitations include high investment costs, changes in milk composition (solids, free fatty acids), and increased risk of ketosis in cows.

Robôs ordenhadores são uma novidade razoavelmente recente no mundo. O primeiro foi instalado em 1992, pela empresa Lely, em um projeto experimental em seu país de origem, a Holanda. Entretanto, trata-se de uma realidade presente e cada vez maior, pois o problema da mão de obra, em diversos locais do mundo, cada vez mais cara, pouco capacitada e/ou difícil de manter na fazenda, é inexorável. Objetivou-se apresentar uma revisão da literatura sobre a utilização da robótica na ordenha de vacas leiteiras, abordando o funcionamento técnico e operacional, bem como vantagens e limitações de sua utilização, visando auxiliar pecuaristas e técnicos na tomada de decisões em adotar, ou não, essa tecnologia. Apresentou-se, ainda, um breve histórico da evolução dos robôs ordenhadores, bem como algumas considerações finais. Constatou-se que os robôs, além de substituírem mão de obra, possuem o potencial de melhorarem a conversão alimentar para leite, a qualidade do leite (baixar CCS), aumentar a produtividade das vacas e proporcionar dados e parâmetros para uma gestão mais adequada dos números da atividade dentro da fazenda. Dentre as possíveis limitações estão o alto valor de investimento, alterações em sólidos do leite, presença de ácidos graxos livres no leite e aumento nos riscos de cetose nas vacas.

Robotic milking of dairy cows: a review / Ordenha robotizada de vacas leiteiras: uma revisão

Automatic milking systems (AMS) have aroused worldwide interest recently. The first installation was by the company Lely in a project in the Netherlands (its homeland) in 1992. But nowadays, AMS represents a growing reality due to lobby for labor issues, rising costs, difficulty finding well-trained workers, and/ or difficulty keeping people on farms. This work aimed to present a review of the literature on AMS, beginning with a brief history of the evolution of the technology, showing advantages and limitations of its use, and ultimately giving some suggestions. The understanding of the technical functioning and operational running can help farmers and technicians in decision making on the adoption of the new technology. Besides workforce reduction and labor quality promotion, AMS has potential to improve feed conversion to milk, milk quality (with lower SCC), and cow productivity, as well as providing useful data and parameters for better farm management. Potential limitations include high investment costs, changes in milk composition (solids, free fatty acids), and increased risk of ketosis in cows.

Robôs ordenhadores são uma novidade razoavelmente recente no mundo. O primeiro foi instalado em 1992, pela empresa Lely, em um projeto experimental em seu país de origem, a Holanda. Entretanto, trata-se de uma realidade presente e cada vez maior, pois o problema da mão de obra, em diversos locais do mundo, cada vez mais cara, pouco capacitada e/ou difícil de manter na fazenda, é inexorável. Objetivou-se apresentar uma revisão da literatura sobre a utilização da robótica na ordenha de vacas leiteiras, abordando o funcionamento técnico e operacional, bem como vantagens e limitações de sua utilização, visando auxiliar pecuaristas e técnicos na tomada de decisões em adotar, ou não, essa tecnologia. Apresentou-se, ainda, um breve histórico da evolução dos robôs ordenhadores, bem como algumas considerações finais. Constatou-se que os robôs, além de substituírem mão de obra, possuem o potencial de melhorarem a conversão alimentar para leite, a qualidade do leite (baixar CCS), aumentar a produtividade das vacas e proporcionar dados e parâmetros para uma gestão mais adequada dos números da atividade dentro da fazenda. Dentre as possíveis limitações estão o alto valor de investimento, alterações em sólidos do leite, presença de ácidos graxos livres no leite e aumento nos riscos de cetose nas vacas.