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By-products from forestry, agriculture and nature areas are used in compost bedded-pack housing (CBP) systems for animals. In this communication, we discuss the application of a CBP system to animal farms and aspects related to the recycling and reuse of the materials in the context of a circular economy. This study is based on data from ongoing projects and literature. The following systems are discussed: (i) composting material applied to a specialized animal housing system; (ii) adding a horticultural component to the animal farm by reusing the compost, and (iii) a cooperative mixed cattle and crop farming system. The success of integrating a compost bedding component in the system depends largely on the skills of managing the composting process, the application of the material in the field, and the cost of acquiring the material. When materials are amply available, then a real contribution to the circular economy can be made. Cooperation between farmers in the utilization of by-products is another route to a more circular economy. Moreover, the analyzed systems can be seen as a Greenhouse Gases (GHG) mitigation practice because they store carbon in the soil and improve soil quality.

The bedding materials used in dairy cow housing systems are extremely important for animal welfare and performance. A wide range of materials can be used as bedding for dairy cattle, but their physical properties must be analysed to evaluate their potential. In the present study, the physical properties of various bedding materials for dairy cattle were investigated, and different fuzzy clustering algorithms were employed to cluster these materials based on their physical properties. A total of 51 different bedding materials from various places in Europe were collected and tested. Physical analyses were carried out for the following parameters: bulk density (BD), water holding capacity (WHC), air-filled porosity (AFP), global density (GD), container capacity (CC), total effective porosity (TEP), saturated humidity (SH), humidity (H), and average particle size (APS). These data were analysed by principal components analysis (PCA) to reduce the amount of data and, subsequently, by fuzzy clustering analysis. Three clustering algorithms were tested: k-means (KM), fuzzy c-means (FCM) and Gustafson&ndash, Kessel (GK) algorithms. Furthermore, different numbers of clusters (2&minus, 8) were evaluated and subsequently compared using five validation indexes. The GK clustering algorithm with eight clusters fit better regarding the division of materials according to their properties. From this clustering analysis, it was possible to understand how the physical properties of the bedding materials may influence their behaviour. Among the materials that fit better as bedding materials for dairy cows, Posidonia oceanica (Cluster 6) can be considered an alternative material.

The use of sensor technologies to monitor cows’ behavior is becoming commonplace in the context of dairy production. This study aimed at validating a commercial collar-based sensor system, the AFICollar® (Afimilk, Kibbutz Afikim, Israel), designed to monitor dairy cattle feeding and ruminating behavior. Additionally, the performances of two versions of the software for behavior classification, the current software AFIfarm® 5.4 and the updated version AFIfarm® 5.5, were compared. The study involved twenty Holstein-Friesian cows fitted with the collars. To evaluate the sensor performance under different feeding scenarios, the animals were divided into four groups and fed three different types of feed (total mixed ration, long hay, animals allowed to graze). Recordings of hourly rumination and feeding time produced by the sensor were compared with visual observation by scan sampling at 1 minute intervals using Spearman correlation, concordance correlation coefficient (CCC), Bland–Altman plots and linear mixed models for assessing the precision and accuracy of the system. The analyses confirmed that the updated software version V5.5 produced better detection performance than the current V5.4. The updated software version produced high correlations between visual observations and data recorded by the sensor for both feeding (r = 0.85, CCC = 0.86) and rumination (r = 0.83, CCC = 0.86). However, the limits of agreement for both behaviors remained quite wide (feeding: −19.60 min/h, 17.46 min/h, rumination: −15.80 min/h, 15.00 min/h). Type of feed did not produce significant effects on the agreement between visual observations and sensor recordings. Overall, the results indicate that the system can provide farmers with adequately accurate data on feeding and rumination time, and can be used to support herd management decisions. Despite all this, the precision of the system remained relatively limited, and should be improved with further developments in the classification algorithm.

In livestock farming, maintaining dry bedding is considered to be important for maximising animal performance and welfare. A better understanding of the mechanisms that regulate drying has the potential to improve bedding management and reduce production costs. A custom laboratory-scale method was developed to explore the effects of environmental conditions and bedding characteristics on drying rate (DR). Samples (n = 256) of different types of bedding materials were exposed to controlled environmental conditions by using a climate chamber equipped with a custom cabinet capable of simulating different levels of air velocity and bedding temperature. The effects of the type of material, bedding moisture content, bedding temperature, air temperature, air relative humidity (RH) and air velocity were evaluated in a full factorial experimental design. Under the experimental conditions tested, DR ranged from 0.28 to 6.04 kg m−2 d−1, with an average of 2.03 kg m−2 d−1. All variables significantly affected DR, but large variation in the magnitude of effects was found. Bedding moisture content, air velocity and air RH had considerably larger effects than the other variables, together accounting for more than 70% of the variance in DR. The DR from bedding samples increased with bedding moisture content and air velocity but decreased with increasing air RH. The results of the current study may have important implications in the design and management of bedded pack barns. To increase the DR and keep bedding dry, producers should focus primarily on providing adequate barn ventilation (both in terms of air velocity and air exchange), whereas maintaining a high pack temperature may yield poorer-than-expected results.

The promised benefits of precision technologies (PTs) include improved efficiency, quality, animal health and welfare and reduced environmental impacts. To date, PTs (including sensors, algorithms, big data, decision-support tools, etc.) have had a relatively modest impact in pasture-based dairying systems in comparison with other agricultural sectors such as arable production. The areas animals roam and graze in pasture-based systems and the associated connectivity challenges may, in part at least, explain the comparatively reduced use of PTs in those systems. Thus, there are very few technologies designed specifically to increase pasture utilisation with the exception of global positioning systems (GPS) and Bluetooth-enabled Plate Meters. Terrestrial and satellite-based spectral analysis of pasture biomass and quality is still in the development phase. Therefore, one of the key drivers of efficiency in pasture-based systems has only been marginally impacted by PTs. In contrast, technological development in the area of fertility and heat detection has been important and offers significant potential value to dairy farmers. In general PTs can be described as good at measurement, data collection and storage but fall down around interpretation and providing useful outputs to end users. As a result, it is unclear if farm management is being sufficiently improved to justify widespread adoption of PTs. A needs-driven development of PTs and decision-support tools are required for the succesful integration within agriculture. Further cost/benefit analysis is also required to determine the efficiency of investing in PTs and what, if any, factors affect the variation in the returns.

peer-reviewed Precision livestock farming uses biosensors to measure different parameters of individual animals to support farmers in the decision making process. Although sensor development is advanced, there is still little implementation of sensor-based solutions on commercial farms. Especially on pasture-based dairy systems, the grazing management of cows is largely not supported by technology. A key factor in pasture-based milk production is the correct grass allocation to maximize the grass utilization per cow, while optimizing cow performance. Currently, grass allocation is mostly based on subjective eye measurements or calculations per herd. The aim of this study was to identify possible indicators of insufficient or sufficient grass allocation in the cow grazing behaviour measures. A total number of 30 cows were allocated a restricted pasture allowance of 60% of their intake capacity. Their behavioural characteristics were compared to those of 10 cows (control group) with pasture allowance of 100% of their intake capacity. Grazing behaviour and activity of cows were measured using the RumiWatchSystem for a complete experimental period of 10 weeks. The results demonstrated that the parameter of bite frequency was significantly different between the restricted and the control groups. There were also consistent differences observed between the groups for rumination time per day, rumination chews per bolus and frequency of cows standing or lying.

The commercially available collar device MooMonitor+ was evaluated with regards to accuracy and application potential for measuring grazing behavior. These automated measurements are crucial as cows feed intake behavior at pasture is an important parameter of animal performance, health and welfare as well as being an indicator of feed availability. Compared to laborious and time-consuming visual observation, the continuous and automated measurement of grazing behavior may support and improve the grazing management of dairy cows on pasture. Therefore, there were two experiments as well as a literature analysis conducted to evaluate the MooMonitor+ under grazing conditions. The first experiment compared the automated measurement of the sensor against visual observation. In a second experiment, the MooMonitor+ was compared to a noseband sensor (RumiWatch), which also allows continuous measurement of grazing behavior. The first experiment on n = 12 cows revealed that the automated sensor MooMonitor+ and visual observation were highly correlated as indicated by the Spearman’s rank correlation coefficient (rs) = 0.94 and concordance correlation coefficient (CCC) = 0.97 for grazing time. An rs-value of 0.97 and CCC = 0.98 was observed for rumination time. In a second experiment with n = 12 cows over 24-h periods, a high correlation between the MooMonitor+ and the RumiWatch was observed for grazing time as indicated by an rs-value of 0.91 and a CCC-value of 0.97. Similarly, a high correlation was observed for rumination time with an rs-value of 0.96 and a CCC-value of 0.99. While a higher level of agreement between the MooMonitor+ and both visual observation and RumiWatch was observed for rumination time compared to grazing time, the overall results showed a high level of accuracy of the collar device in measuring grazing and rumination times. Therefore, the collar device can be applied to monitor cow behavior at pasture on farms. With regards to the application potential of the collar device, it may not only be used on commercial farms but can also be applied to research questions when a data resolution of 15 min is sufficient. Thus, at farm level, the farmer can get an accurate and continuous measurement of grazing behavior of each individual cow and may then use those data for decision-making to optimize the animal management.

The bedding material used in barns for dairy cows has a significant effect on animal welfare and performance. Bedding influences the duration in which animals remain lying down and, consequently, the processes of rumination and milk production. It is crucial to have a complete understanding of the properties of bedding materials and the effects of alternative bedding materials on dairy cattle. This paper aims to evaluate the physical, chemical, and biological properties of various alternative and conventional bedding materials for dairy cattle for use in compost bedded pack or freestall barn systems. We analyzed 50 samples of 17 bedding materials produced in 3 European countries. We analyzed physical properties including the water holding capacity, porosity, moisture content, bulk density, dry bulk density, and particle size. Chemical analyses were performed to determine the total N, total organic C, and C:N ratio. In the biological analyses, the Escherichia coli count, total bacteria count, coliform count, and Klebsiella spp. count were assessed. The results demonstrated how the physical properties of the bedding materials may influence the chemical and biological properties. All of the materials presented adequate chemical properties to be used as bedding material. The physical properties of the bedding materials differed widely among the materials except for the dry bulk density, which presented no difference. Moreover, the contamination of each studied microorganism was observed for each bedding material to determine which material had the lowest level of contamination. Posidonia oceanica, Miscanthus grass, and spelt husks could be considered as a potential alternative material for use as bedding material for dairy cows in both systems (i.e., composted bedded pack and freestall). This experiment illustrated the importance of performing thorough physical, chemical, and biological analyses before implementing a material as bedding for dairy cattle.

Among the most straining trends that farmers have to face there are: on one side, to guarantee welfare and adequate life conditions for animals and to reduce the environmental footprint, on the other side, to develop new strategies to improve farm management reducing costs. The current conditions and the expected developments of the dairy sector highlight a strong need for more efficient and sustainable farming systems. Studying heat stress, herd management and housing and animals’ productive and reproductive performances is fundamental for the economic and environmental sustainability of the dairy chain. New and effective tools to cope with these challenges have been provided by Precision Livestock Farming (PLF), which is nowadays increasingly applied and makes possible to control quali-quantitative parameters related to production, health, behaviour, and real-time locomotion per animal. The research key challenge is to turn these data into knowledge to provide real-time support in farming optimisation. This research focuses specifically on different systems to collect, process and derive useful information from data on animal welfare and productivity. A multi-disciplinary approach has been adopted to generate a decision support system for farmers.

Housing system can affect dairy cow’s welfare and performance and the type of bedding material used can also affect comfort and hygiene level of the animals. A wide range of different materials can be used in bedding for dairy cattle, but their physical proprieties must be analyzed to evaluate their potential. Therefore, this study aimed to investigate the physical properties of Miscanthus grass in comparison to wheat straw, as an affordable alternative being used as bedding material in housing systems for dairy cows. Particle size, bulk density, air-filled porosity and water holding capacity from Miscanthus and wheat straw were measured experimentally in the lab of the DAGRI of the University of Florence. The particle size was determined by applying 50 g of material on six meshes. Bulk density was determined according to the ASABE Standard S269.4 DEC 91. To determine the water holding capacity and air filled porosity of bedding materials samples the Australian Standards AS 3743-2003 were used. The analysis showed that since Miscanthus presented 88% of the particle size bigger than 50 mm, it also presented higher value of water holding capacity (0.072 kg L−1) in comparison with wheat straw (0.057 kg L−1). Miscanthus presented higher bulk density (26 kg m−3) than wheat straw (18 kg m−3). Both materials presented similar air-filled porosity, around 88%. Based on these physical properties results, it was possible to demonstrate the good potential to use Miscanthus as a viable alternative to wheat straw as a bedding material for dairy cattle.

The objective of this review was to describe recent changes and expected developments in housing systems for dairy cows. These new developments should create an appropriate production environment for modern high-producing dairy cows and stimulate dairy farming-related developments in management, agro-technology, and equipment. Increased labor efficiency has been an important driver of the change from tie-stall barns to cubicle barns (also known as freestall barns). In future housing systems, the natural behavior of cows, climate control, emissions of ammonia and greenhouse gases, reuse of waste, manure quality, the aesthetics of buildings in the landscape, and capital efficiency are becoming increasingly important elements. To address future requirements, new concepts beyond cubicle barns must be developed. Freewalk housing systems; that is, loose housing systems without cubicles, would meet some of these future demands. These systems operate with composting bedding material or artificial permeable floors as lying and walking areas. However, these barns are still in development. Combinations of cubicle and freewalk housing systems, together with other techniques being developed, might become a major future housing system. Other techniques and systems that are being explored according to sustainability criteria include the multi-climate shed, the CowToilet (Hanskamp AgroTech, Doetinchem, the Netherlands) to separate feces and urine, and multifunctional buildings. These buildings and techniques can be part of land-based or, less commonly, city-based farming systems, such as floating farms.

Sensor technologies that measure grazing and ruminating behaviour as well as physical activities of individual cows are intended to be included in precision pasture management. One of the advantages of sensor data is they can be analysed to support farmers in many decision-making processes. This article thus considers the performance of a set of RumiWatchSystem recorded variables in the prediction of insufficient herbage allowance for spring calving dairy cows. Several commonly used models in machine learning (ML) were applied to the binary classification problem, i.e., sufficient or insufficient herbage allowance, and the predictive performance was compared based on the classification evaluation metrics. Most of the ML models and generalised linear model (GLM) performed similarly in leave-out-one-animal (LOOA) approach to validation studies. However, cross validation (CV) studies, where a portion of features in the test and training data resulted from the same cows, revealed that support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost) performed relatively better than other candidate models. In general, these ML models attained 88% AUC (area under receiver operating characteristic curve) and around 80% sensitivity, specificity, accuracy, precision and F-score. This study further identified that number of rumination chews per day and grazing bites per minute were the most important predictors and examined the marginal effects of the variables on model prediction towards a decision support system.

Compost-bedded pack barns (CBP) are receiving increasing attention as a housing system for dairy cows that has potential to improve animal welfare. This article reviews current scientific knowledge about CBP with the aim of providing a comprehensive tool for producers and researchers using this housing system. In CBP, cows are provided with an open bedded pack area rather than the individual stalls and concrete alleys found in freestall systems. The bedded pack, a mixture of organic bedding and cattle excreta, is cultivated frequently (1–3 times per day) to incorporate fresh manure and air into the pack, thus promoting an aerobic composting process. To function well, CBP generally require a large area per cow. Optimal animal densities over the bedded area range from 7.4 to more than 15 m2/cow depending on several factors, including climate, bedding, pack management, and cow characteristics. Studies have indicated that CBP, compared with conventional systems such as freestall barns, have the potential to improve the welfare of dairy cows. In particular, the main reported benefits include improved comfort during resting, better foot and leg health, and more natural animal behavior. Research has also indicated that adequate udder health can be achieved in CBP. However, because the bedded pack has been shown to contain high bacterial concentrations, proper management is essential to maintain adequate cow cleanliness and reduce the risk of mastitis. Controlling pack moisture is consistently indicated as the most important issue with CBP. Especially under cold and humid weather conditions, large amounts of bedding may be necessary to keep the pack adequately dry and comfortable for the cows. Nevertheless, the improvements in cow health may offset the higher costs of bedding.

Precision technologies and data have had relatively modest impacts in grass-based livestock ruminant production systems compared with other agricultural sectors such as arable. Precision technologies promise increased efficiency, reduced environmental impact, improved animal health, welfare and product quality. The benefits of precision technologies have, however, been relatively slow to be realised on pasture based farms. Though there is significant overlap with indoor systems, implementing technology in grass-based dairying brings unique opportunities and challenges. The large areas animals roam and graze in pasture based systems and the associated connectivity challenges may, in part at least, explain the comparatively lower adoption of such technologies in pasture based systems. With the exception of sensor and Bluetooth-enabled plate metres, there are thus few technologies designed specifically to increase pasture utilisation. Terrestrial and satellite-based spectral analysis of pasture biomass and quality is still in the development phase. One of the key drivers of efficiency in pasture based systems has thus only been marginally impacted by precision technologies. In contrast, technological development in the area of fertility and heat detection has been significant and offers significant potential value to dairy farmers, including those in pasture based systems. A past review of sensors in health management for dairy farms concluded that although the collection of accurate data was generally achieved, the processing, integration and presentation of the resulting information and decision-support applications were inadequate. These technologies' value to farming systems is thus unclear. As a result, it is not certain that farm management is being sufficiently improved to justify widespread adoption of precision technologies currently. We argue for a user need-driven development of technologies and for a focus on how outputs arising from precision technologies and associated decision support applications are delivered to users to maximise their value. Further cost/benefit analysis is required to determine the efficacy of investing in specific precision technologies, potentially taking account of several yet to ascertained farm specific variables.

Earth-to-air heat exchangers (EAHE) can reduce the energy consumption required for heating and cooling of buildings. The composition and the thermal characteristics of the soil influence the heat exchange capacity, and the soil moisture can furthermore affect thermal performance of EAHE. The aim of this study was to compare the thermal performance of EAHE in dry and artificially wetted soil. Tests were carried out in the Basra Province (Iraq), in a semi-desert area. Two experimental EAHE were built in a poultry barn and tested from June 2013 to September 2013. The pipe exchangers were buried at 2 m deep. One heat exchanger operated in dry soil (DE), while the other one operated in artificially wetted soil (WE). In the WE system, a drip tubing placed 10 cm above the air pipe wetted the soil around the exchanger. Air temperatures at the inlet and at the outlet of both the exchangers as well as soil temperature at 2 m deep were continuously monitored. The experimental results confirmed that wetting the soil around EAHE improves the general heat exchange efficiency. The coefficient of cooling performance (COP) of the earth-to-air heat exchangers system was evaluated on the basis of the ratio between the heat removed from the air or added to the air and the energy input. During the day, with an average COP of 6.41, the WE system cooled the air more than the DE system, which reported a value of 5.07. On average, in the hottest hours of the day, the outlet temperature of the WE was 37.35°C while in the DE it was 38.91°C. Moreover, during the nighttime, the WE system warmed the air more than the DE system. Keywords: Earth-to-air heat exchangers, thermal performance, cooling, artificially wetted soil, poultry barn, heat stress DOI: 10.25165/j.ijabe.20181103.3047 Citation: Morshed W, Leso L, Conti L, Rossi G, Simonini S, Barbari M. Cooling performance of earth-to-air heat exchangers applied to a poultry barn in semi-desert areas of south Iraq. Int J Agric & Biol Eng, 2018; 11(3): 47–53.

Recent testing of an active radio frequency identification (RFID) system within an outdoor fenced-enclosure housing four fattening pigs is described. The system is a modular active-RFID system composed by marker, reader and beacon tag. The enclosure was divided into three areas using three marker's loop-antennas. These areas were the pigs' feeding, drinking and resting areas. The duration in seconds verified by video recordings that individual animals attended in the zones outlined by the markers was compared with the duration acquired by the active-RFID system. The results indicate an acceptable accuracy of position-data, as overall 5% underestimation was achieved. Different levels of precision were achieved by the active-RFID system according to the feeding, drinking and resting areas monitored. In particular, problems were encountered due to the behaviour of the pigs surrounding the perimeter of the marked areas, the size and positioning of the tag on the pig's collar, and other software, hardware and calibration issues some of which may be overcome. These issues, together with the cost, are main limitation when using this technology.

An alternative constructive solution for photovoltaic integration in the roof, which enhances thermal performance of the building during the hot period is presented. To reduce the diurnal heat load and to increase the capacity of discharging heat through the roof at night, the proposed roofing solution was equipped with a ventilated interspace. The roof consisted of two different layers: the top cover was made up of PV modules (m-Si) and the lower layer consisted of fissured wooden boards. A scale model was realized to test the performance of this solution during the hot period in comparison with other two different types of covers: simple PV modules; insulating sandwich panels.