1,720,971 research outputs found
Influence of the milking units on the pulsation curve in dairy sheep milking
No full textMechanical milking is a critical operation in ewe dairy farming where the operative parameters and the milking routine strongly influence milk production and animal welfare. The challenge in adapting dairy animals to the farm environmental conditions may cause illness and compromise the quality of the products. From this perspective, it is important to evaluate the technological and operational aspects that can influence milk quality and animal welfare. Thus, the aim of this work was to investigate the effects on the pulsation curve of several teat cup characteristics (volume of the pulsation chamber) at determined operating parameters (vacuum level and pulsator rate) recorded from nine different milking units. Moreover, the touch point pressure of different liners was measured. Data analysis showed that the sheep milking unit characteristics affected the pulsation curve significantly. The length of both the increasing vacuum phase and the decreasing vacuum phase (phase “a” and “c”, respectively), which affect the milking and massage phases, was directly related to the pulsation chamber volume (R2 = 0.86) and the pulsator rate. No relationship emerged between the touch point pressure and specific characteristics of the liners such as the material, the shape, the diameter, the length, or the extension of the body. Considering the delicate role that the pulsation plays in ensuring animal welfare during milking, it is important to take into account the complete configuration and operative characteristics of the milking units. This will ensure that the complex interaction between the pulsation system and the milking units is considered when planning and assembling milking systems
Use of Heavy Metals Contaminated Industrial Hemp (Cannabis Sativa L.) for Bioenergy Production
No full textWorldwide human-related activities have caused the heavy metals contamination of large areas. Nowadays, different soil remediation activities are undertaken to ameliorate contaminated soils. Among the various soil reclamation technologies, phytoremediation is considered one of the most cost-effective and eco-friendly practices, where the use of industrial hemp (Cannabis sativa L.) has shown promising remediation potential. However, the proper management, disposal or valorization of the contaminated biomass represents a key point for the sustainability of the entire remediation process. This study aims to assess and evaluate the energy and environmental burdens of using heavy metals contaminated industrial hemp for bioenergy production. Specifically, the cumulative energy demand and climate change impact categories were selected from the life cycle assessment methodology. The data sample comes from real heavy metals contaminated sites, located in Sardinia (Italy), which have been subjected to soil reclamation by growing industrial hemp. The energy and environmental impacts of using the contaminated biomass as an energy resource were then modeled from a “field to wire” approach. The designed scenario analyzed the processes associated with field level, transportation, combustion of the contaminated biomass in a power plant and ash disposal. The results obtained underlined that the field level represents the main impacting process, while the electricity produced from the contaminated biomass allowed to save about 32 GJ ha−1 of primary energy while avoiding emissions of 642 kg CO2e per phytoremediated hectare. The study highlights that the use of heavy metals contaminated biomass for bioenergy production, improved the sustainability of soil reclamation activities turning unproductive lands into productive areas
Performance and usability of smartglasses for augmented reality in precision livestock farming operations
No full textIn recent years, smartglasses for augmented reality are becoming increasingly popular in professional contexts. However, no commercial solutions are available for the agricultural field, despite the potential of this technology to help farmers. Many head-wearable devices in development possess a variety of features that may affect the smartglasses wearing experience. Over the last decades, dairy farms have adopted new technologies to improve their productivity and profit. However, there remains a gap in the literature as regards the application of augmented reality in livestock farms. Head-wearable devices may offer invaluable benefits to farmers, allowing real-time information monitoring of each animal during on-farm activities. The aim of this study was to expand the knowledge base on how augmented reality devices (smartglasses) interact with farming environments, focusing primarily on human perception and usability. Research has been conducted examining the GlassUp F4 smartglasses during animal selection process. Sixteen participants performed the identification and grouping trials in the milking parlor, reading different types of contents on the augmented reality device optical display. Two questionnaires were used to evaluate the perceived workload and usability of the device. Results showed that the information type could influence the perceived workload and the animal identification process. Smart glasses for augmented reality were a useful tool in the animal genetic improvement program offering promising opportunities for adoption in livestock operations in terms of assessing data consultation and information about animals
Influence of milking units and working vacuum level on the mechanical milking of goats
No full textThe objectives of this study were to evaluate and compare the effect of working vacuum levels (35 and 44 kPa) and liners dimensions (mouthpiece lip diameter and overall length, 20–185 and 22–170 mm) on the main milking characteristics of goats. The results highlight that both the working vacuum level and the liner dimension have influenced the milk flow curve parameters. The maximum variations were found for peak flow rate, which increased significantly with liner dimensions of 20–185 mm at a working vacuum level of 44 kPa as well as average milk flow rate and for plateau phase duration. The incorrect adoption of operative parameters and unsuitable milking machine components, might affect the performance of the mechanical milking and negatively affecting animal productions and welfare
Evaluating an autonomous electric robot for real farming applications
No full textMobile robotic technologies are emerging in agriculture in recent years, driven by labor shortages, the need of precision farm management, and the improvement of farmers' quality of life. Mobile robotic technologies, both aerial and ground, have been considered as one of the most important and promising solutions to address agricultural challenges. Nevertheless, the implementation rate in farms is still low. The aim of this study was to evaluate the performance of a mobile agricultural ground robot to assess its possible implementation in the farm environment. The mobility performances as well as the energy consumption of the mobile robot were evaluated considering different interaction systems (teleoperated, autonomous driving) and application areas (weeding, tilling). The results show that the forward speed of the tested mobile robot is affected by the towed load, up to 230 kg, and that the robot could be driven continuously for 2 h in the field without decreasing its performances at a maximum speed between 0.71-0.77 m s-1. The autonomy of the tested robot is limited, but this is mainly due to the battery technology used. The mobile robot effectively tow implements for weeding and tilling operations managing grass with a single pass (40 % weed removal) and improving soil bulk density. The average energy consumption across the different settings was about 1.43 kWh for each hour of use. Moreover, although the RTKGNSS autonomous navigation used was a low-cost system, the results showed a good accuracy, which allowed the mobile robot to navigate autonomously in the 2 m inter-row of the vineyard. Finally, the working capacity of the mobile robots, considering the implements used, is on average 0.29 ha h-1. This study provides further evidence for the possible use of ground mobile robot in agriculture to carry out autonomous or semi-autonomous operations
Combining Smart Glasses and Thermal Imaging as a Tool for Water Stress Detection in Greenhouses: A Preliminary Study
No full textThe aim of the study was to combine low-cost thermal imaging camera with smart glasses to evaluate the feasibility of augmented reality system for monitoring water stress under protected conditions. The tests were performed in a greenhouse on 208 Petunia hybrid ‘Surfinia’ plants. All the plants were irrigated to reach field capacity, while 15 of them did not receive irrigation water for seven days before the trials. Three qualified operators had to identify the plants in water stress condition, using 3 operative modes: naked eyes (NE); thermal imaging camera (Thermal Compact Pro, Seek, USA) associated with a smartphone (TSP); thermal imaging camera associated with smart glasses (TSG, M400, Vuzix, USA). The results showed a general low rate of water stressed plants identification in the three operative modes considered. On the other hand, the unsuccessful detection of the plants in water deficit made by the operators was reduced about 40% when adopting the TSG as compared to NE operative mode
A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms
No full textA comprehensive energy analysis and related carbon footprint of dairy farms, part 1: Direct energy requirements
No full textDairy cattle farms are continuously developing more intensive systems of management which require higher utilization of durable and not-durable inputs. These inputs are responsible of significant direct and indirect fossil energy requirements which are related to remarkable emissions of CO2. This study aims to analyze direct energy requirements and the related carbon footprint of a large population of conventional dairy farms located in the south of Italy. A detailed survey of electricity, diesel and Liquefied Petroleum Gas (LPG) consumptions has been carried out among on-farm activities. The results of the analyses showed an annual average fuel consumption of 40 kg per tonne of milk, while electricity accounted for 73 kWh per tonne of milk produced. Expressing the direct energy inputs as primary energy, diesel fuel results the main resource used in on-farm activities, accounting for 72% of the total fossil primary energy requirement, while electricity represents only 27%. Moreover, larger farms were able to use more efficiently the direct energy inputs and reduce the related emissions of carbon dioxide per unit of milk produced, since the milk yield increases with the herd size. The global average farm emissions of carbon dioxide equivalent, due to all direct energy usages, accounted for 156 kg CO2-eq per tonne of Fat and Protein Corrected Milk (FPCM), while farms that raise more than 200 heads emitted 36% less than the average value. In this two-part series, the total energy demand (Part 1 + Part 2) per farm is mainly due to agricultural inputs and fuel consumption, which have the largest quota of the annual requirements for each milk yield class. These results also showed that large size farms held lower CO2-eq emissions when referred to the mass of milk produced
Milkability traits across milk flow curve types in Sarda sheep
Full text linkA temporary interruption of the milk flow is observed between alveolar and cisternal fraction in ewes for the peculiar anatomy of the mammary gland. Often during milking a physiological delay in milk excretion between the cisternal and the alveolar fraction occurs. However, long delays may indicate suboptimal pre-stimulation of teats and/or insufficient oxytocin release in the bloodstream, resulting in undesired protracted interruptions between the 2 milk peaks. Moreover, a clear distinction between the fractions may be undetectable in high-producing ewes, particularly in early lactation. Based on both milk flow curve shape and duration of different excretion phases during milking, 3 curve types can be identified: single-peak (P1), double-peak (P2), and long plateau (PL). The aim of the present study was to compare milkability traits across the 3 milk flow curve types using data recorded in Sarda sheep breed; for this scope, 10 features were measured with a milkmeter in 568 ewes belonging to different parities, lactation stages, and commercial farms. After editing, data of 544 ewes reared in 17 farms were available for the analysis. The P1 curves were the most frequent (57.5 %), but ewes with a PL curve were significantly more productive than those with a P1 curve (0.61 ± 0.03 vs 0.53 ± 0.02 kg of milk/milking). Milk yield of P2 ewes was intermediate (0.58 ± 0.03 kg of milk/milking) and in all curves the majority of milk was excreted in the first 60 s of milking. The highest milk flow rate and the shortest milk emission time were estimated for the P1 curves; moreover, the blind time, indicator of overmilking, was the minimum in PL curves and the maximum in P1 curves. Based on such findings, farmers are recommended to pay more attention to milk emission curves in their herd in order to avoid overmilking, particularly in the presence of P1 curves. Considering the large herd size of Sarda breed farms (170.3 ewes per farm in 2020), part of milking routine could be slightly modified and customized according to milk flow curve type and lactation stage. Ideally, this will allow optimal milking practices to be adopted within groups of ewes with similar milkability. Monitoring milk emission curves and adopting less-standard and more adjusted milking practices is useful to meet the ewe's individual milking ability and in the long term would limit mammary gland stress, reduce antimicrobial use due to udder issues, and improve the udder health in Sarda sheep
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