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Mechanical 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.
Maria Caria; Giuseppe Todde; Antonio Pazzona. Influence of the Milking Units on the Pulsation Curve in Dairy Sheep Milking. Animals 2020, 10, 1213 .
AMA StyleMaria Caria, Giuseppe Todde, Antonio Pazzona. Influence of the Milking Units on the Pulsation Curve in Dairy Sheep Milking. Animals. 2020; 10 (7):1213.
Chicago/Turabian StyleMaria Caria; Giuseppe Todde; Antonio Pazzona. 2020. "Influence of the Milking Units on the Pulsation Curve in Dairy Sheep Milking." Animals 10, no. 7: 1213.
In 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.
Maria Caria; Giuseppe Todde; Gabriele Sara; Marco Piras; Antonio Pazzona. Performance and Usability of Smartglasses for Augmented Reality in Precision Livestock Farming Operations. Applied Sciences 2020, 10, 2318 .
AMA StyleMaria Caria, Giuseppe Todde, Gabriele Sara, Marco Piras, Antonio Pazzona. Performance and Usability of Smartglasses for Augmented Reality in Precision Livestock Farming Operations. Applied Sciences. 2020; 10 (7):2318.
Chicago/Turabian StyleMaria Caria; Giuseppe Todde; Gabriele Sara; Marco Piras; Antonio Pazzona. 2020. "Performance and Usability of Smartglasses for Augmented Reality in Precision Livestock Farming Operations." Applied Sciences 10, no. 7: 2318.
The objective of this study was to assess whether precision photovoltaic irrigation represents a sustainable alternative to traditional systems, where the energy and environmental performances were firstly evaluated through energy and carbon payback times (EPBT and CPBT). The study involved five Photovoltaic Irrigation Systems (PVIS), ranging from 40 to 360 kWp, installed in Spain, Portugal, Morocco and Italy. The results show an average EPBT of 3.3 years and CPBT of 6.3 years, with an energy return on energy invested (EROI) of 9.0. Additionally, the PVIS were able to achieve low emission rates with an average of 77.4 g CO2e per kWh produced. The energy and environmental performance of the PVIS are closely influenced by weather conditions, irrigation requirements and water availability. Moreover, the implementation of precision PVIS allowed improving the irrigation practices, avoiding the exploitation of natural resources and the emissions of large amounts of GHG to the environment.
Giuseppe Todde; Maria Caria; Antonio Pazzona; Luigi Ledda; Luis Narvarte. Does Precision Photovoltaic Irrigation Represent a Sustainable Alternative to Traditional Systems? Lecture Notes in Civil Engineering 2020, 585 -593.
AMA StyleGiuseppe Todde, Maria Caria, Antonio Pazzona, Luigi Ledda, Luis Narvarte. Does Precision Photovoltaic Irrigation Represent a Sustainable Alternative to Traditional Systems? Lecture Notes in Civil Engineering. 2020; ():585-593.
Chicago/Turabian StyleGiuseppe Todde; Maria Caria; Antonio Pazzona; Luigi Ledda; Luis Narvarte. 2020. "Does Precision Photovoltaic Irrigation Represent a Sustainable Alternative to Traditional Systems?" Lecture Notes in Civil Engineering , no. : 585-593.
The growing interest in Augmented Reality (AR) systems is becoming increasingly evident in all production sectors. However, to the authors’ knowledge, a literature gap has been found with regard to the application of smart glasses for AR in the agriculture and livestock sector. In fact, this technology allows farmers to manage animal husbandry in line with precision agriculture principles. The aim of this study was to evaluate the performances of an AR head-wearable device as a valuable and integrative tool in precision livestock farming. In this study, the GlassUp F4 Smart Glasses (F4SG) for AR were explored. Laboratory and farm tests were performed to evaluate the implementation of this new technology in livestock farms. The results highlighted several advantages of F4SG applications in farm activities. The clear and fast readability of the information related to a single issue, combined with the large number of readings that SG performed, allowed F4SG adoption even in large farms. In addition, the 7 h of battery life and the good quality of audio-video features highlighted their valuable attitude in remote assistance, supporting farmers on the field. Nevertheless, other studies are required to provide more findings for future development of software applications specifically designed for agricultural purposes.
Maria Caria; Gabriele Sara; Giuseppe Todde; Marco Polese; Antonio Pazzona. Exploring Smart Glasses for Augmented Reality: A Valuable and Integrative Tool in Precision Livestock Farming. Animals 2019, 9, 903 .
AMA StyleMaria Caria, Gabriele Sara, Giuseppe Todde, Marco Polese, Antonio Pazzona. Exploring Smart Glasses for Augmented Reality: A Valuable and Integrative Tool in Precision Livestock Farming. Animals. 2019; 9 (11):903.
Chicago/Turabian StyleMaria Caria; Gabriele Sara; Giuseppe Todde; Marco Polese; Antonio Pazzona. 2019. "Exploring Smart Glasses for Augmented Reality: A Valuable and Integrative Tool in Precision Livestock Farming." Animals 9, no. 11: 903.
Over the last decades, traditional olive production has been converted to intensive and super-intensive cultivation systems, characterized by high plant density and irrigation. Although this conversion improves product quality and quantity, it requires a larger amount of energy input. The new contributions in this paper are, first, an analysis of the energy and environmental performance of two commercial-scale high peak-power hybrid photovoltaic irrigation systems (HPVIS) installed at intensive and super-intensive Mediterranean olive orchards; second, an analysis of PV hybrid solutions, comparing PV hybridization with the electric power grid and with diesel generators; and finally, a comparison of the environmental benefits of HPVIS with conventional power sources. Energy and environmental performances were assessed through energy and carbon payback times (EPBT and CPBT). The results show EPBT of 1.98 and 4.58 years and CPBT of 1.86 and 9.16 years for HPVIS in Morocco and Portugal, respectively. Moreover, the HPVIS were able to achieve low emission rates, corresponding to 48 and 103 g COe per kWh generated. The EPBT and CPBT obtained in this study were directly linked with the irrigation schedules of the olive orchards; therefore, weather conditions and irrigation management may modify the energy and environmental performances of HPVIS. The consumption of grid electricity and diesel fuel, before and after the implementation of HPVIS, was also analyzed. The results obtained show fossil energy savings of 67% for the Moroccan farm and 41% for the Portuguese installation. These savings suggest that the energy produced by HPVIS in olive orchards will avoid the emissions of a large amount of greenhouse gas and the exploitation of natural resources associated with fossil fuel production.
Giuseppe Todde; Lelia Murgia; Paola A. Deligios; Rita Hogan; Isaac Carrelo; Madalena Moreira; Antonio Pazzona; Luigi Ledda; Luis Narvarte. Energy and environmental performances of hybrid photovoltaic irrigation systems in Mediterranean intensive and super-intensive olive orchards. Science of The Total Environment 2019, 651, 2514 -2523.
AMA StyleGiuseppe Todde, Lelia Murgia, Paola A. Deligios, Rita Hogan, Isaac Carrelo, Madalena Moreira, Antonio Pazzona, Luigi Ledda, Luis Narvarte. Energy and environmental performances of hybrid photovoltaic irrigation systems in Mediterranean intensive and super-intensive olive orchards. Science of The Total Environment. 2019; 651 ():2514-2523.
Chicago/Turabian StyleGiuseppe Todde; Lelia Murgia; Paola A. Deligios; Rita Hogan; Isaac Carrelo; Madalena Moreira; Antonio Pazzona; Luigi Ledda; Luis Narvarte. 2019. "Energy and environmental performances of hybrid photovoltaic irrigation systems in Mediterranean intensive and super-intensive olive orchards." Science of The Total Environment 651, no. : 2514-2523.
The setting up of innovative irrigation water management might contribute to the mitigation of negative issues related to climate change. Our hypothesis was that globe artichoke irrigated with a traditionally drip system could be converted to an innovative water management system based on precision irrigation techniques and on evaporative cooling application in order to improve crop physiological status with positive impacts on earliness, total heads yield and water saving. Over two experiments carried out at plot- and field-scale, two irrigation management systems, differing in type and application time, were compared: (i) conventional, and (ii) canopy-cooling. Plant physiological status at a weekly sampling interval and the head atrophy incidence (as the ratio of the total primary heads collected) were monitored. We also recorded and determined heads production, and yield components. In both experiments, throughout the application period of evaporative cooling (three months), canopy-cooling showed the lowest value of leaf temperature and the highest photosynthesis values compared with the conventional one (+3 °C and −30%, respectively). The physiological advantage gained by the crop with evaporative cooling has led to a higher production both in terms of total yield (+30%), and in terms of harvested first order heads that from an economic viewpoint are the most profitable for farmers. At farm-scale, the canopy-cooling treatment resulted in a higher earliness (35 days) and water productivity (+36%) compared with conventional one. Our findings show that by combining evaporative cooling practice with precision irrigation technique the heads yield can be optimized also leading to a relevant water saving (−34%). Moreover, the study proved that canopy-cooling set up might be a winning strategy in order to mitigate climatic changes and heat stress conditions.
Paola A. Deligios; Anna Paola Chergia; Gavino Sanna; Stefania Solinas; Giuseppe Todde; Luis Narvarte; Luigi Ledda. Climate change adaptation and water saving by innovative irrigation management applied on open field globe artichoke. Science of The Total Environment 2018, 649, 461 -472.
AMA StylePaola A. Deligios, Anna Paola Chergia, Gavino Sanna, Stefania Solinas, Giuseppe Todde, Luis Narvarte, Luigi Ledda. Climate change adaptation and water saving by innovative irrigation management applied on open field globe artichoke. Science of The Total Environment. 2018; 649 ():461-472.
Chicago/Turabian StylePaola A. Deligios; Anna Paola Chergia; Gavino Sanna; Stefania Solinas; Giuseppe Todde; Luis Narvarte; Luigi Ledda. 2018. "Climate change adaptation and water saving by innovative irrigation management applied on open field globe artichoke." Science of The Total Environment 649, no. : 461-472.
A life cycle assessment (LCA) methodology was used to evaluate the cumulative energy demand and the related environmental impact of three large-power stand-alone photovoltaic (PV) irrigation systems ranging from 40 kWp to 360 kWp. The novelty of this analysis is the large power of these systems as the literature up to now is restricted to modeled PV pumping systems scenarios or small power plants, where the size can be a critical factor for energy and environmental issues. The analysis shows that the yearly embodied energy per unit of PV power ranged from 1306 MJ/kWp to 1199 MJ/kWp depending of the PV generator size. Similarly, the related yearly carbon dioxide impacts ranged from 72.6 to 79.8 kg CO2e/kWp. The production of PV modules accounted for the main portion (about 80%) of the primary energy embodied into the PV irrigation system (PVIS). The outcomes of the study also show an inverse trend of the energy and carbon payback times respect to the PV power size: In fact, energy payback time increased from 1.94, to 5.25 years and carbon payback time ranged from 4.62 to 9.38 years. Also the energy return on investment depends on the PV generator dimension, ranging from 12.9 to 4.8. The environmental impact of the stand-alone PV systems was also expressed in reference to the potential amount of electricity generated during the whole PV life. As expected, the largest PVIS performs the best result, obtaining an emission rate of 45.9 g CO2e per kWh, while the smallest one achieves 124.1 g CO2e per kWh. Finally, the energy and environmental indicators obtained in this study are strongly related to the irrigation needs, which in turn are influenced by other factors as the type of cultivated crops, the weather conditions and the water availability.
Giuseppe Todde; Lelia Murgia; Isaac Carrelo; Rita Hogan; Antonio Pazzona; Luigi Ledda; Luis Narvarte. Embodied Energy and Environmental Impact of Large-Power Stand-Alone Photovoltaic Irrigation Systems. Energies 2018, 11, 2110 .
AMA StyleGiuseppe Todde, Lelia Murgia, Isaac Carrelo, Rita Hogan, Antonio Pazzona, Luigi Ledda, Luis Narvarte. Embodied Energy and Environmental Impact of Large-Power Stand-Alone Photovoltaic Irrigation Systems. Energies. 2018; 11 (8):2110.
Chicago/Turabian StyleGiuseppe Todde; Lelia Murgia; Isaac Carrelo; Rita Hogan; Antonio Pazzona; Luigi Ledda; Luis Narvarte. 2018. "Embodied Energy and Environmental Impact of Large-Power Stand-Alone Photovoltaic Irrigation Systems." Energies 11, no. 8: 2110.
Dairy cattle farms are continuously developing more intensive systems of management, which require higher utilization of durable and non-durable inputs. These inputs are responsible for significant direct and indirect fossil energy requirements, which are related to remarkable emissions of CO2. This study focused on investigating the indirect energy requirements of 285 conventional dairy farms and the related carbon footprint. A detailed analysis of the indirect energy inputs related to farm buildings, machinery and agricultural inputs was carried out. A partial life cycle assessment approach was carried out to evaluate indirect energy inputs and the carbon footprint of farms over a period of one harvest year. The investigation highlights the importance and the weight related to the use of agricultural inputs, which represent more than 80% of the total indirect energy requirements. Moreover, the analyses carried out underline that the assumption of similarity in terms of requirements of indirect energy and related carbon emissions among dairy farms is incorrect especially when observing different farm sizes and milk production levels. Moreover, a mathematical model to estimate the indirect energy requirements of dairy farms has been developed in order to provide an instrument allowing researchers to assess the energy incorporated into farm machinery, agricultural inputs and buildings. Combining the results of this two-part series, the total energy demand (expressed in GJ per farm) results in being mostly due to agricultural inputs and fuel consumption, which have the largest share of the annual requirements for each milk yield class. Direct and indirect energy requirements increased, going from small sized farms to larger ones, from 1302–5109 GJ·y−1, respectively. However, the related carbon dioxide emissions expressed per 100 kg of milk showed a negative trend going from class 9000 kg of milk yield, where larger farms were able to emit 48% less carbon dioxide than small herd size farm (43 vs. 82 kg CO2-eq per 100 kg Fat- and Protein-Corrected Milk (FPCM)). Decreasing direct and indirect energy requirements allowed reducing the anthropogenic gas emissions to the environment, reducing the energy costs for dairy farms and improving the efficient utilization of natural resources.
Giuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 2: Investigation and Modeling of Indirect Energy Requirements. Energies 2018, 11, 463 .
AMA StyleGiuseppe Todde, Lelia Murgia, Maria Caria, Antonio Pazzona. A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 2: Investigation and Modeling of Indirect Energy Requirements. Energies. 2018; 11 (2):463.
Chicago/Turabian StyleGiuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. 2018. "A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 2: Investigation and Modeling of Indirect Energy Requirements." Energies 11, no. 2: 463.
Dairy 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.
Giuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 1: Direct Energy Requirements. Energies 2018, 11, 451 .
AMA StyleGiuseppe Todde, Lelia Murgia, Maria Caria, Antonio Pazzona. A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 1: Direct Energy Requirements. Energies. 2018; 11 (2):451.
Chicago/Turabian StyleGiuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. 2018. "A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 1: Direct Energy Requirements." Energies 11, no. 2: 451.
The milk transformation process, in the last thirty years, moved from on-farm to centralised cheese factories, affecting the management of transport logistics. In Sardinia, the presence of about 12,000 dairy sheep farms, located in rural areas with poor condition of road network, makes collecting milk a significant impact on profit, affecting the costs of milk transportation. Moreover, dairy sheep farming is characterized by seasonal production, this means that the amount of milk that is produced by each farm differs significantly over the year. The objective of this work was to develop a decision support tool that, while optimising milk collection routes, reduced the costs of milk transport, thus improving the density of collection. The tool developed ad hoc in this study used GPS map location and milk volumes of farms to calculate the cost per litre of milk for the regular routing, and to recalculate the same cost for the optimised collecting route. Results showed that this tool improved the efficiency of milk collection, reducing the number of routes and the driving distances. Furthermore, optimising the density of collection, the new routes improved the environmental impact and the transportation costs that are associated with logistic and traceability of raw sheep milk.
Maria Caria; Giuseppe Todde; Antonio Pazzona. Modelling the Collection and Delivery of Sheep Milk: A Tool to Optimise the Logistics Costs of Cheese Factories. Agriculture 2018, 8, 5 .
AMA StyleMaria Caria, Giuseppe Todde, Antonio Pazzona. Modelling the Collection and Delivery of Sheep Milk: A Tool to Optimise the Logistics Costs of Cheese Factories. Agriculture. 2018; 8 (1):5.
Chicago/Turabian StyleMaria Caria; Giuseppe Todde; Antonio Pazzona. 2018. "Modelling the Collection and Delivery of Sheep Milk: A Tool to Optimise the Logistics Costs of Cheese Factories." Agriculture 8, no. 1: 5.
Precision Livestock Farming (PLF) is being developed in livestock farms to relieve the human workload and to help farmers to optimize production and management procedure. The objectives of this study were to evaluate the consequences in energy intensity and the related carbon impact, from dairy farm to cheese factory, due to the implementation of a real-time milk analysis and separation (AfiMilk MCS) in milking parlors. The research carried out involved three conventional dairy farms, the collection and delivery of milk from dairy farms to cheese factory and the processing line of a traditional soft cheese into a dairy factory. The AfiMilk MCS system installed in the milking parlors allowed to obtain a large number of information related to the quantity and quality of milk from each individual cow and to separate milk with two different composition (one with high coagulation properties and the other one with low coagulation properties), with different percentage of separation. Due to the presence of an additional milkline and the AfiMilk MCS components, the energy requirements and the related environmental impact at farm level were slightly higher, among 1.1% and 4.4%. The logistic of milk collection was also significantly reorganized in view of the collection of two separate type of milk, hence, it leads an increment of 44% of the energy requirements. The logistic of milk collection and delivery represents the process which the highest incidence in energy consumption occurred after the installation of the PLF technology. Thanks to the availability of milk with high coagulation properties, the dairy plant, produced traditional soft cheese avoiding the standardization of the formula, as a result, the energy uses decreased about 44%, while considering the whole chain, the emissions of carbon dioxide was reduced by 69%. In this study, the application of advance technologies in milking parlors modified not only the on-farm management but mainly the procedure carried out in cheese making plant. This aspect makes precision livestock farming implementation unimportant technology that may provide important benefits throughout the overall milk chain, avoiding about 2.65 MJ of primary energy every 100 kg of processed milk.
Giuseppe Todde; Maria Caria; Filippo Gambella; Antonio Pazzona. Energy and Carbon Impact of Precision Livestock Farming Technologies Implementation in the Milk Chain: From Dairy Farm to Cheese Factory. Agriculture 2017, 7, 79 .
AMA StyleGiuseppe Todde, Maria Caria, Filippo Gambella, Antonio Pazzona. Energy and Carbon Impact of Precision Livestock Farming Technologies Implementation in the Milk Chain: From Dairy Farm to Cheese Factory. Agriculture. 2017; 7 (10):79.
Chicago/Turabian StyleGiuseppe Todde; Maria Caria; Filippo Gambella; Antonio Pazzona. 2017. "Energy and Carbon Impact of Precision Livestock Farming Technologies Implementation in the Milk Chain: From Dairy Farm to Cheese Factory." Agriculture 7, no. 10: 79.
A population of 285 dairy cow farms located in the south of Italy was involved.Linear regression models for predicting diesel and electricity use were developed.A tool (DEP) was developed to predict direct energy related emission and costs.DEP tool is available online at this link: http://bit.ly/DEPTOOL. The need of reducing energy consumption in agriculture through more efficient working methods came first into focus in the 1970s as a consequence of oil crisis and the sharp increase of the energy price. Today, besides the economic issues, other aspects connected to a large use of fossil energies are becoming prominent: the depletion of nonrenewable resources and the pollution of the environment. The consumption of direct energy, as fuels and electricity, in dairy farming is a source of greenhouse gas emissions and contributes significantly to increasing the carbon footprint of milk.The objectives of this study were: (a) to build linear models to estimate the consumption of diesel fuel and electricity in dairy farms; (b) to develop a calculation tool in order to assess efficiency indicators associated to energy consumption, emissions of carbon dioxide and energy costs in dairy farms.Data used in the model development were collected from 285 dairy farms located in southern Italy. Two linear regression models were developed using total fuel (TF, kgyear1) and electricity consumption (TE, kWhyear1) as responses and total number of heads, total number of lactating cows, milk produced, and cultivated land as primary independent variables. Models parameters were then implemented in a spread sheet to develop the Dairy Energy Prediction (DEP) tool. Entering some basic information about dairy farms characteristics, DEP is able to predict diesel fuel and electricity consumptions, to list several Energy Utilization Indices (EUIs), to estimate carbon dioxide emissions from energy uses (kg CO2-eq), to evaluate the costs of energy purchase. DEP may be used by farmers, to evaluate the energy performances of their farms, and by researchers and stakeholders to compare the impact of different energy scenarios (i.e. LCA studies, economic evaluation, environmental assessment, etc.). DEP tool is available online at this link: http://bit.ly/DEPTOOL.
Giuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. Dairy Energy Prediction (DEP) model: A tool for predicting energy use and related emissions and costs in dairy farms. Computers and Electronics in Agriculture 2017, 135, 216 -221.
AMA StyleGiuseppe Todde, Lelia Murgia, Maria Caria, Antonio Pazzona. Dairy Energy Prediction (DEP) model: A tool for predicting energy use and related emissions and costs in dairy farms. Computers and Electronics in Agriculture. 2017; 135 ():216-221.
Chicago/Turabian StyleGiuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. 2017. "Dairy Energy Prediction (DEP) model: A tool for predicting energy use and related emissions and costs in dairy farms." Computers and Electronics in Agriculture 135, no. : 216-221.
The multivariate statistical approach is one of the most common techniques applied in livestock classification, where quantitative and qualitative variables are used throughout the statistical analysis to obtain farms descriptions. The aim of this study was to divide dairy farms on the bases of farm size, mechanization level, energy profile and availability of building and facilities. A population of 285 conventional dairy cow farms located in the south of Italy was involved in this project. Using the principal component analysis and the k-means cluster analysis allowed to obtain 3 different groups. Results showed a repartition where 156 farms were located in cluster 2 “semi-intensive, low structural and mechanized farms”, 110 farms in cluster 1 “semi-intensive, high structural and mechanized farms”, and 19 farms were positioned in cluster 3 characterized by “intensive, high structural and mechanized farms. Larger farms are equipped with a wide number of appliances, holding higher level of power installed, but when reported to the number of raised heads or to the cultivated land area as indices, larger farms resulted more efficient and utilized less power per unit.
Giuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms. Energy Reports 2016, 2, 129 -134.
AMA StyleGiuseppe Todde, Lelia Murgia, Maria Caria, Antonio Pazzona. A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms. Energy Reports. 2016; 2 ():129-134.
Chicago/Turabian StyleGiuseppe Todde; Lelia Murgia; Maria Caria; Antonio Pazzona. 2016. "A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms." Energy Reports 2, no. : 129-134.
Maria Caria; Giovanni Chessa; Lelia Murgia; Giuseppe Todde; Antonio Pazzona. Development and test of a portable device to monitor the health status of Sarda breed sheep by the measurement of the milk electrical conductivity. Italian Journal of Animal Science 2016, 15, 275 -282.
AMA StyleMaria Caria, Giovanni Chessa, Lelia Murgia, Giuseppe Todde, Antonio Pazzona. Development and test of a portable device to monitor the health status of Sarda breed sheep by the measurement of the milk electrical conductivity. Italian Journal of Animal Science. 2016; 15 (2):275-282.
Chicago/Turabian StyleMaria Caria; Giovanni Chessa; Lelia Murgia; Giuseppe Todde; Antonio Pazzona. 2016. "Development and test of a portable device to monitor the health status of Sarda breed sheep by the measurement of the milk electrical conductivity." Italian Journal of Animal Science 15, no. 2: 275-282.
Dairy farming is constantly evolving towards more intensive levels of mechanization and automation which demand more energy consumption and result in higher economic and environmental costs. The usage of fossil energy in agricultural processes contributes to climate change both with on-farm emissions from the combustion of fuels, and by off-farm emissions due to the use of grid power. As a consequence, a more efficient use of fossil resources together with an increased use of renewable energies can play a key role for the development of more sustainable production systems. The aims of this study were to evaluate the energy requirements (fuels and electricity) in dairy farms, define the distribution of the energy demands among the different farm operations, identify the critical point of the process and estimate the amount of CO2 associated with the energy consumption. The inventory of the energy uses has been outlined by a partial Life Cycle Assessment (LCA) approach, setting the system boundaries at the farm level, from cradle to farm gate. All the flows of materials and energy associated to milk production process, including crops cultivation for fodder production, were investigated in 20 dairy commercial farms over a period of one year. Self-produced energy from renewable sources was also accounted as it influence the overall balance of emissions. Data analysis was focused on the calculation of energy and environmental sustainability indicators (EUI, CO2-eq) referred to the functional units. The production of 1 kg of Fat and Protein Corrected Milk (FPCM) required on average 0.044 kWhel and 0.251 kWhth, corresponding to a total emission of 0.085 kg CO2-eq). The farm activities that contribute most to the electricity requirements were milk cooling, milking and slurry management, while feeding management and crop cultivation were the greatest diesel fuel consuming operation and the largest in terms of environmental impact of milk production (73% of energy CO2-eq emissions). The results of the study can assist in the development of dairy farming models based on a more efficient and profitable use of the energy resources.
Lelia Murgia; Giuseppe Todde; Maria Caria; Antonio Pazzona. A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms. Journal of Agricultural Engineering 2013, 44, 1 .
AMA StyleLelia Murgia, Giuseppe Todde, Maria Caria, Antonio Pazzona. A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms. Journal of Agricultural Engineering. 2013; 44 (2):1.
Chicago/Turabian StyleLelia Murgia; Giuseppe Todde; Maria Caria; Antonio Pazzona. 2013. "A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms." Journal of Agricultural Engineering 44, no. 2: 1.
Dairy farming is constantly evolving towards more intensive levels of mechanization and automation which demand more energy consumption and result in higher economic and environmental costs. The usage of fossil energy in agricultural processes contributes to climate change both with on-farm emissions from the combustion of fuels, and by off-farm emissions due to the use of grid power. As a consequence, a more efficient use of fossil resources together with an increased use of renewable energies can play a key role for the development of more sustainable production systems. The aims of this study were to evaluate the energy requirements (fuels and electricity) in dairy farms, define the distribution of the energy demands among the different farm operations, identify the critical point of the process and estimate the amount of CO2 associated with the energy consumption. The inventory of the energy uses has been outlined by a partial Life Cycle Assessment (LCA) approach, setting the system boundaries at the farm level, from cradle to farm gate. All the flows of materials and energy associated to milk production process, including crops cultivation for fodder production, were investigated in 20 dairy commercial farms over a period of one year. Self-produced energy from renewable sources was also accounted as it influence the overall balance of emissions. Data analysis was focused on the calculation of energy and environmental sustainability indicators (EUI, CO2-eq) referred to the functional units. The production of 1 kg of Fat and Protein Corrected Milk (FPCM) required on average 0.044 kWhel and 0.251 kWhth, corresponding to a total emission of 0.085 kg CO2-eq). The farm activities that contribute most to the electricity requirements were milk cooling, milking and slurry management, while feeding management and crop cultivation were the greatest diesel fuel consuming operation and the largest in terms of environmental impact of milk production (73% of energy CO2-eq emissions). The results of the study can assist in the development of dairy farming models based on a more efficient and profitable use of the energy resources.
Lelia Murgia; Giuseppe Todde; Maria Caria; Antonio Pazzona. A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms. Journal of Agricultural Engineering 2013, 44, 1 .
AMA StyleLelia Murgia, Giuseppe Todde, Maria Caria, Antonio Pazzona. A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms. Journal of Agricultural Engineering. 2013; 44 (2):1.
Chicago/Turabian StyleLelia Murgia; Giuseppe Todde; Maria Caria; Antonio Pazzona. 2013. "A partial life cycle assessment approach to evaluate the energy intensity and related greenhouse gas emission in dairy farms." Journal of Agricultural Engineering 44, no. 2: 1.