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Mastitis by non-aureus staphylococci (NAS) is a significant issue in dairy buffalo farming. In a herd with subclinical NAS mastitis, we identified Staphylococcus microti as the predominant species. To assess milk protein integrity and investigate potential disease markers, we characterized 12 NAS-positive and 12 healthy quarter milk samples by shotgun peptidomics combining peptide enrichment and high-performance liquid chromatography/tandem mass spectrometry (LC-MS/MS). We observed significant changes in the milk peptidome. Out of 789 total peptides identified in each group, 49 and 44 were unique or increased in NAS-positive and healthy milk, respectively. In NAS-positive milk, the differential peptides belonged mainly to caseins, followed by milk fat globule membrane proteins (MFGMP) and by the immune defense/antimicrobial proteins osteopontin, lactoperoxidase, and serum amyloid A. In healthy milk, these belonged mainly to MFGMP, followed by caseins. In terms of abundance, peptides from MFGMP and immune defense protein were higher in NAS-positive milk, while peptides from caseins were higher in healthy milk. These findings highlight the impact of NAS on buffalo milk quality and mammary gland health, even when clinical signs are not evident, and underscore the need for clarifying the epidemiology and relevance of the different NAS species in this dairy ruminant.

This observational study determined the lipidome of cow milk during subclinical intramammary infection (IMI) by non-aureus staphylococci (NAS), also defined as coagulase-negative staphylococci, using an untargeted approach. Among the pathogens causing bovine IMI, NAS have become the most frequently isolated bacteria from milk samples. Although the application of system biology approaches to mastitis has provided pivotal information by investigating the transcriptome, proteome, peptidome, and metabolome, the milk lipidome during mammary gland inflammation remains undisclosed. To cover this gap, we determined the milk lipidome of 17 dairy cows with IMI caused by NAS (NAS-IMI), and we compared the results with those of healthy quarter milk from 11 cows. The lipidome was determined following a liquid chromatography-quadrupole time-of-flight mass spectrometry approach. Sixteen subclasses of lipids were identified in both groups of animals. From 2,556 measured lipids, the abundance of 597 changed more than 10-fold in quarter milk with NAS-IMI compared with healthy quarters. The results demonstrate the influence of NAS-IMI on the milk lipidome, implying significant changes in lipid species belonging to the family of triacylglycerols and sphingomyelins, and contribute to the understanding of inflammatory processes in the bovine udder, highlighting potential novel biomarkers for improving mastitis diagnostics.

This study investigated the influence of different loading levels, cutting and mixing times on total mixed ration (TMR) homogeneity delivered along the feeding alley of dairy cows. The TMR homogeneity along the alley was investigated according to three mixing wagon loads (40, 70 and 100% of the nominal capacity), three cutting times (4, 5 and 6 min) and three mixing times (4, 5 and 6 min). The diet (70:30 forage/concentrate ratio) was supplied by a two-screws vertical mixing wagon (maximum nominal capacity, 21 m3). A preliminary variance analysis of chemical parameters was performed on samples collected in the mixing wagon: samples of released TMR were taken at the beginning, in the middle and at the end of the feeding alley (50 m long). The chemical parameters of the diet revealed no significant effects on the homogeneity of the samples for cutting time (p>.05). Mixing wagon loading affected crude protein (CP) (p

Coagulase-negative staphylococci (CNS) are the most prevalent microorganisms isolated from cow milk and are associated with subclinical mastitis and persistent increases in the bulk milk somatic cell count (BMSCC) of low BMSCC herds. By combining peptide enrichment, LC-ESI-MS/MS, and statistical analysis, we investigated the influence of subclinical mastitis and CNS infection on the milk peptidome. Quarter milk samples from clinically healthy Holstein cows were subjected to bacteriological culture (BC) and somatic cell counting (SCC) for two consecutive samplings and 28 (including 11 negatives and 17 positives) were selected for peptidomic analysis. The study identified 1363 different endogenous peptides and highlighted a significant increase of peptides in CNS-positive milk, mainly represented by casein fragments. Milk peptidome changes increased with the SCC, as also demonstrated by protein electrophoresis and densitometry. Peptides significantly different in CNS or CONTROL samples were identified and characterized. Our results indicate that subclinical mastitis by CNS can induce significant changes in the milk peptidome, opening the way to future studies for the identification of a biomarker panel as well as for the understanding of their consequences for the technological and sensorial characteristics of cow milk and dairy products. SIGNIFICANCE: This is the first investigation on the impact of subclinical CNS mastitis on the bovine milk peptidome. The peptide enrichment strategy combined with a highly sensitive MS/MS analysis enabled the compilation of a very large peptide dataset for healthy and mastitic milk. The comparison of CNS and Control samples, also considering SCC classes, highlighted several peptides with potential for understanding milk protein and peptide dynamics in subclinical mastitis, with possible implications for its detection.

The need to reduce labour demand and the increasing size of herds have led - in the last years - to develop specific automated solutions for feeding animals in dairy farms. Currently there are more than 1250 automatic feeding systems (AFS) used worldwide, but there is a lack of information about both their energy requirements and management costs. The primary aim of the present study was to measure the electric energy consumption of an AFS installed in a dairy farm of Northern Italy under practical conditions. The secondary aim was to calculate, using the classic ASABE approach, the costs for preparing and distributing a total mixed ration (TMR) with the same AFS in comparison with the conventional feeding system (CFS) (tractor + TMR wagon) previously adopted by the farm. The average energy consumption of AFS over the experimental period (two months) was 40.2±2.3 kWh per day, 2.11±0.07 kWh per ton of TMR distributed and 29.6 kWh ∙ cow–1 per year. Energy consumptions and labour were reduced respectively of 97% and 79% passing from a CFS (tractor + TMR wagon) to an AFS, contributing to reduce the daily cost for feeding TMR up to 33%. These results highlighting that AFS can represent an interesting option to improve competitiveness of dairy farms.

This study aims to determine the untargeted lipidome of cow milk during non-staphylococcal sub-clinical mastitis. Dairy cow mastitis severely impacts the dairy industry by reducing milk yield and quality and increasing culling rate. Among the pathogens that cause bovine sub-clinical mastitis, non-aureus staphylococci (NAS) have become the most frequently isolated bacteria from milk samples. The molecular mechanisms regulating the mammary gland inflammatory responses to NAS are unclear. Although the application of system biology approaches to mastitis has provided pivotal information by investigating the transcriptome, proteome, and metabolome, the milk lipidome remains undisclosed. We determined the lipidome of 17 dairy cows with NAS sub-clinical mastitis (SM) and we compared the results with the lipidome of the milk of 13 healthy cows. The study was carried out following a liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) approach. Sixteen subclasses of lipids were identified in both groups of animals. From 2,506 measured lipids, 631 were significantly changed more than 10 folds (FDR < 0.01 in milk from cows with mastitis as compared to healthy cows. Our results point out the significant influence of NAS on the milk lipidome, contribute to the understanding of inflammatory processes in the bovine udder, and highlight potential novel biomarkers for improving mastitis diagnosis. Part of this work was carried out in “OMICs”, an advanced mass spectrometry platform established by the Università degli Studi di Milano.

The aim of this study was to assess the effect of alternate and simultaneous pulsation on milking performance (milk yield, machine stripping milk, milking duration, and average milk flow rate) of Alpine goats milked at two different system vacuum levels (38 and 42 kPa). To this end, a field study was carried out in a commercial farm of Northern Italy. A pre-experimental period was carried out and 164 goats with a similar parturition date were selected and distributed into two similar subplots of 82 goats according to their values of milk yield and milking duration. The experiment lasted 24 d and was laid out as a split-plot design. Each treatment lasted 3 days. Once every combination (2 pulsation types × 2 vacuum levels) was tested (Experiment 1), the same experimental design was repeated in reverse order (cross-over design) to control the effect of lactation progress on the results (Experiment 2). Milk traits regarding milking performance (milk yield, machine stripping milk, milking duration, and average milk flow rate) and variables related to vacuum level in the milking cluster (vacuum in the short milk tube and vacuum fluctuation in the short milk tube) were recorded during morning and afternoon milkings. Results showed that the use of alternate pulsation reduced the vacuum fluctuations and increased the average vacuum in the short milk tube. Moreover, when a higher system vacuum level (42 kPa) was set, the use of alternate pulsation reduced the milking duration. We concluded that the use of alternate pulsation offers some advantages compared to simultaneous pulsation in high milk flow conditions.

The objective of the present study was to investigate the effect of pre-milking mechanical teat stimulation on milk yield and milking performance of dairy buffaloes in early lactation. For this purpose, twenty-two healthy Italian Mediterranean buffaloes in their first to third lactation and in early lactation (

Following the concepts of precision feeding, the right components balance (Sova et al., 2014) and the correct particle size distribution (PSD, Khan et al., 2014) of total mixed ration (TMR) are essential for a complete homogeneity of the diet and are strongly influenced by adopted mixing time (MT, Humer et al., 2018, Schingoethe et al.,2017). The aim of the trial was to determine the influence of two MTs (MT1≤7min and MT2>7min) on the chemical homogeneity and PSD along the feeding alley. Diets were performed with a horizontal cutter-mixer wagon (Gulliver 4016, Sgariboldi), and TMR samples were collected from the beginning, middle and end of the feeding alley after discharge. Triplicate samples of the diet were collected for chemical composition analyses (moisture, CP, Ash, EE, NDF and ADF) and PSD evaluation (Heinrichs and Kononoff, 2002) over two months (two sampling/week). Statistical analysis was performed by a PROC MIXED for repeated measurements of SAS. MT1 evidenced a non-uniform distribution of moisture content along the feeding alley (P=0.05): lower moisture was found at the end than at the beginning and in the middle (47.55 vs 51.13 and 51.00%, respectively; P, International Journal of Health, Animal Science and Food Safety, Vol 5, No 1s (2018)

The demand for online monitoring and control of biogas process is increasing, since better monitoring and control system can improve process plants stability and economy. A number of parameters in both the liquid and the gas phase have been suggested as process indicators (pH, alkalinity, VFA and H2, redox potential, biogas production rate, biogas composition, FOS/TAC ratio, COD and/or VS reduction). The present study proposes the use of complex sensors as a possible solution to engineer a consistent control system. Tests were performed to analyze the biogas coming from a biogas plant in which conditions of pre-overloading and overloading were artificially inducted. The different inducted functioning conditions were recognised using a FOS/TAC tester, or the ratio volatile organic acids/alkaline buffer capacity. The FOS/TAC ratio has long been recognized extending as far as the imminent inversion of the digester biology to be detected at an early stage. Data coming from the e-nose were sorted and classified according to FOS/TAC ratio as a reference method. Not all the sensors of the e-nose were reactive to manure digestates, but four of them, sensitive to aromatic compounds, ammonia alkanes and methane, resulted crucial in the samples identification. Results confirmed that the e-nose can discriminate different digestion conditions, demonstrating the possibility to reduce the number of sensors in this innovative tool for biogas control systems. However, this instrument cannot be considered a complete alternative to traditional analysis systems, as, for example, the FOS/TAC titration, but a supporting tool for a quick analysis of the system.

The aim of this study was to compare 2 methods of measuring overpressure (OP) using a new test device designed to make OP measurements more quickly and accurately. Overpressure was measured with no pulsation (OP np ) and with limited pulsation (OP lp ) repeatedly on the same cow during a single milking. Each of the 6 liners (3 round liners and 3 triangular liners) used in this study were tested on the same 6 experimental cows. Both OP np and OP lp were measured on all 4 teats of each experimental cow twice for each liner. The order of OP np and OP lp alternated sequentially for each cow test. The OP results for the 6 liners were also compared with liner compression estimated on the same liners with a novel artificial teat sensor (ATS). The OP lp method showed small but significantly higher values than the OP np method (13.9 vs. 13.4kPa). The OP lp method is recommended as the preferred method as it more closely approximates normal milking condition. Overpressure values decreased significantly between the first and the following measurements, (from 15.0 to 12.4kPa). We recommend performing the OP test at a consistent time, 1min after attaching the teatcup to a well-stimulated teat, to reduce the variability produced by OP changing during the peak flow period. The new test device had several advantages over previously published methods of measuring OP. A high correlation between OP and liner compression estimated by the ATS was found, but difficulties were noted when using the ATS with triangular liners.

The aim of this study is a further characterization of the electrical conductivity (EC) signal of goat milk, acquired on-line by EC sensors, to identify new indexes representative of the EC variations that can be observed during milking, when considering not healthy (NH) glands. Two foremilk gland samples from 42 Saanen goats, were collected for three consecutive weeks and for three different lactation stages (LS: 0–60 Days In Milking (DIM), 61–120 DIM, 121–180 DIM), for a total amount of 1512 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define the health status of the glands. With negative bacteriological analyses and SCC &lt, 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC &gt, 1,000,000 cells/mL, glands were classified as NH. For each milk EC signal, acquired on-line and for each gland considered, the Fourier frequency spectrum of the signal was calculated and three representative frequency peaks were identified. To evaluate data acquired a MIXED procedure was used considering the HS, LS and LS × HS as explanatory variables in the statistical model.Results showed that the studied frequency peaks had a significant relationship with the gland’s health status. Results also explained how the milk EC signals’ pattern change in case of NH glands. In fact, it is characterized by slower fluctuations (due to the lower frequencies of the peaks) and by an irregular trend (due to the higher amplitudes of all the main frequency peaks). Therefore, these frequency peaks could be used as new indexes to improve the performances of algorithms based on multivariate models which evaluate the health status of dairy goats through the use of gland milk EC sensors.

Conventional cage systems will be replaced by housing systems that allow hens to move freely. These systems may improve hens' welfare, but they lead to some disadvantages: disease, bone fractures, cannibalism, piling and lower egg production. New selection criteria for existing commercial strains should be identified considering individual data about laying performance and the behavior of hens. Many recording systems have been developed to collect these data. However, the management of double nest occupations remains critical for the correct egg-to-hen assignment. To limit such events, most systems adopt specific trap devices and additional mechanical components. Others, instead, only prevent these occurrences by narrowing the nest, without any detection and management. The aim of this study was to develop and test a nest usage "sensor", based on imaging analysis, that is able to automatically detect a double nest occupation. Results showed that the developed sensor correctly identified the double nest occupation occurrences. Therefore, the imaging analysis resulted in being a useful solution that could simplify the nest construction for this type of recording system, allowing the collection of more precise and accurate data, since double nest occupations would be managed and the normal laying behavior of hens would not be discouraged by the presence of the trap devices.

Daily dry matter (DM) intake in dairy cow is a central point to meet nutritional requirements and optimal performance, reducing the incidence of metabolic diseases. DM content of some forages, such as silages, can undergo huge variations during storing, affecting the total daily DM consumed. Reference laboratory method is time consuming and cannot be applied to daily changes in diet composition. Currently, new promising real-time technologies are available to monitor the DM content of feeds. The aim of the study was to test and calibrate a portable microwave sensor (MS) for DM content in corn silage samples. Twenty-two samples were collected from a corn silage front; sampling procedure was optimized to collect as much as DM content variability as possible within the samples. MS readings were performed with 3 different methods for each samples: 1) directly on the silage front, 2) with the MS over the collected sample and 3) with MS placed under the sample. After the first MS reading, a correspondent silage sample was obtained by a silage corer for readings 2 and 3 and the laboratory DM content assay. A simple regression analysis was performed (JMP, SAS Institute, Cary, NC, 2015) over obtained data. Results evidences as the best MS reading method is represented by the probe burdening on the sample (R2=0.75) with respect to the other methods. The obtained results outlined as, with a correct reading method, MS can be valuable tool to determine DM content of corn silage directly at farm level., International Journal of Health, Animal Science and Food Safety, V. 4, N. 1s (2017)

The objective of this study was to evaluate the response of buffaloes to automatic milking, examining the relationships between milking interval, milk production, and milking time for this species. A total of 7,550 milking records from an average of 40 buffaloes milked by an automatic milking system (AMS) were analyzed during a 3-mo experimental period at a commercial farm with Italian Mediterranean buffaloes in southern Italy. Date and time of animal identification, milk yield, milking duration, milking interval, and average milk flow rate were determined for each milking. The results were also used to predict the maximum number of milkings per day and the optimal number of buffaloes per AMS for different levels of milk production. The average interval period between 2 consecutive milkings was 10.3 h [standard deviation (SD) 3.3]. Overall, 3.4 and 25.7% of the milkings had an interval of ≤6 h or >12 h, respectively. Milking duration averaged 8.3 min per buffalo per milking (SD 2.7). The average milk flow rate was 1.3kg/min (SD 0.5) at a milk yield of 2.8kg per milking (SD 1.4). Assuming that the milking station is occupied 80% of the time, the number of milkings ranged from 136 to 152 per day and the optimal number of buffaloes per AMS ranged from 59 to 66 when the production level increased from 2 to 5kg of milk per milking. Automatic milking systems are suitable for buffalo, opening new options for the management of dairy buffalo farms.

We have developed an innovative birth alarm system for grazing cows.The system implements a GSM device to alert via SMS the farmer in case of calving.A GPS receiver calculates the geographical coordinates where the birth has took place.In this way the farmer can reach the cow easily in case of necessity.The economical analysis confirms the feasibility of the proposed system. In livestock farming, during calving often human assistance is required to the cow and the unborn in order to guarantee their health and preserve the herd. Reliable calving time prediction is fundamental to enable the operator to act quickly and reduce potential injury to the calf directly caused by the mother or by environmental factors. The prediction is of particular importance for pregnant cows in extensive grazing areas where, because of the territorial extension, it is difficult to quickly intervene when needed. In order to solve these problems, a new GPS-Calving Alarm (GPS-CAL) was designed, manufactured and tested to analyze its technical and economic performance. The device accurately identifies the time when delivery begins and advises the farmer via SMS. The SMS includes birth event date and hour, animal ID and geographical coordinates of the partum point. The position is measured through a GPS receiver embedded in the device. By importing the GPS coordinates into a common application for mobile phones and following the visual instructions, it is possible to reach the animals at pasture. In order to evaluate device performance, both laboratory and field tests were carried out. Laboratory tests showed GPS adopted receiver accuracy (1.2m) and an adequate battery life (over 1month) for monitoring calving events in grazing areas. Field tests, carried out in intensive and extensive breeding conditions, confirmed that the GPS-CAL system worked well, and was highly reliable (sensitivity of 100%, positive predictive value PPV of 100%). Finally, the economic aspects relative to the adoption of the GPS-CAL system were analyzed. The possibility to monitor 10calvings/year by each device, at a unitary cost of ?31,5/birth, sustainable by the farmer were taken into consideration. The originality and effectiveness of the GPS-CAL system, as confirmed by workers in the sector, allowed the authors, the Universiti? degli Studi di Milano and the Sisteck (Sassuolo, Italy) to patent the system in Italy and Europe.

Mastitis in small ruminants has a major effect in reducing both yield and quality of milk leading to strong economic losses. In addition, mastitis is one the most frequently cited reason for culling. In dairy cows electrical conductivity (EC) of milk has been introduced as an indicator trait for mastitis. When the measurement of electrical conductivity (EC) of milk is based on time-series analysis of historical data, comparing values from different quarters within milking, satisfactory results in mastitis detection can be achieved. On the contrary, mastitis detection models based on EC measurement of milk within milking are not available in literature for dairy goats. Aim of the study was to evaluate the usefulness of milk EC, measured within milking from halves of each udder, to predict mastitis status in dairy goats at farm level. For this purpose, a group of 8 Saanen goats was involved in a 225-day study. Two foremilk samples were daily collected during morning milking from halves of each udder for a total of 4 samples per animal/day. Results of bacteriological analyses were used to distinguish between healthy (absence of mastitis agents) and infected (presence of contagious or environmental mastitis agents) udder halves. EC was measured in milk from halves of each udder during every morning milking at 1-s intervals using four experimental milking units equipped with conductimetric sensors. The average of the 20 highest EC values (X20) and the variation of the 20 highest EC values ( σ 20 2 ) within milking were calculated for each udder halves. In addition 4 EC traits based on X20 and σ 20 2 were computed: the highest half udder X20 value within goat and milking (Max_X20), the highest half udder σ 20 2 value within goat and milking ( Max _ σ 20 2 ), the inter-udder halves ratio between the udder halves X20 values within goat and milking (IHR_X20), and the inter-udder halves ratio between udder halves σ 20 2 value within goat and milking ( IHR _ σ 20 2 ). Values for the traits were calculated for every milking throughout the whole lactation. Proc Mixed of SAS® 9.1 (SAS Institute Inc., Cary, NC, USA, 2008) was performed to test for significant differences in EC traits between healthy and infected udder halves and between healthy (absence of infected udder halves) and infected (presence of at least one infected udder half) goats. Results highlighted that the average of the 20 highest electrical conductivity half udder values recorded within milking in early lactation and the highest half udder X20 value within goat and milking in mid lactation could be potentially used in monitoring udder health of dairy goats.

Accurate milk yield measurement is important to maintain production efficiency and improve farm management: yield data enable to implement and evaluate feed rations for individual cows or groups, calculate actual lactation curves and identify potential health problems proactively. Nowadays, many electronic milk metering devices, based on different methods of measurement, are available on the market. Vacuum drop across the meter, accuracy over a wide range of flow rates and farm conditions (e.g. foaming of milk) are the key problems of currently available electronic milk meters. Aim of this project was the development of a free-flow milk meter, able to work with different flow rates and different combination of air-milk flows, with a measuring chamber essentially made by a portion of linear pipe, horizontally disposed and with no mechanical movement parts, to minimize the interferences with the milk flow and on the electric conductivity (EC), to calculate the milk yield, in order to obtain a low-cost device. A prototype was built up and laboratory and farm tests were carried out during 2004 and 2005, in order to evaluate the accuracy and reproducibility of the new device. Laboratory and farm tests were carried out following the guidelines of the International Committee for Animal Recording (ICAR). Laboratory tests showed a bias of 1.4% and a standard deviation of 5.0%, while farm tests showed a bias of -4.5% and a standard deviation of 12.7%.

Automatic milking systems (AMS) have been a revolutionary innovation in dairy cow farming. Currently, more than 10,000 dairy cow farms worldwide use AMS to milk their cows. Electric consumption is one of the most relevant and uncontrollable operational cost of AMS, ranging between 35 and 40% of their total annual operational costs. The aim of the present study was to measure and analyze the electric energy consumption of 4 AMS with different configurations: single box, central unit featuring a central vacuum system for 1 cow unit and for 2 cow units. The electrical consumption (daily consumption, daily consumption per cow milked, consumption per milking, and consumption per 100L of milk) of each AMS (milking unit + air compressor) was measured using 2 energy analyzers. The measurement period lasted 24h with a sampling frequency of 0.2Hz. The daily total energy consumption (milking unit + air compressor) ranged between 45.4 and 81.3 kWh; the consumption per cow milked ranged between 0.59 and 0.99 kWh; the consumption per milking ranged between 0.21 and 0.33 kWh; and the consumption per 100L of milk ranged between 1.80 to 2.44 kWh according to the different configurations and operational contexts considered. Results showed that AMS electric consumption was mainly conditioned by farm management rather than machine characteristics/architectures.

Intramammary infection affects quality and quantity of milk. Having as final target the improving of animal health’ monitoring, this research studied the gland milk electrical conductivity (EC) signal in order to identify a possible parameter more representative of the EC variations that can be observed, during a milking, when not healthy (NH) glands are considered. Two foremilk gland samples, from 40 Saanen goats, were acquired for three weeks and lactation stages (LS: 0-60 Days In Milking; 61-120 DIM; =>120 DIM), for a total amount of 1440 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define glands health status. In case of negative bacteriological analyses and SCC

The objective of this study was to estimate the space occupied by a pig, calculated from direct measurements on the animal or from digital images. A total of 100 pigs with body weight (BW) ranging from 47 to 198 kg were individually weighed and measured for body length, back and shoulder height. The area of the rectangle into which each pig can be fitted was calculated, following the same method as Petherick and Baxter [Petherick, J.C., Baxter, S.H., 1981. Modelling the static spatial requirements of livestock. In: MacCormack, J.A.D. (Ed.), Proceedings of the CIGR Section II Seminar on Modelling, Design and Evaluation of Agricultural Buildings, Aberdeen, August 1981, Scottish Farm Buildings Investigation Unit, Bucksburn, Aberdeen, UK. pp 75–82]. In addition, pictures of the pigs were taken with a digital camera at the same distance and resolution to estimate the area of the geometrical shape of each animal by counting the number of pixels. Values of Petherick and Baxter's data space (A = 0.047 × BW0.67) are significantly higher (p

Intramammary infection affects the quality and quantity of dairy goat milk. Health status (HS) and milk quality can be monitored by electrical conductivity (EC). The aim of the study was to determine the detection potential of EC when measured on-line on a daily basis and compared with readings from previous milkings. Milk yields (MYs) were investigated with the same approach. To evaluate these relative traits, a multivariate model based on fuzzy logic technology – which provided interesting results in cows – was used. Two foremilk samples from 8 healthy Saanen goats were measured daily over the course of six months. Bacteriological tests and somatic cells counts were used to define the HS. On-line EC measurements for each gland and MYs were also considered. Predicted deviations of EC and MY were calculated using a moving-average model and entered in the fuzzy logic model. The reported accuracy has a sensitivity of 81% and a specificity of 69%. Conclusions show that fuzzy logic is an interesting approach for dairy goats, since it offered better accuracy than other methods previously published. Nevertheless, specificity was lower than in dairy cows, probably due to the lack of a significant decrease of MY in diseased glands. Still, results show that the detection of the HS characteristics with EC is improved, when measured on-line, daily and compared with the readings from previous milkings.

Fontina cheese is a DOP (Designation of Protected Origin) cheese produced in Aosta Valley (Western Alps, North Italy) by dairy farms and cheese factories members of Fontina Cheese Producers’ Consortium. Since 2003 Fontina Consortium has developed an identification and branding system to trace the cheese from the factories to the consumers, but till now no operative instruments have been developed for the traceability of the milk produced by the farms members of the Consortium. This lack is mainly due to the traditional dairy cattle breeding system of Aosta Valley that is based on small family-operated dairy farms characterized by a low technological level. In these farms cows are housed in stall barns during winter, while in spring and summer livestock are herded to upland pastures located at the highest elevations (up to 2300 m a.s.l.). The average number of lactating cows is lower than 20 and they are milked by mobile milking units, bucket or pipeline milking systems. Following the European Union Regulation (EC Reg. 178/2002), a traceability system of the milk was developed for the dairy farms located in mountain areas. The project has been articulated in three sequential phases: • development of a database model (Entity and Relationship model) to identify all the farm data (livestock treatments, feed registration, external foodstuff records, etc) required and useful to trace the milk yield; • implementation of the database model by a user friendly software application to simplify the storage and the management of all the farm data; • development of a special mobile milking unit to record milking data (cows production and milk electric conductivity). The mobile milking unit was equipped with: a RFID antenna to identify the cows by transponders (ruminal bolus); a mastitis detection device, based on the measurement of the milk electrical conductivity, to monitor the quality of the milk produced by each cow; a milk meter to measure the milk yield of each cow; a palm PC with a customized software application to record milking data and then transfer them to the farm database. Presently a field test of the developed system is in progress in a farm in Aosta Valley. Preliminary results showed a fairly good effectiveness of the system in tracing milk production from the stable to the dairy factory nailing the traceability system implemented by Fontina Consortium.

Compared to traditional plowing and minimum tillage, the sod seeding technique has been tested in order to evaluate the differences in energy consumption, labor and machinery requirement and CO2 emission reduction. The experiments were conducted on winter cereal seeding in a Po valley farm in October 2011. The tests were carried out as follows: wheat variety seeding, over corn and alfalfa crops, in large plots with three repetitions for each thesis. They included: sod seeding anticipated by round up weeding in the case of the plots over alfalfa; traditional plowing at 35 cm followed by rotary tillage and combined seeding (seeder plus rotary tiller); minimum tillage based on ripping at the same depth (35 cm) and combined seeder ( seeder plus rotary tiller). The following farm operations - fertilizer, and other agrochemical distributionshave been the same in all the considered theses. The results, statistically significant (P

Reproductive and economic data were recorded before and one year after the installation of Herd Navigator™ in a dairy farm with AMS (Automatic Milking System) located in a mountain area of Northern Italy. Number of days open reduced from 166 to 103 days, number of days between the first and second insemination decreased from 45 to 28 days, and days for identifying an abortion were 80 % less, from 31 to 6 days. The preliminary results highlight the usefulness of the proactive herd management system installed for the reproduction management. A basic economic model is proposed to evaluate the potential economic benefits coming from the introduction of this technology. The model considers the benefits deriving from the reduction of reproduction problems and, consequently, of days open. Considering the effects related to the above mentioned aspects in a case study involving 60 dairy cows, a return on investment over 5 years has been calculated.

The aim of this study was to develop and test a new fuzzy logic model for monitoring the udder health status (HS) of goats. The model evaluated, as input variables, the milk electrical conductivity (EC) signal, acquired on-line for each gland by a dedicated sensor, the bandwidth length and the frequency and amplitude of the first main peak of the Fourier frequency spectrum of the recorded milk EC signal. Two foremilk gland samples were collected from eight Saanen goats for six months at morning milking (lactation stages (LS): 0–60 Days In Milking (DIM); 61–120 DIM; 121–180 DIM), for a total of 5592 samples. Bacteriological analyses and somatic cell counts (SCC) were used to define the HS of the glands. With negative bacteriological analyses and SCC < 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC > 1,000,000 cells/mL, glands were classified as not healthy (NH). For each EC signal, an estimated EC value was calculated and a relative deviation was obtained. Furthermore, the Fourier frequency spectrum was evaluated and bandwidth length, frequency and amplitude of the first main peak were identified. Before using these indexes as input variables of the fuzzy logic model a linear mixed-effects model was developed to evaluate the acquired data considering the HS, LS and LS × HS as explanatory variables. Results showed that performance of a fuzzy logic model, in the monitoring of mammary gland HS, could be improved by the use of EC indexes derived from the Fourier frequency spectra of gland milk EC signals recorded by on-line EC sensors.

In Italy, the bovine meat production chain is extremely complex both under structural and organizational profile. This is due to: high number of operators involved; large fragmentation in agricultural and industrial phases; existence of remarkable import flow of animals and meat; commercial channels complexity. Traceability can be easily reached in each single separate step of the food chain (breeding, slaughtering, packaging and selling). Problems arise in integrating each productive process subsystem. Aim of the project was to study and develop an integrated automatic traceability system for the bovine meat chain based on RFID technologies.

Over some years a new concept, identified as “precision farming”, was introduced to improve field and farm management from agronomical, technical, environmental and economical perspectives through the use of new technologies, such as global positioning systems (GPS), sensors, satellite images and geographical information systems (GIS). Environmental and food safety regulations are becoming more and more hard-and-fast asking farmers to increase their organizational and technical skills for a well-integrated agro-territorial management. Aim of the research activity was the implementation of an integrated system for animal slurry management monitoring and electronic reports drawing up in cattle breeding in order to optimize the fertilization management and reduce the agricultural impacts.

A veterinary electronic patient record, compliant with the IT standards (HL7, DICOM and IHE), was developed at the School of Veterinary Medicine, University of Milan (Italy) in order to improve the veterinary hospital workflows, making the stored clinical data more homogenous and sharable, thereby increasing the integration with current and future software applications. The system was developed by open-source software in order to reduce the implementation and maintenance costs and to make the system sharable with other veterinary hospitals or research centers without additional costs. The system was tested from May to October 2006. Results show that the majority of the veterinarians involved in the test agreed on the advantages obtained by the use of application software concerning the availability of all the useful clinical data [71.4%], the quality of the diagnostic procedures [78.58%] and the efficiency [85.58%] of hospital activities.

Precise calving monitoring is important for reducing the effects of dystocia in cows and calves. The C6 birth control system is an electronic device that detects the time of the expulsion phase during calving. Several 53 Holstein were fitted on Day 280 ± 5 of gestation with the C6 birth control system, which was left in place until confirmation of calving. Sensitivity and PPV of the system were calculated as 100 and 95%, respectively. The partum events occurring at the group fitted with the system where compared with the analogous occurred at 59 animals without device. When alarmed by the system farm staff were in the calving barn during the expulsion phase in 100% of cases. On the contrary the cows without the device were assisted only in 17% of cases (P < 0.001).

A system, based on microwave resonance technology, to measure the forages moisture during TMR mixer wagon loading was implemented and tested. A commercial microwave moisture sensor for bulk materials was used. It was first calibrated over different types of silages (corn, high moisture corn, grass) using samples collected from different dairy farms located in Lombardy (Northern Italy), then it was mounted behind the loading drum of the conveyor arm of a horizontal self-propelled mixer wagon and integrated in an online measurement system designed to record in real-time and continuously the silages moisture content during the TMR mixer wagon loading. The system was tested at the University of Milan experimental farm (Landriano, Italy) on corn and high moisture corn silages. Additional tests were carried out also on barley and soybean silages. Preliminary results highlighted that the microwave sensor provided accurate silage moisture data, especially for corn silage. The accurate estimation of silages moisture content during the loading phase will enable the realtime adjustment of the as fed inclusion rate of each silage in the ration, ensuring the provision of the right dry matter amount. This is expected to increase TMR consistency, finally benefiting animals’ health and performances.

Proper dry matter intake in dairy cows is a key factor to meet nutritional requirements and optimal performance, reducing the incidence of metabolic diseases. Moisture content of silages, can undergo variations during storing, affecting the total dry matter daily consumed by the animals. The aim of the study was to develop a system, based on microwave resonance technology, to measure the silages moisture content during feed mixer wagon loading. A commercial microwave moisture sensor for bulk materials was used. It was first calibrated over different types of silages (corn, high moisture corn, barley, soybean) using samples collected from different dairy farms located in Lombardy (Northern Italy), then it was mounted behind the loading drum of the conveyor arm of a horizontal self-propelled mixer wagon and integrated in an on-line measurement system designed to record in real-time and continuously the silages moisture content during the feed mixer wagon loading. The system was tested at the University of Milan experimental farm (Landriano, Italy). Preliminary results highlighted that the microwave sensor provided, except for soybean silage (R2 = 0.95), a moderately accurate silage moisture data (R2 = 0.62 for corn and high moisture corn silages; R2 = 0.61 for barley silage).