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Author |
Vitali, A.; Lana, E.; Amadori, M.; Bernabucci, U.; Nardone, A.; Lacetera, N. |
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Title |
Analysis of factors associated with mortality of heavy slaughter pigs during transport and lairage |
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Journal Article |
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Year |
2014 |
Publication |
Journal of Animal Science |
Abbreviated Journal |
J. Anim. Sci. |
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Volume |
92 |
Issue |
11 |
Pages |
5134-5141 |
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Keywords |
Abattoirs/*statistics & numerical data; Animals; *Data Interpretation, Statistical; Humidity/adverse effects; Light/adverse effects; *Mortality; Retrospective Studies; Seasons; Swine/*physiology; Temperature; Time Factors; Transportation/*statistics & numerical data; lairage; mortality; pigs; temperature-humidity index; transport |
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Abstract |
The study was based on data collected during 5 yr (2003-2007) and was aimed at assessing the effects of the month, slaughter house of destination (differing for stocking density, openings, brightness, and cooling device types), length of the journey, and temperature-humidity index (THI) on mortality of heavy slaughter pigs (approximately 160 kg live weight) during transport and lairage. Data were obtained from 24,098 journeys and 3,676,153 pigs transported from 1,618 farms to 3 slaughter houses. Individual shipments were the unit of observation. The terms dead on arrival (DOA) and dead in pen (DIP) refer to pigs that died during transport and in lairage at the abattoir before slaughtering, respectively. These 2 variables were assessed as the dependent counts in separate univariate Poisson regressions. The independent variables assessed univariately in each set of regressions were month of shipment, slaughter house of destination, time traveled, and each combination of the month with the time traveled. Two separate piecewise regressions were done. One used DOA counts within THI levels over pigs transported as a dependent ratio and the second used DIP counts within THI levels over pigs from a transport kept in lairage as a dependent ratio. The THI was the sole independent variable in each case. The month with the greatest frequency of deaths was July with a risk ratio of 1.22 (confidence interval: 1.06-1.36; P < 0.05) and 1.27 (confidence interval: 1.06-1.51; P < 0.05) for DOA and DIP, respectively. The lower mortality risk ratios for DOA and DIP were recorded for January and March (P < 0.05). The aggregated data of the summer (June, July, and August) versus non-summer (January, March, September, and November) months showed a greater risk of pigs dying during the hot season when considering both transport and lairage (P < 0.05). The mortality risk ratio of DIP was lower at the slaughter house with the lowest stocking density (0.64 m(2)/100 kg live weight), large open windows on the roof and sidewalls, low brightness (40 lx) lights, and high-pressure sprinklers as cooling devices. The mortality risk ratio of DOA increased significantly for journeys longer than 2 h, whereas no relationship was found between length of transport and DIP. The piecewise analysis pointed out that 78.5 and 73.6 THI were the thresholds above which the mortality rate increased significantly for DOA and DIP, respectively. These results may help the pig industry to improve the welfare of heavy slaughter pigs during transport and lairage. |
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1525-3163 (Electronic) 0021-8812 (Linking) |
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LiveM, ft_macsur |
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MA @ admin @ |
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4641 |
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Author |
Özkan, Ş.; Hill, J.; Cullen, B. |
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Title |
Effect of climate variability on pasture-based dairy feeding systems in south-east Australia |
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Journal Article |
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Year |
2014 |
Publication |
Animal Production Science |
Abbreviated Journal |
Animal Production Science |
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Volume |
55 |
Issue |
9 |
Pages |
1106-1116 |
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Keywords |
carry-forward surplus; conserved-hay; probability; winter deficit; grown forage consumption; new-zealand; nutritive characteristics; interannual variation; botanical composition; herbage accumulation; crop; systems; cows; management; profit |
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Abstract |
The Australian dairy industry relies primarily on pasture for its feed supply. However, the variability in climate affects plant growth, leading to uncertainty in dryland pasture supply. This paper models the impact of climate variability on pasture production and examines the potential of two pasture-based dairy feeding systems: (1) to experience winter deficits; (2) to carry forward the conserved pasture surpluses as silage for future use; and (3) to conserve pasture surpluses as hay. The two dairy feeding systems examined were a traditional perennial ryegrass-based feeding system (ryegrass max. – RM) and a system that incorporated double cropping into the perennial ryegrass pasture base (complementary forage – CF). The conditional probability of the RM and CF systems to generate pasture deficits in winter were 94% and 96%, respectively. Both systems could carry forward the surplus silage into the following lactation almost once in every 4-5 years with the RM system performing slightly better than the CF system. The proportions of the grain-based concentrates fed in the two systems were 25% and 27% for the RM and CF systems, respectively. This study suggests that double-cropping systems have the potential to provide high-quality feed to support the feed gaps when pasture is not available due to increased variability in climatic conditions. |
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2015-09-23 |
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1836-5787 |
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LiveM |
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MA @ admin @ |
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4689 |
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Sollitto, D.; De Benedetto, D.; Castrignanò, A.; Crescimanno, G.; Provenzano, G.; Ventrella, D. |
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Title |
Spatial data fusion and analysis for soil characterization: a case study in a coastal basin of south-western Sicily (southern Italy) |
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Journal Article |
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Year |
2012 |
Publication |
Italian Journal of Agronomy |
Abbreviated Journal |
Ital. J. Agron. |
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7 |
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1 |
Pages |
4 |
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Keywords |
salinization risk; soil retention curve; geostatistics; factor Kriging; intrinsic random funciton |
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Salinization is one of the most serious problems confronting sustainable agriculture in semi-arid and arid regions. Accurate mapping of soil salinization and the associated risk represent a fundamental step in planning agricultural and remediation activities. Geostatistical analysis is very useful for soil quality assessment because it makes it possible to determine the spatial relationships between selected variables and to produce synthetic maps of spatial variation. The main objective of this paper was to map the soil salinization risk in the Delia-Nivolelli alluvial basin (south-western Sicily, southern Italy), using multivariate geostatistical techniques and a set of topographical, physical and soil hydraulic properties. Elevation data were collected from existing topographic maps and analysed preliminarily to improve the estimate precision of sparsely sampled primary variables. For interpolation multi-collocated cokriging was applied to the dataset, including textural and hydraulic properties and electrical conductivity measurements carried out on 128 collected soil samples, using elevation data as auxiliary variable. Spatial dependence among elevation and physical soil properties was explored with factorial kriging analysis (FKA) that could isolate and display the sources of variation acting at different spatial scales. FKA isolated significant regionalised factors which give a concise description of the complex soil physical variability at the different selected spatial scales. These factors mapped, allowed the delineation of zones at different salinisation risk to be managed separately to control and prevent salinization risk. The proposed methodology could be a valid support for land use and soil remediation planning at regional scale. |
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2039-6805 1125-4718 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4595 |
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Author |
Andreoli, V.; Cassardo, C.; Iacona, L.T.; Spanna, F. |
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Title |
Description and Preliminary Simulations with the Italian Vineyard Integrated Numerical Model for Estimating Physiological Values (IVINE) |
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Journal Article |
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Year |
2019 |
Publication |
Agronomy |
Abbreviated Journal |
Agronomy |
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Volume |
9 |
Issue |
2 |
Pages |
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Keywords |
viticulture; crop model; phenology; physiological processes; climate; micrometeorology; microclimate; climate change; water status; balance model; crop; phenology; growth; STICS; implementation; carbon; yield |
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Abstract |
The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at a vineyard scale. It requires a set of meteorology data and soil water status as boundary conditions. The primary model outputs are main phenological stages, leaf development, yield, and sugar concentration. The model requires setting some variety information depending on the cultivar: At present, IVINE is optimized for Vitis vinifera L. Nebbiolo, a variety grown mostly in the Piedmont region (northwestern Italy). In order to evaluate the model accuracy, IVINE was validated using experimental observations gathered in Piedmontese vineyards, showing performances similar or slightly better than those of other widely used crop models. The results of a sensitivity analysis performed to highlight the effects of the variations of air temperature and soil water potential input variables on IVINE outputs showed that most phenological stages anticipated with increasing temperatures, while berry sugar content saturated at about 25.5 °Bx. Long-term (60 years, in the period 1950–2009) simulations performed over a Piedmontese subregion showed statistically significant variations of most IVINE output variables, with larger time trend slopes referring to the most recent 30-year period (1980–2009), thus confirming that ongoing climate change started influencing Piedmontese vineyards in 1980. |
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2019-02-21 |
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2073-4395 |
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CropM, ft_macsur |
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MA @ admin @ |
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5218 |
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