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The effects of restricted access time to pasture (2, 4 or 6 h d−1; 2H, 4H or 6H) on ingestive behaviour and performance were assessed on four occasions per target grazing day (D1, initial day; D4, intermediate day; and D7, final day) in dairy ewes rotationally grazing berseem clover with a 7-day grazing period and a 21-day recovery period. A randomized block design with two replicates per treatment was used. All ewes were supplemented daily with 700 g per head of concentrates and 700 g per head of ryegrass-based hay. Pasture subplot and animal group data were analysed by a factorial model including access time ( AT), grazing day (D) and their interaction as fixed factors. Sward height decreased from D1 ( P < 0·001) and green leaf mass from D4 ( P < 0·001) onwards during the grazing period. Grazing time as a proportion of AT was higher in 2H than in 4H and 6H ewes on D1 and D4 but not on D7 ( P < 0·05 for AT × D). Herbage intake rate was higher in 2H than in 4H and 6H ewes ( P < 0·001). Herbage and total intakes were higher in 4H and 6H than in 2H ewes ( P < 0·001), with herbage intake varying non-linearly during the grazing period ( P < 0·05). Milk yield was higher in 4H and 6H than in 2H ewes ( P < 0·01). To conclude, despite the evidence of compensatory behaviour, restricting access time to 2 h d−1 constrained intake and performance of dairy ewes rotationally grazing berseem clover. [ABSTRACT FROM AUTHOR]

Knowledge of how grazing cattle utilize heterogeneous landscapes in Mediterranean silvopastoral areas is scarce. Global positioning systems (GPS) to track animals, together with geographic information systems (GIS), can relate animal distribution to landscape features. With the aim to develop a general spatial model that provides accurate prediction of cattle resource selection patterns within a Mediterranean mountainous silvopastoral area, free-roaming Sarda cows were fitted with GPS collars to track their spatial behaviors. Resource selection function models (RSF) were developed to estimate the probability of resource use as a function of environmental variables. A set of over 500 candidate RSF models, composed of up to five environmental predictor variables, were fitted to data. To identify a final model providing a robust prediction of cattle resource selection pattern across the different seasons, the 10 best models (ranked on the basis of the AIC score) were fitted to seasonal data. Prediction performance of the models was evaluated with a Spearman correlation analysis using the GPS position data sets previously reserved for model validation. The final model emphasized that watering point, elevation, and distance to fences were important factors affecting cattle resource-selection patterns. The prediction performances (as Spearman rank correlation scores) of the final model, when fitted to each season, ranged between 0.7 and 0.94. The cows were more likely to select areas lower in elevation and farther from the watering point in winter than in summer (693 ± 1 m and 847 ± 13 m vs. 707 ± 1 m and 635 ± 21 m, respectively), and in spring opted for the areas furthest from the water (963 ± 12). Although caution should be exercised in generalizing to other silvopastoral areas, the satisfactory Spearman correlations scores from the final RSF model applied to different seasons indicate resource selection function is a powerful predictive model. The relative importance of the individual predictors within the model varied among the different seasons, demonstrating the RSF model's ability to interpret changes in animal behavior at different times of the year. The RSF model has proven to be a useful tool to interpret the spatial behaviors of cows grazing in Mediterranean silvopastoral areas and could therefore be helpful in managing and preserving ecosystem services of these areas., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MB declared a shared parent affiliation with the author PC to the handling editor at the time of review., (Copyright © 2024 Acciaro, Pittarello, Decandia, Sitzia, Giovanetti, Lombardi and Clark.)

The fatty acid profile, vitamins A and E, cholesterol, antioxidant power colour and the phenols profile of Sarda sheep milk from 11 commercial sheep flocks managed under permanent grassland were investigated. In each farm, the structural and managerial data and milk samples were collected during four periods (sampling dates, SD): January, March, May, and July. Data from the milk composition (fat, protein, casein, lactose, and somatic cell count), 68 fatty acids, 7 phenols, 1 total gallocatechin equivalent, ferric reducing antioxidant power, vitamins A and E, cholesterol, degree of antioxidant protection, and the colour (b *, a * and L *) were analyzed by multivariate factorial analysis using a principal component analysis approach. A proc mixed model for repeated measurement to point out the studied factors affecting significant macro and micro milk composition was also used. Only the first five components were detailed in this paper, with approximately 70% of the explained variance detected. PC1 presented the highest positive loadings for milk lactose, de novo FA synthesis and the BH intermediate, whereas OBCFA had negative loadings values. The PC2, LCFA, UFA, MUFA, vitamins E, and DAP showed positive loadings values, while SFA had a negative value. The PC3 showed a high positive loading for total phenols and non-flavonoids. PC4 presented a high positive loading for the milk macro-composition and negative values for n-3 FAs. The PC5 is characterized by high positive loadings for the a * and L * colour parameters whereas negative loadings were detected for the milk flavonoids content. These preliminary results could help to establish future threshold values for the biomarkers in milk sourced from grazing dairy sheep in natural, permanent pasture-based diets.

The beef livestock system in Sardinia is based on suckler cows, often belonging to autochthonous breeds, such as the Sarda breed, and they often graze silvopastoral areas. Besides beef meat, silvopastoral systems (SPSs) provide several Ecosystem Services (ESs), such as timber provision, harvested as wood, and watershed protection. Livestock distribution is a critical factor for the sustainable use of SPSs (e.g., to avoid uneven grazing patterns) and information on patterns of spatial use are required. A study was conducted to determine: (i) the spatial distribution and (ii) the habitat selection of Sarda cattle grazing in a Mediterranean silvopastoral area. Over different seasons, 12 free-roaming adult Sarda cows were fitted with Global Positioning System (GPS) Knight tracking collars to calculate an index mapping of the incidence of livestock in the landscape (LRI) and a preference index (PI) for different areas. Since the PI data were not normally distributed, the Aligned Rank Transform (ART) procedure was used for the analysis. LRI was able to represent the spatial variability in resource utilization by livestock as a LRI map. Overall, the areas where the animals drank and received supplementation were strongly preferred by the cows, reaching PI values in the summer of 19.3 ± 4.9 (median ± interquartile range), whereas areas with predominantly rocks were strongly avoided (the worst PI value in the spring was 0.2 ± 0.6). Grasslands were, in general, used in proportion to their presence in the area, with slightly increased use in the spring (PI 1.1 ± 0.5). Forest area was avoided by cows, except in the spring when it was used in proportion to their presence in the area.

Catastrophic incidents can significantly disrupt supply chains, but most of these disruptions remain localized. It was not until the onset of COVID-19 that a disruption in our lifetimes achieved a global magnitude. In order to contain the pandemic, governments around the world resorted to closing borders, shutting down manufacturing plants, and imposing lockdowns, which resulted in disrupted production capabilities and weakened consumer spending. The effects of these measures have been clearly visible in global transport networks, where disruptions ripple through the system and serve as a precursor to the disruptions in the broader economy. In this study, we use liner shipping schedule cancellations, a form of serious transport network disruption, as distress signals of the pandemic's impact on global supply chains. Our study applies a three-stage approach and provides insights into operator behaviors when under distress. We show that the pandemic challenged service network integrity and that network disruptions first clustered in Asia before rippling along main trade routes. Agile liner shipping operations, aided by planned service suspensions, prevented the collapse of the global maritime transport networks and indicated the maritime industry's ability to withstand even major catastrophic incidents., (© 2021 Published by Elsevier Ltd.)

The aim of the study is to evaluate the preparedness of retirement and nursing homes in the city of Sassari at the end of the first wave of the severe acute respiratory syndrome coronavirus 2 epidemic, first by investigating the risk perception of epidemic outbreaks by the facility managers and subsequently by carrying out a field assessment of these facilities. To perform the field assessment, a checklist developed by the CDC (Infection Prevention and Control Assessment Tool for Nursing Homes Preparing for COVID-19) and adapted to the Italian context was used. Fourteen facilities took part in the survey (87.5%). The application of good practices for each survey area was expressed as a percentage with the following median values: restriction policies (87.5%), staff training (53.8%), resident training (67.6%), availability of personal protective equipment (41.7%), infection control practices (73.5%) and communication (80%). Among the facilities, considerable variability was observed in these evaluation fields: only the restriction policies and communication activities were applied uniformly. A discrepancy was found between perceived risk and real danger in the facilities, requiring targeted communication actions. At present, it is necessary to promote a new approach based on the prediction of critical events, thereby providing the means to effectively address them.

This work aimed to compare pre- and post-slaughter methodologies to estimate body fat reserves in dairy goats. Twenty-six lactating Saanen goats ranging from 43.6 to 69.4 kg of body weight (BW) and from 1.84 to 2.96 of body condition score (BCS; 0-5 range) were used. Fifteen pre-slaughter and four post-slaughter measurement values were used to estimate the weight of fat in the omental (OM), mesenteric (MES), perirenal (PR), organ (ORG), carcass (CARC), and non-carcass components (NC) and total (TOT, calculated as the sum of CARC and NC) depots in goats. The pre-slaughter measurements were withers height; rump height; rump length; pelvis width; chest depth; shoulder width; heart girth; body length; sternum height; BW; BCS assessed in the lumbar (BCSl) and sternal (BCSs) regions; and fat thickness measured by ultrasound in the lumbar (FTUSl), sternal (FTUSs), and perirenal (FTUSpr) regions. The post-slaughter measurements were hot carcass weight (HCW), empty body weight (EBW), and fat thickness measured by digital caliper in the lumbar (FTDCl) and sternal (FTDCs) regions. Linear and multiple regressions were fit to data collected. BW, BCS (from lumbar and sternal regions), all somatic measurements, and fat thickness measured by ultrasound in the lumbar and sternal regions were not adequate to estimate the weight of total fat in lactating Saanen goats ( R 2 ≤ 0.55). The best pre-slaughter and post-slaughter estimators of OM, MES, PR, ORG, NC, and TOT fat were FTUSpr and EBW, respectively. Among pre- and post-slaughter measurements, BCSl ( R 2 = 0.63) and HCW ( R 2 = 0.82) provided the most accurate predictions of CARC fat, respectively. Multiple regression using the pre-slaughter variables FTUSpr, BW, and BCSl yielded estimates of TOT fat with an R 2 = 0.92 (RSD = 1.14 kg). On the other hand, TOT fat predicted using the post-slaughter variables HCW and FTDCs had an R 2 = 0.83 (RSD = 1.41 kg). These results confirm that fat reserves can be predicted in lactating Saanen goats with high precision using multiple regression equations combining in vivo measurements.

Milk from grazing ruminants is usually rich in beneficial components for human health, but distinguishing milks sourced from grazing is difficult, and this hinders the valuing of the grazing benefit. This study aimed at evaluating the ability of milk biomarkers (1) to trace milks sourced from sheep submitted to different access times (ATs) to pasture and (2) to estimate sheep herbage dry matter intake (HDMI, g DM ewe -1 d -1 ) and herbage percentage (HP, % DM) in sheep diet. Animal data derive from a published experiment in which six replicated groups of mid-lactation Sarda sheep had ATs of 2, 4, or 6 h d -1 to a ryegrass pasture. Sheep HDMI and HP of each group were measured on four dates in April 2013. Group milk was sampled, and milk fatty acids (FAs) and n-alkanes were determined by gas chromatography. The latter markers were also measured in feces samples bulked by group. The data ( N = 24 records) were submitted to Linear Discriminant Analysis (LDA) aimed at distinguishing the AT to pasture based on biomarkers previously selected by Genetic Algorithms (GA). Partial Least Square Regression (PLSR) models were used to estimate HDMI and HP using biomarkers selected by GA. Based on one milk alkane and six milk FAs as biomarkers, estimates of the AT using GA-LDA were 95.8% accurate. The estimation of HDMI by GA-PLSR based on five milk FAs was moderately precise [explained variance = 75.2%; percentage of the residual mean square error of cross-validation over the mean value (RMSECV%) = 15.0%]. The estimation of HP by GA-PLSR based on 1 milk alkane and 10 FAs was precise (explained variance = 80.8%; RMSECV% = 7.4%). To conclude, these preliminary results suggest that milks sourced from sheep flocks with AT to pasture differentiated by 2 h in the range 2-6 h d -1 can be precisely discriminated using milk biomarkers. The contribution of herbage to sheep diet can also be precisely estimated., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Molle, Cabiddu, Decandia, Acciaro, Scanu, Addis, Fiori and Caredda.)