The use of sensor technologies to monitor cows’ behavior is becoming commonplace in the context of dairy production. This study aimed at validating a commercial collar-based sensor system, the AFICollar^® (Afimilk, Kibbutz Afikim, Israel), designed to monitor dairy cattle feeding and ruminating behavior. Additionally, the performances of two versions of the software for behavior classification, the current software AFIfarm^® 5.4 and the updated version AFIfarm^® 5.5, were compared. The study involved twenty Holstein-Friesian cows fitted with the collars. To evaluate the sensor performance under different feeding scenarios, the animals were divided into four groups and fed three different types of feed (total mixed ration, long hay, animals allowed to graze). Recordings of hourly rumination and feeding time produced by the sensor were compared with visual observation by scan sampling at 1 minute intervals using Spearman correlation, concordance correlation coefficient (CCC), Bland–Altman plots and linear mixed models for assessing the precision and accuracy of the system. The analyses confirmed that the updated software version V5.5 produced better detection performance than the current V5.4. The updated software version produced high correlations between visual observations and data recorded by the sensor for both feeding (r = 0.85, CCC = 0.86) and rumination (r = 0.83, CCC = 0.86). However, the limits of agreement for both behaviors remained quite wide (feeding: −19.60 min/h, 17.46 min/h; rumination: −15.80 min/h, 15.00 min/h). Type of feed did not produce significant effects on the agreement between visual observations and sensor recordings. Overall, the results indicate that the system can provide farmers with adequately accurate data on feeding and rumination time, and can be used to support herd management decisions. Despite all this, the precision of the system remained relatively limited, and should be improved with further developments in the classification algorithm.

(1) Background: Human–wildlife conflict can lead to adverse consequences for both parties, particularly in areas with a high concentration of wild ungulates. Ungulates cause frequent, severe plant damage by stripping the bark or browsing on the youngest plants. In the latter case, they damage vegetative sprouts and leaves, which can cause a delay in growth or the plant’s death. Tuscany is notable for its significant population of wild boar, which cause substantial damage to vineyards and cereal crops, costing farmers millions annually. In Tuscany, given the highly cultivated landscape of olive trees, damage has also been recorded in these plants. Balancing human and wildlife needs is crucial for minimizing damage and ensuring coexistence. (2) Methods: This study tested innovative electronic playback devices using long-range radio technology (LoRa) to deter wild ungulates and prevent crop damage. These devices use sounds and lights to induce wild animals to be afraid and thus run away from the cultivated plot to be protected. The experiment was conducted on a farm in Chianti, Tuscany, involving four plots of land planted with olive trees: in two test areas, four playback devices and four camera traps were installed, and in the two control areas, only camera traps were installed. Playback devices aimed to deter wild ungulates and camera traps aimed to test their effectiveness. Data from the camera traps were analyzed statistically and behaviorally. (3) Results: Playback devices significantly reduced wild animal activity in the equipped areas. Statistical analysis revealed that the use of acoustic–luminous deterrent devices (PDs) significantly reduced wildlife visits to the olive groves. (4) Conclusion: The study’s findings, supported by heatmaps and frequency analyses, provide insights into wildlife activity patterns and guide the development of targeted, effective wildlife management strategies.

In the islands of the Tuscan Archipelago, dry-stone walls represent an extensive cultural heritage in state of generalized abandonment. Considering the multifunctionality recognized to surviving terraced systems needs to be safeguarded through surveys aimed at providing characterization and indications for possible recovery interventions. After a preliminary quantitative G.I.S. remote analysis, qualitative characterization of the realities deemed most significant was carried out by on-site surveys. 48 sample areas have been analyzed by studying parameters related to constructive, functional aspects and state of conservation. A variety of construction and management techniques has been found and it appears that there are strong differences in the state of conservation even between neighboring fields: on one side farmers and virtuous private individuals who maintain the terraces, on the other side, abandoned areas where the decay produces a fragmentation of the landscape continuity and originates sometimes non-negligible potential danger situations. Thus, technical indications are proposed for the restoration of degraded structures requiring priority interventions.

Terraced systems represent a valuable resource, increasing productive areas on steep slopes often unsuitable for cultivation. Over the years, these ecosystems have been recognised as having functions beyond agronomic value, such as hydrogeological, historical-cultural, economic, and biodiversity conservation. This research intends to contribute to mapping the terraced areas of the Tuscan Archipelago to estimate the areas falling within four of the seven islands of the Archipelago. In addition to a quantitative analysis, terraced systems were studied in terms of morphological and anthropic parameters, which may influence their functionality or cultivation abandonment. The analyses were conducted in a GIS environment, using the Tuscany Region Spatial Information Database and georeferenced orthophotos acquired from drone field surveys. Through the spatial analyses, it was possible to identify the distribution of the terraced system concerning parameters such as slope, altitude, aspect, distance from road networks and land fragmentation, providing a key to understanding how these parameters may influence the causes of conservation or abandonment of these fragile landscapes. Analyses of the terraced areas showed that the prevalent slopes are between 10 and 30% and that the altitude is variable depending on the island but predominantly between 0 and 200 m. Exposure was found to be the most heterogeneous parameter, and a strong relationship emerged between the functional abandonment of agricultural terraced areas and the distance from road networks. Furthermore, the land register analysis revealed a high degree of land fragmentation, which complicates the management and conservation of terraced systems.