Increased Cattle Feeding Precision from Automatic Feeding Systems: Considerations on Technology Spread and Farm Level Perceived Advantages in Italy.

Automation reduces the impact of farming on climate change and helps farmers adapt to its financial impact. Automatic feeding systems (AFSs) increase the ruminant's feeding precision and ease operators' workload. Such systems exist on a spectrum, requiring varied levels of operator support and installation complexity. A recent survey on farmers pointed out that those already running an AFS and those willing to buy one appreciate its ease of use, the resulting animal welfare, and the resulting overall benefits (increased production, farm profitability, and reduced feed waste). Whether technologically complex or not, studies have confirmed the benefits that farmers perceive to be underlying the remarkable reduction in the environmental impact of feeding operations (AFSs are electrically powered), the increase in animal welfare resulting from reduced conflicts around accessing the feed bunk, and the constant availability of fresh feed. However, their introduction should follow accurate and holistic structural and economic planning for existing and newly built facilities. The availability of public subsidies plays an essential role in pushing farmers to adopt the most modern digital technologies, whose benefits may even increase when farmers couple them with interconnected sensors to monitor animals' physiological states.

Assessment of Comfort Variation among Different Types of Driving Agricultural Tractors: Traditional, Satellite-Assisted and Semi-Automatic.

Over the past years, in the agricultural field, geo-localization has been introduced in order to develop specific farming processes, optimize resources, and reduce environmental pollution. Researchers have found alternative driving methods to traditional ones, such as assisted and semi-automatic driving. The aim of this study was to monitor the musculoskeletal efforts necessary to carry out different kinds of driving. The muscular strain was assessed using surface electromyographic devices, the distribution of the pressure exerted by the operator's body on the seat was observed by using two barometric pads applied on the seat back and on the seat, respectively, while the body movements and postures were analyzed through a Microsoft Kinect Camera 3D acquisition system. Results showed a significantly greater muscular activation during manual and assisted driving conditions. The pressure exerted by the operator on the barometric pads was significantly higher in manual and semi-automatic driving modes than in the assisted one. A remarkable increase in the average swinging speed of examined joints was also detected, as well as the distances run by the joints in semi-automatic driving. From our study, assisted driving seems to be the best driving mode both in terms of joint economy and from the efficiency of agricultural processes.

EVALUATION OF AGRICULTURAL TRACTOR SEAT COMFORT WITH A NEW PROTOCOL BASED ON PRESSURE DISTRIBUTION ASSESSMENT.

Professional drivers have been found to be at a high risk of developing low back pain due to prolonged sitting and vehicle vibration. In a previous survey carried out on 1,155 tractor drivers, tractor vibration and/or incorrect posture while driving were found to cause low back disorders in more than 80% of the interviewed drivers. In this context, the present research introduces a new evaluation protocol to assess the ergonomic characteristics of agricultural tractor seats through the use of pressure sensors, taking into account both static and dynamic conditions. The degree of comfort was defined by analyzing the pressure distribution exerted by a sample of 12 drivers sitting on two seats in five different operating conditions. The pressure distribution values thus obtained were compared with the corresponding pressures recorded with the 12 drivers sitting on a reference seat (rigid seat, backrest, and suspension) designed for the purpose. From the comparison, it was possible to define a comfort index (CI) that allowed an objective assessment of the two seats. Statistical analysis showed that the CIs of the two seats were significantly different in all five operating conditions. Moreover, the two seats showed different CIs as a function of the operating condition. Although less comfortable, one seat showed almost constant CI values in all five operating conditions. Conversely, the other seat showed a progressively decreasing CI from the static condition to the uneven ground condition.