Risk analysis of tractor rollover in the normal operation in field

Tractor rollover represent a primary cause of death or serious injury in agriculture and despite the mandatory Roll-Over Protective Structures (ROPS), that reduced the number of injuries, tractor accidents are still of great concern. Because of their versatility and wide use many studies on safety are concerned with the stability of tractors, but they often prefer controlled tests or laboratory tests. The evaluation of tractors working in field, instead, is a very complex issue because the rollover could be influenced by the interaction among operator, tractor and environment. Recent studies are oriented towards the evaluation of the actual working conditions developing prototypes for driver assistance and data acquisition. Currently these devices are produced and sold by manufacturers. A warning device was assessed in this study with the aim to evaluate its performance and to collect data on different variables influencing the dynamics of tractors in field by monitoring continuously the working conditions of tractors operating at the experimental farm of the Bologna University. The device consists of accelerometers, gyroscope, GSM/GPRS, GPS for geo-referencing and a transceiver for the automatic recognition of tractor-connected equipment. A microprocessor processes data and provides information, through a dedicated algorithm requiring data on the geometry of the tested tractor, on the level of risk for the operator in terms of probable loss of stability and suggests corrective measures to reduce the potential instability of the tractor.

Hyperspectral imaging and other optical techniques for (in-field/in-lab) physico-chemical attributes estimation of agri-food vegetal products

In the agri-food sector, measurement and monitoring activities contribute to high quality end products. In particular, considering food of plant origin, several product quality attributes can be monitored. Among the non-destructive measurement techniques, a large variety of optical techniques are available, including hyperspectral imaging (HSI) in the visible/near-infrared (Vis/NIR) range, which, due to the capacity to integrate image analysis and spectroscopy, proved particularly useful in agronomy and food science. Many published studies regarding HSI systems were carried out under controlled laboratory conditions. In contrast, few studies describe the application of HSI technology directly in the field, in particular for high-resolution proximal measurements carried out on the ground. Based on this background, the activities of the present PhD project were aimed at exploring and deepening knowledge in the application of optical techniques for the estimation of quality attributes of agri-food plant products. First, research activities on laboratory trials carried out on apricots and kiwis for the estimation of soluble solids content (SSC) and flesh firmness (FF) through HSI were reported; subsequently, FF was estimated on kiwis using a NIR-sensitive device; finally, the procyanidin content of red wine was estimated through a device based on the pulsed spectral sensitive photometry technique. In the second part, trials were carried out directly in the field to assess the degree of ripeness of red wine grapes by estimating SSC through HSI, and finally a method for the automatic selection of regions of interest in hyperspectral images of the vineyard was developed. The activities described above have revealed the potential of the optical techniques for sorting-line application; moreover, the application of the HSI technique directly in the field has proved particularly interesting, suggesting further investigations to solve a variety of problems arising from the many environmental variables that may affect the results of the analyses.