Abstract. In the present work, the role played by vegetation parameters, necessary to the hydrological distributed modeling, is investigated focusing on the correct use of remote sensing products for the evaluation of hydrological losses in the soil water balance. The research was carried out over a medium-sized river basin in Southern Italy, where the vegetation status is characterised through a data-set of multitemporal NDVI images. The model adopted uses one layer of vegetation whose status is defined by the Leaf Area Index (LAI), which is often obtained from NDVI images. The inherent problem is that the vegetation heterogeneity -including soil disturbances -has a large influence on the spectral bands and so the relation between LAI and NDVI is not unambiguous.We present a rationale for the basin scale calibration of a non-linear NDVI-LAI regression, based on the comparison between NDVI values and literature LAI estimations of the vegetation cover in recognized landscape elements of the study catchment. Adopting a process-based model (DREAM) with a distributed parameterisation, the influence of different NDVI-LAI regression models on main features of water balance predictions is investigated. The results show a significant sensitivity of the hydrological losses and soil water regime to the alternative LAI estimations. These crucially affects the model performances especially in lowflows simulation and in the identification of the intermittent regime.

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In recent years, there has been an increasing interest on donkey milk production, on its characteristics, and also on breeding techniques. Donkey milk is characterized by high economic value, although the productive level of jennies is poor. During the milking process, foals are usually separated from their dams, allowing the milk collection in the mammary gland of jennies before milking session. This takes 8 h per day of fastening period for lactating donkey foals. During this period, it could be possible to apply a partial artificial suckling system (artificial suckling during daytime and natural suckling during the night). The aim of the work is the evaluation of the effect of this innovative technique on in vivo performances and on meat production traits of Martina Franca donkey foals. Forty Martina Franca jennies with their foals were used for the trial. After colostrum assumption, 20 foals were partially artificially suckled (AS) during each day, and 20 foals were naturally suckled (NS). From 8.00 to 20.00, both groups were separated from their mothers in order to allow the milking procedures of the jennies. The AS group was in a stall equipped with an automatic calf-suckling machine. For each group, 10 foals were slaughtered at 12 months and 10 foals at 18 months. Artificial suckling system positively affected the growth rate of donkey foals, particularly in the first 6 months from birth, with higher weekly weight gain (P < 0.01), higher final live weight (P < 0.001), and carcass weight (P < 0.01), but no effects were observed on carcass dressing percentage (P > 0.05). Artificial suckling system permitted to extend the time of foal separation from their mothers increasing milk collection time per day, awarding fastening periods in foals.

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