The use and timing of many agronomical practices such as the scheduling of irrigation and harvesting are dependent on
accurate vineyard sampling of qualitative and productive parameters. Crop forecasting also depends on the
representativeness of vineyard samples during the whole phenological period. This manuscript summarizes the last two
years of precision viticulture in Sicily (Italy); agronomic campaigns were carried out in 2012 and 2013 within the
“Tenute Rapitalà” and “Donnafugata” farms. Normalized Difference Vegetation Index derived from satellite images
(RapidEye) acquired at berry set, pre-veraison and ripening phenological stages (occurred at June, July and August
respectively) have been related to production parameters (sugar and anthocyanins contents) at harvesting of a selected
red autochthonous cultivar (Nero D’Avola). The research aims to assess how robust are prediction models based on
simple linear regression analysis, in particular: 1) whether there is a suitable period for acquiring the remote sensing
image to evaluate these parameters at harvesting, when their knowledge is required; 2) if these relationships are
consistent between years or need to be re-calibrated; 3) the models transferability to other vineyard of the same cultivar.
Agricultural water requirement in arid and semi-arid environments represents an important fraction of the total water
consumption, suggesting the need of appropriate water management practices to sparingly use the resource. Furthermore
the quality and quantity of some crops products, such as grape, is improved under a controlled amount of water stress.
The latter is related, on a side to actual evapotranspiration (ET) through water demand, on the other side to plant water
content through leaf water potential. Residual energy balance approaches based on remote sensing allow to estimate the
spatial distribution of daily actual ET at plant scale, representing an useful tool to detect its spatial variability across
different cultivars and even within each parcel. Moreover, the connection between actual ET and leaf water potential is
still not well assessed, especially under water stress conditions, even if farmers use leaf water potential to plan irrigation.
However residual energy balance methods are based on the hypothesis that storage terms are negligible, at least during
the remote sensor overpass. Indeed, energy balance approaches estimate daily actual ET from the instantaneous value at
the overpass time using a daily integration method. The paper first verifies this latter assumption using field data
acquired by a flux tower on a whole phenological period. Then, the actual ET values measured by eddy covariance tower
were analyzed together with water potential measured using a Scholander chamber; the analysis highlights that, under
water stress conditions, daily actual ET is inversely linearly related with water potential. These results suggest the
possibility to use remote sensing-based ET as support for irrigation management at plot scale.
The LAI is a key parameter in hydrological processes, especially in the physically based distribution models. It is a
critical ecosystem attribute since physiological processes such as photosynthesis, transpiration and evaporation depend
on it. The diffusion of water vapor, momentum, heat and light through the canopy is regulated by the distribution and
density of the leaves, branches, twigs and stems. The LAI influences the sensible heat flux H in the surface energy
balance single source models through the calculation of the roughness length and of the displacement height. The
aerodynamic resistance between the soil and within-canopy source height is a function of the LAI through the roughness
length. This research carried out a sensitivity analysis of some of the most important parameters of surface energy
balance models to the LAI time variation, in order to take into account the effects of the LAI variation with the phenological period. Finally empirical retrieved relationships between field spectroradiometric data and the field LAI measured via a
light-sensitive instrument are presented for a cereal field.
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