Estimating leaf area index (LAI) of Vitis vinifera using indirect methods involves some critical issues, related to its discontinuous and non-homogeneous canopy. This study evaluates the smart app PocketLAI and hemispherical photography in vineyards against destructive LAI measurements. Data were collected during six surveys in an experimental site characterized by a high level of heterogeneity among plants, allowing us to explore a wide range of LAI values. During the last survey, the possibility to combine remote sensing data and in-situ PocketLAI estimates (smart scouting) was evaluated. Results showed a good agreement between PocketLAI data and direct measurements, especially for LAI ranging from 0.13 to 1.41 (R² = 0.94, RRMSE = 17.27%), whereas the accuracy decreased when an outlying value (vineyard LAI = 2.84) was included (R² = 0.77, RRMSE = 43.00%), due to the saturation effect in case of very dense canopies arising from lack of green pruning. The hemispherical photography showed very high values of R², even in presence of the outlying value (R² = 0.94), although it showed a marked and quite constant overestimation error (RRMSE = 99.46%), suggesting the need to introduce a correction factor specific for vineyards. During the smart scouting, PocketLAI showed its reliability to monitor the spatial-temporal variability of vine vigor in cordon-trained systems, and showed a potential for a wide range of applications, also in combination with remote sensing.

SUMMARY: Modern agriculture is based on the control of in-field variability, which is determined by the interactions of numerous factors such as soil, climate and crop. For this reason, the use of remote sensing is becoming increasingly important, thanks to the technological development of satellites able to supply information with high spatial resolution and revisit frequency. Despite the large number of studies on the use of remote sensing for crop monitoring, very few have addressed the problem of spatial variability at field scale or the early prediction of crop yield and grain quality. The aim of the current research was to assess the potential use of high resolution satellite imagery for monitoring durum wheat growth and development, addressing forecast grain yield and protein content, through vegetation indices at two stages of crop development. To best represent the natural variability of agricultural production, the study was conducted in wheat fields managed by local farmers. As regards dry weight, leaf area index and nitrogen (N) content, the possibility of describing the crop state is evident at stem elongation, while at anthesis this potential is completely lost. However, satellites seem to be unable to estimate the N concentration. Aboveground biomass accumulated from emergence to stem elongation is strictly related to the final yield, while it has been confirmed that the crop parameters observed at anthesis are less informative, despite approaching harvesting time.

Soil represents an important pool of biodiversity, hosting about a quarter of the living species on our planet. This soil richness has led to increasing interest in the structural and functional characteristics of its biodiversity. Studies of arthropod responses, in terms of abundance and taxon richness, have increased in relation to their ecological value as bioindicators of environmental change. This research was carried out over the 2014–2018 period with the aim to better understand arthropod taxa responses in vineyard soils in Franciacorta (Lombardy, Italy). To determine the biological composition in terms of arthropod taxa presence, one hundred soil samples were analysed. Environmental characteristics, such as chemical composition, soil moisture and temperature, and soil management were characterized for each soil sample. A total of 19 taxa were identified; the NMDS model analysis and the cluster analysis divided them into five groups according to their co-occurrence patterns. Each group was related to certain abiotic conditions; of these, soil moisture, temperature and organic matter were shown to be significant. A decision tree analysis showed that a longer period since conversion from conventional to organic farming lead to a higher arthropod biodiversity defined as a higher number of taxa.