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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.

Since the Green Revolution, worldwide agriculture has been characterized by a typical top–down approach. The degree of autonomy, creativity, and responsibility of farmers has been limited by the continuous external inputs of chemicals, machinery, advice, subsidies and knowledge.The issue of sustainability has brought complexity and uncertainty to this mainly linear process of innovation, steering agriculture toward alternative models. Agroecology represents an innovative paradigm of agriculture in which external inputs are minimized, and the assets of the farm are greatly valued. Agroecological production relies on the farmers’ direct management of resources and on their active engagement in the agricultural knowledge and innovation system.This paper focuses on the experience of a group of farmers, scientists, public officials, and managers of private companies who are experimenting with agroecology in rice production in one of the most intensively farmed, profitable and environmentally sensitive areas of Italy. The partnership regularly comes together to discuss agricultural techniques and results, needs, and paths of innovation; in addition, it stimulates and takes part in research projects, following a participatory process based on co-learning and mutual responsibility. By using ethnographic methods such as direct observations and in-depth interviews, our work may contribute to understanding the role of participatory research in sustainable agriculture and what makes for good participation.

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.

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