Harvesting orchard pruning residues in southern Piedmont: a first evaluation of biomass production and harvest loss

In recent years, interest in farming residues has grown and orchard pruning residues are no exception. Several factors define pruned branch mass and dimensional characteristics: fruit variety, vigor, training system used, and pruning intensity and periodicity. While many studies have been performed to determine residue biomass availability, dating and surveying are not always accurate. Detailed qualitative and quantitative knowledge is needed to evaluate the economic sustainability of exploiting orchard pruning residues as an energy source. To assess the real chain potential of renewable energy production from orchard pruning residues in the area of Cuneo, in the Region of Piedmont, northwestern Italy, a study was conducted on the species Actinidia (kiwi tree) pruned according to the Peyracchia system, and Malus (apple tree) pruned according to two different systems, i.e. traditional and taille longue. For each species, pruning residue amounts were quantified and their basal diameter measured. Surveys were performed on some half trees, spaced as crop, for three randomised replications. Pruning residues were determined by dynamometer (accuracy 0.02N); individual cut-off branch diameters were measured at their base with mechanical calipers. Pruning residues were blown by rotating rake and harvested by a modified fixed chamber round baler. Harvest losses were determined by the methodology used for the initial residue quantification. Results showed the average biomass availability was 2.51 Mg DM ha–1 (SD 0.83) for kiwi tree, 3.04 Mg DM ha–1 (SD 1.17) for traditionally-pruned apple trees, and 0.46 Mg DM ha–1 (SD 0.36) for apple trees pruned with the taille longue system. Harvest losses (total pruned dry mass) averaged approximately 19% in kiwi trees and 16% in apple trees (95% to 10% for variety

Advances in developing a new test method to assess spray drift potential from air blast sprayers

Drift is one of the most important issues to consider for realising sustainable pesticide sprays. This study proposes and tests an alternative methodology for quantifying the drift potential (DP) of air blast sprayers, trying to avoid the difficulties faced in conducting field trials according to the standard protocol (ISO 22866:2005). For this purpose, an ad hoc test bench designed for DP comparative measurements was used. The proposed methodology was evaluated in terms of robustness, repetitiveness and coherence by arranging a series of trials at two laboratories. Representative orchard and vineyard air blast sprayers in eight configurations (combination of two forward speeds, two air fan flow rates, and two nozzle types) were tested. The test bench was placed perpendicular to the spray track to collect the fraction of spray liquid remaining in the air after the spray process and potentially susceptible to drift out of the treated area. Downwind spray deposition curves were obtained and a new approach was proposed to calculate an index value of the DP estimation that could allow the differences among the tested configurations to be described. Results indicated that forward speed of 1.67 m/s allows better discrimination among configurations tested. Highest DP reduction, over 87.5%, was achieved using the TVI nozzles in combination with low air fan flow rate in both laboratories; conversely, the highest DP value was obtained with the ATR nozzles in combination with high air fan flow rate. Although the proposed method shows a promising potential to evaluate drift potential of different sprayer types and nozzles types used for bush and tree crops further research and tests are necessary to improve and validate this method.Postprint (published version

Block-sparsity-based localization in wireless sensor networks

In this paper, we deal with the localization problem in wireless sensor networks, where a target sensor location must be estimated starting from few measurements of the power present in a radio signal received from sensors with known locations. Inspired by the recent advances in sparse approximation, the localization problem is recast as a block-sparse signal recovery problem in the discrete spatial domain. In this paper, we develop different RSS-fingerprinting localization algorithms and propose a dictionary optimization based on the notion of the coherence to improve the reconstruction efficiency. The proposed protocols are then compared with traditional fingerprinting methods both via simulation and on-field experiments. The results prove that our methods outperform the existing ones in terms of the achieved localization accuracy