Biomass sorghum (Sorghum bicolor L. Moench) is a crop that can be used for energy production in the bioethanol chain and a greater knowledge of its potential and response to irrigation water levels could help to assess its potential diffusion in Mediterranean areas. A twoyear field experiment was carried out in Southern Italy; two irrigation regimes were compared in biomass sorghum, optimal watered (irrigation supplies greater than actual crop evapotranspiration, ETc) and stressed watered (about 65% of the optimal one). Growth analysis, soil water content and aboveground dry biomass (ADM) yield at harvest were measured and analyzed. Radiation use efficiency (RUE), irrigation (IWUE) and water use efficiencies (WUE) were also calculated. Seasonal water use ranged from 830 mm in the optimal treatment to 589 mm in the stressed one. Similarly, ADM proved to be statistically different between the two irrigation treatments (34.6 vs 19.8 t of dry matter ha -1 ). The RUE, calculated as the slope of the first order equation between dry biomass and intercepted photosynthetically active radiation along a crop cycle, showed an average of 2.84±0.65 g MJ -1 . No statistical differences for IWUE and WUE were obtained between irrigation regimes (8.22 and 5.87 kg m -3 , on average). The two years of experiment influenced IWUE and WUE (both larger in the rainier growing season), but not the RUE. The high RUE and WUE obtained values confirmed that biomass sorghum is a crop with considerable dry matter production efficiency. The experimental results suggest that the introduction of biomass sorghum in the cropping systems of Mediterranean environments as an alternative crop for energy purposes is feasible, but requires an adequate seasonal irrigation water supply (not less than 500 mm).
Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in the world. Identified in 2013 in olive trees in south–eastern Italy, it is spreading to the Mediterranean countries. The bacterium is transmitted by insects that feed on sap, and causes rapid wilting in olive trees. The paper explores the use of Unmanned Aerial Vehicle (UAV) in combination with a multispectral radiometer for early detection of infection. The study was carried out in three olive groves in the Apulia region (Italy) and involved four drone flights from 2017 to 2019. To classify Xfp severity level in olive trees at an early stage, a combined method of geostatistics and discriminant analysis was implemented. The results of cross-validation for the non-parametric classification method were of overall accuracy = 0.69, mean error rate = 0.31, and for the early detection class of accuracy 0.77 and misclassification probability 0.23. The results are promising and encourage the application of UAV technology for the early detection of Xfp infection.
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