Must obtained from Airén grapes was fermented in the presence of wood chips (4 and 7 g/L) of either French oak (from Vosges, central France, and Allier zones) or American oak. Fermentation yields were higher than in the control fermentations carried out in the absence of wood, and production of volatile substances during fermentation (alcohols, esters, and acetates) was also higher. The volatile substances that leached out of the wood were analyzed by GC-MS-SIR. The results showed that their concentrations depended on the type and amount of the oak; some of these substances were consumed in part by the yeasts during fermentation. A taste panel favorably assessed the wines produced by fermentation in the presence of oak chips, which retained part of the must original fruity aroma.
Satisfactory results relating to the natural regeneration of the Spanish black pine (Pinus nigra Arn ssp. salzmannii) is generally difficult to achieve. The natural regeneration of this pine was studied comparing two types of soil treatment and various overstory densities in six experimental forests. These studies were conducted from 1999 to 2002 and seed rain and germination, as well as seedling survival were observed in a number of specific plots: Brushing, scalping and control plots. In addition various overstory densities were used (measured as base area (square m/ha). Soil and air temperature together with soil moisture were continuously recorded throughout this summer period. The results showed that seed germination was higher in plots using the scalping technique, as opposed to the brushed or controlled plots. The best seedling survival percentage was found in scalped plots together with a larger basal area. It was also found that seedling survival was lower during the first year than during the second one. The results have practical implications for management of Spanish black pine forests as well as valuable information which could improve the conditions for regeneration.
Information on plant seed dispersal, natural loss dynamics of seeds and germination are critical for understanding natural regeneration mechanisms. The aim of this study was to assess the effect of different forest stand densities on seedfall, seed predation, and seedling germination of two populations of the endangered Spanish black Pine forests located at lower (Central population) and higher elevation near the limit of the species’ range (peripheral population) in the Cuenca Mountains of Central Spain. The seed predation and germination experiment also included a nested site preparation treatment. Seed fall varied significantly between 2006 and 2005 or 2007 in both populations. During the only mast year of 2006, higher seedfall was observed at lower elevation and in higher density stands. Predation rates were influenced by the seed crop since predators consumed more than 75 % of seeds in years with lower production and less than 15 % in a mast year. Seed germination is influenced by forest habitat, stand density and soil scalping. For common habitat types, and in a high seed production year, better seed germination rates were observed in medium and dense stands (25–30 and 35–40 m2 ha−1, respectively, in terms of basal area). No statistical difference in seed germination rate was found for Spanish black pine forest at its ecological distribution limit between lower and higher densities (15–20 and 35–40 m2 ha−1, in terms of basal area). In both sites, closed stands with soil scalping exhibited higher germination rates.
Machine learning is a branch of artificial intelligence (AI) that consists of the application of various algorithms to obtain information from large data sets. These algorithms are especially useful to solve nonlinear problems that appear frequently in some engineering fields. Geotechnical engineering presents situations with complex relationships of multiple variables, making it an ideal field for the application of machine learning techniques. Thus, these techniques have already been applied with a certain degree of success to determine such things as soil parameters, admissible load, settlement, or slope stability. Moreover, dynamic penetrometers are a very common type of test in geotechnical studies, and, in many cases, they are used to design the foundation solution. In addition, its continuous nature allows us to know the variations of the terrain profile. The objective of this study was to correlate the drilling parameters of deep foundation machinery (Measurement-While-Drilling, MWD) with the number of blows of the dynamic penetrometer test. Therefore, the drilling logs could be equated with said tests, providing information that can be easily interpreted by a geotechnical engineer and that would allow the validation of the design hypotheses. Decision trees and random forest algorithms have been used for this purpose. The ability of these algorithms to replicate the complex relationships between drilling parameters and terrain characteristics has allowed obtaining a reliable reproduction of the penetrometric profile of the traversed soil.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.