A Comparison between Numerical Simulation Models for the Prediction of Acoustic Behavior of Giant Reeds Shredded

Giant reeds represent a natural fiber widely available in some areas of the world. Its use can be particularly useful as the uncontrolled growth of giant reeds can be a problem because large areas are invaded by them and the crops are damaged. In this study, two models of numerical simulation of the acoustic behavior of giant reeds were put in comparison: the Hamet model and a model based on artificial neural networks. First, the characteristics of the reeds were examined and the procedures for the preparation of the samples to be analyzed were described. Then air flow resistance, porosity and sound absorption coefficient were measured and analyzed in detail. Finally, the results of the numerical modeling of the acoustic coefficient were compared. The neural network-based model showed high Pearson correlation coefficient value, indicating a large number of correct predictions.

Use of In Situ Soil Solution Electric Conductivity to Evaluate Mineral N in Commercial Orchards: Preliminary Results

The aim of the present experiment was to evaluate the effectiveness of soil electrical conductivity (EC) measurement as a fast tool to assess mineral nitrogen (N) in orchards, in order to define precise N inputs that can help farmers to reduce useless fertilizer application. During one vegetative season, seven orchards of different species, supplied with mineral or organic fertilization, were monitored. Nitrate soil concentration was measured monthly by laboratory analyses, while soil EC and moisture were recorded continuously by soil probes. Nitrate and EC were positively correlated, laying the foundation for the identification of a fast and reliable index. However, while some dates showed a high Pearson correlation coefficient, no correlation was found for others. The correlation was not affected by type of fertilizer, and was higher in silty-clay-loam than in loam soils. Pooling all of the data, a significant correlation with a Pearson coefficient of 0.75 was found. The soil optimal nitrate N availability was defined by an EC in the range of 0.3 to 0.6 mS cm−1. Although these are only preliminary results, our data are promising, showing a good suitability of soil EC measurement as a means to monitor soil mineral N availability.

The canopy coverage is correlated with the number of shoots produced by Eucalyptus clones in a clonal mini-garden

In this work, we analyzed the correlation between the canopy coverage of two commercial clones of Eucalyptus benthamii Maiden & Cambage and one of Eucalyptus dunnii Maiden and their shoot yields in a clonal mini-garden system. By canopy coverage, we referred to the area of a picture occupied by leaves (green area) when analyzed using computational resources. The mini-garden was set up to yield shoots on a regular time schedule (between 20 and 30 days) to obtain mini-cuttings for clonal propagation. Pictures were taken at approximately 30 cm above the upper leaves from the plots containing mini-stumps of each clone on the day before the collection of mini-cuttings for six consecutive harvests (approximately 6 months). The leaf coverage was obtained using the computational package Easy Leaf Area. Our results indicated a significantly high Pearson correlation coefficient (r = 0744, P < 0.001) between the canopy coverage and the number of shoots produced by each clone. A logistic regression model was adjusted to this dataset, enabling a prediction of the number of shoots based on the canopy coverage. This approach has the potential for assisting forest nurseries in predicting the yield of mini-cuttings while conducting clonal propagation of their genetic materials.