1246 | 160 | Soil salinity and its economic effects: a Machine Learning approach

Soil salinity is one of the most significant problems for agriculture. The phenomenon occurs when soils accumulate excessive amounts of salts, compromising the fertility and productivity of crops. Salinity can be caused by natural phenomena (such as soil erosion) or human activity (such as the use of fertilizers or irrigation with saline water)._x000D_
The creation of a Machine Learning model for predicting the salinity of Italian soils can be a valuable tool for land management and identifying areas at risk. Thanks to the large amount of data available, predictive analysis techniques can be used to identify correlations between factors that influence salinity (such as soil type, groundwater presence, rainfall, temperature) and the salt concentration in the soil. The model thus created could be used to build a European soil salinity map, useful for farmers and entities responsible for land management._x000D_
The economic analysis of soil salinization highlights how this represents a serious problem for European agriculture, with damages estimated at several billion euros each year. Reduced crop productivity, decreased quality of agricultural products, and increased production costs are just some of the consequences of soil salinity. Moreover, the presence of uncultivable land due to salinity results in a loss of land value and a negative impact on tourism and activities related to the rural landscape._x000D_

Matteo Dalle Vaglie
University of Florence

ID Abstract: 160

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