Soil property prediction with recommendation system for best plants for planting in it.
ENSIAS: Ecole Nationale Supérieure d'Informatique et d'Analyse des Systèmes | Morocco
ABDERRAHIM BOUMAHDI | ANASS EL GHAOUI | TAHA ALAMI IDRISSI | EL MEHDI ASSALI
We propose a method for predicting functional and chemical properties of soil samples with low cost and rapid analysis s using infrared spectroscopy. These properties will give us soil’s capacity to support essential ecosystem services such as primary productivity, nutrient and water retention, and resistance to soil erosion and will improve management of agricultural and natural resources. We propose also a recommendation system that will recommend to us the best plants that will grow well in each type of soil.