Download the Conference Proceedings
Proceedings
Authors
| Filter results3 paper(s) found. |
|---|
1. QUANTIFICATION OF OPTIMAL FERTILIZERS DEMAND IN WHEAT AND CORN FIELDS IN MOROCCO USING VERY HIGH-RESOLUTION REMOTE SENSED IMAGERY AND HYBRID COMPUTATIONAL APPROACHESAbstract. Demand on agricultural products is increasing as population continues to grow. Data driven management of macronutrients (i.e., nitrogen (N), phosphorus (P) and potassium (K)) and crops are of critical prominence to get the most out of soil in terms of crop yield while preserving environment. This study aims to establish a quantitative framework for macronutrient (i.e., nitrogen, phosphorus, and potassium) status (i.e., excess, deficiency) for winter wheat (Triticum aestivum... K. Misbah, A. Laamrani, A. Chehbouni , D. Dhiba , J. Ezzahar, K. Khechba |
2. Analysis, design and development of a web and mobile application for fertilizer olive orchards recommendationsFarmer’s fertilization practices (FFP) in olive intensive or super intensive orchards must be improved to a better control of fertilization costs, to increase olive yielding, to maintain soil fertility and to avoid environment pollution. Indeed, a large category of fertilizer users apply fertilizers arbitrary (66%) without any knowledge about the adequate nutrient requirements of a such planting system. To improve the FFP in intensive and super intensive olive orchards, and in the frame... A. Larbi, H. Boulal, H. El arbi, W. Ben hamouda |
3. Proximal Soil Sensing Combined with Machine Learning for Estimation and Management of Soil Potassium Site SpecificallyHigh-resolution data on soil potassium (K) is crucial to optimize variable rate potassium fertiliser recommendations and improve crop growth and yield. The portable X-ray fluorescence (PXRF) and portable gamma-ray spectroscopy (PGRS) enable onsite soil K analysis. However, using PXRF and PGRS often remains cumbersome, following the soil matrix's poor performance and complex nature, introducing background noise. The potential of spectral analysis based on machine learning (ML) combined with... S. Nawar |