Download the Conference Proceedings
Proceedings
Authors
Filter results4 paper(s) found. |
---|
1. Soil fertility mapping of Dry savannah zone of TogoIncreasing agricultural productivity and therefore the production requires a good knowledge of the soil fertility status and a sustainable nutrients management. The objective of this study is to map spatial distribution of some selected soil fertility parameters in the dry savannah agro-ecological zone that covers the regions of Savanes and Kara in Togo. Soil fertility parameters such as pH, available phosphorus (P), exchangeable potassium (K) and organic matter were determined in soil samples... K.K. Ganyo, K.A. Ablede , K. Koudjega, S. Ani, K. Afawoubo, D.A. Anoumou, A.T. Mensah, E. Assih-faram, M. Tchalla-kpondji, K. Kpemoua, Y. Lombo |
2. A geostatistical approach to define a soil fertility index based on the main soil macronutrientsSoil fertility is greatly affected by main soil macronutrients such as nitrogen (N), phosphorus (P), and potassium (K). These macronutrients can be used to define a synthetic fertility index to support soil fertilization. The study was aimed to propose a geostatistical approach to define a synthetic fertility index based on factorial cokriging. It consists in quantifying and reducing the spatial variability of multivariate data to only a few factors, related to different spatial scales. Such factors... H. Aboelkhier, A. Nasrallah, S. Shaddad, G. Buttafuoco |
3. Modelling Fertigation and Micro-Climate Parameters for Greenhouse Tomato (Solanum Lycopersicum L.)Amidst the hiking price of fertilizer and projected water scarcity across the world, it is imperative to explore the interaction between fertilizer, irrigation and genotype notwithstanding the micro-climate parameters so as to maximize yield while protecting the environment. The Decision Support System for Agrotechnology Transfer (DSSAT) is a model which employs all these input factors to help predict yield and thereby make an informed decision. The study sort to calibrate and validate the... Y.K. Agbemabiese, P. Abubakari, P.K. Dzomeku, I. Shaibu |
4. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear RegressionTraditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud |