Download the Conference Proceedings
Proceedings
Authors
| Filter results7 paper(s) found. |
|---|
1. Using Site-Specific Management Zones for Potato Crop Management, East Nile Delta, EgyptThe field management zones (MZ) delineated using soil electrical conductivity (EC) and topographic parameters are the basis for site-specific crop management (SSCM). The objective of this paper was to delineation site-specific management zones of 155 feddans (67.2 ha) of a potato pivot field at East of Nile Delta, Egypt for use in smart farming based on spatial variability of soil and plant properties, yield and topographic attributes. The salinity measurement in the field... A.B. Belal, E.S. Mohamed, M.E. Jalhoum, M. zahran, M.A. Abdellatif, M.S. Emam, E.A. Hendway |
2. 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 |
3. Development of Lodging Direction Determination System Using Image ProcessingIn this study, image processing system was developed for application on rice plants to determine lodging condition, which was contributing factor to declining harvester efficiency by using combine harvester. Therefore, We developed a system for determination of the lodging direction by algorithm based on convolutional neural network (CNN). As for deep learning framework, Pytorch1.1.0 were used to train and test the judging direction. GoogLeNet was used as a pre-trained CNN model. Lodging... E. Morimoto, Y. Arai, K. Nonami, T. Ito |
4. Chlorophyll Meter Based Precision Nitrogen Management in Maize Grown in Alluvial Soil in EgyptPrecision nitrogen (N) management is essential for profitable crop production and to minimize N losses to the environment that are a consequence of an excessive N supply. Chlorophyll meter-based N management can help to achieve high N use efficiency, as aquick and non-destructive spectral characteristics of leaves, which can be used to diagnose plant N deficiency and graduate N fertilization with improve N use efficiency. Field experiments were conducted during two consecutive years, 2019 and... A. Soaud, S. Abou-zeid , A. Ali, D. Hassan |
5. 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 |
6. Performance of Remote Sensing Data and Machine Learning for Wheat Disease DetectionThe use of agrochemicals has many impacts on humans’ health and generates many environmental issues. However, a suitable management of agrochemicals inputs, such as insecticides, fungicides, and herbicides, is crucial to the success of wheat crops under climate change conditions. The use of remote sensing technologies in agriculture was raised within the technological evolution of materials and techniques during last decades. The development of new and cheap sensors has been the main reason... Y. Lebrini, A. Ayerdi-gotor |
7. Development of a Decision Support Tool to Derive Site-specific Nutrient Management Recommendations for Maize Production Using Machine LearningAgriculture is the main source of food and income for rural communities in developing countries, especially in Africa. Given current population growth, pressures on agricultural systems will continue to increase. Many countries have agricultural economies that are highly dependent on agricultural productivity. For example, several variables can influence fertilization for optimal grain yields. Quantifying the effects and relative importance of soil properties such as soil type, pH, Olsen-P, climate,... O. Ennaji, L. Vergutz, A. El allali |
