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AfPCA Proceedings 2024

Proceedings

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Nyawasha, R
NONAMI, K
Ennaji, O
Laamrani, A
Naeve, S.L
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Authors
Dias Paiao, G
Nigon, T.J
Fernández, F.G
Cummings, C
Naeve, S.L
MORIMOTO, E
LEE, J
NONAMI, K
MATUMURA, I
IKEBE, M
SATO, S
Hmimou, M
Laamrani, A
Sehbaoui, F
Chehbouni, A
Khabba, S
Dhiba, D
MORIMOTO, E
ARAI, Y
NONAMI, K
ITO, T
Misbah, K
Laamrani, A
Chehbouni , A
Dhiba , D
Ezzahar, J
Khechba, K
Ennaji, O
Vergutz, L
El Allali, A
choukri, M
Laamrani , A
simonneaux , V
Gerard , B
Belaqziz, S
Chehbouni, A
misbah, K
Mcnairn, H
Topics
Proximal and Remote Sensing
Precision Agriculture for Field and Plantation Crops
Precision Nutrient Management
Adoption of Precision Agriculture
Precision Nutrient Management
Mapping and Geostatistics
Type
Oral
Poster
Year
2020
2022
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Authors

Filter results7 paper(s) found.

1. Estimating greensnap yield damage with canopy reflectance: a case study

Grain yield reduction caused by storm-induced plant breakage (green snap) occurs often in corn fields. With climate change and an increasing frequency in the occurrence of extreme weather events, it is essential to develop methods that can accurately estimate green snap damage, so growers can be properly compensated by insurance companies for yield loss.  Because plant breakage also affects crop canopy reflectance, this case study aimed to characterize the changes in crop canopy reflectance... G. Dias paiao, T.J. Nigon, F.G. Fernández, C. Cummings, S.L. Naeve

2. Development of Canopy Mapping System of Asian pears (Pyrus pyrifolia Naka) Using Terrestrial Laser Scanning

In this paper, the canopy mapping system (CMS) of Asian pears for estimating yield during Bud thinning and Pruning operations using point cloud data was proposed. Bud thinning and Pruning in Asian pear (Pyrus pyrifolia Naka) is necessary to ensure quality and yield but is time-consuming and heavily depends on work knowledge. This study described a method of estimating the number of fruits through the length of a branch based on remote sensing. The CMS would be useful to support more efficient... E. Morimoto, J. Lee, K. Nonami, I. Matumura, M. Ikebe, S. Sato

3. MAPPING AND ASSESSING AFRICAN SOILS FERTILITY USING HIGH-RESOLUTION REMOTE SENSING AND MACHINE LEARNING APPROACHES: STATE-OF-THE-ART AND PERSPECTIVES

Africa is far from exploiting its true agricultural potential. United Nations Food and Agriculture Organization (FAO) indicates that the continent has 60% of non-cultivated lands worldwide. While soil fertility is well highlighted as one of the major limiting factors, only limited information is available on soil nutrient contents and nutrient availability in the African soils. Soil fertility of agricultural fields is related to many physical and chemical properties, such as texture, organic matter... M. Hmimou, A. Laamrani, F. Sehbaoui, A. Chehbouni, S. Khabba, D. Dhiba

4. Development of Lodging Direction Determination System Using Image Processing

In 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

5. QUANTIFICATION OF OPTIMAL FERTILIZERS DEMAND IN WHEAT AND CORN FIELDS IN MOROCCO USING VERY HIGH-RESOLUTION REMOTE SENSED IMAGERY AND HYBRID COMPUTATIONAL APPROACHES

Abstract. 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

6. Development of a Decision Support Tool to Derive Site-specific Nutrient Management Recommendations for Maize Production Using Machine Learning​

Agriculture 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

7. Use of Earth Observation Imagery, Advanced Modelling Algorithms and Other Monitoring Systems to Produce Operational Agricultural Annual Crop Inventories for Morocco.

African farmers are facing the challenges of a changing climate, increased temperatures, changes in rainfall patterns, more frequent extreme weather events and reductions in water availability. The digital transformation of the agricultural sector is one of the opportunities that can promote good practices of the African agricultural through  the sharing of information and tools for decision-making, thereby, boost economic growth of our African country. The shift to digital technologies is... M. Choukri, A. Laamrani , V. simonneaux , B. Gerard , S. Belaqziz, A. Chehbouni, K. Misbah, H. Mcnairn