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Fassinou Hotegni, N.V

Belal, A.A

Persson, K

ITO, T

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Authors

MORIMOTO, E

ARAI, Y

NONAMI, K

ITO, T

Söderström, M

Persson, K

Fassinou Hotegni, N.V

Godonou, Y.L

Gnanglè, L.M

Coulibaly, O.N

Achigan-Dako, E.G

Amin, M.E

Abdelfattah, M.A

Mohamed, E.S

Belal, A.A

Nabil, M

Mahmoud, A.G

Topics

Adoption of Precision Agriculture

Proximal and Remote Sensing

Adoption of Precision Agriculture

Precision Planting/Harvesting

Type

Oral

Poster

Year

2020

2022

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Filter results4 paper(s) found.
1. 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 Download paper
2. From Drone to Satellite – Does It Work? Multispectral drone-sensors are useful for detailed studies of crop characteristics in field trials, e.g. to create prediction models on nitrogen (N) uptake, or even estimates of optimal N rate to apply. To enable wide application of such models, they may be applied in satellite image-based decision support systems for farmers. However, successful transfer of models based on spectral data from one platform to another, requires strong and stable correlation between data from the different sensors.... M. Söderström, K. Persson Download paper
3. Engaging Stakeholders in Precision Agriculture Toolbox Conception: Case of Cowpea Atlas Platform Establishment in Benin Republic Cowpea [(Vigna Unguiculata (L.) Walpers] is among the most preferred and consumed legumes in West Africa and grown by many smallholder farmers. The crop has huge potential, is easy to grow and constitute a source of income of many actors involved in different value chains. Unfortunately, despite many interventions which aimed at promoting the crop in West Africa mainly Benin, areas under cowpea crop decrease over the years along with the loss of cowpea-based products. Such problem is... N.V. Fassinou hotegni, Y.L. Godonou, L.M. Gnanglè, O.N. Coulibaly, E.G. Achigan-dako
4. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear Regression Traditional 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

Filter results4 paper(s) found.

1. 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

Download paper

2. From Drone to Satellite – Does It Work?

Multispectral drone-sensors are useful for detailed studies of crop characteristics in field trials, e.g. to create prediction models on nitrogen (N) uptake, or even estimates of optimal N rate to apply. To enable wide application of such models, they may be applied in satellite image-based decision support systems for farmers. However, successful transfer of models based on spectral data from one platform to another, requires strong and stable correlation between data from the different sensors.... M. Söderström, K. Persson

Download paper

3. Engaging Stakeholders in Precision Agriculture Toolbox Conception: Case of Cowpea Atlas Platform Establishment in Benin Republic

Cowpea [(Vigna Unguiculata (L.) Walpers] is among the most preferred and consumed legumes in West Africa and grown by many smallholder farmers. The crop has huge potential, is easy to grow and constitute a source of income of many actors involved in different value chains. Unfortunately, despite many interventions which aimed at promoting the crop in West Africa mainly Benin, areas under cowpea crop decrease over the years along with the loss of cowpea-based products. Such problem is... N.V. Fassinou hotegni, Y.L. Godonou, L.M. Gnanglè, O.N. Coulibaly, E.G. Achigan-dako

4. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear Regression

Traditional 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