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AfPCA Proceedings 2024

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MORIMOTO, E
Tsado, P.A
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Authors
Lawal, B
Adeboye, M.K
Tsado, P.A
MORIMOTO, E
LEE, J
NONAMI, K
MATUMURA, I
IKEBE, M
SATO, S
MORIMOTO, E
ARAI, Y
NONAMI, K
ITO, T
Topics
Precision Agriculture for Small Holders
Precision Agriculture for Field and Plantation Crops
Adoption of Precision Agriculture
Type
Oral
Year
2020
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Authors

Filter results3 paper(s) found.

1. Spatial variability and mapping of selected soil quality indicators for precision farming at a smallholding level in Minna, Nigeria

Smallholding farmers in Nigeria still practice blanket application of fertilizers, without giving consideration to spatial variations in soil properties across their fields. Understanding of spatial variability in soil properties is essential for precision farming, especially in this era of resource scarcity and high cost of fertilizers. This study was carried out to assess and map the spatial variability in selected soil quality indicators in a smallholder farm in Minna, North-central Nigeria,... B. Lawal, M.K. Adeboye, P.A. Tsado

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. 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