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1. 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 |
2. Performance agronomique et économique de différentes stratégies de gestion de la fertilité du sol sous culture de soja (Glycine max L. Merril) dans la zone littorale du Togo.Ce travail a pour objectif de valoriser les émondes de deux légumineuses arbustives et quelques fertilisants organiques pour améliorer la production du soja. Afin de parvenir à cet objectif, les paramètres comme la masse de mille graines, les rendements en gousses, en graines, en fanes du soja et autres ont été déterminés. L’étude a eu lieu à la Station d’Expérimentation Agronomique de Lomé (SEAL)... K.M. Amouzouvi, K.E. Ozou, L. Kolani, K.A. Amouzouvi, J.M. Sogbedji |
3. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture ApplicationsCurrently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto |
4. Implementing Field-Based High Throughput Plant Phenotyping: The Open Source Way... Y. Kassim |
5. Detecting the Impact of Hail Damage on Maize Crops in Smallholder Farms Using Unmanned Aerial Vehicles Derived Multispectral DataNatural disasters such as hailstorms are now frequent and negatively impact smallholder farmers' livelihoods. In these events, there is a need for robust and innovative techniques for monitoring the extent of their damage in smallholder croplands to optimise production. In this regard, this study sought to evaluate the utility of drone-derived multispectral data in estimating crop health elements (i.e., equivalent water thickness (EWT), chlorophyll content, and leaf area index (LAI) of maize... M. Sibanda |