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| Filter results9 paper(s) found. |
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1. Estimating greensnap yield damage with canopy reflectance: a case studyGrain 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 ScanningIn 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 PERSPECTIVESAfrica 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 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 |
5. QUANTIFICATION OF OPTIMAL FERTILIZERS DEMAND IN WHEAT AND CORN FIELDS IN MOROCCO USING VERY HIGH-RESOLUTION REMOTE SENSED IMAGERY AND HYBRID COMPUTATIONAL APPROACHESAbstract. 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. Monitoring irrigation water use at large scale irrigated areas using remote sensing in water scarce environmentIncreasing pressure on available water resources in semi-arid region will affect the availability of water for irrigated agriculture. In this context, adoption of innovative and cost-effective tools for water management and analysis of water use patterns in irrigated areas is required for an efficient and sustainable use of water resources. This study aims to evaluate a remote sensing-based approach which allows estimation of the temporal and spatial distribution of crop evapotranspiration... M. Kharrou, V. Simonneaux, M. Le page, S. Er-raki, G. Boulet, J. Ezzahar, S. Khabba, A. Chehbouni |
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 |
8. 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 |
9. Use of “FertiEdge” Application for Optimizing Wheat FertilizationWheat is a crop of global importance, and effective fertilization is crucial to maximize yield and quality. Traditional methods of fertilization often result in under- or over-application of nutrients, resulting in environmental problems and suboptimal crop yields. FertiEdge is a digital application that provides accurate fertilization recommendations based on real-time data, it’s an innovative tool designed to enhance the efficiency of wheat fertilization. This study evaluates its impact... I. Sbai, F. Sehbaoui, M. Hmimou |