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| Filter results7 paper(s) found. |
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1. Maximisation de l’efficience d’utilisation de l’azote par la tomate(Solanum lycopersicum L.) sur les ferrasols au Sud du TogoMaximiser l'efficience d'utilisation de l'Azote (N) en culture de tomate s'impose pour améliorer le rendement et la rentabilité de la culture. Il a été mené sur trois ans, six cultures de tomate réparties sur deux périodes (septembre à janvier 2017-2019 et de février à mai 2018-2020) sur un sol ferralitique à la Station d'Expérimentations Agronomiques de Lomé suivant un dispositif expérimental... M. Lare, M.J. Sogbedji |
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. Methodology for Assessing Nutrient Status of Nigeria Croplands: AfSIS/NiSIS Pilot Project - Pathway for Precision Agriculture MappingInherently low soil fertility, nutrient imbalances and accelerating degradation constitute threats to precision agriculture (PA), agricultural productivity and ecosystem services in sub-Saharan Africa (Nigeria inclusive). Presently, the geographical extent of existing nutrient constraints, location specific trends and opportunities for managing these over time are highly uncertain. The AfSIS/NiSIS project assessment aims to provide spatially explicit observations, measurements and predictions... V. Aduramigba-modupe, I. Amapu, M. Walsh, B. Scott |
4. Mapping African soils at 30m resolution - iSDAsoil - Western Time Zones“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty. iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry... J. Crouch, K. Shephard, M. Miller, J. Collinson, P. Singh, P. Pypers, R. Van den bosch, C. Van beek, M. Chernet, S. Aston |
5. Mapping African soils at 30m resolution - iSDAsoil - Eastern Time Zones“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty. iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry... C. Van beek, M. Chernet, S. Aston, M. Miller, J. Collinson, K. Shephard, J. Crouch, T. Terhoeven-urselmans |
6. Performance of Remote Sensing Data and Machine Learning for Wheat Disease DetectionThe use of agrochemicals has many impacts on humans’ health and generates many environmental issues. However, a suitable management of agrochemicals inputs, such as insecticides, fungicides, and herbicides, is crucial to the success of wheat crops under climate change conditions. The use of remote sensing technologies in agriculture was raised within the technological evolution of materials and techniques during last decades. The development of new and cheap sensors has been the main reason... Y. Lebrini, A. Ayerdi-gotor |
7. 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 |