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1. Estimating soil organic carbon from cell phone imagesSoil organic matter (SOM) is considered as the backbone of soil health and soil quality. Thus, its’ estimation is critical to support the development of management decision including precision agriculture. To overcome challenges of laborious, rather expensive and time-consuming laboratory measurements, recent advances in image acquisition systems provided a new dimension of image-based SOM prediction. However, challenges remain in using soil images taken directly in the field due to var... A. Biswas, Y. Fu, P. Taneja, S. Lin, P. Daggupati, H. Vasava |
2. Cashew Trees Detection and Yield Analysis using UAV-based MapIn this study we developed a novel method to detect cashew trees in an orthophoto map derived from images collected by an unmanned aerial vehicle (UAV). We also suggest a way in which these detections can be used to analyse the yield of the cashew farm. The proposed method uses images analysis to find the tops of trees, to merge different tops located on the same tree, and to segment individual tree. The segmented trees are used in a deep learning framework to know the exact location of cashe... T. Bayala, I. Ouattara, A. Visala, S. Malo |
3. REVISITING INLAND VALLEYS MANAGEMENT STANDARDS IN THE CONTEXT OF GLOBAL CHANGE IN WEST AFRICAConsidered as main alternative to the crisis of traditional production systems, inland valleys management pains more and more to fill expectations of West African’s farmers due to the inadequacy, in the current context of climate, agrarian and environmental change of the management standards applied to these ecosystems. One consequence of this inadequacy is the inefficient exploitation of the inland valleys with the results being the persistence of the food insecurity, environmental deg... A. Tidjani, P. Tovihoudji |
4. 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 reflecta... G. Dias paiao, T.J. Nigon, F.G. Fernández, C. Cummings, S.L. Naeve |
5. Spectral assessment of chickpea morpho-physiological traits from space, air and groundChickpea (Cicer arietinum) is an important grain legume in semi-arid regions and water-stress is a major constraint to its productivity. Area under chickpea cultivation is growing but climate change toward greater aridity results in higher precipitation instability and risks yields. The ability to assess water potential can support irrigation decisions. Thus, improved ability to spatially assess plants water status can promote more efficient irrigation. The cu... I. Herrmann, R. Sadeh, A. Avneri, Y. Tubul, R. Lati, S. Abbo, D.J. Bonfil, Z. Peleg |
6. Autonomous Hexacopter Spraying drones for plants protectionAbbes KAILIL1, Hassan BENAOUDA2, Abdelhakim MOHCINE3, 1 Eng. Doctor in aerospace engineering, Moroccan Industry Services & Engineering SARL, Morocco. 2 Eng. Doctor in Agriculture, INRA, Morocco. 3 Engineer in agriculture, ONCA, Morocco. Farming technologies have consi... H. Benaouda, A. Mohsine, A. Kailil |
7. An Open Source Multispectral Camera for Crop MonitoringPrecision agriculture is one of the most important economic issues of the 21st century because it will make it possible to respond to the new challenges of agriculture, which are population growth, global warming, global epidemics, and inflation, to name a few. Remote sensing makes it possible to monitor the plantation from a distance and makes it possible to know the level of growth and the state of health and hydration of the plants. This paper outlines an affordable and open-source multisp... H. Nardjes, M. Yagoubi |
8. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat LeavesThe assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium conte... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris |
9. 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 sens... M. Söderström, K. Persson |
10. 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 re... Y. Lebrini, A. Ayerdi-gotor |
11. Sqat: a Python Package for Soil Quality AssessmentSoil quality Assessment Tool (sqat) is an open-source python programming language package for researchers to facilitate carrying out soil quality assessment. The package provides the necessary modules required for soil and terrain indicators scoring and quality indexing. The package developed using Python programming language which currently is widely used for numerical problem solving and scientific data analyses. The package developed under the open-source principal where the programming co... A. Saleh |
12. Unmanned Aerial Vehicles (UAVs) for Phenotypic Traits Estimation & Yellow Rust Disease Severity Assessment in Small-scale Wheat Breeding Trials in EthiopiaRemote Sensing (RS) platforms; like the Unmanned Aerial Vehicles (UAVs) are recently gaining traction in agricultural data collection systems and used for various phenotyping of breeding field trials and capturing different biophysical, biochemical and sanitary traits which can be used to predict and explain the resulting yield and selecting better verities. Compared to the conventional phenotyping usually done by visual scoring and manual measurements which is time consuming/back breakings, ... T. Anberbir, G. Mamo , A. Dabi |
13. Photogrammetrically Assessed Smallholder Pineapple Fields in Ghana Using Small Unmanned Aircraft SystemsUltra-high-resolution imagery taken by small unmanned aircraft systems (sUAS, drones) has been proven beneficial for the monitoring of agricultural crops in conventional farming especially in the context of precision farming. For smallholder pineapple cultivation, the use of sUAS imagery is still sparsely evaluated. However, technical developments in low cost sUAS-sensor combinations make assessments of agricultural areas by service providers more and more affordable for Africa. In this study... M. Hobart, E. Anin-adjei, E. Hanyabui, G. Badu-marfo, M. Schirrmann, N. Schiller |
14. Utilizing Guards (Growing Universal Agronomic Research Data Standard) and the Fair Principles for Data Standardization and Agronomic InsightsThe quantity and scope of agronomic data available for researchers in both industry and academia is increasing rapidly. Data sources include a myriad of different streams, such as field experiments, sensors, climatic data, socioeconomic data or remote sensing. The lack of standards and workflows frequently leads agronomic data to be fragmented and siloed, hampering collaboration efforts within research labs, university departments, or research institutes. Researchers and businesses therefore ... S. Sela |
15. Application of Remote Sensing Technologies for Monitoring within Field Soil and Crop Growth Variability... N. Majozi |
16. A Comparative Estimation of Maize Leaf Moisture Content on Smallholder Farming Systems Using Unmanned Aerial Vehicle (UAV) Based Proximal Remote SensingUnderstanding maize moisture conditions is necessary for crop monitoring and developing early warning systems to optimise agricultural production in smallholder farms. Therefore, this study evaluated the utility of UAV derived multispectral imagery and machine learning techniques in estimating maize leaf moisture indicators; equivalent water thickness (EWT), fuel moisture content (FMC) and specific leaf area (SLA). The results illustrated that both NIR and red-edge derived spectral variables ... S. Ndlovu |