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| Filter results9 paper(s) found. |
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1. SPOT5 Multispectral Data Potentialities To Monitor Potato Crop Nitrogen Status At Specific Field ScaleThe many challenges facing European agriculture and farm of tomorrow are such that they increasingly require the setting up of Decision Support Systems (DSS) that favour integrated crop management at farm or regional level. A valuable DSS for management of split fertilizer N applications was developed in Belgium for potato crop. It combines total N recommendation based on field predictive balance-sheet method along with Crop Nitrogen Status (CNS) monitoring through hand-held chlorophyll meter... J. Goffart, A. Leonard, D. Buffet, P. Defourny, L. Van den wyngaert |
2. 3D Acquisition System Applied to Agronomic ScenesTo enable a better decision making by the farmer in order to optimize the crop management, it is essential to provide a set of information on basic parameters of the crops. These information are numerous and the image processing is increasingly used for disease detection, weed detection or yield estimation. We will focus initially on assessing the yield of a wheat crop in automatic way. This yield is directly related to the number of ears per square meter for which the counting is currently... F. Cointault, P. Gouton, B. Billiot |
3. Potential Indicators Based On Leaf Flavonoids Content for the Evaluation of Potato Crop Nitrogen StatusNitrogen (N) fertilization strategies aim to limit environmental pollution by improving potato crop N use efficiency. Such strategies may use indicators for the assessment of in season crop N status (CNS). Leaf polyphenolics (flavonoids) content appears as a valuable indicator of CNS. Because of their absorption features in... J. Goffart, F. Ben abdallah |
4. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine VisionHand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten |
5. High Resolution Vegetation Mapping with a Novel Compact Hyperspectral Camera SystemThe COSI-system is a novel compact hyperspectral imaging solution designed for small remotely piloted aircraft systems (RPAS). It is designed to supply accurate action and information maps related to the crop status and health for precision agricultural applications. The COSI-Cam makes use of a thin film hyperspectral filter technology which is deposited onto an image sensor chip resulting in a compact and lightweight instrument design. This paper reports on the agricultural monitoring... B. Delauré, P. Baeck, J. Blommaert, S. Delalieux, S. Livens, A. Sima, M. Boonen, J. Goffart, G. Jacquemin, D. Nuyttens |
6. Economics of Gps-enabled Navigation TechnologiesTo address the economic feasibility of global positioning system (GPS) enabled navigation technologies including automated guidance and lightbar, a linear programming model was formulated using data from Midwestern U.S. Corn Belt farms. Five scenarios were compared: (i) a baseline scenario with foam, disk or other visual marker reference, (ii) lightbar navigation with basic GPS availability (+/-3 dm accuracy), (iii) lightbar with satellite subscription correction GPS (+/-1 dm), (iv) automated... T.W. Griffin, D.M. Lambert, J. Lowenberg-deboer |
7. Evaluating Spatial Effects Induced by Alternative On- Farm Trial Experimental Designs with Cross-regressive Variables Using Monte Carlo MethodsThe goal of this research was to adapt spatial regression methods to on-farm trials in a farm management context. Different experimental designs and statistical analysis methods are tested with site-specific data under a range of spatial autocorrelation levels using Monte Carlo simulation techniques. Simulations indicated that data usable for farm management decision making could be gathered from limited replication experimental designs if that data were analyzed with the appropriate spatial statistical... T.W. Griffin, R.J. G.m. florax, J. Lowenberg-deboer |
8. Predicting Soybean Yield Using Remote Sensing and a Machine Learning ModelSoybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore |
9. Optimizing Soil Nutrient Management: Agricultural Policy/environmental Extender (APEX) Model Simulation for Field Scale Phosphorous Loss Reduction in VirginiaManaging soil nutrients is crucial for enhancing crop productivity and meeting consumptions demands while minimizing environmental impacts. Sustainable agriculture relies on well-planned soil nutrient management strategies. Phosphorous (P) stands out among the 16 essential soil nutrients, particularly in Virginia, where natural P levels are typically low. Adequate amount of P is necessary for the early root formation and plant growth. However, excess amount of P in the soil leads to increase the... S. Kumari, J. Rathore, S. Mitra, M. Gardezi, O. Walsh |