Authors
| Filter results9 paper(s) found. |
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1. A Model For Wheat Yield Prediction Based On Real-time Monitoring Of Environmental Factors... B. Dumont, F. Vancutsem, J. Destain, B. Bodson, F. Lebeau, M. Destain |
2. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat YieldIn crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to predict... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont |
3. Evaluation of the Sensor Suite for Detection of Plant Water Stress in Orchard and Vineyard CropsA mobile sensor suite was developed and evaluated to predict plant water status by measuring the leaf temperature of nut trees and grapevines. It consists of an infrared thermometer to measure leaf temperature along with relevant ambient condition sensors to measure microclimatic variables in the vicinity of the leaf. Sensor suite was successfully evaluated in three crops (almonds, walnuts and grapevines) for both sunlit and shaded leaves. Stepwise linear regression models developed for shaded... R. Dhillon, V. Udompetaikul, F. Rojo, S. Upadhyaya, D. Slaughter, B. lampinen, K. Shackel |
4. Development And Evaluation Of A Leaf Monitoring System For Continuous Measurement Of Plant Water Status In Almond And Walnut CropsAbstract: Leaf temperature measurements using handheld infrared thermometers have been used to predict plant water stress by calculating crop water stress index (CWSI). However, for CWSI calculations it is recommended to measure canopy temperature of trees under saturated, stressed and current conditions simultaneously, which is not very practical while using handheld units. An inexpensive, easy to use sensing system was developed to predict plant water status for tree crops by measuring... F. Rojo, J. Roach, R. Coates, S. Upadhyaya, M. Delwiche, C. Han, R. Dhillon |
5. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont |
6. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut TreesA knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightbar... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo |
7. An Inexpensive Aerial Platform For Precise Remote Sensing Of Almond And Walnut Canopy TemperatureCurrent irrigation practices depend largely on imprecise applications of water over fields with varying degrees of heterogeneity. In most cases, the amount of water applied over a given field is determined by the amount the most water-stressed part of the field needs. This equates to over-watering most of the field in order to satisfy the needs of one part of the field. This approach not only wastes resources, but can have a detrimental effect on the value of that crop. A system to... K. Crawford, S. Upadhyaya, R. Dhillon, F. Rojo, J. Roach |
8. Management Zone-specific N Mineralization Rate Estimation in Unamended SoilSince nitrogen (N) mineralization from soil organic matter is governed by basic soil properties (soil organic matter content, pH, soil texture, …) that are known to exhibit strong in-field spatial variability, N mineralization is also expected to exhibit significant spatial variability at field scale. An ideal and efficient N recommendation for precision fertilization should therefore account for potential soil mineralizable N considering this spatial variability. Therefore, this study... F.Y. Ruma, M.A. Munnaf, S. De neve, A.M. Mouazen |
9. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean YieldClimate is one of the primary factors that affects agricultural production. Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effect... R. Dhillon, G. Takoo |