Proceedings
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| Filter results8 paper(s) found. |
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1. Prediction Of Cation Exchange Capacity Using Visible And Near Infrared SpectroscopyCation exchange capacity (CEC) of the soil is a measure of the soil ability to hold positively charged ions and is an important indicator of soil physicochemical characteristic. It is an important property for site specific management of soil nutrients in precision agriculture. The conventional analytical methods used for the determination of CEC are expensive, difficult and time consuming, because different cations must be extracted and determined. Visible and near infrared (vis-NIR) spectroscopy... Y. Ulusoy, Z. Tümsavas, A.M. Mouazen, Y. Tekin |
2. Toward More Precise Sugar Beet Management Based On Geostatistical Analysis Of Spatial Variabilty Within FieldsAbstract: Sugar beet (Beta vulgaris L.) yields in England are predicted to increase in the future, due to the advances in plant breeding and agronomic progress, but the intra-field variations in yield due to the variability in soil properties is considerable. This paper explores the within-field spatial variation in environmental variables and crop development during the growing season and their link to spatial variation in sugar beet yield.... A.J. Murdoch, S.A. Mahmood |
3. Remote Sensing-based Biomass Maps for an Efficient Use of FertilizersFor decades the main objective of farmers was to get the highest yields from their farmland. Nowadays, quality of agricultural products is becoming more and more important for the largest returns. In addition, the effects on our environment are also becoming important. These put increasing limitations on modern agriculture. So-called site-specific management can optimize the input of, for instance, nutrients and pesticides to the need of the plants. In this study, the objective was to study whether... J.G. P.w clevers, K.H. Wijnholds, J.N. Jukema |
4. Overview and Value of Digital Technologies for North American Soybean ProducersIn the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers. Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies. However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide. The objective of this... J. Lee, J. Fulton, K. Port, R. Colley iii |
5. Potential of UAS Multispectral Imagery for Predicting Yield Determining Physiological Parameters of CottonThe use of unmanned aerial systems (UAS) in precision agriculture has increased rapidly due to the availability of reliable, low-cost, and high-resolution sensors as well as advanced image processing software. Lint yield in cotton is the product of three physiological parameters: photosynthetically active radiation intercepted by canopy (IPAR), the efficiency of converting intercepted active radiation to biomass (RUE), and the ratio of economic yield to total dry matter (HI). The relationships... A. Pokhrel, S. Virk, J.L. Snider, G. Vellidis, V. Parkash |
6. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather DataNitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia |
7. Comparing Proximal and Remote Sensors for Variable Rate Nitrogen Management in CottonSensing and variable rate technology are becoming increasingly important in precision agriculture. These technologies utilize sensors to monitor crop growth and health, enabling informed decisions such as diagnosing nitrogen (N) stress and applying variable rates of N. Sensor-based solutions allow for customized N applications based on plant needs and environmental factors. This approach has led to notable reductions in N application rates, minimized N losses by improving N use efficiency (NUE),... A. Bhattarai, A. Jakhar, L. Bastos, G.J. Scarpin |
8. Multivariate Linear Regression Modeling for Predicting Chicken Body Weight Using Age, Uniformity, and Growth RateAccurate estimation of chicken body weight is critical for optimizing feed management, harvesting schedules, and animal welfare in commercial poultry systems. This study proposes a robust predictive framework using multivariate linear regression to estimate the average weight of native broiler chickens based on three explanatory variables: age, uniformity, and daily growth rate. After rigorous data cleaning and outlier removal, the model was trained and validated on 43 field observations collected... H. Lin |