Proceedings
Authors
| Filter results5 paper(s) found. |
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1. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs |
2. Studies on Soil Spatial Variability and Its Impact on Cane Yield Under Precision Nutrient Management SystemIn present investigation an attempt was made to quantify the soil variability of 30 grids of 10 m x 10 m dimension at research farm of Nandi Sahakari Sakkare Karkhane (NSSK), Krishna Nagar, District. Bijapur. Each grid (10 m x 10 m) showed variation with available nitrogen as low as 140 kg ha-1 to as high as 245 kg/ha with a range of 105 kg/ha, phosphorus as low as 53 kg P2O5 ha-1 and as high as 89.3 kg P2O5 ha-1 with... M. Kumar r, M. Kumar r, D. Nadagouda |
3. An Efficient Data Warehouse for Crop Yield PredictionNowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-processed... V.M. Ngo, N. Le-khac, M. Kechadi |
4. 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 |
5. Smartflow: Ai Optimization of Desalination for Sustainable Agricultural Water ManagementLimited access to reliable freshwater sources is a persistent barrier to agricultural productivity, particularly in coastal and arid regions where rivers, lakes, and groundwater reserves are rapidly declining. Farmers in these areas often struggle to meet irrigation demands, resulting in reduced yields and heightened vulnerability to climate variability. Although seawater desalination provides a potential alternative, conventional reverse osmosis (RO) systems are typically too energy-intensive... M. Jamaludin |