Proceedings
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| Filter results5 paper(s) found. |
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1. Closing Yield Gaps with GxExM and Precision AgricultureThere are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate. A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges. The yield gap –defined as the difference between current farmer yields and potential... C. Walthall, J. Hatfield, S. Schneider, M. Vigil |
2. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case StudyWhile on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson |
3. Development of a Crop Edge Line Detection Algorithm Using a Laser Scanner for an Autonomous Combine HarvesterThe high cost of real-time kinematic (RTK) differential GPS units required for autonomous guidance of agricultural machinery has limited their use in practical auto-guided systems especially applicable to small-sized farming conditions. A laser range finder (LRF) scanner system with a pan-tilt unit (PTU) has the ability to create a 3D profile of objects with a high level of accuracy by scanning their surroundings in a fan shape based on the time-of-flight measurement principle. This paper describes... C. Jeon, H. Kim, X. Han, H. Moon |
4. Weed Detection Among Crops by Convolutional Neural Networks with Sliding WindowsOne of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neural... K. Kantipudi, C. Lai, C. Min, R.C. Chiang |
5. Use of MLP Neural Networks for Sucrose Yield Prediction in SugarbeetINTRODUCTION Sugar beet is one of the more technified agro industries in Spain. In the last years, it has leaded as well the digital transformation with the objective of maintaining sugar beet competitivity both national and internationally. Among other lines, very high potential has been identified in determining the sucrose content using a combination of Artificial Intelligence and Remote Sensing. This work presents the conclusions of an extensive data acquisition task, creation of... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes |