Proceedings
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| Filter results8 paper(s) found. |
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1. Nugis: The Development Of A Nutrient Use Geographic Information SystemNuGIS is a project of the International Plant Nutrition Institute (IPNI). The goal was to examine sources of nutrients (fertilizers and manure) and compare this to crop removal. The project used GIS and database analysis to create maps at the state and county level and then used GIS to migrate the budget analysis to the local watershed and regional watershed levels. This paper will cover the sources of data used, how the data was processed to generate county level numbers, and how GIS was used... Q. Rund, R. Williams |
2. Evaluating Leaf Fluorescence Sensor Dualex 4 For Estimating Rice Nitrogen Status In Northeast ChinaReal-time non-destructive diagnosis of crop nitrogen (N) status is crucially important for the success of in-season site-specific N management. Chlorophyll meter (CM) has been commonly used to non-destructively estimate crop leaf chlorophyll concentration, and indirectly estimate crop N status. Dualex 4 is a newly developed leaf fluorescence sensor that can estimate both leaf chlorophyll concentration and polyphenolics, especially flavonoids. When N is deficient, N stress can induce... W. Yu, Y. Miao, S. Hu, J. Shen, H. Wang |
3. North American Soil Test SummaryWith the assistance and cooperation of numerous private and public soil testing laboratories, the International Plant Nutrition Institute (IPNI) periodically summarizes soil test levels in North America (NA). Soil tests indicate the relative capacity of soil to provide nutrients to plants. Therefore, this summary can be viewed as an indicator of the nutrient supplying capacity or fertility of soils in NA. This is the eleventh summary completed by IPNI or its predecessor, the Potash &... Q. Rund, S. Murrell, A. Erbe, R. Williams, E. Williams |
4. Active Canopy Sensor-Based Precision Rice Management Strategy for Improving Grain Yield, Nitrogen and Water UseThe objective of this research was to develop an active crop sensor-based precision rice (Oryza sativa L.) management (PRM) strategy to improve rice yield, N and water use efficiencies and evaluate it against farmer’s rice management in Northeast China. Two field experiments were conducted from 2011 to 2013 in Jiansanjiang, Heilongjiang Province, China, involving four treatments and two varieties (Kongyu 131 and Longjing 21). The results indicated that PRM system significantly increased... J. Lu, H. Wang, Y. Miao |
5. Investigation of Automated Analysis of Snowmelt from Time-series Sentinel 2 Imagery to Inform Spatial Patterns of Spring Soil Moisture in the American Mountain WestVariable rate irrigation of crops is a promising approach for saving water whilst maintaining crop yields in the semi-arid American Mountain West – much of which is currently experiencing a mega drought. The first step in determining irrigation zones involves characterizing the patterns of spatial variation in soil moisture and determining if these are relatively stable temporally in relation to topographic features and soil texture. Characterizing variable rate irrigation zones is usually... I. Turner, R. Kerry, R. Jensen, E. Woolley, N. Hansen, B. Hopkins |
6. Cloud Correction of Sentinel-2 NDVI Using S2cloudless PackageOptical satellite-derived Normalized Difference Vegetation Index (NDVI) is by far the most commonly used vegetation index value for crop monitoring. However, it is quite sensitive to the cloud, and cloud shadows and significantly decreases its usability, especially in agricultural applications. Therefore, an accurate and reliable cloud correction method is mandatory for its effective application. To address this issue, we have developed an approach to correct the NDVI values of each and every... A. Saxena, M. Dash, A.P. Verma |
7. Robotic Arm Tomato Harvesting System and Next Best View Algorithm DevelopmentReplacing human labor with robots is a trend for future agriculture due to its efficiency and consistency. However, in automatic fruit harvesting tasks, leaf occlusion and the dynamic orientation of fruit make it difficult for robots to directly observe the picking point. To address this problem, this research focuses on tomato harvesting, and proposes a next-best-view (NBV) algorithm based on two main structures: “tomato pose prediction” and a “target-hit-gain function”.... P. Yen |
8. Null Dataset-Based Detection Enhances Robotic Vision in Greenhouse Cherry Tomato HarvestingCluttered cherry tomato greenhouse environments with visually similar distractors often trigger False Positives (FPs) in robotic vision, misguiding the robot’s motion and reducing harvesting success. We introduce a null-dataset strategy that integrates unannotated distractor images into YOLOv8l training, with their proportion tuned through loop refinement to suppress FPs while preserving precision. Optimal null proportions were identified as 12.3% for tomato detection and 8.3% for pedicel... P. Yen |