Proceedings
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| Filter results13 paper(s) found. |
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1. A Comparison Of Conventional And Sensor-based Lime Requirement MapsSuccessful variable-rate applications of agricultural inputs, such as lime, rely on quality of input data. Systematic soil sampling is... A.K. Jonjak, V.I. Adamchuk, C.S. Wortmann, C.A. Shapiro, R.B. Fergugson |
2. Attaching Multiple Conductivity Meters To An Atv To Speed Up Precision Agriculture Soil SurveysGround conductivity meters are used in a number of precision agriculture applications, including the estimation of water content, nutrient levels, salinity and depth of topsoil. Typically the Geonics EM38 conductivity meter, and to a lesser extent the EM31, are used for soil surveys. Most conductivity surveys involve towing a ground conductivity meter behind an all-terrain vehicle (ATV). In some situations, such as rutted or sloping fields, it is preferable to mount the conductivity meter directly... E. Morris, A. Clarke, S. Sunley, C. Hill, G. Cranfield |
3. Measuring And Mapping Sugarcane GapsSugarcane is an important crop in tropical regions of the world and especially for Brazil, the largest sugar supplier in the market, also running a domestic fleet of flex-fuel driven vehicles based on ethanol. Site specific production management can impact sugarcane production by increasing yield and reducing cost. Sugarcane fields are planted each five years, in average, and an important parameter that is measured after the planting operation is the gaps caused by problems during planting... J.P. Veiga, D.S. Cavalcante, J.P. Molin |
4. Monitoring Ratio Of Leaf Carbon To Nitrogen In Winter Wheat Based On Hyperspectral MeasurementsThe metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production. Leaf is the major organ of plant photosynthesis and physiological activity, and in leaf tissues the ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), can... X. Xu |
5. Helvis - a Small-scale Agricultural Mobile Robot Prototype for Precision AgricultureThe use of agricultural robots is emerging in a complex scenario where it is necessary to produce more food to feed a crescent population, decrease production costs, fight plagues and diseases, and preserve nature. Around the world, there are many research institutes and companies trying to apply mobile robotics techniques in agricultural fields. Mostly, large prototypes are being used and their shapes and dimensions are very similar to tractors and trucks. In the present study, a small-scale... M. Becker, A.E. Velasquez, H.B. Guerrero, V.A. Higuti, D.M. Milori, D.V. Magalhães |
6. Simulation of Curiosity and Exo Mars Rovers on Agriculture TerrainImproving agricultural productivity is one of the biggest challenges Agriculture and Engineering face. A possible solution is the creation of soil databases and/or maps to apply precision agriculture techniques, aiming to produce more in the same land, using less agricultural supplies. This practice may be developed with the help of rovers applied to e.g. agricultural data collect, mapping, scouting and supply tasks. However, the rover needs to move and adapt to the terrain to obtain a real appropriate... J.F. Archila-diaz, M. Becker |
7. Design of VAV System of Air Assisted Sprayer in Orchard and Experimental Study in ChinaOne type of new automatic target detecting based on size of canopy with variable chemical dosage and air-flow of fan orchard sprayer was designed and developed to meet the demand of chemical pest control in orchards. Canopy parameter data scanned by infrared sensors and LIDAR (Light Detection and Ranging) were used to detect the target and to design spraying algorithm and PWM (Pulse Width Modulation) control system. Four integrated five-finger atomizers were equipped on each side of sprayer, independent... H. Xiongkui, L. Longlong, S. Jianli, Z. Aijun, L. Yajia |
8. Optical High-Resolution Camera System with Computer Vision Software for Recognizing Insects, Fruit on Trees, Growth of CropsWith the inspiration of helping the farmer to grow his crop in the optimal way, Pessl Instruments GmbH, from Weiz, Austria, developed optical high-resolution camera system, together with a computer vision software which is able to recognize insects, fruits on trees and growth of crop. Pessl Instruments develops decision support system which is consisting from remote monitoring of insect traps and remote monitoring of fields and crops. Optical high-resolution camera system can be installed on the... J. Potrpin, G. Pessl, D. Najvirt, C. Pilz |
9. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course FairwaysTurfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received less... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky |
10. Predicting, Mapping, and Understanding the Drivers of Grain Protein Content Variability – Utilising John Deere’s New Harvestlab 3000 Grain Sensing SystemGrain protein content (GPC) is a key determinant of the prices that grain growers receive, and the rising cost of production is shifting management focus towards optimising this to maximise return on investment. In 2023, John Deere released the HarvestLab 3000TM Grain Sensing system in Australia for real-time, on-the-go measurement of protein, starch, and oil values for wheat, barley, and canola. However, while the uptake of these sensors is increasing, GPC maps are not available for... M.J. Tilse, P. Filippi, T. Bishop |
11. Are Pulses Really More Variable Than Cereals? a Country-wide Analysis of Within-field VariabilityIn Australia, pulses are underutilised by growers relative to cereal crops. There is significant global interest in growing pulses to provide more plant protein, and they also provide a string of agronomic and environmental benefits, such as their ability to fix nitrogen, and provide a pest and disease break for cereal crops. Many studies attribute this underutilisation to pulses exhibiting greater within-field yield variability than cereals. However, this has never been comprehensively examined... P. Filippi, T. Bishop, D. Al-shammari, T. Mcpherson |
12. Comparison of NDVI Values at Different Phenological Stages of Winter Wheat (Triticum Aestivum L.)The main objective of this study is to monitor, detect and quantify the presence of live green vegetation with the MicaSense RedEdge-MX Dual Camera System (MS) mounted on a DJI Matrice 210 V2 and GreenSeeker HCS 250 (GS) in winter wheat (Triticum aestivum L.) by using Normalized Difference Vegetation Index (NDVI). Surveys were conducted in the North-Western part of Hungary, in Mosonmagyaróvár on six different dates. A small-scale field trial in winter wheat was constructed as a randomized... S. Zsebő, G. Kukorelli, V. Vona, L. Bede, D. Stencinger, A. Kovacs, G. Milics, I.M. Kulmany, B. Horváth, G. Hegedűs, J.A. Abdinoor |
13. On Data-driven Crop Yield Modelling, Predicting, and Forecasting and the Common Flaws in Published StudiesThere has been a recent surge in the number of studies that aim to model crop yield using data-driven approaches. This has largely come about due to the increasing amounts of remote sensing (e.g. satellite imagery) and precision agriculture data available (e.g. high-resolution crop yield monitor data), and abundance of machine learning modelling approaches. This is a particular problem in the field of Precision Agriculture, where many studies will take a crop yield map (or a small number), create... P. Filippi, T. Bishop, S. Han, I. Rund |