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| Filter results14 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. Estimating Spatial Variation In Annual Pasture YieldYield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers. Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett |
3. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial InformationFarmland quality represents various properties, including two parts of natural influencing factors and social influencing factors. The natural factors and social factors are interrelated and interaction, which determine the developing direction of farmland system. In order to overcome the limitation of subjective factors and fuzzy incompatible information, a more scientific evaluation method of farmland quality should be developed to reflect the essential characteristic of farmland.... Y. Dong, Y. Wang, X. Song, X. Gu |
4. Planet Labs' Monitoring Solution in Support of Precision Agriculture PracticesSatellite imagery is particularly useful for efficiently monitoring very large areas and providing regular feedback on the status and productivity of agricultural fields. These data are now widely used in precision farming; however, many challenges to making optimal use of this technology remain, such as easy access to data, management and exploitation of large datasets with deep time series, and sharing of the data and derived analytics with users. Providing satellite imagery through a cloud... K.J. Frotscher, R. Schacht, L. Smith, E. Zillmann |
5. Identifying Critical Landscape Areas for Precision Conservation in the Minnesota River BasinThe Minnesota River Basin generates a disproportionately high amount of total suspended sediments to the Upper Mississippi River Basin. Many reaches in the Minnesota River Basin have impaired water quality due to turbidity. Critical landscapes can be divided into depressional areas, riparian areas, highly erodible lands, and areas susceptible to ephemeral gullies or ravines. Geographic Information Systems (GIS) were utilized, and terrain analysis was conducted using digital elevation models in... J. Galzki, J. Nelson, D. Mulla |
6. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter WheatNitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng |
7. Mapping Leaf Area Index of Maize in Tasseling Stage Based on Beer-Lambert Law and Landsat-8 ImageLeaf area index (LAI) is one of the important structural parameters of crop population, which could be used to monitor the variety of crop canopy structure and analyze photosynthesis rate. Mapping leaf area index of maize in a large scale by using remote sensing technology is very important for management of fertilizer and water, monitoring growth change and predicting yield. The Beer-Lambert law has been preliminarily applied to develop inversion model of crop LAI, and has achieved good application... X. Gu, S. Wang, G. Yang, X. Xu |
8. Design of Ground Surface Sensing Using RADARGround sensing is the key task in harvesting head control system. Real time sensing of field topography under vegetation canopy is very challenging task in wild blueberry cropping system. This paper presents the design of an ultra-wide band RADAR sensing, scanning device to recognize the soil surface level under the canopy structure. Requirements for software and hardware were considered to determine the usability of the ultra-wide band RADAR system.An automated head elevation... M.M. Mohamed, Q. Zaman, T. Esau, A. Farooque |
9. Development of a Granular Herbicide Spot Applicator for Management of Hair Fescue (Festuca Filiformis) in Wild Blueberry (Vaccinium Angustifolium)Hair fescue has quickly become the pest of greatest concern for the wild blueberry industry. This is largely due to its ability to outcompete wild blueberry for critical resources including water, nutrients and most importantly space. In Nova Scotia, between 2001 and 2019, hair fescue had increased in field frequency from 7% to 68% and in field uniformity from 1.4% to 25%. This rapidly spreading and economically destructive weed is likewise a significant challenge to manage, with only a single... C. Maceachern, T. Esau, Q. Zaman |
10. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild BlueberryDeep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White |
11. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, CanadaSoil water characteristics curve (SWCC), for Prince Edward Island (PEI), is much more needed currently for the sustainable production of agriculture yields. It will not only fulfil the requirements of the province’s farmers for irrigation scheduling but also help the government to decide about permitting the use of groundwater for supplemental irrigation on the island. A soil water characteristics curve in PEI does not exist to support precision agriculture practices. Precision irrigation... S.J. Cheema, A.A. Farooque, F. Abbas, T. Esau, K. Grewal |
12. Suitability of ML Algorithms to Predict Wild Blueberry Harvesting LossesThe production of wild blueberries (Vaccinium angustifolium.) is contributing 112.2 million dollars to the Canada’s revenue which can be further increased through controlling harvest losses. A precise prediction of blueberry harvesting losses is necessary to mitigate such losses. In this study, the performance of three machine learning (ML) models was evaluated to predict the wild blueberry harvest losses on the ground. The data from four commercial fields in Atlantic Canada were... H. Khan, T. Esau, A. Farooque, F. Abbas |
13. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV ImageryGoss Wilt has become a common disease in corn fields in North Dakota. It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew |
14. Limitations of Yield Monitor Data to Support Field-scale ResearchPrecision agriculture adoption on farms continues to grow globally on farms. Today, yield monitors have become standard technologies on grain, cotton and sugarcane harvesters. In recent years, we have seen industry and even academics leveraging the adoption of precision agriculture technologies to conduct field-scale, on-farm research. Industry has been a primary driver of the increase in on-farm research globally through the development of software to support on-farm research. ... J.P. Fulton, S.A. Shearer, A. Gauci, A. Lindsey, D. Barker, E. Hawkins |