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1. Precision Nitrogen Management Based on Nitrogen Removal in Rainfed WheatGrowers of hard red spring wheat may capture price premiums for maximizing the protein concentration of their grain. Nitrogen (N) nutrition adequacy is crucial to achieving high grain protein concentration. The objective of this study was to determine the usefulness of N removal maps by comparing grain protein, yields, and dollar returns obtained from this precision N management approach with that from conventional uniform N management. Strip plot experiments were designed to compare spatiall... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long |
2. Using Pricise Gps/gis Based Barley Yield Maps to Predict Site-specific Phosphorus RequirementsThree fundamental stages and technologies as main parts of a precision farming project should be considered precisely. These are access to actual multi- dimensional variability detail or variable description on farms, creating a suitable variable-rate technology, and finally providing a decision support system. Some results of a long term practical research conducted by the author in Upon-Tyne Newcastle University of UK for reliable yield monitoring and mapping were utilised to prepare this p... A. Sanaei |
3. Land Cover and Crop Types Classification Using Sentinel-2A Derived Vegetation Indices and an Artificial Neural NetworkDevelopments in remote sensing data acquisition capabilities, data processing and interpretation of ground-based, airborne and satellite observations have made it possible to couple remote sensing technologies and precision crop management systems. Land cover and crop types classification is a fundamental task in remote sensing and is crucial in various environmental and agricultural applications. Accurate and timely information on land cover and crop types is essential for land management, l... B. Bantchina |
4. Portable Soil EC - Development of an Electronic Device for Determining Soil Electrical ConductivityDecision-making in agriculture demands continuous monitoring, a factor that propels the advancement of tools within Agriculture 4.0. In this context, understanding soil characteristics is essential. Electrical conductivity (EC) sensors play a pivotal role in this comprehension. Given this backdrop, the core motivation of this research was developing an accessible and effective electronic device to measure the apparent EC of the soil. It provides features like geolocation, recording of the dat... C.L. Bazzi, L.A. Rauber, W.K. Oliveira, R. Sobjak, K. Schenatto, L. Gebler, L.M. Rabello |
5. Integrating Nonlinear Models and Remotely Sensed Data to Estimate Crop Cardinal DatesCrop planting and harvest dates are a major component affecting agricultural productivity, risk, and nutrient cycling. The ability to track these cardinal dates allows researchers to investigate strategies to manage risk and adapt to climate change. This study was conducted to determine whether nonlinear statistical models combined with remotely sensed data from satellites can be used to estimate planting and harvest dates. Time of planting and harvest were reported by farmers for 16 commerci... C.L. Dos santos, F. Miguez, L. Puntel, D. Bullock |
6. Delineation of Yield Zones Using Optical and Radar Remote SensingIdentifying yield zones in agricultural areas is essential for efficient resource allocation, operational optimization, and decision-making. While optical remote sensing is widely used in precision agriculture, the interest in radar remote sensing data, notably from the Sentinel-1 Synthetic Aperture Radar (SAR), has increased due to its operation in the C-band frequency, capturing data through cloud cover and the availability of free data. The main objective of this study was to evaluate ... I.A. Da cunha, H. Oldoni, D.D. Melo, L.R. Amaral |
7. Influence of Ground Control Points and Processing Parameters on UAS Image Mosaicking for Plant Height EstimationDigital surface models (DSMs) and 3D point clouds, generated using overlapping images from unmanned aircraft systems (UASs), are often used for plant height estimation in phenotyping and precision agriculture. This study examined the effects of the quantity and placement of ground control points (GCPs) and image processing parameters on the creation of DSMs and 3D point clouds for plant height estimation. A 2-ha field containing multiple experimental plots with four crops (corn, cotton, ... C. Yang, H. Zhao, W. Guo, J. Zhang, C. Suh, B.K. Fritz |
8. A Flexible Software Architecture for General Precision Agriculture Decision Support SystemsAgricultural data management is a complex problem. Both the data and the needs of the users are diverse. Given the complexity of the problem, it's easy to ascertain that a single solution will not be able to meet the needs of all users. This paper presents a software architecture designed to be extensible as well as flexible enough to provide agricultural management tools for a wide variety of users. The solution is based on a microservice architecture, which allows for the creation of ne... W. Neils, D. Mommen |
9. Dynamic Management Zones for Real-time Precision Agriculture OptimizationPrecision agriculture is an evolving management approach aimed at optimizing resource utilization, enhancing financial returns, and mitigating environmental impacts. The dynamic nature of agricultural conditions throughout a growing season necessitates the integration of innovative remote sensing and precision agriculture techniques. This research explores the creation of dynamic management zones (DMZ) that adapt in real-time to evolving soil and crop conditions. This study focuses on the est... A.H. Rabia, E. Eldeeb |
10. Comparative Analysis of Different On-the-go Soil Sensor SystemsThis study is part of the field of precision agriculture. This management mode is one of the great revolutions in the agriculture field, and it means better management of farm inputs such as fertilizers, herbicides, and seeds by applying the right amount at the right place and at the right time. To succeed in this, we should dispose of a tool that allows a precise assessment of the soil’s physical state. Thus, on-the-go soil sensors can be used as a creative tool to gain bette... H. Moulay, B. Arnall, S. Phillips |