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Montoya Sevilla, F
Ikpi, A
March, M
Moon, H
Mulla, D
Igwe, K.E
Moon, J
Martin, R
Ma, W
Farooque, A.A
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Authors
Nigon, T.J
Rosen, C
Mulla, D
Cohen, Y
Alchanatis, V
Rud, R
Cohen, Y
Alchanatis, V
Heuer, B
Lemcoff, H
Sprintsin, M
Rosen, C
Mulla, D
Nigon, T
Dar, Z
Cohen, A
Levi, A
Brikman, R
Markovits, T
Rud, R
Ma, W
Zhao, C
Zaman, Q.U
Zach, D
Ma, W
Wang, X
Moon, J
Kim, S
Lee, J
Yang, W
Kim, D
Mulla, D
Zermas, D
Kaiser, D
Bazakos, M
Papanikolopoulos, N
Stanitsas, P
Morellas, V
Mulla, D
Laacouri, A
Kaiser, D
Jeon, C
Kim, H
Han, X
Moon, H
Brockgreitens, J
Bui, M
Abbas, A
Mulla, D
Olayide, O
Alene, A
Ikpi, A
Nziguheba, G
Alabi, T
Nigon, T
Mulla, D
Yang, C
Laacouri, A
Nigon, T
Mulla, D
Yang, C
Laamrani, A
Berg, A
March, M
McLaren, A
Martin, R
Bohman, B
Mulla, D
Rosen, C
Esau, T.J
Farooque, A.A
Abbas, F
Hennessy, P.J
Esau, T.J
Schumann, A.W
Farooque, A.A
Zaman, Q.U
White, S.N
Igwe, K.E
Onyekwelu, I
Sharda, V
Sánchez Virosta, Ã
Gómez-Candón, D
Montoya Sevilla, F
Pérez García, Y
Jiménez Castaño, V
González Piqueras, J
López-Urrea, R
Sánchez Tomás, J
Topics
Remote Sensing Applications in Precision Agriculture
Precision Horticulture
Precision Crop Protection
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Unmanned Aerial Systems
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Spatial and Temporal Variability in Crop, Soil and Natural Resources
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Applications of Unmanned Aerial Systems
Precision Horticulture
Big Data, Data Mining and Deep Learning
Decision Support Systems
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results18 paper(s) found.

1. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management

... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud

2. Evaluating Water Status in Potato Fields Using Combined Information from RGB and Thermal Aerial Images

Potato yield and quality are highly dependent on an adequate supply of water. In this study the combined information from RGB and thermal aerial images to evaluate... Y. Cohen, V. Alchanatis, B. Heuer, H. Lemcoff, M. Sprintsin, C. Rosen, D. Mulla, T. Nigon, Z. Dar, A. Cohen, A. Levi, R. Brikman, T. Markovits, R. Rud

3. Design And Experiment On Target Spraying Robot For Greenhouse

In greenhouse, the robot sprayers give rise to concern as they  reduce the labor intensity and improve the accuracy of  the spraying. This paper details the progress to date in the development of a precision robot sprayer. The precision robot sprayer is able to adjust both liquid and air volume to match, the branches contour and location of the greenhouse crops with two ultrasonic sensors  which ensures the position of the plants in the greenhouse. The spraying robot with the... W. Ma, C. Zhao, Q.U. Zaman, D. Zach

4. Development Of Variable Rate System For Soil Disinfection Based On Injection Technique

Abstract:  A variable rate system injection of soil pesticide was developed for control of soil pesticide amount by PWM. The paper analyzes the input and output conditions of control system, and designed hardware, algorithm and control of soil pesticide, mainly software flow and a feedback control way. In the paper, the variable-rate control system consisted of time delay, interface module, micro controller, speed sensor, PWM valve, and hydraulic... W. Ma, X. Wang

5. A Study On Diagnostic System Based On ISOAgLIB For Agricultural Vehicles

  Nowadays the growth of the embedded electronics and communications has demanded the development of applications in agricultural machinery in Korean agroindustry. The root reason is that most of agricultural machineries produced in Korea does not apply international standard. Therefore, the incompatibility problem between hardware, software and data formats has become a major obstacle for exporting agricultural products made by Korea to the world. In... J. Moon, S. Kim, J. Lee, W. Yang, D. Kim

6. Early Detection of Nitrogen Deficiency in Corn Using High Resolution Remote Sensing and Computer Vision

The continuously growing need for increasing the production of food and reducing the degradation of water supplies, has led to the development of several precision agriculture systems over the past decade so as to meet the needs of modern societies. The present study describes a methodology for the detection and characterization of Nitrogen (N) deficiencies in corn fields. Current methods of field surveillance are either completed manually or with the assistance of satellite imaging, which offer... D. Mulla, D. Zermas, D. Kaiser, M. Bazakos, N. Papanikolopoulos, P. Stanitsas, V. Morellas

7. Comparison Between High Resolution Spectral Indices and SPAD Meter Estimates of Nitrogen Deficiency in Corn

Low altitude remote sensing provides an ideal platform for monitoring time sensitive nitrogen status in crops. Research is needed however to understand the interaction between crop growth stage, spatial resolution and spectral indices derived from low altitude remote sensing. A TetraCam camera equipped with six bands including the red edge and near infrared (NIR) was used to investigate corn nitrogen dynamics. Remote sensing data were collected during the 2013 and 2014 growing seasons at four... D. Mulla, A. Laacouri, D. Kaiser

8. Development of a Crop Edge Line Detection Algorithm Using a Laser Scanner for an Autonomous Combine Harvester

The 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

9. Field Sampling and Electrochemical Detection of Nitrate in Agricultural Soils

Nitrate is an essential plant nutrient and is added to farm fields to increase crop yields. While the addition of nitrate is important for production, over-fertilization with nitrate can lead to leaching and contamination of water bodies. Increased nitrate loading in water sources then leads to eutrophication and hypoxia in downstream regions. Many efforts are being made to accurately control nitrate fertilizer additions to fields. Here, we present a soil sampling device that directly samples... J. Brockgreitens, M. Bui, A. Abbas, D. Mulla

10. Application of Geographic Information Systems in Socioeconomic Analysis: A Case of Integrated Soil Fertility Management in the Savannas of Nigeria

Population pressure increases, shortened fallow cycles, cropping intensification, inaccessibility and low output prices as well as concerns about agricultural sustainability and self-sufficiency have combined to contribute to increased demand for integrated soil fertility management of the agricultural resource base. Following this situation, organic fertilizer in the form of animal manure becomes one of the principal sources of nutrients for soil fertility maintenance and crop production. Hence,... O. Olayide, A. Alene, A. Ikpi, G. Nziguheba, T. Alabi

11. Utilization of Spatially Precise Measurements to Autocalibrate the EPIC Agroecosystem Model

Corn nitrogen recommendations for individual fields must improve to minimize the negative influence that agriculture has on the environment and society. Two adaptive N management approaches for making in-season N fertilizer recommendations are remote sensing and crop systems modeling. Remote sensing has the advantage of characterizing the spatial variability at a high spatial resolution, and crop models are prognostic and can assess expected additions and losses that are not yet reflected by the... T. Nigon, D. Mulla, C. Yang

12. A Case Study Comparing Machine Learning and Vegetation Indices for Assessing Corn Nitrogen Status in an Agricultural Field in Minnesota

Compact hyperspectral sensors compatible with UAV platforms are becoming more readily available. These sensors provide reflectance in narrow spectral bands while covering a wide range of the electromagnetic spectrum. However, because of the narrow spectral bands and wide spectral range, hyperspectral data analysis can benefit greatly from data mining and machine learning techniques to leverage its power. In this study, rainfed corn was grown during the 2017 growing season using four nitrogen treatments... A. Laacouri, T. Nigon, D. Mulla, C. Yang

13. Use of UAV Acquired Imagery As a Precision Agriculture Method for Measuring Crop Residue in Southwestern Ontario, Canada

Residue management on agriculture land is a practice of great importance in southwestern Ontario, where soil management practices have an important effect on Great Lakes water quality. The ability of tillage or planting system to maintain soil residue cover is currently measured by using one or more of the common methods, line transect (e.g. knotted rope, Meter stick) and photographic (grid, script, and image analysis) methods. Each of these techniques has various advantages and disadvantages;... A. Laamrani, A. Berg, M. March, A. Mclaren, R. Martin

14. Evaluating Remote Sensing Based Adaptive Nitrogen Management for Potato Production

Conventional nitrogen (N) management for potato production in the Upper Midwest, USA relies on using split-applications of N fertilizer or a controlled release N product. Using remote sensing to adaptively manage N applications has the potential to improve N use efficiency and reduce losses of nitrate to groundwater, which are important regional concerns. A two-year plot-scale experiment was established to evaluate adaptive N-management using remote sensing compared to conventional practices for... B. Bohman, D. Mulla, C. Rosen

15. Temperature Effect on Wild Blueberry Fruit Quality During Mechanical Harvest

Mechanical harvesters, utilizing a range of technologies, have been developed for timely operations and remain the most cost-effective means of picking the wild blueberry crop. Approximately 95% of wild blueberries in Atlantic Canada are immediately frozen and processed, while only a small percentage is sold in the fresh market. However, the producers can benefit by increasing the value of their harvested crop through fresh market sales. The objective of this study was to determine the optimum... T.J. Esau, A.A. Farooque, F. Abbas

16. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild Blueberry

Deep 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

17. Precision Irrigation Strategies for Climate-resilient Crop Production and Water Resource Management

Deficit irrigation management practices that best optimize the use of limited water resources without impacting crop yield are necessary to ensure the sustainability of agricultural production. This is particularly crucial in regions characterized by semi-arid climate, like Western Kansas, where the challenge of depleting water resources is worsened by the occurrence of extreme climate conditions. Therefore, a data-driven irrigation management strategy such as one developed based on crop evapotranspiration... K.E. Igwe, I. Onyekwelu, V. Sharda

18. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming Context

The increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an...