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Araujo, A.G
Adamchuk, V
Alsheri, S.A
Abbas, F
Azzam, T
Astillo, P
Andales, A.A
Apolo-Apolo, E
Alarcon, V.J
Arnold, S
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Authors
Alwabel, M.I
Alsheri, S.A
Alomran, A.M
Araujo, A.G
Toledo, A.D
Hirakawa, A.R
Johann, A.L
Astillo, P
Maja, J
Greene, J
Sassenrath, G.F
Mueller, T
Alarcon, V.J
Kulesza, S.E
Shoup, D
Ahuja, L.R
Saseendran, S.A
Ma, L
Nielsen, D.C
Trout, T.J
Andales, A.A
Hansen, N.C
Cambouris, A
Lajili, A
Chokmani , K
Perron, I
Adamchuk, V
Biswas , A
Zebrath, B
Biswas, A
Ji, W
Perron, I
Cambouris, A
Zebarth, B
Adamchuk, V
Cambouris, A
Perron, I
Zebarth, B
Vargas, F
Chokmani, K
Biswas, A
Adamchuk, V
Johnston, A
Adamchuk, V
Biswas, A
Cambouris, A
Lafond, J
Perron, I
Tikasz, P
Buelvas, R.M
Lefsrud, M
Adamchuk, V
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
Leksono, E
Adamchuk, V
Ji, W
Leclerc, M
Huang, H
Adamchuk, V
Biswas, A
Ji, W
Lauzon, S
Marmette, M
Adamchuk, V
Nault, J
Tabatabai, S
Cocciardi, R
Leksono, E
Adamchuk, V
Whalen, J
Buelvas, R
Adamchuk, V
Debbagh, M
Madramootoo, C
Whalen, J
Cook, S
Lacoste, M
Evans, F
Tremblay, N
Adamchuk, V
Esau, T.J
Farooque, A.A
Abbas, F
Hoffmann Silva Karp, F
Adamchuk, V
Melnitchouck, A
Dutilleul, P
Cheema, S.J
Farooque, A.A
Abbas, F
Esau, T
Grewal, K
Khan, H
Esau, T
Farooque, A
Abbas, F
Saifuzzaman, M
Adamchuk, V
Leduc , M
Javed, B
Cambouris, A
Duchemin, M
Longchamps, L
Basran, P.S
Arnold, S
Fenech, A
Karam, A
Scudiero, E
Nugent, C.I
Ng, C
Jones, N
Azzam, T
Salunga, N.G
Lemus, S
Hoffmann Silva Karp, F
Adamchuk, V
Dutilleul, P
Melnitchouck, A
Biswas, A
Topics
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Modelling and Geo-Statistics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
Precision Horticulture
Decision Support Systems
Geospatial Data
Wireless Sensor Networks
Workshops
Precision Horticulture
Geospatial Data
Drainage Optimization and Variable Rate Irrigation
Precision Agriculture and Global Food Security
Decision Support Systems
Precision Agriculture and Global Food Security
Education of Precision Agriculture Topics and Practices
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2014
2016
2008
2018
2022
2024
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Authors

Filter results26 paper(s) found.

1. Long Term Effects of Irrigation with Sewage Effluent on Some Soil Properties

In the arid and semiarid regions, the use of treated sewage water increases as an alternative for non-renewable resources in irrigation. The objective of this research is to identify the effect of irrigation with sewage effluent and well water for long... M.I. Alwabel, S.A. Alsheri, A.M. Alomran

2. Control System Applied To No-Till Seeding For High-Quality Operation

A high quality crop seeding operation should enable a rapid and uniform establishment of a desired plant population. Therefore, a no-till seeder must provide a seeding environment that allows the absorption of water by seeds and appropriate temperature and aeration conditions for germination and emergence processes. To stimulate these processes, the seed needs full contact with soil in order to accelerate the absorption of water and oxygen. Covering the furrow with straw is another important... A.G. Araujo, A.D. Toledo, A.R. Hirakawa, A.L. Johann

3. Development of a Sensing Device for Detecting Defoliation in Soybean

Estimating defoliation by insects in an agricultural field, specifically soybean, is performed by manually removing multiple leaf samples, visually inspecting the leaves for feeding, and assigning a value representing a “best guess” at the level of leaf material missing. These estimates can require considerable time and are subjective. The goal of this study was to design a low-cost system containing light sensors and a microcontroller that could remotely record and report long-term... P. Astillo, J. Maja, J. Greene

4. In-field Variability of Terrain and Soils in Southeast Kansas: Challenges for Effective Conservation

A particular challenge for crop production in southeast Kansas is the shallow topsoil, underlain with a dense, unproductive clay layer. Concerns for topsoil loss have shifted production systems to reduced tillage or conservation management practices. However, historical erosion events and continued nutrient and sediment loss still limit the productive capacity of fields. To improve crop production and further adoption of conservation practices, identification of vulnerable areas of fields was... G.F. Sassenrath, T. Mueller, V.J. Alarcon, S.E. Kulesza, D. Shoup

5. Use of a Cropping System Model for Soil-specific Optimization of Limited Water

In the arena of modern agriculture, system models capable of simulating the complex interactions of all the relevant processes in the soil-water-plant- atmosphere continuum are widely accepted as potential tools for decision support to optimize crop inputs of water to achieve location specific yield potential while minimizing environmental (soil and water resources) impacts. In a recent study, we calibrated, validated, and applied the CERES-Maize v4.0 model for simulating limited-water irrigation... L.R. Ahuja, S.A. Saseendran, L. Ma, D.C. Nielsen, T.J. Trout, A.A. Andales, N.C. Hansen

6. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, Canada

Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath

7. Proximal Soil Sensing-Led Management Zone Delineation for Potato Fields

A fundamental aspect of precision agriculture or site-specific crop management is the ability to recognize and address local changes in the crop production environment (e.g. soil) within the boundaries of a traditional management unit. However, the status quo approach to define local fertilizer need relies on systematic soil sampling followed by time and labour-intensive laboratory analysis. Proximal soil sensing offers numerous advantages over conventional soil characterization and has shown... A. Biswas, W. Ji, I. Perron, A. Cambouris, B. Zebarth, V. Adamchuk

8. Delineation of Soil Management Zones: Comparison of Three Proximal Soil Sensor Systems Under Commercial Potato Field in Eastern Canada.

Precision agriculture (PA) involves optimization of seeding, fertilizer application, irrigation, and pesticide use to optimize crop production for the purpose of increasing grower revenue and protecting the environment. Potato crops (Solanum tuberosum L.) are recognized as good candidates for the adoption of PA because of the high cost of inputs. In addition, the sensitivity of potato yield and quality to crop management and environmental conditions makes precision management economically... A. Cambouris, I. Perron, B. Zebarth, F. Vargas, K. Chokmani, A. Biswas, V. Adamchuk

9. Integration of Proximal and Remote Sensing Data for Site-Specific Management of Wild Blueberry

In Saguenay-Lac-St-Jean, there are nearly 27,000 ha of wild blueberries (Vaccinium angustifolium Ait.). This production is carried out in fields with heterogeneous growing conditions due to the local changes in topography, key soil properties, and crop density. The main objective of this study was to develop a regression-based approach to site-specific management (SSM) by integrating proximally and remotely sensed data layers, namely, apparent soil electrical conductivity (ECa), field elevation,... A. Johnston, V. Adamchuk, A. Biswas, A. Cambouris, J. Lafond, I. Perron

10. Implementation of a CAN Bus System to Monitor Hydroponic Systems

Controlled Area Network (CAN) bus systems designed for greenhouse monitoring have been proposed to measure soil moisture content, yet they are still absent from hydroponic systems. In this study, irrigation control, monitoring of substrate moisture levels and temperature were achieved using a CAN bus system connected to hydroponic beds. In total, five nodes were mounted on five hydroponic beds and two irrigation methods were compared on lettuce and kale: first, where a pre-set timer activated... P. Tikasz, R.M. Buelvas, M. Lefsrud, V. Adamchuk

11. Feasibility of Estimating the Leaf Area Index of Maize Traits with Hemispherical Images Captured from Unmanned Aerial Vehicles

Feeding a global population of 9.1 billion in 2050 will require food production to be increased by approximately 60%. In this context, plant breeders are demanding more effective and efficient field-based phenotyping methods to accelerate the development of more productive cultivars under contrasting environmental constraints. The leaf area index (LAI) is a dimensionless biophysical parameter of great interest to maize breeders since it is directly related to crop productivity. The LAI is defined... M. Perez-ruiz, E. Apolo-apolo, G. Egea, J. Martinez-guanter, C. Marin-barrero

12. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

13. Development of a Soil ECa Inversion Algorithm for Topsoil Depth Characterization

Electromagnetic induction (EMI) proximal soil sensor systems can deliver rapid information about soil. One such example is the DUALEM-21S (Dualem, Inc. Milton, Ontario, Canada). EMI sensors measure soil apparent electrical conductivity (ECa) corresponding to different depth of investigation depending on the instrument configuration. The interpretation of the ECa measurements is not straightforward and it is often site-specific. Inversion is required to explore specific depths. This inversion process... E. Leksono, V. Adamchuk, W. Ji, M. Leclerc

14. Analysis of Soil Properties Predictability Using Different On-the-Go Soil Mapping Systems

Understanding the spatial variability of soil chemical and physical attributes allows for the optimization of the profitability of nutrient and water management for crop development. Considering the advantages and accessibility of various types of multi-sensor platforms capable of acquiring large sensing data pertaining to soil information across a landscape, this study compares data obtained using four common soil mapping systems: 1) topography obtained using a real-time kinematic (RTK) global... H. Huang, V. Adamchuk, A. Biswas, W. Ji, S. Lauzon

15. Comparison of the Performance of Two Vis-NIR Spectrometers in the Prediction of Various Soil Properties

Spectroscopy has shown capabilities of predicting certain soil properties. Hence, it is a promising avenue to complement traditional wet chemistry analysis that is costly and time-consuming. This study focuses on the comparison of two Vis-NIR instruments of different resolution to assess the effect of the resolution on the ability of an instrument to predict various soil properties. In this study, 798 air dried and compressed soil samples representing different agro-climatic conditions across... M. Marmette, V. Adamchuk, J. Nault, S. Tabatabai, R. Cocciardi

16. Development of a Manual Soil Sensing System for Measuring Multiple Chemical Soil Properties in the Field

Variable Rate Fertilizer Application (VRA) requires the input of soil chemical data. One of the preferred methods for analyzing soil chemical properties in the field is by using Ion Selective Electrodes (ISEs). To accommodate portability in soil measurements, a manual soil sampling system was developed. Nitrate, Phosphate and pH ISEs were integrated to provide a general outlook on the condition of essential soil nutrients. These ISEs were placed on a modified hand-held soil sampler equipped... E. Leksono, V. Adamchuk, J. Whalen, R. Buelvas

17. Development of a Wireless Sensor Network for Passive in situ Measurement of Soil CO2 Gas Emissions in the Agriculture Landscape

Quantification of soil Greenhouse Gas (GHG) emissions from agricultural fields is essential for understanding the environmental impact of intensive crop and livestock production systems. Current methods of analysis include flux calculations derived from the concentration of gases (CO2, N2O, CH4) exchanged between soil and the atmosphere. Samples of these GHG are obtained manually by closed non-steady state non-flow through,or “static”, chambers and analyzed ex situvia gas... V. Adamchuk, M. Debbagh, C. Madramootoo, J. Whalen

18. On-Farm Experimentation and Decision-Support Workshop

This 3-hour workshop discusses the requirements, methods and theories that may be used to assist in making optimal crop management decisions. The first part will focus on on-farm experimentation (OFE): 1) organization and benefits of OFE; 2) social processes and engagement; 3) designs, data and statistics. The second part will demonstrate how to generate insights applicable at the individual farm level using results from research trials collected in a diversity of contexts. Data sharing, meta-analyses... S. Cook, M. Lacoste, F. Evans, N. Tremblay, V. Adamchuk

19. 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

20. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes

The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul

21. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, Canada

Soil 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

22. Suitability of ML Algorithms to Predict Wild Blueberry Harvesting Losses

The 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

23. Stem Characteristics and Local Environmental Variables for Assessment of Alfalfa Winter Survival

Alfalfa (Medicago sativa L.) is considered the queen of forage due to its high yield, nutritional qualities, and capacity to sequester carbon. However, there are issues with its relatively low persistency and winter survival as compared to grass. Winter survival in alfalfa is affected by diverse factors, including the environment (e.g., snow cover, hardiness period, etc.) and management (e.g., cutting timing, manure application, etc.). Alfalfa's poor winter survival reduces the number of living... M. Saifuzzaman, V. Adamchuk, M. Leduc

24. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato Production

In modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam

25. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, Riverside

Funded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus

26. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study

Using proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas