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On Farm Experimentation with Site-Specific Technologies
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Authors
Attanayake, A.U
Barker, D
Brorsen, W
Duddu, H.U
Fulton, J.P
Gauci, A
Gnatowski, T
Hawkins, E
Hegedus, P
Johnson, E.U
Jones, J
Krmenec, A
Leszczyńska, R
Lindsey, A
Loewen, S
Longchamps, L
Maxwell, B
Maxwell, B.D
Morata, G.T
Oliveira, L.P
Ortiz, B.V
Poursina, D
Samborski, S.M
Shearer, S.A
Shirtliffe, S.U
Squires, T
Stelford, M
Szatylowicz, J
Thornton, M
Walsh, O
Topics
On Farm Experimentation with Site-Specific Technologies
Type
Oral
Year
2022
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Topics

Filter results9 paper(s) found.

1. Constraint of Data Availability on the Predictive Ability of Crop Response Models Developed from On-farm Experimentation

Due to the variability between fields and across years, on-farm experimentation combined with crop response modeling are crucial aspects of decision support systems to make accurate predictions of yield and grain protein content in upcoming years for a given field. To maximize accuracy of models, models fit using environmental covariate and experimental data gathered up to the point that crop responses (yield/grain protein) are fit repeatedly over time until the model can predict future crop ... P. Hegedus, B. Maxwell

2. Use of Precision Technologies to Conduct Successful Within-field, On-farm Trials

Performing randomized replicated trials in row crop field environments has the potential to increase crop production in environmentally sustainable ways.  Successful implementation requires an understanding of implement capabilities and sources of potential systematic error, including operator error.  Equipment capabilities can be thought of as a series of several critical “links in a chain,” each with implications that propagate downstream.   We will... M. Stelford, A. Krmenec

3. Precision Application of Seeding Rates for Weed and Nitrogen Management in Organic Grain Systems

In a time of increasing ecological awareness, organic agriculture offers sustainable solutions to many of the polluting aspects of conventional agriculture. However, without synthetic inputs, organic agriculture faces unique challenges such as weed control and fertility management. Precision Agriculture (PA) has been used to successfully increase input use efficiency in conventional systems and now offers itself as a potential tool for organic farmers as well. PA enables on farm experimentati... S. Loewen, B.D. Maxwell

4. Modulated On-farm Response Surface Experiments with Image-based High Throughput Techniques for Evidence-based Precision Agronomy

Agronomic research is vital to determining optimum inputs for crops to perform profitably at a local scale. However, the small-plot experiment validity is often uncertain due to on-farm variations. Furthermore, the likelihood of conducting a fully randomized trial at a local farm is low given various practical and technical challenges. We propose a new methodology with many inputs to allow for a response surface that fits the yield response to the input levels with higher accuracy to make on-... A.U. Attanayake, E.U. Johnson, H.U. Duddu, S.U. Shirtliffe

5. Where to Put Treatments for On-farm Experimentation

On-farm experimentation has become more and more popular due to advancements in technology. These experiments are not as costly as before, as current machinery can allocate different levels of treatment to specific plots. The main goal of this kind of experiment is to obtain a site-specific nutrient level. The yield behavior is different based on the researcher’s treatment. One unanswered question for on-farm experimentation is how the treatments should be allocated in the first place s... D. Poursina, W. Brorsen

6. Enhancing NY State On-farm Experimentation with Digital Agronomy

Agriculture is putting pressure on the ecosystems and practices need to evolve towards a more sustainable way of producing food. Industrial agriculture has imposed a unique production model on the ecosystems while it is now understood that it is more sustainable to adapt the production model to the ecosystem. This involves adapting existing solutions to the local agricultural context and developing new solutions that are best suited to the local ecosystem. Farmers are doing this by conducting... L. Longchamps

7. Limitations of Yield Monitor Data to Support Field-scale Research

Precision 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 resear... J.P. Fulton, S.A. Shearer, A. Gauci, A. Lindsey, D. Barker, E. Hawkins

8. Is Row-unit Vibration Affected by Planter Speeds and Downforce?

Row-unit vibration is an issue created mainly by planter`s opening disks and gauge-wheels contact with the ground. Variability on row-unit vibration could interfere on seed metering and delivery process, affecting crop emergence and final stand. With the amount of embedded technology present on planters, producers are being encouraged to increase planting speeds, which is also one of the main factors for row-unit vibration increasement. In this way, knowing the proper speeds, and using other ... L.P. Oliveira, B.V. Ortiz, G.T. Morata, T. Squires, J. Jones

9. Use of Remotely Measured Potato Canopy Characteristics As Indirect Yield Estimators

Prediction of potato yield before harvest is important for making agronomic and marketing decisions. Active optical sensors (AOS) are rarely used together with other hand-held instruments for monitoring potato growth, including yield prediction. The aim of the research was to determine the relationship between manually and remotely measured potato crop characteristics throughout the growing season and yield in commercial potato fields. Objective was also to identify crop characteristics that ... S.M. Samborski, J. Szatylowicz, T. Gnatowski, R. Leszczyńska, M. Thornton, O. Walsh