Design and Evaluation of Variable Rate Stover Collection Control System For a Single Pass Dual Stream Biomass Harvester System

The increased need for renewable fuel sources has driven research to focus on agricultural by-products in the form of corn stover. Corn stover is the single largest available biomass feedstock in the U.S. and is also a vital part of agriculture as it provides soil protection and maintains the carbon cycle. Removing this material requires it be done using sustainable practices, with this research focusing specifically on protecting soil loss. Achieving this requires variable rate removal of corn stover to provide site specific management to account for spatial variability of a field by field basis. Utilizing two modes of control with a single pass dual stream biomass harvester, target rates of stover can be removed or returned to attain sustainable corn stover harvesting

Estimation of Optimal Biomass Removal Rate Based on Tolerable Soil Erosion for Single-Pass Crop Grain and Biomass Harvesting System

As the demand for biomass feedstocks grows, it is likely that agricultural residue will be removed in a way that compromises soil sustainability due to increased soil erosion, depletion of organic matter, and deterioration of soil physical characteristics. Since soil erosion from agricultural fields depends on several factors including soil type, field terrain, and cropping practices, the amount of biomass that can be removed while maintaining soil tilth varies substantially over space and time. The RUSLE2 soil erosion model, which takes into account these spatio-temporal variations, was used to estimate tolerable agricultural biomass removal rates at field scales for a single-pass crop grain and biomass harvesting system. Soil type, field topography, climate data, management practices, and conservation practices were stored in individual databases on a state or county basis. Geographic position of the field was used as a spatial key to access the databases to select site-specific information such as soil, topography, and management related parameters. These parameters along with actual grain yield were provided as inputs to the RUSLE2 model to calculate yearly soil loss per unit area of the field. An iterative technique was then used to determine site-specific tolerable biomass removal rates that keep the soil loss below the soil loss thresholds (T) of the field. The tolerable removal rates varied substantially with field terrain, crop management practices, and soil type. At a location in a field in Winnebago county, Iowa, with ~1% slope and conventional tillage practices, up to 98% of the 11 Mg ha-1 total above-ground biomass was available for collection with negligible soil loss. There was no biomass available to remove with conventional tillage practices on steep slopes, as in a field in Crawford county, Iowa, with a 12.6% slope. If no-till crop practices were adopted, up to 70% of the total above-ground biomass could be collected at the same location with 12.6% slope. In the case of a soybean-corn rotation with no-till practices, about 98% of total biomass was available for removal at the locations in the Winnebago field with low slopes, whereas 77% of total biomass was available at a location in the Crawford field with a 7.5% slope. Tolerable removal rates varied substantially over an agricultural field, which showed the importance of site-specific removal rate estimation. These removal rates can be useful in developing recommended rates for producers to use during a single-pass crop grain and biomass harvesting operation. However, this study only considered the soil erosion tolerance level in estimating biomass removal rates. Before providing the final recommendation to end users, further investigations will be necessary to study the potential effects of continuous biomass removal on organic matter content and other biophysical properties of the soil

Using Yield Monitors to Assess On-Farm Test Plots

Farmer test plots have become a staple for production agriculture. These plots can range from simple side-by-side demonstration plots to a replicated research study. The rush of harvest often creates a challenge for harvesting these plots. Yield monitor data were collected from field scale plots in multiple states to assess ability to measure on-farm research. Grain mass was also measured for each plot with a weigh wagon or certified scale. The variability of yield monitor error (standard deviation) was not correlated with the magnitude of the error (mean). Thus calibration in and of itself will likely not result in more consistent yield monitor error. Determining if treatments or observations from non-replicated studies are different will be challenging. Depending on the chosen probability level, this data indicate that distinguishing a 3 to 9 percent difference was possible. Statistical analysis of replicated trials results in similar conclusions with reference and yield monitor data. Mass flow rate is one factor impacting yield monitor error

Design and Evaluation of Variable Rate Stover Collection Control System For a Single Pass Dual Stream Biomass Harvester System

The increased need for renewable fuel sources has driven research to focus on agricultural by-products in the form of corn stover. Corn stover is the single largest available biomass feedstock in the U.S. and is also a vital part of agriculture as it provides soil protection and maintains the carbon cycle. Removing this material requires it be done using sustainable practices, with this research focusing specifically on protecting soil loss. Achieving this requires variable rate removal of corn stover to provide site specific management to account for spatial variability of a field by field basis. Utilizing two modes of control with a single pass dual stream biomass harvester, target rates of stover can be removed or returned to attain sustainable corn stover harvesting.</p

Development of a real-time algorithm for automation of the grain yield monitor calibration

This study sought to develop an understanding of the accuracy of the impact based yield monitor and characterize field performance. The study evaluated yield monitor performance on the mass flow signal, individual load, field level, and season level. An automated system utilizing pressure pads located in the combine grain tank combined with an algorithm was developed and implemented to calibrate the impact based yield monitor in harvesting of corn. The developed algorithm defined specific bounds for the calibration period and estimated partial tank load weight, replacing the operator entered load weights from the prescribed manual calibration process. The automatic calibration system was integrated with the impact based yield monitor system, entirely removing operator interaction in the yield monitor calibration process. The complete yield monitor with integrated automatic calibration was field tested during the 2015 corn harvest season and compared versus a manual calibration. The automated system outperformed the manual calibration in long term studies, successfully compensating the yield monitor calibration for changing crop conditions

Ambient assisted living flexible interface (AALFI) : context aware flexible interface for ambient assisted living

Ambient Assisted Living (AAL) systems must strike a careful balance between interaction and automated assistance. This is particularly the case for older people, who may not have the skills for conventional interaction with computer interfaces. Findings show that current AAL systems do not specifically address the older person's auditory, visual or physical needs or support changes to these needs that result from the normal ageing process. The resulting interaction with these systems often provides information in a format that the older person finds difficult to interpret and utilise. This research proposes an Ambient Assisted Living Flexible Interface (AALFI) that is tailored to individual interaction requirements, and is capable of detecting the context associated with an event or activity. Previously identified limitations are overcome by the provision of two distinct forms of assistance: feedback designed to analyse recurring events in order to provide longer term assistance and intervention assistance designed to make the older person aware of urgent issues that require immediate action. During the implementation of AALFI the features and functionality were assessed by carrying out usability testing with 8 university students. These results were found to be positive as no major initial usability issues were found. Usability studies have been found to be useful in giving an indication on AAL system usability. AALFI was found to have good usability. This laid the foundations for further development and formal evaluation at a workshop at Age Northern Ireland, a group which champions the needs of the older person. AALFI was evaluated by 10 participants including older persons, care providers and health professionals. A final workshop, split between two sessions was conducted with the target demographic, older people and the results obtained provide further validation of the choices that have been made and assistance that is offered. The features, functionality and complexity of the assistance and interaction techniques were assessed by potential users and the underlying ideas behind the implementation were validated. Analysis of the results demonstrates that interactions between AALFI and the potential users are understandable and the assistance offered is timely, meaningful and worthwhile.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Large-scale field study of impact-based yield monitor performance

The grain yield monitor is the most common evaluation tool for determining the productivity of grain cropping systems. Most evaluations of grain yield monitors have focused on lab scale tests of the sensor performance and its ability to be calibrated in field trials. This study focused on the performance of the impact-based grain yield monitor during a full corn harvest season with observations and conclusions drawn on the load-to-load variation, field level, and full season accuracy from data collected over five seasons and encompassing over 2,000 evaluation loads. The load variance expectation of the impact-based yield monitor was characterized and the yield difference requirements for statistical significance were developed to aid in yield monitor based evaluations of agronomic strip trials. Following manufacturer recommended calibrations, a single cropping season calibration in corn produced field mean errors of ±5% and a season mean error of 1%. Results showed statistically significant shift in the yield monitor accuracy for grain moisture content greater than 22.5% and a load accuracy dependency on the mean mass flow rate during the full harvest season calibration evaluation.This article is published as McNaull, Robert P., and M. J. Darr. "Large-scale field study of impact-based yield monitor performance." Applied Engineering in Agriculture 36, no. 2 (2020): 197-204. DOI: 10.13031/aea.13527. Copyright 2022 American Society of Agricultural and Biological Engineers. Posted with permission