Control system response for seed placement accuracy on row crop planters

Doctor of PhilosophyDepartment of Biological & Agricultural EngineeringAjay ShardaPlanting is one of the most critical field operations that can highly influence early season vigor, final plant density and ultimately potential crop yield. It is the opportunity to place seeds at a uniform depth and spacing providing them the ideal environment for proper growth and development. However, inherent field spatial variability could influence seed placement and requires proper implementation of planter settings to prevent shallow seeding depth, sidewall compaction and uneven spacing. The overall goal of this research is to evaluate the response of the planter and crop to downforce control system implementation across a wide range of machine and field operating conditions. Planting operations were performed in corn production fields using a Horsch row-crop planter with 12 row units equipped with a hydraulic downforce system capable of implementing fixed and active downforce settings. A custom-made data acquisition system was developed to record sensor data at 10 Hz sampling frequency. From this study, the following conclusions were drawn. First, soil texture and soil compaction due to tractor tires influenced real-time gauge wheel load (GWL). Implementing a fixed downforce setting with target GWL set at 35 kg showed that 25% of the total planting time GWL was less than 0 suggesting areas planted with uncertain seeding depth due to potential loss of ground contact of the gauge wheels. Likewise, fewer row units per section could provide lower variability in GWL indicating the need for an automatic section control to maintain target GWL within an acceptable range for all row units. Second, implementing an active downforce setting showed no significant difference between downforce A (63 kg) and downforce B (100 kg) on plant spacing, although downforce setting B resulted to higher plant spacing accuracy. Higher variability in spacing was observed when ground speed is over 12 kph. To achieve desired seeding depth, downforce greater than 100 kg is needed when ground speed is over 7.2 kph on no-till field and when ground speed is over 12 kph on strip-tilled field. Third, response of row units segregated in sections revealed that row unit acceleration on wing, track and non-track sections increases with speed. Strip-tilled soil exhibited lower row unit acceleration by 18% compared to no-till soil. Finally, a proof-of-concept sensing and measurement (SAM) system was developed to calculate seed spacing, depth and geo-location of corn. This system could provide real-time feedback on seed spacing and depth allowing appropriate downforce control system management for more consistent seed placement during planting. In summary, advances in planter technology paved the way for the addition of more row units across on the planter to increase planting productivity. With increasing width of planter toolbar, each row unit may need different downforce control to varying field and machine operating conditions. Appropriate downforce control management should be implemented to compensate for increased dynamics of planter row units across a highly variable field conditions to achieve the desired seed placement accuracy

Utilizing commercial soil sensing technology for agronomic decisions

Planters with mounted proximal soil sensing systems can densely quantify seed zone soil variability. Technology now allows for real-time sensor information to control multiple row-unit functions on-the-go (e.g., planting depth). These and other developing sensor-based control systems have the potential to greatly improve correctness when planting, and therefore row-crop performance. For sensor-based control to be widely adopted, practitioners must understand the precision and utility of the systems. Therefore, research was conducted to: (i) determine how well commercially available sensors can estimate soil organic matter (OM) and whether sensor output was repeatable among sensing dates; (ii) evaluate OM prediction accuracy across selected soils and soil volumetric water contents with both a commercially-available, planter-mounted sensor, and machine learning techniques applied to multiple combinations of soil reflectance bands within the visible and near infrared spectrum; and (iii) investigate if planter and other proximal soil sensor data, in combination with topographic features, could predict field-scale corn emergence rate at varying planting depths. Results found that commercial sensors could estimate general trends in spatial variability of OM, but that some inconsistencies were associated with a "global" calibration that appeared susceptible to temporal variations in soil water content. In the controlled environment, results for sensor estimation of OM were similar to the field study. Further, results showed that spectral information within the entire range used by the commercial systems evaluated was required to consistently predict OM at varying volumetric water contents. Lastly, the field-scale agronomic analysis found that inherent soil and landscape variability drove the emergence rate response at the site. However, planter metrics were still usefulIncludes bibliographical references

Determination of Time Dependent Stress Distribution on Potato Tubers at Mechanical Collision

This study focuses on determining internal stress progression and the realistic representation of time dependent deformation behaviour of potato tubers under a sample mechanical collision case. A reverse engineering approach, physical material tests and finite element method (FEM)-based explicit dynamics simulations were utilised to investigate the collision based deformation characteristics of the potato tubers. Useful numerical data and deformation visuals were obtained from the simulation results. The numerical results are presented in a format that can be used for the determination of bruise susceptibility magnitude on solid-like agricultural products. The modulus of elasticity was calculated from experimental data as 3.12 [MPa] and simulation results showed that the maximum equivalent stress was 1.40 [MPa] and 3.13 [MPa] on the impacting and impacted tubers respectively. These stress values indicate that bruising is likely on the tubers. This study contributes to further research on the usage of numerical-methods-based nonlinear explicit dynamics simulation techniques in complicated deformation and bruising investigations and industrial applications related to solid-like agricultural products

Site-specific seeding using multi-sensor and data fusion techniques : a review

Site-specific seeding (SSS) is a precision agricultural (PA) practice aiming at optimizing seeding rate and depth, depending on the within field variability in soil fertility and yield potential. Unlike other site-specific applications, SSS was not adopted sufficiently by farmers due to some technological and practical challenges that need to be overcome. Success of site-specific application strongly depends on the accuracy of measurement of key parameters in the system, modeling and delineation of management zone maps, accurate recommendations and finally the right choice of variable rate (VR) technologies and their integrations. The current study reviews available principles and technologies for both map-based and senor-based SSS. It covers the background of crop and soil quality indicators (SQI), various soil and crop sensor technologies and recommendation approaches of map-based and sensor-based SSS applications. It also discusses the potential of socio-economic benefits of SSS against uniform seeding. The current review proposes prospective future technology synthesis for implementation of SSS in practice. A multi-sensor data fusion system, integrating proper sensor combinations, is suggested as an essential approach for putting SSS into practice

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings