Development and evaluation of forage yield measure sensors in a mowing-conditioning machine

Kumhála, F.; Kroulík, M.; Prošek, V.

doi:10.1016/j.compag.2007.03.013

Cited by 14 publications

(7 citation statements)

References 3 publications

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“…6) could best be described as logarithmic (R 2 = 0.80, solid line) rather than linear (R 2 = 0.74, dashed line). The coefficient of determination found in this study was comparable to the coefficient of determination (R 2 = 0.73) found by Kumhála et al (2007), indicating a degree of yield prediction accuracy achievable under field conditions. Sensed stem bending force increased as Miscanthus yield increased.…”

Section: Correlation Of Sensed Stem Bending Force and Miscanthus Yieldsupporting

confidence: 82%

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Sensing Miscanthus Stem Bending Force for Maximizing Throughput Rate in a Disk Mower-Conditioner

et al. 2014

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One of the reasons for relatively high biomass harvesting cost is challenges in adjusting the ground speed of harvesting machines with respect to the yield level within a field. A real-time biomass yield sensor that can predict the yield in front of a machine could be a useful tool to control ground speed. It was hypothesized that the force required to bend Miscanthus stems is a reliable predictor of biomass yield. Based on this novel concept, a stem bending force-sensing system was developed and field tested with a disk mower-conditioner. A bale-specific method, segmenting the field area from which a bale was formed, was developed to correlate sensed bending force and Miscanthus yield. The measured bending force showed a logarithmic relationship (R 2 = 0.80) with Miscanthus yield. The average error in predicting balespecific yield was 10.3% for training data and 12.9% for validation data. The average error in predicting plot yield was 3.4% for training plots and 10.0% for validation plots. Using the developed logarithmic correlation model, yield maps were also generated. For the specific case analyzed, a proper control strategy to maximize throughput rate (mass per unit time) would be to either operate the mower-conditioner at the maximum feasible ground speed (9 km h-1) or at the maximum achievable throughput rate (60 Mg h-1). The yield-sensor controlled machine would result in 44.2% higher field capacity, 41.3% higher throughput rate, and 31.2% lower mowing-conditioning cost for the specific case analyzed compared to the operator-controlled machine. Studies are needed to extend the stem bending force-sensing concept to other thickstemmed crop harvesting machines, such as sugarcane harvesters and coppice harvesters.

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Section: Correlation Of Sensed Stem Bending Force and Miscanthus Yieldsupporting

confidence: 82%

“…The influence of conveyer belt parameters on grass mass flow was also investigated (Wild and Ruhland, 2007). Conditioner power measured with a torque sensor was correlated (R 2 = 0.73) with alfalfa yield (Kumhála et al, 2007). A weighing plate predicted sugarcane yield with an accuracy of 89% on a billet-type sugarcane harvester (Mailander et al, 2010).…”

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confidence: 99%

Sensing Miscanthus Stem Bending Force for Maximizing Throughput Rate in a Disk Mower-Conditioner

et al. 2014

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“…They equipped a drum mower with a torque sensor and a curved impact plate (behind a mower conditioner) which was hit by the mowed grass. [14] Some small smart applications already found their way into practice like a torque sensor for warning the driver if the rotation of the mower and the rotation of tractors power take off (PTO) distinguish too much to give him assistance for an optimum velocity and motor speed.…”

Section: Devices For Precision Farming In Grasslandmentioning

confidence: 99%

Smart solution for safe and long-lasting operation of agricultural equipment

Magó¹

2019

Poljoprivredna tehnika

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Nowadays the increasing of the efficiency of agricultural production and the increasing of crop yields cannot be achieved without modern digital technology and smart machines that are a part of it. With the spread of precision agriculture and the digitalisation next to the power machines the attached equipment is becoming smarter and smarter. Through permanent technological and IT development, it became possible to thoroughly monitor and analyse operating functions and parameters not only for the most important power machines such as tractors, combines and other, but also there are existing solutions for measurement-and related to that a collection and an analyse of data-of specific utilisation parameters for other attached equipment. All of these processed data are essential for making well-considered actions related to the production technology and the machine operating. They help us to gain information about the quality of machine operations of the technology, the environmental factors, or even about the state of attached working equipment and machines. In this work, the vibration control system as smart solutions on the fail movers will be presented which are effective tools for the utilization of machines, for the precision machine work as well as for prolonging the machine life cycle.

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“…Research on sensing and yield mapping applications for forage crop harvesting has been lesser in amount. Some recent examples are [ 96 ] and [ 97 ]. Lee et al .…”

Section: Sensors and Sensor Network Applications In Arable Crop Produmentioning

confidence: 99%

Geosensors to Support Crop Production: Current Applications and User Requirements

Thessler

Kooistra

Teye

et al. 2011

Sensors

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Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The present paper explores how sensors and sensor networks have been utilised in the crop production process and what their added-value and the main bottlenecks are from the perspective of users. The focus is on sensor based applications and on requirements that users pose for them. Literature and two use cases were reviewed and applications were classified according to the crop production process: sensing of growth conditions, fertilising, irrigation, plant protection, harvesting and fleet control. The potential of sensor technology was widely acknowledged along the crop production chain. Users of the sensors require easy-to-use and reliable applications that are actionable in crop production at reasonable costs. The challenges are to develop sensor technology, data interoperability and management tools as well as data and measurement services in a way that requirements can be met, and potential benefits and added value can be realized in the farms in terms of higher yields, improved quality of yields, decreased input costs and production risks, and less work time and load.

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Development and evaluation of forage yield measure sensors in a mowing-conditioning machine

Cited by 14 publications

References 3 publications

Sensing Miscanthus Stem Bending Force for Maximizing Throughput Rate in a Disk Mower-Conditioner

Sensing Miscanthus Stem Bending Force for Maximizing Throughput Rate in a Disk Mower-Conditioner

Smart solution for safe and long-lasting operation of agricultural equipment

Geosensors to Support Crop Production: Current Applications and User Requirements

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