Test Engineering and Quality Assurance

Aktuelle komplexe Sensortechnik und eine zugehörige Datenanalyse erfassen die Einsatzbedingungen von Landmaschinen heute genauer und sind dadurch die Grundlage für eine höhere Effizienz der Maschinennutzung und der auszubringenden Betriebsmittel. Die vielfach angestrebte Reduktion von chemisch-synthetischen Pflanzenschutzmitteln ist heute nur möglich mit einer Kombination aus traditioneller Hacktechnik und moderner Sensortechnik, da diese in der Arbeitsqualität und der Flächenleistung gesteigert werden konnten. Für das Prüfwesen in der räumlichen Positionsbestimmung sind zielverfolgende Ortungssysteme (Tachymeter) auch unter dynamischen Bedingungen geeignet, eine hohe Genauigkeit zu erreichen.Today's complex sensor technology and associated data analysis record the operating conditions of agricultural machinery more accurately and thus form the basis for greater efficiency in machine use and the inputs to be applied. The much sought-after reduction in the use of chemical-synthetic crop protection agents is only possible today with a combination of traditional hoeing technology and modern sensor technology, as this has made it possible to increase the quality of work and area output. For testing in spatial positioning, target-tracking positioning systems (tachymeters) are suitable for achieving high accuracy even under dynamic conditions

Review: Trends in the park of agricultural machinery in Estonia in the period 2010–2018

ArticleSaabunud / Received 08.04.2019 ; Aktsepteeritud / Accepted 06.06.2019 ; Avaldatud veebis / Published online 12.06.2019 ; Vastutav autor / Corresponding author: Jüri Olt e-mail: [email protected] aim of the current research is to provide an overview of the trends in the park of agricultural machinery in Estonia during the period 2010–2018. For this purpose, data obtained from the registers of Agriculture and Transport of Statistics Estonia have been used. The article outlines, firstly, changes in the number of agricultural holdings by the size of arable land and growing area of grain, secondly, changes in the number of tractors and grain harvesters, including the number of new tractors and harvesters sold over the years, thirdly, the preferences of holdings for tractors and grain harvesters, and fourthly, the categorization of new tractors and grain harvesters by the manufacturing company in the given time period. What is more, developments concomitant with trends in the park of agricultural machinery have been described

Evaluation of the variable rate capabilities of a sprayer equipped with pulse width modulation nozzle control and direct chemical injection systems

Variable-rate technologies coupled with broadcast spray systems serve to reduce chemical inputs, misapplication of chemicals, and environmental pollution, thus improving profitability and sustainability. Sprayer variable rate control involves using pulse width modulation (PWM) solenoids and/or direct chemical injection to adjust the application rate. The objectives of this research were to: outfit a conventional broadcast sprayer with PWM and direct inject technologies; evaluate the accuracy of the PWM system to control application rate for strait line and turn segments; and characterize the direct injection system’s transport delay time. For the PWM evaluation, the mean flow rate and coefficient of variation of individual nozzles indicated consistent performance. For the direct injection evaluation, the manufacturer recommended plumbing scheme and injection point location resulted in unsatisfactory delay times, ranging from 105 to 150s for the 8 km h-1 (5 mph) speed and 60 to 90s for the 16 km h-1 (10 mph) speed

DEVELOPMENT OF A SPRAYER PERFORMANCE DIAGNOSTIC TOOL USING IMPROVED MAPPING AND ERROR QUANTIFICATION PRACTICES

While sprayer technologies have advanced greatly over the past decade and a half, chemical application errors are still prominent in many in-field operations. Over-application of pesticides can cause harm to the crop, reducing yield, and result in added pollution to the environment. Under-application of pesticides fails to control pests within the field, again lowering crop yields, and causing profit loss for the producer. Current operator feedback from in-field pesticide application operations conveys limited information and often times does not allow the operator to visualize a true representation of their performance. Farm Management Information Systems (FMIS) typically do not account for overlap, varying application rates across the width of the spray boom during turns, or off-rate errors due to controller response. Improved mapping systems and product distribution summaries would allow operators to make better-informed decisions leading to improved management practices during spraying operations. The Pesticide Application Coverage Training (PACT) tool was developed to deploy data analytics methodologies to sprayer operations data collected during field applications. The goal was to provide improved operator feedback allowing for better management practices by providing enhanced feedback to operators over the course of two years. Data were collected for multiple Nebraska fields and processed by the PACT program which generated high-resolution as-applied maps and quantified error reports. PACT program output metrics were compared with currently available sprayer feedback software and previous studies related to high-resolution as-applied maps. Field-average metrics were not found to be significantly different when comparing the PACT program with these systems. However, when examining how in-field errors were distributed amongst various application rate ranges, significant differences were found. Differences in errors broken down by application rate ranges implied successful inclusion of previously unaccounted for error types by the PACT program. In addition, the program showed potential for technology adoption decision support. The PACT program successfully improved upon current sprayer operator feedback systems which will offer a platform for supporting better management practices in the future. Advisor: Joe D. Luc

Disruptive Technologies in Agricultural Operations: A Systematic Review of AI-driven AgriTech Research

YesThe evolving field of disruptive technologies has recently gained significant interest in various industries, including agriculture. The fourth industrial revolution has reshaped the context of Agricultural Technology (AgriTech) with applications of Artificial Intelligence (AI) and a strong focus on data-driven analytical techniques. Motivated by the advances in AgriTech for agrarian operations, the study presents a state-of-the-art review of the research advances which are, evolving in a fast pace over the last decades (due to the disruptive potential of the technological context). Following a systematic literature approach, we develop a categorisation of the various types of AgriTech, as well as the associated AI-driven techniques which form the continuously shifting definition of AgriTech. The contribution primarily draws on the conceptualisation and awareness about AI-driven AgriTech context relevant to the agricultural operations for smart, efficient, and sustainable farming. The study provides a single normative reference for the definition, context and future directions of the field for further research towards the operational context of AgriTech. Our findings indicate that AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy in Operations Research. Through the systematic review, we also intend to inform a wide range of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide research agenda for a growing field with multiple potentialities for the future of the agricultural operations

Predicting Agricultural Implement Hydraulic Power Demand Using Synchronized Controller Area Network and Ancillary Sensor Data

As agricultural implement designs have progressed in recent years, there has been an increase in hydraulic power demand from the tractor. Current power estimation standards do not accurately estimate hydraulic power demand for implements designed with higher hydraulic power requirements. Several stakeholders, including agricultural producers, tractor and implement manufacturers, and government agencies would benefit from accurate published data on these power requirements. While an increasing amount of operational data available on the Controller Area Network (CAN) of tractors has assisted researchers in more easily obtaining machinery performance data, hydraulic control valve flow rate and pressure measurements are not currently publically available on modern tractor CAN systems. Thus, this study attempted to determine the minimal amount of additional instrumentation needed to measure these parameters. Results validated that CAN-reported valve spool position could successfully predict flow rate when the tractor’s pump was capable of producing a sufficient flow rate to satisfy the overall tractor and implement flow demand. However, this message failed to predict flow rate in all valves whenever the pump became flow-limited due to circumstances including multiple valves actuated simultaneously, low engine speeds, or high circuit pressure requirements. A customized orifice flowmeter was found to be a compact, cost-effective solution to estimate flow rate under such flow-limited pump conditions. A flow rate prediction method was tested incorporating temperature compensation using CAN-reported valve spool position in flow-sufficient conditions and the orifice flowmeter in flow-limited conditions. Mean absolute errors below 3 Lpm (5.5% MAPE) were observed between the predicted flow rate and measurements from a laboratory-based turbine flowmeter for various simulated tests. Once determining the flow rate prediction methodology was acceptable, hydraulic power requirements were analyzed between two no-till air drills utilized for small grain planting operations in Eastern Nebraska. To allow a CAN data logger to serve as the sole data acquisition system, a customized instrumentation integration device, the Sensor CAN Gateway (SCANGate), was developed and used to publish all added pressure sensor data onto the CAN bus. In addition to quantifying both planters’ hydraulic power requirements, comparisons were made between the time and fuel requirements per area for both operations. Advisors: Joe D. Luck & Santosh K. Pitl

CAN bus technology for agricultural machine management research and undergraduate education

To evaluate each agricultural operation, we need data to measure and monitor the mechanization unit performance. Many systems have been developed to determine tractor performance monitoring and optimization (TPMO), but the majority of these systems were not fully adequate. In 1986, the Mercedes Corporation collaborated with Robert Bosch and developed Controller Area Network (CAN) Bus technology. This technology is a communication system in vehicles and allows connections between multiple Electrical Control Units (ECUs). Currently, the improvement in electronic technology has made field operational management easier to monitor. This new CAN Bus technique is becoming widely used application in agriculture to help farmers determine and improve field efficiency, while decreasing equipment costs using the data obtained from tractors. Prior to CAN Bus, ECUs were developed to make communication between systems easier, faster, and more efficient without using point to point connection. Modern tractors are supplied with monitors to show engine rpm, forward speed, and slip percentage. CAN messages depend on the broadcast system and can be controlled and filtered through dedicated software such as Vector Canoe and CAN Analyzer. These messages are continuously updating information about the engine, power train, equipment, power take off, hydraulic system, and others. The emergence of the new technology of extensive field monitoring and data collection programs has caused many operational practices to be abandoned. For example, in the last century, the need for measuring fuel consumption at each speed, gear shift and to the whole operation has been reduced with the application of the telemetry systems. Also, we can reduce the amount of labor, tools, operational costs and time required. A major purpose for evaluating agricultural machinery is to obtain accurate information and assessment about different agricultural practices. This information provides the operators with feedback that can assist the operator in acquiring and improving the field data, managing limited resources, and acting accordingly. Such data logging systems will help the users of agricultural machinery have a good understanding of performance activities by gathering and saving the data efficiently and make a significant progress in improving performance parameters

Sensors Application in Agriculture

Novel technologies are playing an important role in the development of crop and livestock farming and have the potential to be the key drivers of sustainable intensification of agricultural systems. In particular, new sensors are now available with reduced dimensions, reduced costs, and increased performances, which can be implemented and integrated in production systems, providing more data and eventually an increase in information. It is of great importance to support the digital transformation, precision agriculture, and smart farming, and to eventually allow a revolution in the way food is produced. In order to exploit these results, authoritative studies from the research world are still needed to support the development and implementation of new solutions and best practices. This Special Issue is aimed at bringing together recent developments related to novel sensors and their proved or potential applications in agriculture