Yield monitors have become an indispensable part of precision agriculture systemsbecause of their ability to measure the yield variability. Accurate yield monitor data availabilityis essential for the assessment of farm practices. The current technology of measuring grainyields is prone to errors that can be attributed to mass flow variations caused by the mechanismswithin a grain combine. Because of throughput variations, there are doubts regarding thecorrelation between the mass flow measurement and the actual grain volume produced at aspecific location. Another inaccuracy observed in yield monitor data can be attributed to inexactcut-widths values entered by the machine operator.To effectively address these yield monitor errors, two crop mass flow sensing deviceswere developed and used to correct yield monitor data. The two quantities associated with cropmaterial mass flow that were sensed were tension on the feeder housing drive chain and thehydraulic pressure on the threshing cylinder's variable speed drive. Both sensing approacheswere capable of detecting zero mass flow conditions better than the traditional grain mass flowsensor. The alternative sensors also operate without being adversely affected by materialtransport delays. The feeder housing-based sensor was more sensitive to variations in cropmaterial throughput than the hydraulic pressure sensor. Crop mass flow is not a surrogate forgrain mass flow because of a weak relationship (R2 andlt; 0.60) between the two quantities. The cropmass flow signal does denote the location and magnitude of material throughput variations intothe combine. This delineation was used to redistribute grain mass flow by aligning grain andcrop mass flow transitions using sensor fusion techniques. Significant improvements (?? = 0.05)in yield distribution profile were found after the correction was applied.To address the cut-width entry error, a GIS-based post-processing algorithm wasdeveloped to calculate the true harvest area for each yield monitor data point. Based on theresults of this method, a combine operator can introduce yield calculation errors of 15%. Whenthese two correction methods applied to yield monitor data, the result is yield maps withdramatically improved yield estimates and enhanced spatial accuracy.

Master of Agribusiness / Department of Agricultural Economics / Gregory Ibendahl / One of the latest buzzes amongst agriculture is the storage and analysis of “Big Data.” There are a number of questions surrounding the quality, quantity, and capacity of big data to form real-world decisions based upon past information. Much like the teachings of history, the storybook that big data can reveal about a grower’s operation may hold the answers to the question of: “what is necessary to increase food production which will be required to feed an ever-growing world?” With the increase in interest in precision agriculture, sustainability practices, and the processing of the immense spatial dataset generated on the farm, the next challenge at hand will be in determining how to make technology not only streamlined, but also profitable. Over the past few years, precision agriculture technology has become widely adopted as an agronomic decision making tool. Much like a scientific experiment, the greater the number of similar observations, the greater the degree of confidence can be placed upon a decision. As a means of increasing the number of observations that a farmer can use to base a decision upon, there is becoming increasing demand in being able to combine the data of similar farming operations in order to increase the size and scope of the dataset to generate better decisions benefitting many farms instead of just one. The growing interest in forming community data pools for farm data demonstrates the need for a study for determining how farming practices can be properly benchmarked. The goal was be to evaluate how to use farm data to make economic decisions in a similar manner as one would make agronomic decisions using similar observations. The objective was to design the proper protocol for benchmarking the farm’s potential, and evaluating potential increases in technical efficiency by adopting precision agriculture technology. To accomplish this, a data envelopment analysis was conducted using scale efficiency as a means of determining the frontier of efficient farms. The resounding goal for this study in the future will be to use the model as a means of implementing the secondary process of pooling precision agriculture data to analyze efficiencies gained by the adoption of technology. By demonstrating the value of generating peer groups to increase observations and refine farming practices, farmers can find increased profitability and efficiency by using resources that may already be held within the operation.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Precision Farming (PF) has been studied mainly in soybean, corn and wheat crops, and its use has been increasing in commercial fields. However, in irrigated rice crop, the use of this technology has not yet been fully evaluated, as well as its tools, machinery and equipment such as yield mapping systems. This study aimed to evaluate the precision and accuracy of the response to variations in grain flow of a yield mapping system equipped with an optical sensor in irrigated rice crop both in leveled or non leveled fields. The evaluations were carried out during the 2008/2009 agricultural season on a commercial farm located in the city of Cachoeira do Sul-RS. This evaluation analyzed the behavior of the system when submitted to increased and decreased variations of flow as well as abrupt changes in grain flow using plots that simulated the innumerous situations that occur in a field. To evaluate the behavior of the system, parallel instrumentation was installed on the same harvester, which served as reference. Under the evaluated conditions, the system, presented distortions in accuracy, not responding adequately to all the variations it was submitted to. In the accumulated weight evaluation of each plot, the percentage difference was greater than 3% in almost all the treatments. The results indicate that the evaluated yield monitor did not have satisfactory performance in most of the treatments applied. The Yield data had its quality reduced by the inaccuracy of the speed data provided by the GPS receiver, which makes it unsuitable tool for PF in irrigated rice.crop. / A Agricultura de Precisão (AP) tem sido estudada principalmente nas culturas da soja, milho e trigo, sendo que seu uso tem sido crescente em lavouras comerciais. No entanto, na cultura do arroz irrigado, o uso dessa tecnologia ainda não foi devidamente avaliado, nem tampouco suas ferramentas, máquinas e equipamentos como sistemas para mapeamento da produtividade. Este trabalho teve por objetivo avaliar a precisão e a acurácia da resposta a variações de fluxo de grãos de um sistema de mapeamento de produtividade dotado de sensor volumétrico ótico na cultura do arroz irrigado, em terreno sistematizado e não sistematizado. As avaliações foram realizadas na safra 2008/2009 em uma lavoura comercial localizada no município de Cachoeira do Sul, RS. Foi analisada a resposta do sistema quando submetido a variações de aumento e diminuição de fluxo e, também, a mudanças abruptas no fluxo de grãos, por meio de parcelas que simularam as inúmeras situações que ocorrem numa lavoura. Para avaliar o comportamento do sistema foi instalada uma instrumentação paralela na mesma colhedora, que serviu como referência. Nas condições avaliadas, o sistema apresentou distorções em sua acurácia, não respondendo adequadamente a todas as variações a que foi submetido. Na avaliação de totalização da massa de grãos colhida em cada parcela, a diferença percentual foi superior a 3% em quase todos os tratamentos. Os resultados indicam que o monitor de produtividade avaliado não obteve um desempenho satisfatório na maioria dos tratamentos aplicados. Os dados de produtividade tiveram diminuída a sua qualidade pela imprecisão dos dados de velocidade fornecidos pelo receptor GPS, o que não torna adequada a sua utilização como uma ferramenta da AP na cultura do arroz irrigado.

No description available.