A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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Subject: search.filters.subject.Agriculture engineering

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    Prediction Of Air Pollutant From Poultry Houses By A Modified Gaussian Plume Model
    (2017) Yang, Zijiang; Torrents, Alba; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Concentrated animal feeding operations release a variety of potential pollutants, such as ammonia and particulate matters (PM). Field measurements are time consuming, costly, and only provide a limited amount of spatial and temporal information. Air dispersion models can serve as an alternative solution, especially if coupled with field sampling. The Gaussian plume model (GPM) is a mathematical model that assumes steady state condition. Previous studies have used the GPM to evaluate and analyze source. However, much less is known about utilizing GPM to simulate plumes from horizontal sources, such as the exhaust fans from poultry houses. The purpose of this study is to modify and validate a GPM to predict air pollutant emissions from the poultry houses. Two major assumptions were applied on the model, 1) a virtual releasing point was proposed behind the ventilation fan, and 2) ventilation fan was considered as the dominant wind direction in the model for short distance (< 50 m). The modified model was validated with field experimental data. Performance and sensitivity of the model were also evaluated. Fraction of predictions within a factor of two of observations (FAC2) of NH3 and PM were 0.609 and 0.625. Model-predicted concentrations of NH3 were 1.5 times of the measured values on average. Model-predicted concentrations of PM was 0.98 times of the observed values on average.
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    Design and Pilot Study for an Efficient High-Throughput Automated Computer-Vision Guided Intelligent De-Calyxing Machine for Post-Harvest Strawberry Processing
    (2016) Lin, John; Tao, Yang; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Strawberries harvested for processing as frozen fruits are currently de-calyxed manually in the field. This process requires the removal of the stem cap with green leaves (i.e. the calyx) and incurs many disadvantages when performed by hand. Not only does it necessitate the need to maintain cutting tool sanitation, but it also increases labor time and exposure of the de-capped strawberries before in-plant processing. This leads to labor inefficiency and decreased harvest yield. By moving the calyx removal process from the fields to the processing plants, this new practice would reduce field labor and improve management and logistics, while increasing annual yield. As labor prices continue to increase, the strawberry industry has shown great interest in the development and implementation of an automated calyx removal system. In response, this dissertation describes the design, operation, and performance of a full-scale automatic vision-guided intelligent de-calyxing (AVID) prototype machine. The AVID machine utilizes commercially available equipment to produce a relatively low cost automated de-calyxing system that can be retrofitted into existing food processing facilities. This dissertation is broken up into five sections. The first two sections include a machine overview and a 12-week processing plant pilot study. Results of the pilot study indicate the AVID machine is able to de-calyx grade-1-with-cap conical strawberries at roughly 66 percent output weight yield at a throughput of 10,000 pounds per hour. The remaining three sections describe in detail the three main components of the machine: a strawberry loading and orientation conveyor, a machine vision system for calyx identification, and a synchronized multi-waterjet knife calyx removal system. In short, the loading system utilizes rotational energy to orient conical strawberries. The machine vision system determines cut locations through RGB real-time feature extraction. The high-speed multi-waterjet knife system uses direct drive actuation to locate 30,000 psi cutting streams to precise coordinates for calyx removal. Based on the observations and studies performed within this dissertation, the AVID machine is seen to be a viable option for automated high-throughput strawberry calyx removal. A summary of future tasks and further improvements is discussed at the end.