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Research Corner
Page Content The Research Corner is where members conducting research share the cutting-edge work taking place throughout our scientific community. Watch these short, on-demand, research presentations highlighting the current work of up-and-coming contributors in our field!
Student and Early Career members in academia, here is your chance to present your research year-round!
Upload a .mp4 video and share your work in under 10 minutes:
- Get visibility and recognition of your work.
- Learn about research from your peers at other universities.
- Introduce yourself to future employers in academia and industry.
- Build your presentation skills.
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Student Research Videos
Interested in learning more about a project or the accomplishments of one of the presenters? Simply click on each student's name to pull up their contact information in our
Member Directory.
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Blend Matters: Interaction of Rice Cultivars on Milling, Physicochemical and End Use Traits
Presenter:
Bindu Regonda
Advisor: Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
The research discusses the impact of blending/commingling different rice cultivars on milling yield and rice quality in Arkansas. Specifically, it explores the effects of commingling contemporary long grain varieties, providing insights into physicochemical properties, milling yield, and end-use traits. The research aims to assist growers and processors in making decisions that align with their economic interests by understanding the implications of rice commingling.
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Rice Gelatinization Temperature Prediction using the Rapid Visco Analyser vis-à-vis the Traditional DSC Method
Presenter: Evans Ameyaw Owusu
Advisor: Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
Discover the efficiency of the Rapid Visco Analyzer (RVA) for measuring rice gelatinization temperatures compared to traditional methods. This study evaluates RVA's precision and accuracy against Differential Scanning Calorimetry (DSC) using contemporary rice cultivars from Arkansas. The results reveal RVA's potential as a cost-effective and rapid alternative, offering precise measurements and promising applications in both industry and academia.
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Optimizing of Parboiling Process for Contemporary Rice Cultivars using a Custom-made Parboiling Unit
Presenter: Evans Ameyaw Owusu
Advisor Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
This research investigates the delicate balance of gelatinization degrees crucial for achieving maximum head rice yield and optimal quality in parboiled rice. Utilizing 26 diverse contemporary cultivars from Arkansas, the study delves into the ideal soaking temperatures, durations, and steaming conditions. By identifying these optimal parameters, the study will enhance the quality of parboiled rice including the head rice yield, texture, and color, while also conserving energy efficiently
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Analyzing Milled Rice Breakage Patterns Under Diverse Environmental Conditions
Presenter: Devisree Chukkapalli
Advisor: Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
Explore the intricacies of rice breakage and its implications for the agricultural industry. Through controlled experiments, the study replicates real-world conditions to gain insights into optimal storage and transportation environments. Additionally, investigations into sub-freezing storage shed light on further aspects of rice quality. The ultimate goal is to improve storage conditions, minimize waste, and enhance the overall quality of milled rice, facilitating its transportation and storage for both farmers and industries.
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Chalkiness detection in rice using non-destructive methods and machine learning (ML)
Presenter: Christabel Yeboah Edina Tachie
Advisor: Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
The research discusses the effect of chalkiness, a quality defect in rice, its current detection methods and investigates the combination of machine learning techniques and hyperspectral imaging (HSI) as a non-destructive method for rapid identification of chalky rice. The aim is to use convolutional neural network (CNN) techniques and image data from HSI to create a model with good accuracy and precision in detecting chalkiness in rough rice. This will improve head rice yield by eliminating defective rice before milling to improve the market value of rice, decrease cost, serve as quality control, and a reliable method for faster and large-scale detection of rice chalk.
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Impacts of drying and storage on physiological characteristics of seed rice
Presenter: Samuel Olaoni
Advisor: Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
Improper drying, which causes the fissuring of rice kernels, may influence the seed's overall physiological health. As a result, this research investigated the impact of some drying and storage conditions on the physiological characteristics of seed rice, specifically its germination and vigor. The results of this study aim to provide growers with valuable insights for optimizing seed preservation in the industry while ensuring high crop yields.
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Rice Instantization and Enrichment Issues
Presenter: Faith Ouma
Dr. Griffiths Atungulu
University of Arkansas, Fayetteville, Arkansas
With busy lifestyles and growing health consciousness, the demand for convenient yet nutritious food options has never been higher. This research focuses on enhancing the nutritional quality and convenience of rice through a combination of instantization and germination techniques. By enriching brown rice with gamma-aminobutyric acid (GABA) through germination and subsequently instantizing it, we aim to create a novel rice product that offers both enhanced nutritional benefits and quick cooking convenience. This research will help address consumers’ dietary needs as well as provide a healthier and more convenient alternative to traditional rice products.
How to Submit a Video- Videos must be 10 minutes or less in length and in .mp4 format.
- The submitter must be a current student member or early career member of Cereals & Grains Association.
- Each video must be based on an original idea from the author. Secondary contributors (such as professors) may be consultants but not major contributors.
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