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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Publications at this Location » Publication #391514
Research Project: Assessment of Quality Attributes of Poultry Products, Grain, Seed, Nuts, and Feed

Location: Quality and Safety Assessment Research Unit

Title: Investigating Density Increase During Grain Drying With a Microwave Sensor

Author
item Lewis, Micah
item Trabelsi, Samir

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 3/22/2022
Publication Date: 7/20/2022
Citation: Lewis, M.A., Trabelsi, S. 2022. Investigating Density Increase During Grain Drying With a Microwave Sensor. ASABE Annual International Meeting. https://doi.org/10.13031/aim.2201136.
DOI: https://doi.org/10.13031/aim.2201136

Interpretive Summary:

Technical Abstract: When agricultural goods are harvested, they are dried during, and some cases before, storage to ensure preservation of quality. As they are dried, heat and mass transfer occur simultaneously as moisture is removed from the product over time. As moisture is removed from the product, the mass decreases. Shrinkage also occurs causing the volume of the product to decrease. Thus, changes in density occur continuously throughout the product during drying. Density is an important parameter because it can be indicative of parameters such as crop yield and meat content. However, it is difficult to measure at “local” locations within a bed of stored grain or seed. The bulk density can be calculated in most instances; however, it has been shown that the density at different locations within a bed vary. To this end, the real-time change in density was modeled as corn and wheat dried within an eighth-scale drying system. Beds of materials with volume ranging from 158,000 to 180,000 cm3 were used for drying trials. The models were verified by using empirical data obtained from a microwave sensor used to determine “local” density from measurements of the dielectric properties. The microwave sensor predicted density with an accuracy of < 0.01 g/cm3. Verification of the models confirmed their accuracy and showed that density was successfully modeled at various locations within the bed. Knowledge of density in real-time can aid in monitoring the quality of the product during drying and provide even more accuracy in shrinkage predictions.