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Research Article

Measurement and modelling of dielectric properties of different animal feed resources as a function of feed type and moisture content

ORCID Icon, , , ORCID Icon, & ORCID Icon
Pages 273-286 | Received 25 Feb 2021, Accepted 28 Jul 2021, Published online: 21 Oct 2021
 

Abstract

Dielectric properties of any particular material will determine the level of microwave (MW) heating. Therefore, measurement of the dielectric properties of MW treatment subject materials is necessary. This study investigated the dielectric properties of six roughages and three concentrate animal feeds across the microwave frequency range of 1 × 109 to 5 × 109 Hz. Six treatment groups, named control (at equilibrium moisture constant), oven dried (0% moisture), 25% moisture added, 50% moisture added, 75% moisture added, and 100% moisture added groups were prepared for the study. Three separate replications and five observations for each replication were used to assess the dielectric properties of these materials. The results showed that for increasing moisture content, from oven-dried, though the control status, to 100% added moisture, both the dielectric constant (real part) and the dielectric loss factor (imaginary part) increased for both the roughages and concentrates. However, the responses were not linear. The oven-dried plant samples' dielectric properties were very low compared with those of the higher moisture content samples. Thus, the sample's moisture content was the dominant contributor to the feed samples' dielectric behavior. Among all the feed samples, faba bean and wheat grain showed the highest response to added moisture. Mathematical models were developed to explain the dielectric properties of feeds as a function of frequency and moisture content. The goodness of fit (r2) for these models' real part varied between 0.85–0.99 for roughage and 0.98–0.99 for concentrate feed type. On the other hand, the goodness of fit for the imaginary part varied between 0.59–0.78 for roughage, and 0.81–0.93 for concentrate feeds.

Acknowledgments

The authors want to acknowledge Dr. Ravneet Kaur, Laboratory manager, Dookie Analytical laboratory, for assisting with the laboratory work.

Disclosure statement

There is no conflict of interest to report for this research work.

Additional information

Notes on contributors

Md Safiqur Rahaman Shishir

Md Safiqur Rahaman Shishir is currently a Ph.D. student at the University of Melbourne, Faculty of Veterinary and Agricultural Sciences. He received his bachelor's degree in Animal Husbandry from Bangladesh Agricultural University (BAU), Bangladesh, and a master's degree in Animal Nutrition from the Department of Animal Nutrition, BAU. He is interested in the application of novel processing techniques on animal feed for improving quality.

Mohan Jacob

Mohan Jacob is a Professor in Electrical Engineering and Associate Dean Research Education at James Cook University. He obtained his Ph.D. from University of Delhi in 1999. He is actively involved in non-destructive characterization of various materials at microwave frequencies and cryogenic temperatures. He is also involved in developing sustainable, natural resource-based environmentally friendly biomaterials and electronic and biomedical devices. He developed graphene from non-conventional sustainable sources using plasma-enhanced chemical vapor deposition. He published over 150 peers reviewed journal papers and conference papers.

Kenneth Leong

Kenneth Leong received the B.Eng. (with honors) and a Ph.D. degree in electrical engineering from the James Cook University, Townsville, QLD, Australia, in 1994 and 2000, respectively. He is currently in the lecturer position in the School of Engineering, James Cook University, where he is involved with microwave measurements on materials including high-$T_$thin-film superconductors and dielectrics for applications in wireless communications. His novel development is known as the TMQF, which is currently being utilized at the James Cook University for accurate measurements of the surface resistance parameter of high-$T_{c}$thin-film superconductor.

Long Cheng

Long Cheng graduated from Lincoln University (New Zealand's specialist land-based university), New Zealand, in 2008, with a Bachelor of Agricultural Science with Honours. In 2009, Dr. Cheng commenced his Ph.D., investigating the use of nitrogen isotopic fractionation as a biomarker to indicate nitrogen use efficiency of ruminants, graduating in 2013 from Lincoln University, New Zealand. Dr. Cheng's research interest includes energy and nitrogen metabolism, Precision agriculture, Nitrogen use efficiency in ruminant animals.

Brendan Cullen

Brendan Cullen is a Senior lecturer in Sustainable Agriculture (Pasture Systems) in the Faculty of Veterinary & Agricultural Sciences at the University of Melbourne. Over the last 15 years, Brendan has worked on a series of research projects with the dairy and red meat industries to understand the impacts of projected climate changes on livestock production businesses across Australia. The research aims to identify industry pathways that are adapted to a variable and changing climate, using farms systems modelling approaches. Brendan has published more than 40 peer-reviewed scientific papers and currently supervise 3 Ph.D. students working in this field. He also teaches into the Bachelor and Masters coursework programs on pasture and livestock production, livestock production systems, dairy systems, and climate change adaptation.

Graham Brodie

Graham Brodie is an Associate Professor in the Faculty of Veterinary and Agricultural Sciences. He earned his electrical engineering degree from James Cook University and worked in the electrical power industry before turning his hand to academia. Dr. Brodie's research interests include microwave heating of bio-materials; using microwaves for sensing and communication in agriculture and forestry; improving water use efficiency in agriculture; producing renewable energy on farms; on-farm animal waste management; and applications of Geographic Information System (GIS) and Remote Sensing technologies in agriculture and archaeology.

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