| Title |
Moisture content prediction of Iranian wheat using dielectric technique
|
|---|---|
| Published in |
Journal of Food Science and Technology, September 2012
|
| DOI | 10.1007/s13197-012-0845-2 |
| Pubmed ID | |
| Authors |
Mahmoud Soltani, Fatemeh Alimardani |
| Abstract |
The moisture measurement is the most important criteria in harvesting and post harvesting processing of wheat. This paper investigates the moisture dependent dielectric constant and calibration equation of three most cultivated wheat varieties in Iran. An instrument with a cylindrical capacitive sensor was used to measure the dielectric constant of grain at different moisture contents. Samples were prepared at five levels of moisture content. To validate the proposed equations, the dried material dielectric constant was estimated and compared with the measured ones. Homographic regression models showed an acceptable prediction of dried wheat dielectric constant. Results showed that the calibration equation obtained for Shahriar variety was able to predict the moisture content of other varieties confidently. The lowest value of R (2) = 0.985 between predicted and reference moisture content for Tajan variety is still a good result. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 30% |
| Student > Ph. D. Student | 3 | 30% |
| Researcher | 1 | 10% |
| Unknown | 3 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 40% |
| Agricultural and Biological Sciences | 2 | 20% |
| Unknown | 4 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 September 2015.
All research outputs
#18,427,608
of 22,829,083 outputs
Outputs from Journal of Food Science and Technology
#913
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Outputs of similar age
#128,535
of 168,865 outputs
Outputs of similar age from Journal of Food Science and Technology
#18
of 25 outputs
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