Abstract
Grain temperature and moisture content (MC) are considered to be principal factors for safe storage of grain.Continuous monitoring of temperatures within grain masses is relatively easy using thermocouples, but monitoring of MCis limited by availability of sensors. However, temperature and relative humidity (RH) can be used to predict grain MC basedon equilibrium moisture content (EMC) equations such as the Modified Henderson, Chung-Pfost, or Oswin. These modelsare limited to quasi-static thermodynamic conditions but do provide a method to predict MC with commercial sensors. Erroranalysis was performed using EMC relationships for wheat to determine the error in grain MC prediction due to sensor error.EMC prediction errors were found to be .0.25% to .0.65% MCdb between the RH ranges of 20% to 70% RH. At higher RHlevels, prediction error increased substantially. Sensor error was set to .2% RH and .0.4.C, for the error analysis. The sensorerror was adopted from a commercial sensor that could be potentially used for a cabled monitoring system. At higher levelsof sensor error (.3% RH, .0.4.C and .4% RH, .0.4.C), prediction error increased from .0.38% to .0.96% MCdb and from.0.65% to .1.29% MCdb , respectively, for the same RH range. Prediction error due to sensor error was found to be of thesame magnitude as the standard errors of regression models developed for wheat. Measurements of sensor accuracy were alsoperformed and accuracy was found to be within or better than rated manufacturer specifications for RH but temperatureaccuracy was less than rated accuracy.
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Claims 7
Claim · model-written summary
Predicted wheat grain moisture errors were .0.25% to .0.65% MCdb at 20% to 70% RH.
- Taxon
- wheat
Triticum aestivume1 - Outcome
- EMC prediction errorse0
- Value
- .0.25% to .0.65% MCdbe0
- Qualifier
- 20% to 70% RHe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“EMC prediction errors were found to be .0.25% to .0.65% MCdb between the RH ranges of 20% to 70% RH”
e1“Erroranalysis was performed using EMC relationships for wheat”
Claim · model-written summary
Wheat grain moisture prediction error increased substantially at higher RH levels.
- Taxon
- wheatTriticum aestivume1
- Outcome
- prediction errore0
- Direction
- increasede0
- Comparator
- higher RHlevelse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“At higher RHlevels, prediction error increased substantially”
e1“Erroranalysis was performed using EMC relationships for wheat”
Claim · model-written summary
With .3% RH and .0.4.C sensor error, predicted moisture error increased from .0.38% to .0.96% MCdb.
Not reportedTaxonQualifier
Verbatim
e0“At higher levelsof sensor error (.3% RH, .0.4.C and .4% RH, .0.4.C), prediction error increased from .0.38% to .0.96% MCdb and from.0.65% to .1.29% MCdb , respectively”
Claim · model-written summary
With .4% RH and .0.4.C sensor error, predicted moisture error increased from .0.65% to .1.29% MCdb.
Verbatim
e0“At higher levelsof sensor error (.3% RH, .0.4.C and .4% RH, .0.4.C), prediction error increased from .0.38% to .0.96% MCdb and from.0.65% to .1.29% MCdb , respectively”
Claim · model-written summary
Sensor-induced prediction error was of the same magnitude as wheat regression model standard errors.
- Taxon
- wheatTriticum aestivume0
- Outcome
- Prediction error due to sensor errore0
- Direction
- same magnitudee0
- Comparator
- standard errors of regression modelse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Prediction error due to sensor error was found to be of thesame magnitude as the standard errors of regression models developed for wheat”
Claim · model-written summary
Measured RH sensor accuracy met or exceeded manufacturer specifications.
Verbatim
e0“accuracy was found to be within or better than rated manufacturer specifications for RH”
Claim · model-written summary
Measured temperature sensor accuracy was below rated accuracy.
Verbatim
e0“temperatureaccuracy was less than rated accuracy”