北海道大学 大学院農学院 修士論文発表会，2015 年 2 月 9 日，10 日

Development of a Real-time Quality Sensor for Wheat on a Combine Harvester
Division of Environmental Resources Chair of Bioproduction Engineering Vehicle Robotics Ziyi Fan

1. Introduction
Moisture content and temperature of the grain are the essential parameters that determine the storage life ofgrain and protein content determines the process and usage of wheat grain harvested. In this research, todevelop a real-time quality sensor for moisture and protein prediction of wheat, based on reflectancespectroscopy, calibration based on static experiments and prediction on a grain conveyor of a combine
harvester were performed. Additionally, experimental trials for assessing the feasibility of yield monitoring bysingle wavelength reflectance was conducted.

2. Methods
1) Materials Wheat samples used in the present study include two places of production, Sapporo from 2011
to 2014 and Tokachi region in 2013 and 2014. A mini-spectrometer had been used to get reflectance spectra ofwheat samples in the range of 435 nm to 1144 nm. A grain conveyor separated from a specified combine
harvester was used to conduct experiments of real-time prediction and yield monitoring.
2) Calibration and prediction Reference moisture and protein contents data and pretreated reflectancespectra were used for calibration and prediction. Partial least squares regression were used for calibration.
Calibration and prediction were performed based on only data of static experiments for evaluating thefeasibility of the data processing methods. Then, models of moisture and protein were calibrated based on thedata from 2011 to 2014 of Sapporo and the data of 2013 and 2014 of Tokachi region and used for theprediction in real time on the grain conveyor. In addition, preliminary experiments of yield monitoring werealso conducted.

3. Results and Discussion
1) Real-time prediction Numbers of component of
PLS models were 12 in both of moisture and protein
contents calibrations. There were four samples forreal-time experiments on the grain conveyor and twotimes of each sample were performed to verify thereproducibility. The results of errors of two times

Table 1 Results of real-time prediction
Prediction
Moisture(%)
Protein(%)

Reference
1st Errors
2nd Errors
Reference
1st Errors
2nd Errors

No. 1

No. 2

No. 3

No. 421.57
-0.90
-0.15
12.13
-0.33
-0.24

22.57
-0.72
-0.38
12.63
-0.22
-0.50

19.00
0.12
0.13
10.93
0.16
0.01

19.37
-0.64
-0.11
11.17
-0.19
0.06

prediction were shown in Table 1. The overall prediction errors were not more than 0.9% and mostly less than
0.5%. Prediction of moisture and protein contents performed well and shown fine reproducibility.
2) Yield monitoring The relationship between integral of reflectance of a single wavelength and weightreference of wheat grains transported was used for yield monitoring by simple least squares regression. The
feasibility of this method was confirmed.

4. Conclusions
Reflectance spectroscopy was used to develop a real-time wheat quality sensor on a combine harvester
mainly for moisture and protein contents. The models performed good prediction accuracy and reproducibility.
Additionally, experiments of yield monitoring by integral of reflectance of specified single wavelength was
conducted tentatively and confirmed the feasibility of the present methodology.