Investigation on the Integration of Low-Cost NIR Spectrometers in Mill Flour Industries for Protein, Moisture and Ash Content Estimation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Low-Cost NIR Spectrometers
2.2. Investigation on the Effectiveness of Low-Cost Spectrometer NeoSpectra Scanner
2.3. NIR Spectrums Pre-Processing
2.3.1. Multiplicative Scatter Correction
2.3.2. First Derivatives
2.3.3. Smooth Filtering
2.4. Fuzzy Cognitive Maps and Design of the Parameter Estimation Models
3. Experimental Setup and Samples Preparation
Samples Preparation
4. Results Evaluation and Discussion
4.1. Results on the Investigation of Wavelengths’ Effectiveness on Wheat and Flour Chemical Parameters
4.2. Optimization Results of the FCMs Estimation Models
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Appendix B
References
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Sample | Number of Samples | Parameter (%) | Average | Variance | SD | SE |
---|---|---|---|---|---|---|
Wheat | 25 | Protein | 14.25 | 1.77 | 1.33 | 0.27 |
Moisture | 11.30 | 0.74 | 0.86 | 0.17 | ||
Flour | 17 | Protein | 12.50 | 3.62 | 1.904 | 0.462 |
Moisture | 13.00 | 0.12 | 0.342 | 0.082 | ||
Ash | 0.58 | 0.002 | 0.047 | 0.012 |
Weight | Protein Estimator | Selected Wavelength | Moisture Estimator | Selected Wavelength |
---|---|---|---|---|
W1,1 | 3.11 | 2440.50 | 2.43 | 2487.05 |
W1,2 | 3.58 | 2381.07 | 0.03 | 2194.07 |
W1,3 | 0.17 | 2366.66 | 0.61 | 1759.74 |
W1,4 | −0.11 | 1380.79 | 3.21 | 1736.30 |
W1,5 | 0.18 | 1375.93 | −1.52 | 1728.63 |
W2,1 | 18.00 | 22.48 | ||
W2,2 | 10.23 | 5.24 | ||
W2,3 | 12.95 | 11.17 | ||
W2,4 | −6.69 | −15.38 |
Weight | Protein Estimator | Selected Wavelength | Moisture Estimator | Selected Wavelength (nm) | Ash Estimator | Selected Wavelength (nm) |
---|---|---|---|---|---|---|
W1,1 | 8.00 | 2055.69 | 15.46 | 1933.73 | −9.87 | 1775.71 |
W1,2 | −4.83 | 2044.94 | −14.67 | 1924.22 | 0.01 | 1759.73 |
W1,3 | −7.53 | 1683.97 | −0.16 | 1457.99 | 0.03 | 1751.85 |
W1,4 | 4.05 | 1375.93 | 0.03 | 1405.59 | −0.41 | 1491.35 |
W1,5 | −0.71 | 1371.10 | −0.54 | 1347.49 | 5.70 | 1480.06 |
W2,1 | 0 | 0 | 0 | |||
W2,2 | 0 | 0 | 0 | |||
W2,3 | −0.08 | 0.05 | 0.01 | |||
W2,4 | 9.01 | 12.75 | 1.97 |
Sample | Parameter (%) | FCM Model RMSE | PLS Model RMSE |
---|---|---|---|
Wheat | Protein | 0.581 | 0.65 |
Moisture | 0.412 | 1.93 | |
Flour | Protein | 1.06 | 2.40 |
Moisture | 0.09 | 0.38 | |
Ash | 0.020 | 0.055 |
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Boglou, V.; Verginadis, D.; Karlis, A. Investigation on the Integration of Low-Cost NIR Spectrometers in Mill Flour Industries for Protein, Moisture and Ash Content Estimation. Sensors 2023, 23, 8476. https://doi.org/10.3390/s23208476
Boglou V, Verginadis D, Karlis A. Investigation on the Integration of Low-Cost NIR Spectrometers in Mill Flour Industries for Protein, Moisture and Ash Content Estimation. Sensors. 2023; 23(20):8476. https://doi.org/10.3390/s23208476
Chicago/Turabian StyleBoglou, Vasileios, Dimosthenis Verginadis, and Athanasios Karlis. 2023. "Investigation on the Integration of Low-Cost NIR Spectrometers in Mill Flour Industries for Protein, Moisture and Ash Content Estimation" Sensors 23, no. 20: 8476. https://doi.org/10.3390/s23208476