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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
C. B. M. Rashidi
Universiti Malaysia Perlis
Computer Science & IT Electrical & Electronics Engineering Engineering

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Analysis of Near-infrared (NIR) spectroscopy for chlorophyll prediction in oil palm leaves Mohd. Shafiq Amirul Sabri; R. Endut; C. B. M. Rashidi; A. R. Laili; S. A. Aljunid; N. Ali
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.723 KB) | DOI: 10.11591/eei.v8i2.1412

Abstract

Oil palm nutrient content is investigated with using chlorophyll as a representative factor correlated with NIR spectroscopy spectral absorbance. NIR spectroscopy method of sampling have been tested to overcome time consuming, complex chemical analysis procedure and invasive sampling method in order to identify chlorophyll content in an oil palm tree. Spectral absorbance data from range 900 nm to 1700 nm and chlorophyll data, then tested through five pre-processing methods which is Savitzky-Golay Smoothing (SGS), Multiplicative Scatter Correction (MSC), Single Normal Variation (SNV), First Derivative (1D) and also Second Derivative (2D) using Partial Least Square (PLS) regression prediction model to evaluate the correlation between both data. The overall results show, SGS has the best performance for preprocessing method with the results, the coefficient of determination (R2) values of 0.9998 and root mean square error (RMSE) values of 0.0639. In summary, correlation of NIR spectral absorbance data and chlorophyll can be achieved using a PLS regression model with SGS pre-processing technique. Thus, we can conclude that NIR spectroscopy method can be used to identify chlorophyll content in oil palm with using time saving, simple sampling and non-invasive method.
Comparison study of 8-PPM, 8-DPIM, and 8-RDH-PIM modulator FPGA hardware design in term of bandwidth efficiency and transmission rate M. A. Ilyas; Maisara Othman; Rahmat Talib; R. Yahya; M. Yaacob; S. M. Mustam; M. B. Jaafar; C. B. M. Rashidi
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (562.883 KB) | DOI: 10.11591/eei.v9i2.1871

Abstract

In this paper, a performance study of 8-Pulse-Position Modulation (PPM), 8-Digital Pulse Interval Modulation (DPIM), and 8-Reverse Dual Header-Pulse Interval Modulation (RDH-PIM) implementation in Verilog hardware design language is presented. The hardware design is chosen over software design since it could provide much more flexibility in term of transmission rate and reduce the workload of the processor in the complete system. Using 50 MHz clock as the reference data clock speeds, the transmission rate recorded are 11.11 Msymbol/second or 33.33 Mbps, 9.09 Msymbol/s or 27.27 Mbps, and 6.25 Msymbol/s or 18.75 Mbps for 8-RDH-PIM, 8-DPIM, and 8-PPM respectively. We conclude that 8-RDH-PIM modulator design provides better performance in term of bandwidth utilization and transmission rate as compared to 8-PPM and 8-DPIM.
Analysis of Near-infrared (NIR) spectroscopy for chlorophyll prediction in oil palm leaves Mohd. Shafiq Amirul Sabri; R. Endut; C. B. M. Rashidi; A. R. Laili; S. A. Aljunid; N. Ali
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.723 KB) | DOI: 10.11591/eei.v8i2.1412

Abstract

Oil palm nutrient content is investigated with using chlorophyll as a representative factor correlated with NIR spectroscopy spectral absorbance. NIR spectroscopy method of sampling have been tested to overcome time consuming, complex chemical analysis procedure and invasive sampling method in order to identify chlorophyll content in an oil palm tree. Spectral absorbance data from range 900 nm to 1700 nm and chlorophyll data, then tested through five pre-processing methods which is Savitzky-Golay Smoothing (SGS), Multiplicative Scatter Correction (MSC), Single Normal Variation (SNV), First Derivative (1D) and also Second Derivative (2D) using Partial Least Square (PLS) regression prediction model to evaluate the correlation between both data. The overall results show, SGS has the best performance for preprocessing method with the results, the coefficient of determination (R2) values of 0.9998 and root mean square error (RMSE) values of 0.0639. In summary, correlation of NIR spectral absorbance data and chlorophyll can be achieved using a PLS regression model with SGS pre-processing technique. Thus, we can conclude that NIR spectroscopy method can be used to identify chlorophyll content in oil palm with using time saving, simple sampling and non-invasive method.
Analysis of Near-infrared (NIR) spectroscopy for chlorophyll prediction in oil palm leaves Mohd. Shafiq Amirul Sabri; R. Endut; C. B. M. Rashidi; A. R. Laili; S. A. Aljunid; N. Ali
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.723 KB) | DOI: 10.11591/eei.v8i2.1412

Abstract

Oil palm nutrient content is investigated with using chlorophyll as a representative factor correlated with NIR spectroscopy spectral absorbance. NIR spectroscopy method of sampling have been tested to overcome time consuming, complex chemical analysis procedure and invasive sampling method in order to identify chlorophyll content in an oil palm tree. Spectral absorbance data from range 900 nm to 1700 nm and chlorophyll data, then tested through five pre-processing methods which is Savitzky-Golay Smoothing (SGS), Multiplicative Scatter Correction (MSC), Single Normal Variation (SNV), First Derivative (1D) and also Second Derivative (2D) using Partial Least Square (PLS) regression prediction model to evaluate the correlation between both data. The overall results show, SGS has the best performance for preprocessing method with the results, the coefficient of determination (R2) values of 0.9998 and root mean square error (RMSE) values of 0.0639. In summary, correlation of NIR spectral absorbance data and chlorophyll can be achieved using a PLS regression model with SGS pre-processing technique. Thus, we can conclude that NIR spectroscopy method can be used to identify chlorophyll content in oil palm with using time saving, simple sampling and non-invasive method.
Co-Authors A. R. Laili M. A. Ilyas M. B. Jaafar M. Yaacob Maisara Othman Mohd. Shafiq Amirul Sabri N. Ali R. Endut R. Yahya Rahmat Talib S. A. Aljunid S. M. Mustam