Development of Partial Least Square (PLS) Prediction Model to Measure the Ripeness of Oil Palm Fresh Fruit Bunch (FFB) by Using NIR Spectroscopy
作者： Zaqlul Iqbal , Sam Herodian , Slamet Widodo
DOI: 10.1088/1755-1315/347/1/012079
关键词:
摘要: In order to develop a model for predicting the oil palm Fresh Fruit Bunch (FFB) ripeness, rapid and non-destructive method such as NIR spectroscopy is utilized. This has shown its capability determine quality of some crops by their internal chemical contents. The objective research investigate feasibility predict water content in FFB developing calibration model. Sixty samples were scanned using NIRFlex N-500 spectrometer ranging from 1000 2500nm. Water measured after scanned. To model, Partial Least Square (PLS) Regression pre-processing conducted Unscrambler X 10.3. results showed that PLS performs well establish MSC with r2, factor, RSMECV, RPD are 0.93, 3, 5.24, 2, respectively. On other hand, could not be used establishing because result did meet statistic parameters. For laboratory measurement, FFB; but it was limited taken same variety plantation. However, Spectroscopy proposed promising detect ripeness FFB.
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