Aplikasi VIS/NIR spectroscopy dan partial least square regression untuk pendugaan nilai warna kulit buah cabai rawit
Ine Elisa Putri, Universitas Padjadjaran, Indonesia
Wawan Sutari, Universitas Padjadjaran
Jajang Sauman Hamdani, Universitas Padjadjaran
Abstract
Application of VIS/NIR spectroscopy and partial least square regression for estimation of skin color in cayenne pepper fruit
The skin fruit color of cayenne pepper (Capsicum Frutescens L.) is one of indicators of fruit maturity. Visible/near infrared (Vis/NIR) spectroscopy is alternative technology to predict of skin color fruit combined with partial least square regression (PLSR). The research was aimed to predict skin color fruit of cayenne pepper using Vis/NIR spectroscopy. Analysis at Horticulture Laboratory, Faculty of Agriculture, Universitas Padjadjaran. The samples used was cayenne pepper var. Domba. The smples were divided into 3 groups, green, orange red cayenne pepper. The spectrometer used was NirVana AG410 spectrometer with 300 to 1065 nm with 3 nm intervals. All of absorbance data were pre-treated using spectra correction methods including multiplicative scatter correction (MSC), orthogonal signal correction (OSC) dan standard normal variate (SNV). The result showed that the best spectra correction method for predicting L*and b* in cayenne pepper was PLSR+ OSC while a*was PLSR+ SNV. The accuracy value of * with OSC is R calibration = 0.99 and b*with OSC is R calibration = 0.76. This research resumed that Vis/NIR spectroscopy and PLSR have high accuracy and can be used to predict the skin color of cayenne pepper fruit.
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DOI: https://doi.org/10.21831/jps.v1i1.47930
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