Aplikasi VIS/NIR spectroscopy dan partial least square regression untuk pendugaan nilai warna kulit buah cabai rawit

Kusumiyati Kusumiyati, Ine Elisa Putri, Wawan Sutari, Jajang Sauman Hamdani

Abstract


Warna kulit buah buah cabai rawit (Capsicum Frutescens L.) merupakan salah satu indikator dari kematangan buah. Visible/near infrared (Vis/NIR) spectroscopy merupakan teknologi alternatif untuk memprediksi warna kulit buah yang dikombinasikan dengan partial least square regression (PLSR). Penelitian ini bertujuan untuk memprediksi warna kulit buah cabai rawit menggunakan Vis/NIR spectroscopy. Analisis di Laboratorium Hortikultura, Fakultas Pertanian, Universitas Padj+!adjaran. Sampel yang digunakan yaitu buah cabai rawit var. Domba. Sampel dibagi ke dalam 3 grup, buah cabai rawit hijau, oranye, dan merah. Spectrometer yang digunakan yaitu NirVana AG410 dengan panjang gelombang 300-1065 nm dengan interval 3 nm. Semua data absorban dikoreksi dengan menggunakan metode prapengolahan spektra multiplicative scatter correction (MSC), orthogonal signal correction (OSC), dan standard normal variate (SNV). Hasil penelitian menunjukkan bahwa prapengolahan spektra terbaik untuk memprediksi L*dan b* pada buah cabai rawit yaitu PLSR+OSC sedangkan a* yaitu PLSR+SNV. Nilai akurasi L* dengan OSC yaitu R kalibrasi = 0,99 dan b* dengan OSC yaitu R kalibrasi = 0,76. Akurasi pada a* dengan SNV menghasilkan R kalibrasi = 0.99. Penelitian ini membuktikan bahwa Vis/NIR spectroscopy dan PLSR memiliki akurasi yang tinggi dan dapat digunakan untuk memprediksi warna kulit buah cabai rawit.

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.


Keywords


data absorban, kualitas buah, model kalibrasi, panjang gelombang, spektra koreksi

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References


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DOI: https://doi.org/10.21831/jps.v1i1.47930

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