APLIKASI ANALISIS MULTIVARIAT BERDASARKAN WARNA UNTUK MEMPREDIKSI BRIX DAN pH PADA BUAH-BUAHAN - , YOHANITA MAULINA AKBAR ([Yogyakarta] : Universitas Gadjah Mada, 2014)
In this study, Multiple Linear Regression (MLR) was used to predict Brix and pH on climacteric fruit i.e. bananas and tomatoes as well as non-climacteric fruit i.e. strawberry and lime based on RGB and the La*b* color value. Fruits used in this study were in various maturity stage from unripe to ripen. RGB and La*b* color parameters were measured non-destructively using colormeter, meanwhile, the internal quality measurements such as Brix and pH were determined destructively or by conventional procedures in the laboratory. The Unscrambler Â® X 10.3 (CAMO, U.S., OLSO, Norway, the trial version) was used for multivariate analysis. The accuracy of the statistics used in selecting the model MLR was the correlation coefficient (r), Standard Error of Prediction (SEP), and Bias. The minimum limit of the correlation coefficient should be greater than 0.5 (r> 0.5), followed by SEP and bias were small. Result showed that MLR calibration model resulted in good calibration model based on RGB and La*b* for banana, but less satisfactory calibration model for tomato, strawberry, and lime. Therefore, validation model was only used for banana using different samples. The relationship between the actual and predicted values of the MLR models was determined from R2 (coefficient of determination). The best model for predicting Brix and pH of banana based on La*b* color values resulted in the coefficient determination (R2) between actual and prediction values of 0.78 and 0.61 for validation model. Keywords: RGB, La*b*, Brix, pH, multivariate analysis, Multiple Linear Regression (MLR)