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Abstrak . Total padatan terlarut (TPT) dan vitamin C merupakan suatu komponen penting dalam mangga. Total padatan terlarut (TPT) merupakan total unsur atau elemen mineral yang terlarut didalam suatu larutan. TPT disebut juga dengan kadar gula total, karena  kualitas rasa  manis dari buah diukur dengan pengukuran kadar gula. Vitamin C merupakan vitamin yang larut dalam air dan esensial untuk biosintesis kolagen. Pengukuran TPT dapat dilakukan menggunakan alat refraktometer, sedangkan vitamin C diukur menggunakan metode titrasi, serta dengan penggunaan gelombang elektromagnetik seperti NIRS. Penelitian ini bertujuan menguji dan mengevaluasi teknologi NIRS sebagai metode cepat dan tepat dalam memprediksi kandungan TPT dan vitamin C pada mangga dengan metode Partial Least Squares (PLS) serta menentukan metode koreksi spektrum yang terbaik dan akurat untuk memprediksi TPT dan vitamin C pada mangga dengan menggunakan pre-treatment Baseline Correction, dan Multiplicative Scatter Correction (MSC). Penelitian ini menggunakan buah mangga jenis Arumanis, yang berjumlah 30 sampel. Prediksi TPT dan vitamin C dengan NIRS menggunakan alat FT-IR IPTEK T-1516. Pengolahan data menggunakan Unscramble software® X version 10.5. Hasil penelitian menunjukkan prediksi TPT pada mangga dengan metode Partial Least Squares (PLS) menghasilkan sufficient performance dengan nilai RPD yang didapat yaitu 1,29 dan metode koreksi terbaik pada pendugaan TPT ialah Baseline Correction dengan nilai RPD 1,53, r sebesar 0,4783 , R2 sebesar 0,5600 dan RMSEC sebesar 2,9048. Sedangkan hasil prediksi vitamin C pada mangga menghasilkan good model performance dengan nilai RPD yang didapat yaitu 2,18 dan metode koreksi terbaik pada pendugaan vitamin C ialah MSC dengan nilai RPD 2,36, r sebesar 0,9026, R2 sebesar 0,8147 dan RMSEC sebesar 4,4067. Prediction of Soluble Solids Content (SSC) and Vitamin C on Mangoes (Mangifera Indica L) Using Near Infrared Spectroscopy (NIRS) with Partial Least Square (PLS) Method Abstract. Soluble solids content (SSC) and vitamin C are important components in mangoes. Soluble solids content (SSC) is the total element or mineral element dissolved in a solution. SSC is also called total sugar content, because the quality of the sweet taste of the fruit is measured by measuring the total sugar. Vitamin C is a water-soluble vitamin and essential for collagen biosynthesis. Measurement of SSC can be done using a refractometer, while vitamin C is measured using the titration method, and by the use of electromagnetic waves such as NIRS. This study aims to test and evaluate NIRS technology as a fast and appropriate method in predicting the content of SSC and vitamin C in mangoes using the Partial Least Squares (PLS) method and determining the best and accurate spectrum correction method to predict SSC and vitamin C in mango by using pre-treatment Baseline Correction, and Multiplicative Scatter Correction (MSC). This study used Arumanis mangoes, which amounted to 30 samples. Prediction of TPT and vitamin C with NIRS using FT-IR tool of Science and Technology T-1516. Processing data using the Unscramble software® X version 10.5. The results showed that the prediction of SSC on mangoes using the Partial Least Squares (PLS) method resulted in sufficient performance with the obtained RPD value is 1,29 and the best correction method in estimating SSC is Baseline Correction with a value of RPD is 1,53, r is 0,4783, R2 is 0,5600 and RMSEC is 2,9048. While the prediction results of vitamin C on mangoes obtain a good performance model with the value of RPD obtained is 2,18 and the best correction method for estimating vitamin C is MSC with a value of RPD is 2,36, r is 0,9026, R2 is 0,8147 and RMSEC is 4,4067.

jurnal ilmiah mahasiswa pertanian

Prediksi Kadar Total Padatan Terlarut (TPT) dan Vitamin C Buah Mangga Arumanis (Mangifera indica L) Menggunakan Near Infrared Spectroscopy (NIRS) dengan Metode Partial Least Square (PLS)