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      Pendugaan Karakteristik Fisiko-kimia Buah Apel Menggunakan Spektroskopi Near Infrared

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      Date
      2022
      Author
      Rizky, Diana
      Ahmad, Usman
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      Abstract
      Apel (Malus sylvestris.) merupakan buah yang memiliki nilai ekonomi cukup tinggi di Indonesia. Apel banyak digemari oleh masyarakat Indonesia karena memiliki cita rasa yang khas dan menimbulkan efek segar pada orang yang mengonsumsinya. Cita rasa apel terbaik diperoleh ketika buah sudah matang sempurna dan apel merupakan buah klimaterik sehingga tingkat kematangan dipengaruhi oleh ketuaan buah saat dipanen. Namun penentuan ketuaan apel masih dilakukan secara visual tanpa alat bantu sehingga hasilnya kurang akurat, kurang objektif sehingga berpotensi kematangan tidak sempurna. Metode spektroskopi NIR (Near Infrared Spectroscopy) memberikan alternatif dalam menentukan tingkat ketuaan buah apel tanpa merusak bagian buah tersebut. Penelitian ini bertujuan untuk menduga sifat fisiko-kimia buah apel manalagi dengan tiga umur panen berbeda (130, 140, dan 150 hari setelah bunga mekar, HSBM) secara nondestruktif dengan menggunakan metode spektroskopi NIR. Sifat atau kandungan fisiko-kimia buah apel terkait dengan tingkat ketuaan buah apel. Parameter yang diuji untuk menentukan kandungan fisiko-kimia buah apel adalah total padatan terlarut, kekerasan daging, dan kadar air. Hasil penelitian menunjukkan hasil terbaik untuk pendugaan total padatan terlarut buah apel didapatkan menggunakan pra-pengolahan data Smoothing Savitzky-Golay (SGs) dengan nilai koefisien korelasi sebesar 0.93; standard error of calibration (SEC) sebesar 0.81 %brix; standard error of prediction (SEP) sebesar 0.86 %brix dan ratio of standard error of prediction to deviaton (RPD)sebesar 2.61. Untuk parameter kekerasan buah hasil terbaik didapatkan dengan pra-pengolahan data Multiplicative Scatter Correction (MSC) dengan nilai koefisien korelasi sebesar 0.78; SEC sebesar 0.47 N; SEP sebesar 0.45 N dan RPD sebesar 1.53. Untuk parameter kadar air didapatkan hasil terbaik dengan pra-pengolahan data Standard Normal Variate (SNV) dengan nilai koefisien korelasi sebesar 0.75; SEC sebesar 0.92%; SEP sebesar 0.85% dan RPD sebesar 1.50.
       
      Apple (Malus sylvestris.) is a fruit with high economic value in Indonesia. Apples are much favored by people in Indonesia because they have a distinctive taste and have a fresh effect on people who consume them. The best apple taste is obtained when the fruit is fully ripe and the apple is a climacteric fruit so that the level of maturity is influenced by the age of the fruit when it is harvested. However, the determination of the aging of apples is still done visually without any tools so that the results are less accurate, less objective so that the potential for ripeness is not perfect. The NIRS (Near Infrared spectroscopy) method provides an alternative to determine the level of maturity of apples without damaging the fruit. This study aims to estimate the physico-chemical properties of manalagi apples with three different harvest ages (130, 140, and 150 days after blooming, DAB) nondestructively by using the NIR spectroscopy method. The properties or physicochemical properties of apples are related to the level of maturity of apples. The parameters tested to determine the physico-chemical content of apples were total dissolved solids, flesh hardness, and moisture content. The results showed that the best results for estimating total soluble solids of apples were obtained using Smoothing Savitzky-Golay (SGs) data pre-processing with a correlation coefficient of 0.93; standard error of calibration (SEC) of 0.81 %brix; standard error of prediction (SEP) is 0.86 %brix and ratio of standard error of prediction to deviation (RPD) is 2.61. For fruit hardness parameters, the best results were obtained by preprocessing Multiplicative Scatter Correction (MSC) data with a correlation coefficient of 0.78; SEC of 0.47 N; SEP is 0.45 N and RPD is 1.53. For water content parameters, the best results were obtained by pre-processing Standard Normal Variate (SNV) data with a correlation coefficient of 0.75; SEC of 0.92%; SEP is 0.85% and RPD is 1.50.
       
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      http://repository.ipb.ac.id/handle/123456789/114903
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      • UT - Agricultural and Bio-system Engineering [2159]

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      Indonesia DSpace Group 
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