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Quality parameter characteristics of tomato powder during strorage at various temperature and packaging materials Masithoh, Rudiati Evi; Fauzi, Ratyan
Jurnal Teknologi Pertanian Vol 15, No 3 (2014)
Publisher : Fakultas Teknologi Pertanian Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.22 KB)

Abstract

The study aimed at determining color, moisture contents, and soluble solid contents (Brix) of tomato powder stored at various temperature and packaging. Tomatoes were dried at 50 oC then blended as powder. Tomato powder stored for 8 days in various packaging, i.e. aluminium foil, glass bottles, and PE plastic, at various storage temperature, i.e. 5, 15, and 30 oC. Results showed that L color value and Brix decreased while moisture content increased for all storage temperature and packaging. The rate of decrease of L was higher for PE plastic then other packaging. There was a significant effect of storage temperature to moisture contents but no effect of the packaging. Brix decreased insignificantly for all storage temperature and packaging materials.Keywords:  Tomato powder, Brix, moisture content, L color value
Kinetics Model of Tomato Quality Changes During Storage Masithoh, Rudiati Evi; Rahardjo, Budi; Sutiarso, Lilik; Harjoko, Agus
Jurnal Teknologi Pertanian Vol 14, No 1 (2013)
Publisher : Fakultas Teknologi Pertanian Universitas Brawijaya

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Abstract

This study aims at developing a kinetics model of changes in tomatoes quality during storage. Samples were stored at temperature of 6, 15, and 28 °C. Quality parameters measured were total carotene, citric acid, and vitamin C. On the development of kinetic models of quality parameter changes the k values of total carotenoids, citric acid, and vitamin C were 0.075, -0.008, and 0.042 at 6 °C, 0.056, -0.029, and 0.049 at 28 °C, as well as 0.125, -0.039, dan 0.044 at 28 °C, respectively. Activation energy of the decrease of citric acid was 47.91 kJ/mol, whereas for total carotene and vitamin C were 17.83 kJ/mol dan 0.96 kJ/mol. The coefficient of determination (R2) of the quality content between observation and prediction were 0.70-0.96. Keywords: Kinetics, total carotene, citric acid, vitamin C, tomato
Optimalisasi Penggunaan Pompa dalam Sistem Irigasi dengan Metode Analytical Hierarchy Process di Daerah Irigasi Pacal, Kabupaten Bojonegoro Murtiningrum Murtiningrum; Rudiati Evi Masithoh; Meiana Wahyu Jatmiko
agriTECH Vol 27, No 2 (2007)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.468 KB) | DOI: 10.22146/agritech.9493

Abstract

Pacal Irrigation System in Bojonegoro District is an irrigation system designed to apply surface irrigation gravitationally. Pump uses to abstract irrigation water from canals to irrigate rainfed area outside the system was against the original design. This paper aims to develop the decision making model to decide optimum pump use to achieve optimum operation pattern. The choice of optimum operation pattern was developed using the Analytical Hierarchy Procees (AHP) method to meet the irrigation management aspects. Alternatives of pump operation used were no pump, 68 pumps, 47 pumps, and 21 pumps. Criterias to choose pump operation pattern were RWS, RIS, KPA, efektiveness dan eficiency. The results showed that main criterias to affect the choice of pump operation patteren were RWS and RIS with proportion as 40,73% and 28,19% respectively. Considering all criterias, the optimum pump operation pattern was operation with 47 pumps.ABSTRAKDI Pacal di Kabupaten Bojonegoro adalah sistem irigasi teknis yang didesain untuk menerapkan irigasi permukaan dengan cara gravitasi. Penggunaan pompa yang mengambil air dari saluran irigasi untuk mengairi lahan tadah hujan di luar wilayah DI Pacal tidak sesuai dengan desain awal sistem irigasi teknis tersebut. Tujuan penelitian ini adalah membuat model pengambilan keputusan untuk penggunaan pompa dalam operasi sistem irigasi untuk mendapatkan pola operasi optimal. Pemilihan pola operasi optimal menggunakan metode The Analytical Hierarchy Procees (AHP) dengan penyesuaian dari aspek manajemen irigasi. Alternatif pola operasi yang digunakan adalah operasi tanpa pompa, operasi 68 pompa, operasi 47 pompa dan operasi 21 pompa. Kriteria yang mempengaruhi pemilihan pola operasi berupa RWS, RIS, KPA, efektivitas dan Efisiensi. Hasil analisa menunjukkan bahwa kriteria utama yang mempengaruhi pemilihan pola operasi optimal adalah RWS sebesar 40, 73% dan RIS sebesar 28,19%. Ditinjau dari berbagai kriteria, alternatif operasi dengan 47 pompa merupakan pola operasi optimal.
Model Jaringan Syaraf Tiruan untuk Memprediksi Parameter Kualitas Tomat Berdasarkan Parameter Warna RGB Rudiati Evi Masithoh; Budi Rahardjo; Lilik Sutiarso; Agus Hardjoko
agriTECH Vol 32, No 4 (2012)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (184.081 KB) | DOI: 10.22146/agritech.9585

Abstract

Artificial neural networks (ANN) was used to predict the quality parameters of tomato, i.e. Brix, citric acid, total carotene, and vitamin C. ANN was developed from Red Green Blue (RGB) image data of tomatoes measured using a developed computer vision system (CVS). Qualitative analysis of tomato compositions were obtained from laboratory experiments. ANN model was based on a feedforward backpropagation network with different training functions, namely gradient descent (traingd), gradient descent with the resilient backpropagation (trainrp), Broyden, Fletcher, Goldfrab and Shanno (BFGS) quasi-Newton (trainbfg), as well as Levenberg Marquardt (trainlm).  The network structure using logsig and linear (purelin) activation function at the hidden and output layer, respectively, and using  the trainlm as a training function resulted in the best performance. Correlation coefficient (r) of training and validation process were 0.97 - 0.99 and 0.92 - 0.99, whereas the MAE values ranged from 0.01 to 0.23 and 0.03 to 0.59, respectively.ABSTRAKJaringan syaraf tiruan (JST) digunakan untuk memprediksi parameter kualitas tomat, yaitu Brix, asam sitrat, karoten total, dan vitamin C. JST dikembangkan dari data Red Green Blue (RGB)  citra tomat yang diukur menggunakan computer vision system. Data kualitas tomat diperoleh dari analisis di laboratorium. Struktur model JST didasarkan pada jaringan feedforward backpropagation dengan berbagai fungsi pelatihan, yaitu gradient descent (traingd), gradient descent dengan resilient backpropagation (trainrp), Broyden, Fletcher, Goldfrab dan Shanno (BFGS) quasi-Newton (trainbfg), serta Levenberg Marquardt (trainlm). Fungsi pelatihan yang terbaik adalah menggunakan trainlm, serta pada struktur jaringan digunakan fungsi aktivasi logsig pada lapisan tersembunyi dan linier (purelin) pada lapisan keluaran. dengan 1000 epoch. Nilai koefisien korelasi (r) pada tahap pelatihan dan validasi secara berturut-turut adalah 0.97 - 0.99 dan 0.92 - 0.99; sedangkan nilai MAE berkisar antara 0.01-0.23 dan 0.03-0.59.
Penentuan Dimensi Terong Jepang (Soalnum melongena L) dengan Teknik Pengolahan Citra Secara Waktu Nyata Rudiati Evi Masithoh; Yodana S. Rachmadany; Balza Achmad
agriTECH Vol 26, No 3 (2006)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1399.449 KB) | DOI: 10.22146/agritech.9593

Abstract

A real-time image processing technique was applied to determine the dimensions, i.e. length and width, of eggplants. Results showed that illuminations performed a significant role; the ideal illumination type for the experiment was TL lamp (fluorescent lamp), which was placed in perpendicular position toward conveyor. Meanwhile, the ideal eggplant-positions were longwise on the conveyor. Applying those kind of circumstances, a relationship between developed program and manual measurement of eggplant length and width showed linier equation, i.e. y = x and y = 0,99 x, respectively.
Pendekatan Multivariat untuk Pengukuran Kualitas Tomat (Lycopersicon esculentum) Berdasarkan Parameter Warna Pendekatan Multivariat untuk Pengukuran Kualitas Tomat (Lycopersicon esculentum) Berdasarkan Parameter Warna Rudiati Evi Masithoh; Budi Rahardjo; Lilik Sutiarso; Agus Hardjoko
agriTECH Vol 32, No 1 (2012)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (206.419 KB) | DOI: 10.22146/agritech.9660

Abstract

In this study, multivariate linear regression (MLR) was used to predict the content of Brix, total carotene, citric acid,and vitamin C of tomato based on RGB color parameters. Tomatoes were stored at 6 °C and 28 °C then their quality parameters were measured. R, G, and B values were measured non-destructively using computer vision system developed in the previous study. Brix, total carotene, citric acid, and vitamin C were determined by conventional procedures in the laboratory. Data analysis showed that the MLR calibration models could be used to predict Brix, total carotene, citric acid, and vitamin C with R2  of  0.77and 0.72, 0.902 and 0.85, 0.71 and 0.77, as well as 0.88 and 0.82 for temperature of 6 °C and 28 °C, respectively.ABSTRAKPada penelitian ini, multivariate linier regression (MLR) digunakan untuk memprediksi kandungan Brix, karoten total,asam sitrat, dan vitamin C dari tomat berdasarkan parameter warna RGB. Tomat disimpan pada suhu 6 °C dan 28 °C kemudian diukur parameter kualitasnya. Nilai R, G, dan B diukur secara non-destructive dari computer vision system yang dikembangkan pada penelitian sebelumnya. Parameter kualitas Brix, karoten total, asam sitrat, dan vitamin C ditentukan secara destructive dengan prosedur konvensional di laboratorium. Analisis data menunjukkan bahwa model kalibrasi MLR dapat digunakan untuk memprediksi Brix, karoten total, asam sitrat, dan vitamin C dengan R2 sebesar0,77dan 0,72, 0,902 dan 0,85, 0,71 dan 0,77, serta 0,88 dan 0,82 untuk suhu 6 °C dan 28 °C secara berturutan.
Pengembangan Computer Vision System Sederhana untuk Menentukan Kualitas Tomat Rudiati Evi Masithoh; Budi Rahardjo; Lilik Sutiarso; Agus Hardjoko
agriTECH Vol 31, No 2 (2011)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1825.52 KB) | DOI: 10.22146/agritech.9734

Abstract

The purpose of this research was to develop a simple computer vision system (CVS) to non-destructively measure tomato quality based on its Red Gren Blue (RGB) color parameter. Tomato quality parameters measured were Brix, citric acid, vitamin C, and total sugar. This system consisted of a box to place object, a webcam to capture images, a computer to process images, illumination system, and an image analysis software which was equipped with artificial neural networks technique for determining tomato quality. Network architecture was formed with 3 layers consisting of1 input layer with 3 input neurons, 1 hidden layer with 14 neurons using logsig activation function, and 5 output layers using purelin activation function by using backpropagation training algorithm. CVS developed was able to predict the quality parameters of a Brix value, vitamin C, citric acid, and total sugar. To obtain the predicted values which were equal or close to the actual values, a calibration model was required. For Brix value, the actual value obtained from the equation y = 12,16x – 26,46, with x was Brix predicted. The actual values of vitamin C, citric acid, and total sugar were obtained from y = 1,09x - 3.13, y = 7,35x – 19,44,  and  y = 1.58x – 0,18,, with x was the value of vitamin C, citric acid, and total sugar, respectively.ABSTRAKTujuan penelitian adalah mengembangkan computer vision system (CVS) sederhana untuk menentukan kualitas tomat secara non­destruktif berdasarkan parameter warna Red Green Blue (RGB). Parameter kualitas tomat yang diukur ada­ lah Brix, asam sitrat, vitamin C, dan gula total. Sistem ini terdiri peralatan utama yaitu kotak untuk meletakkan obyek, webcam untuk menangkap citra, komputer untuk mengolah data, sistem penerangan, dan perangkat lunak analisis citra yang dilengkapi dengan jaringan syaraf tiruan untuk menentukan kualitas tomat. Arsitektur jaringan dibentuk dengan3 lapisan yang terdiri dari 1 lapisan masukan dengan 3 sel syaraf masukan, 1 lapisan tersembunyi dengan 14 sel syaraf berfungsi aktivasi logsig dan 5 lapisan keluaran dengan fungsi aktivasi purelin menggunakan algoritma pelatihan back­ propagation. CVS yang dikembangkan dapat digunakan untuk memprediksi nilai parameter kualitas tomat yaitu Brix, vitamin C, asam sitrat, dan gula total, meskipun dibutuhkan persamaan kalibrasi. Persamaan kalibrasi untuk Brix, nilai aktualnya diperoleh dari persamaan y = 12,16x – 26,46 dengan x adalah nilai Brix prediksi. Sedangkan kadar vitamin C, asam sitrat, dan gula total aktual secara berturut-turut diperoleh dari y = 1,09x - 3.13, y = 7,35x – 19,44, dan y =1.58x – 0,18, dengan x adalah nilai vitamin C prediksi, asam sitrat prediksi, dan gula total prediksi.
Analisis Citra untuk Mengamati Perubahan Kenampakan Visual Bawang Merah (Allium Ascalonicum, L) Karena Pengeringan ) Rudiati Evi Masithoh; Sony Anshory Kusuma
agriTECH Vol 28, No 3 (2008)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2856.542 KB) | DOI: 10.22146/agritech.9774

Abstract

This research aimed at observing changes of visual appearance of dehydrated sliced red onion (Allium ascalonicum L)and its image parameters, i.e. area and textures (entropy, energy, contrast, and homogeneity) using image processing and analysis. Images analysis was conducted using the image processing system consisted of a webcam, illuminations, computer hardware, and image processing software. Entropy and contrast increased as moisture contents decreased, whereas energy, homogeneity and area decreased as the moisture contents decreased. Statistical analysis resulted in the relationship between red onion moisture content and its textural image parameters, i.e. entropy, energy, homogene- ity and area; while contrast did not contribute significantly to the moisture content. Using the developed machine vision system it is expected to determine the moisture content of sliced red onion based on image parameters, i.e. texture and area.ABSTRAKPenelitian ini bertujuan untuk mengamati perubahan kenampakan visual bawang merah (Allium ascalonicum, L) yangdikeringkan yang dinyatakan dalam parameter citra yaitu area dan tekstur (entropi, energi, kontras, dan homogenitas) menggunakan teknik pengolahan dan analisis citra. Analisis citra dilakukan dengan menggunakan machine vision yang terdiri dari webcam, iluminasi (lampu), komputer dan perangkat lunak pengolah citra. Nilai entropi dan kontras akan mempunyai kecenderungan meningkat jika terjadi penurunan kadar air pada bahan, sedangkan energi, homoge- nitas, dan area akan menurun dengan berkurangnya kadar air. Dari analisis statistik dapat dinyatakan bahwa kadar air bawang merah merupakan fungsi dari parameter citra, yaitu energi, entropi, homogenitas, dan area; sedangkan nilai kontras tidak memberikan kontribusi. Dengan menggunakan machine visión system yang dikembangkan maka diharapkan dapat digunakan untuk memprediksi kadar air berdasarkan parameter tekstur dan area.
Aplikasi Analisis Multivariat Berdasarkan Warna untuk Memprediksi Brix dan pH pada Pisang Yohanita Maulina Akbar; Rudiati Evi Masithoh; Nafis Khuriyati
agriTECH Vol 37, No 1 (2017)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (680.035 KB) | DOI: 10.22146/agritech.17022

Abstract

In this research, Multiple Linear Regression (MLR) model was used to predict Brix and pH of banana based on RGB and Lab color values. Banana samples varied in color and ripening level from less ripen to ripen. RGB and Lab values were measured non-destructively using colormeter, while Brix and pH were determined using conventional method in laboratory. Multivariate analysis was done using the Unscrambler ® X 10.3 (CAMO, AS, OLSO, Norway, and trial version). Results showed that calibration model using MLR was able to predict Brix and pH of banana based on RGB and Lab color values. Furthermore, validation data were used to test the selected models. MLR model to predict Brix based on RGB and Lab validation resulted in 0.8 and 0.84 of determination coefficient between observation and prediction data. The model was also able to predict pH based on RGB and Lab values with 0.71 and 0.79 of determination coefficient between observation and prediction data. ABSTRAKPada penelitian ini, model Multiple Linear Regression (MLR) digunakan untuk memprediksi Brix dan pH pada buah pisang berdasarkan nilai warna Red Green Blue (RGB) dan Lab. Pisang yang dianalisis mempunyai variasi warna dari kurang masak sampai masak. Parameter warna RGB dan Lab dilakukan secara non-destruktif dengan menggunakan colormeter, sedangkan pengukuran kualitas internal yaitu Brix dan pH ditentukan secara destruktif atau dengan prosedur konvensional di laboratorium. Aplikasi analisis multivariat yang digunakan adalah Unscrambler ® X 10.3 (CAMO, AS, OLSO, Norway, versi trial). Analisis data menunjukkan bahwa model kalibrasi MLR dapat digunakan untuk memprediksi Brix dan pH berdasarkan parameter warna RGB dan Lab pada buah pisang. Selanjutnya, data validasi digunakan untuk menguji model MLR terpilih. Model kalibrasi MLR dapat memprediksi Brix berdasarkan nilai RGB dan Lab dengan nilai koefisien determinasi (R2) sebesar 0,8 dan 0,84, secara berurutan. Sedangkan koefisien determinasi (R2) untuk pH berdasarkan warna RGB dan Lab adalah 0,71 dan 0,79.
Kinetika Reaksi Penurunan Kafein dan Asam Klorogenat Biji Kopi Robusta melalui Pengukusan Sistem Tertutup Sapto Kuncoro; Lilik Sutiarso; Joko Nugroho Wahyu Karyadi; Rudiati Evi Masithoh
agriTECH Vol 38, No 1 (2018)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.29 KB) | DOI: 10.22146/agritech.26469

Abstract

This study was aimed to examine the correlation between temperature and duration of steaming on caffeine and chlorogenic acid reduction as well as to determine energy activation (Ea) according to Arrhenius equation. About 750 g of Robusta coffee was steamed by autoclaving at 100, 110, 120 °C for 1, 2, 3, 4, 5, 6 and 7 hours. The study was conducted in 3 replications. Analyses of caffeine and chlorogenic acid were performed using HPLC.  Steaming coffee beans at 100, 110 and 120 °C resulted in the highest decrease of caffeine and chlorogenic acids content for 7 hours by 13%, 18% and 25% for caffeine; and by 37%, 50% and 59% for chlorogenic acids. At all temperatures investigated, decaffeination and chlorogenic acid reduction followed first order reaction. The decaffeination equation at 100 °C, 110 °C and  120 °C followed equation of  y = -0.019x + 0.862, y = -0.023x + 0.820, and y = -0.033x + 0.759, respectively. Meanwhile, the chlorogenic acid reduction at 100 °C, 110 °C,  and 120 °C followed equation of y = -0.071x + 1.421, y = -0.089x + 1.271, and y = -0.120x + 1.201. Activation energies of decaffeination and chlorogenic acid reduction were 33,543.66 kJ/mol K and 31,934.91 kJ/mol K, respectively. ABSTRAKPenelitian ini bertujuan untuk mengkaji hubungan antara suhu dan lama pengukusan terhadap penurunan kandungan kafein dan asam klorogenat serta menentukan energi aktivasi (Ea) dengan pendekatan persamaan Arrhenius. Biji kopi Robusta masing-masing seberat 750 g dikukus dalam autoklaf (sistem tertutup) pada suhu 100, 110, dan 120 °C masing-masing selama 1, 2, 3, 4, 5, 6, dan 7 jam. Penelitian dilakukan dengan 3 kali ulangan. Analisis kafein dan asam klorogenat dilakukan menggunakan HPLC. Pengukusan biji kopi pada suhu 100, 110, dan 120 °C, menghasilkan penurunan kandungan kafein dan asam klorogenat tertinggi pada pengukusan selama 7 jam. Penurunan kandungan kafein selama 7 jam pada suhu pengukusan 100, 110, dan 120 °C berturut-turut 13%, 18%, dan 25%. Kandungan asam klorogenat mengalami penurunan 37%, 50%, dan 59% berturut-turut pada suhu 100, 110, dan 120 °C.  Pada semua suhu yang diuji, penurunan kafein dan asam klorogenat mengikuti reaksi orde satu. Penurunan kafein mengikuti persamaan y = -0,019x + 0,862,  y = -0,023x + 0,820, dan y = -0,033x + 0,759, sedangkan untuk asam klorogenat mengikuti persamaan y = -0,071x + 1,421,  y = -0,089x + 1,271, dan y = -0,120x + 1,201. Besarnya energi aktivasi penurunan kafein dan asam klorogenat berturut turut adalah 33.543,66 kJ/molK dan 31.934,91 kJ/Mok.