Reconstruction of Rice Drying Model and Analysis of Tempering Characteristics Based on Drying Accumulated Temperature

Previous research has shown that the accumulated temperature can describe drying processes as well as crop growth. To describe the mass and heat transfer processes in the rice drying process more accurately, a mathematical model of rice drying was proposed based on the drying accumulated temperature, and the optimal tempering ratio for conventional hot air drying was obtained through data comparison and analysis. First, it was proven that there was an exponential relationship between the moisture ratio and the drying accumulated temperature of rice. Second, by comparing and analyzing the fitting results of seven different drying mathematical models, the model with the highest fitting degree was selected and reconstructed to obtain the drying accumulated temperature–moisture ratio model. Finally, the new model was used to fit the results of two drying experiments without and with tempering, and the tempering characteristics of rice drying were proved by comparing and analyzing the coefficient difference between the two models. The results showed that the optimal tempering ratio was 3. This study thus provides a reference for rice drying process parameters.

Honey sugars profile of stingless bee Tetragonula laeviceps (Hymenoptera: Meliponinae)

Agus A, Agussalim, Sahlan M, Sabir A. 2021. Honey sugars profile of stingless bee Tetragonula laeviceps (Hymenoptera: Meliponinae). Biodiversitas 22: 5205-5210. Honey was a functional food to improve human health, but irresponsible people used this circumstance to make fake honey. This study aimed to evaluate the profile of the sugar of stingless bee honey [Tetragonula laeviceps (Smith, 1857)] from different geographical origins in Indonesia. Honey, three samples were directly collected from three other sources for meliponiculture of T. laeviceps in Indonesia: Sleman, Klaten, and Gunungkidul. The honey sugars profile was analyzed: glucose, fructose, sucrose, reducing sugar, the sum of fructose and glucose, glucose to moisture ratio, fructose to glucose ratio, and honey pH. Glucose and fructose were analyzed by HPLC, sucrose by Luff Schoorl, reducing the sugar by Layne-Enyon, and pH by a pH meter. The current findings revealed that the geographical origins had a highly significant effect on glucose, fructose, the sum of fructose and glucose, glucose to moisture ratio, fructose to glucose ratio, and honey pH (P<0.01) and significant effect on reducing sugar (P<0.05), but not on sucrose content. Thus, it can be concluded that the origins were affecting the honey sugars profile and honey from Sleman has the highest sugars content, followed by honey from Klaten and the lower was honey from Gunungkidul.

KINETIKA PENGERINGAN LAPIS TIPIS PUREE LABU KUNING (Cucurbita moschata)

Pengolahan daging buah labu kuning menjadi tepung melalui proses pengeringan dapat meningkatkan umur simpan produk, mempermudah penggunaan dan pengolahannya menjadi berbagai produk lanjutan, mempermudah proses penyimpanan serta dapat digunakan untuk berbagai keperluan. Penelitian ini bertujuan untuk mengkaji pengaruh suhu pada proses pengeringan daging buah labu kuning serta memvalidasi model kinetika lapis tipis Lewis, Henderson Pabis, Page, Midili dan Two Term menggunakan data eksperimen pengeringan daging buah labu kuning. Proses pengeringan dilakukan menggunakan pengering tipe rak pada suhu 60-70 . Hasil penelitian menunjukkan jika proses pengeringan pada suhu 70 selama 165 menit merupakan kondisi proses pengeringan yang dianggap relatif baik karena mampu menghasilkan produk dengan nilai moisture ratio yang rendah yakni 0,04. Berdasarkan nilai RSS-nya, model kinetika pengeringan Midili merupakan model kinetika pengeringan lapis tipis yang memiliki kesesuaian tertinggi dengan data eksperimen proses pengeringan puree labu dibandingkan model kinetika lapis tipis Lewis, Henderson Pabis, Page, dan Two Term. Nilai konstanta kinetika pengeringan puree labu kuning adalah 9.10-8- 2,4.10-71/menit untuk proses pada suhu 60-70 .Kata kunci: labu kuning, model kinetika, Midili, lapis tipis

Efficient Model Selection for Moisture Ratio Removal of Seaweed Using Hybrid Of Sparse And Robust Regression Analysis

The Internet of things ((IoT) consisted of physical devices networks such as sensors, home appliances, electronics, and software’s. It enables us to collect and exchange data in several fields. After data collection from IoT, variable selection is considered a major problem because many variables are involved in real life datasets. The current study focused on large data analysis of the problem of model selection, including interaction terms. The dataset used in this study is taken from solar drier with moisture ratio removal (%) as dependent variable while ambient temperature, chamber temperature, collector temperature, chamber relative humidity, ambient relative humidity, and solar radiation as independent variables. LASSO with Huber M, LASSO with Hampel M and LASSO with Bisquare M are proposed in this study. Comparison of proposed techniques are made with ridge regression and OLS (ordinary least square) after multicollinearity test and coefficient test. MAPE (mean absolute percentage error) is calculated for the efficient selected model to forecast. As a result, the model using LASSO with Bisquare-M provides a minimum MAPE value for the best efficient model. Thus, the resulting model with the selected variables can be used to predict Moisture Ratio Removal (%) to determine seaweed drying behavior.

Pemodelan Karakteristik Pengeringan dan Analisis Perpindahan Panas pada Pengeringan Kentang (Solanum Tuberosum L.)

ABSTRAKKentang merupakan salah satu jenis bahan makanan yang yang mempunyai kadar air tinggi. Karena itu kentang mudah rusak di suhu ruang dan menyebabkan kerugian yang besar sehingga dilakukan pengeringan. Penelitian ini untuk menentukan model karakteristik pengeringan secara empiris dan fundamental. Model karakteristik pengeringan digunakan untuk menjelaskan proses pengeringan pada bahan agar mengetahui nilai moisture ratio, analisis perpindahan panas dan dapat memodelkan ke jenis alat pengeringan lainnya. Pada penelitian ini hasil menunjukan model pengeringan lapis tipis midilli paling baik akurasinya dengan data eksperimen pengeringan Kentang (Solanum tuberosum L.). Adapun pada hasil analisis pemodelan secara fundamental dapat memodelkan ke jenis alat pengering lainnya pada kondisi yang sama pada data eksperimen yaitu dengan sistem closedloop dengan menggunakan adsorbent berupa silica gel. Pada pemodelan ini waktu yang dibutuhkan selama pengeringan lebih cepat dibandingkan dengan alat yang digunakan pada eksperimen dengan tray dryer. Kata kunci: Pengeringan, Solanum tuberosum L., Model matematika pengeringan lapis tipis, sistem closedloop, adsorbent ABSTRACTPotatoes are a type of food that has a high water content. Because of this, potatoes are easily damaged at room temperature and cause large losses so as to reduce the losses done drying. This study is to determine the model of drying characteristics empirically and fundamentally. The model of drying characteristics is used to explain the drying process in the material to know the moisture ratio value, heat transfer analysis and can model to other types of drying tools. In this study the results showed a thin layer drying midilli model best accuracy with data experiment drying Potato (Solanum tuberosum L.)As for the results of the modeling analysis are fundamentally able to model all kinds of other dryer on the same conditions on the experimental data, namely the system by using an adsorbent such closedloop silica gel. In this type of drying using adsorbent, the time required for drying is faster than the tool used in the experiment with the tray dryer.Keywords: drying, solanun tuberosum L., mathematical model of thin layer drying, closedloop system, adsorbent

The physicochemical composition of honey from Indonesian stingless bee (Tetragonula laeviceps)

Agussalim, Umami N, Nurliyani, Agus A. 2021. The physicochemical composition of honey from Indonesian stingless bee (Tetragonula laeviceps). Biodiversitas 22: 3257-3263. The demand of honey has recently increased significantly, but this situation is widely used by irresponsible humans who made a fake honey. This present study aims to evaluate the quality based on the physicochemical composition of honey from Indonesian stingless bee Tetragonula laeviceps. Honey was obtained from three geographical origins in Indonesia, i.e. Sleman, Gunungkidul, and Lombok. The physicochemical composition of honey was analyzed such as moisture, ash, protein, pH, glucose/moisture ratio, and electrical conductivity, and amino acids. The results showed that the geographical origins had a highly significant effect (P<0.01) on moisture, pH, and significant effect (P<0.05) on ash, electrical conductivity, protein, and glucose/moisture ratio. Honey from Indonesian stingless bee T. laeviceps was found 17 amino acids were arginine, histidine, lysine, phenylalanine, isoleucine, leucine, methionine, valine, threonine, tyrosine, proline, glutamic acid, aspartic acid, serine, alanine, glycine, and cysteine. The dominant amino acids of honey from Sleman were glutamic acid, histidine, lysine, and arginine. Honey from Lombok were glutamic acid, aspartic acid, lysine, and histidine. Furthermore, honey from Gunungkidul were lysine, arginine, histidine, and phenylalanine. Honey from Sleman and Lombok have the best quality than honey from Gunungkidul based on the chemical composition and amino acids profile.

The Evaluasi Kinerja Model Page Pada Pengeringan Lapisan Tipis Umbi Iles-Iles

Tanaman iles-iles (Amorphophallus muelleri) merupakan jenis umbi-umbian dengannilaipotensial ekonomi yang cukuptinggi. Tanaman ini hanya dapat tumbuh di daerah tropis dan sub-tropis.Penelitian ini dimaksudkan untuk mengevaluasi keakuratan model Page dalam menduga moisture ratio umbi iles-iles (Amorphophallus muelleri)yang berbentuk irisan selama proses pengeringan lapisan tipis. Penelitian dilakukan dengan menggunakan suhu pengeringan 45oC dan 55 oC dengan ketebalan sampel iles-iles 1.0 cm dan 0.5 cm. Kecepatan udara pengeringan digunakan sebesar 1.0 m/s. Parameter pengamatan yang digunakan berat sampel selama proses pengeringan dan waktu pengeringan. Sehingga diperoleh hasil seperti pola penurunan kadar air, pola penurunan moisture rasio, nilai konstanta pengeringan Model Page, dan evaluasi kinerja Model Page yang menggambarkan hubungan antara nilai prediksi dan nilai observasi moisture ratio yg menghasilkan persamaan regresi tanpa intersept dengan nilai R2 yang mendekati 1.0, maka Model Page yang diperoleh dianggap baik dalam melakukan prediksi moisture ratio umbi iles-iles. Adapun nilai R2 yaitu 0.998, nilai Chi-squared yaitu 5.202x10-2 dan nilai RMSE yaitu 0.006. Selisih nilai R2, Chi-squared, dan RMSE antara berbagai penelitian yg dilakukan terdahulu dengan penelitian ini yg relatif sangat kecil mengindikasikan bahwa kinerja Model Page pada penelitian ini juga cukup baik.

Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling

Two different drying methods were applied for dehydration of apple, i.e., convective drying (CD) and microwave drying (MD). The process of convective drying through divergent temperatures; 50, 60 and 70 °C at 1.0 m/s air velocity and three different levels of microwave power (90, 180, and 360 W) were studied. In the analysis of the performance of our approach on moisture ratio (MR) of apple slices, artificial neural networks (ANNs) was used to provide with a background for further discussion and evaluation. In order to evaluate the models mentioned in the literature, the Midilli et al. model was proper for dehydrating of apple slices in both MD and CD. The MD drying technology enhanced the drying rate when compared with CD drying significantly. Effective diffusivity (Deff) of moisture in CD drying (1.95 × 10−7–4.09 × 10−7 m2/s) was found to be lower than that observed in MD (2.94 × 10−7–8.21 × 10−7 m2/s). The activation energy (Ea) values of CD drying and MD drying were 122.28–125 kJ/mol and 14.01–15.03 W/g respectively. The MD had the lowest specific energy consumption (SEC) as compared to CD drying methods. According to ANN results, the best R2 values for prediction of MR in CD and MD were 0.9993 and 0.9991, respectively.