Indonesia Conference Directory

Corresponding Author
Daniel Useng

Institutions
Dept. of Agric. Engineering, Hasanuddin University
Makassar
Indonesia, 90245

Abstract
The rice production estimation in Indonesia conducted by several government agencies, among others: Central Statistics Agency (BPS), Director General of Food Crop Production and Horticulture, Ministry of Agriculture, and the Logistics Affairs Agency (BULOG). The approach used to predict rice production from each of these institutions is different from one another. Because of the different approaches the information obtained varies, making it difficult for users of information to utilize existing data. The estimation are based on the plot sampling prior to the harvest. This technique are not only laborious but also time consuming and need large funding support. In order to overcome these limitations, we applied the oblique photographic analysis technique to cover large area to predict the potential yield. Oblique Photographic Image skews in the air. This photograph done by shooting the near-mature rice crops with unmanned aircraft carrying the carrying camera that has a slightly angled. This skewing aerial photography has the character of the aerial photograph that looks slightly tilted but covering larger area compared to the vertical shooting. The yield prediction conducted by image processing software applying Neural Network method of MLP (Multi-Layer Perceptron). The result shows the neural network classification technique on oblique image can determined the rice field productivity especially for low productivity plots with overall accuracy of 69.23 percent.

Keywords
oblique image, unmanned aerial vehicle (UAV), image processing

Topic
Biophysics engineering

Link: https://ifory.id/abstract/RLXZAhjQmkDT

Corresponding Author
NOORAKMAR BINTI AB WAHAB

Institutions
Faculty of Food Science and Nutrition, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Malaysia.

Abstract
Pindang egg and tea egg were processed by boiling in hot water for a few hours with variety of leaves and spices to provide brownish colour and aroma onto the boiled eggs. The aim of this study was to compare the physicochemical and sensory properties as well as shelf life of the boiled eggs upon storage at room (250C) and chill (40C) temperatures. Therefore, analyses of ash, protein, fat, minerals, tannin content and texture profile analysis were conducted to determine the physicochemical properties of the boiled eggs. Quantitative Descriptive Analysis (QDA) and microbiological study were used to investigate the sensory properties and shelf life of the boiled eggs, respectively. The results showed that pindang egg was higher in protein and ash content compared to tea egg (p<0.05), but there was no significant different in fat content (p>0.05). Pindang egg also had high sodium (Na), calcium (Ca), iron (Fe) and magnesium (Mg) content compared to tea egg and hard-boiled egg (p<0.05). Moreover, tannin content of pindang egg and tea egg were higher than hard-boiled egg (p<0.05), and decreasing in trend of tannin content were found up to four days of storage at room and chill temperatures (p<0.05). At day 0, hardness and cohesiveness of pindang egg and tea egg were higher than hard-boiled egg (p<0.05), but the eggs were adhesive (p>0.05). Upon storage at room and chill temperatures, the hardness, adhesiveness and cohesiveness of all eggs were increased (p<0.05). Both pindang egg and tea egg had strong aroma, darker colour, hard and bitter compared to hard-boiled egg, however tea egg showed better overall acceptance than others (p<0.05). Pindang egg and tea egg could last up to four days at chill storage (40C). In conclusion, pindang egg and tea egg had better chemical values, hard, well accepted and longer shelf life than hard-boiled egg.

Keywords
Egg, physicochemical properties, sensory properties, shelf life

Topic
Biophysics engineering

Link: https://ifory.id/abstract/2NxFPWJ37ype

Corresponding Author
Rudiati Evi Masithoh

Institutions
Faculty of Agricultural Technology, Universitas Gadjah Mada, Indonesia

Abstract
Indonesia has abundant crops that can be used as carbohydrate sources. Those crops are made into flour to prolong the shelf life, as well to ease for handling and cooking. Crops as carbohydrate sources are usually high energy but low protein. The aim of this research was to classify flours made of various crops using near infra-red spectroscopy (NIRS) and principle component analysis (PCA). The samples used in this study were six types of flour made of banana, breadfruit, taro, arrowroot, purple sweet potato, and modified cassava (mocaf). The reflectance data were taken using the NIRFlex N500 Fiber Optic Solids Cell at wavelengths of 1000-2500 nm. The spectral obtained were pre-processed and analyzed using The Unscrambler X version 10.5.1. Three pre-processing methods were used, i.e. 1st Savitzky Golay Derivative, Normalization, and Standard Normal Variate (SNV). PCA was able to classify flours based on types of crops. The best transformation was SNV which was able to classify all groups of samples with 100% success rate. PCA model was also able to differentiate low and high protein level of samples aligned with the chemical analysis.

Keywords
Protein, Crops, Near Infrared Reflectance Spectroscopy (NIRS), Principal Component Analysis (PCA), Standard Normal Variate (SNV)

Topic
Biophysics engineering

Link: https://ifory.id/abstract/j47PdmXvkyn8

Corresponding Author
Rudiati Evi Masithoh

Institutions
Faculty of Agricultural Technology, Universitas Gadjah Mada, Indonesia

Abstract
Recent advanced technology enables Android smartphone suitable for quality evaluation of food. In this research, image processing technique was used to detect food color additives. In this research, a smartphone application was developed to determine the availability of color additives in food products. Local food namely geplak was made by adding food grade (i.e. tartrazine and erythrosine) and non-food grade (Rhodamin B and Methanyl Yellow) additives in three concentrations. A mobile phone captured geplak images resulting 1200 images which were divided into 1000 images for training and 200 images for validation. Image data was processed with the python programming language of tensorflow function. The output of python in nominal weight was then trained and tested by using a convolutional neural networks (CNN) method. The weights were then processed by Android Studio version 3.2.1 using .java as backend from CNN and .xml as an application layout. Validation result showed that the program successfully determined class of food additive in high degree accuracy of 98 %.

Keywords
CNN, food, additives, smartphone, image processing

Topic
Biophysics engineering

Link: https://ifory.id/abstract/HuxFUVLKaT6R

Corresponding Author
Radi Radi

Institutions
1Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jl. Flora No.1 Bulaksumur, Yogyakarta 55281, Indonesia

Abstract
Water is one of the elements needed for plant growth. The water is generally supplied from rain. However, non-uniform rainfall throughout the year results in periods where plants need additional water. Besides, surface irrigation system is costly, especially for large area. For efficiency reason, providing water to plantation crops must be regulated. This paper proposes an economical irrigation model for plantation crops. This study uses pineapple plantations as a topic of study. This irrigation model is developed from a drip irrigation model that has been investigated in recent year. Previous study showed that a drip irrigation device has a limited operating range. Therefore, for large working areas, land is divided into a number of plots where each plot is managed by an automatic drip irrigation device. In order to simplify management, all automatic drip irrigation devices are connected a master node which acts as a data and information collection centre. While each irrigation device in each plot acts as a client or slave node. This model has been simulated in a laboratory, where the model consists of 3 slave nodes and a master node. Communication between master and slave nodes is done with a wireless network. The simulation results show that the master can manage slave work properly, can collect the data from the slave, while the slave node can provide irrigation water according to the target conditions.

Keywords
irrigation, smart, plantation, drip, wireless.

Topic
Biophysics engineering

Link: https://ifory.id/abstract/QxyCjRBdH98G

Corresponding Author
Y Aris Purwanto

Institutions
1Department of Mechanical and Biosystem, IPB University
2Center for Tropical Horticulture Study, IPB University

Abstract
Ultrafine Bubble technology is a new and emerging science, capable of infusing ultrafine bubbles in liquids for longer periods of time. Ultrafine bubble are extremely small gas bubbles in liquid. This paper discussed the application of ultrafine bubbles water for seed germination. Seed germination is the process from seed to a sprout in which the metabolic process of a plant gets activated after a period of dormancy. A high seed germination percentage is important for vegetable production. During germination process, the seeds rapidly recover physically from maturation drying, resume a sustained intensity of metabolism, complete essential cellular events to allow the embryo to emerge and prepare for subsequent seeding growth. Comparison experiments of seed germination rate were performed using distilled water and water containing ultrafine bubbles. This experiment utilized the dissolved oxygen concentrations of distilled water with approximately 8-9 and 20-24 mg/L. Rice, soybean, papaya and garlic seed was used as seed samples. The result indicates that the application of ultrafine bubbles water had an effect on seed germination rate.

Keywords
Ultrafine bubble, seed germination, sprout, dissolved oxygen

Topic
Biophysics engineering

Link: https://ifory.id/abstract/4tuNZFLhA3va

Corresponding Author
Rudiati Evi Masithoh

Institutions
Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Indonesia

Abstract
A total of 72 spectra of flour samples taken from 6 types of crops, i.e. of banana, breadfruit, taro, arrowroot, purple sweet potato, and modified cassava (mocaf). The reflectance data were measured using the NIRFlex N500 Fiber Optic Solids Cell at 4000-10,000 cm-1. The spectral obtained were pre-processed and analyzed using The Unscrambler X version 10.5.1. A 2nd derivative Savitzky-Golay (polynomial order 2, 25 smoothing points) followed by a Standard Normal Variate (SNV) were used for pre-treatment data. Characterization of the flours was done using chemometric models based on principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) explained for each group of flour samples of banana, breadfruit, taro, arrowroot, purple sweet potato, and modified cassava (mocaf). SIMCA calibration models were constructed using 6 spectral measurements for each type of flours; classification set were constructed using 6 spectral measurements. The SIMCA accuracy classification were 100% for mocaf, banana, arrowroot, bread fruit, and taro, and 67% for purple sweet potato.

Keywords
Near Infrared Spectroscopy (NIRS), PCA, SIMCA, SNV

Topic
Biophysics engineering

Link: https://ifory.id/abstract/QVTck9Yf3vR7

Corresponding Author
Rizki Maftukhah

Institutions
Departement of Agricultural and Biosystem Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jl. Flora No. 1, Bulaksumur, Yogyakarta 55281, Indonesia

Abstract
Rice is a semi aquatic plant and grown under anaerobic condition as long as water is available. Nowadays, water scarcity and climate change issues need to be address with new technology to increase water use efficiency in rice production. In the other hand, rice varieties must be able to adapt climate change in the future, especially drought even during rice growth periods. A shallow water depth irrigation, as a strategy to reduce water use might influence the rice growth development. The aim of this study was to characterize the leaf area index development of three different rice varieties grown in continuous flooding and shallow water depth irrigation. Pot experiments were conducted in Yogyakarta, Indonesia with three different rice varieties, i.e Mutiara, IR 64, and Hitam, and cultivated with two different irrigation system namely shallow water depth (SWD) and continuous flooding (CF). Leaf Area Index (LAI) was measured every 10 days and polynomial equation was used to describe LAI development during plant growth. Analysis of variance (ANOVA) was performed using Ms. Excel to determine significant differences between treatments. Pearson correlation coefficient (R) was used to evaluate the performance of mathematical model. Leaf Area Index (LAI) under shallow water depth irrigation in different rice varieties were not significantly different compare to continuous flooding irrigation. LAI development in different treatment were described by polynomial equation, with various correlation value, ranged between 0.71 to 0.97. IR64 variety under control irrigation resulted lowest R (0.71), indicated that prediction value from observation data was not strongly correlated. However, other treatments showed strong relationship between prediction and observation data.

Keywords
water scarcity, rice, irrigation, leaf area index

Topic
Biophysics engineering

Link: https://ifory.id/abstract/UtApmcDrJn8M

Corresponding Author
Dewi Sartika

Institutions
1Department of Agroindustrial Technology, Faculty of Agricultural Engineering and Technology, Bogor Agricultural University, Bogor 16680, West Java, Indonesia.
2Faculty of Agriculture, Muhammadiyah University of Makassar, Makassar 90221, South Sulawesi, Indonesia

*khaswars[at]yahoo.com

Abstract
Abstract. Kapok is a source of natural fiber in addition to cotton, which availability is abundant and contain high cellulose but not been utilized optimally. This study aimed to determine the optimal conditions of sulfuric acid concentration and hydrolysis time in the production process of nanocrystalline cellulose (NCC) from kapok fiber. The research was conducted in several stages, namely the delignification with alkali hydrothermal, bleaching with alkaline hydrogen peroxide agents, isolation with sulfuric acid solutions, and NCC characterization. The optimization used Response Surface Methodology (RSM) with Central Composite Design (CCD), which consisted of two factors, namely H2SO4 concentration and hydrolysis time. The optimized parameter was the crystallinity degree of the NCC. NCC characterization included functional group analysis with Fourier Transform Infrared Spectroscopy (FTIR), surface profiles and dimensions by Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM). The results showed that the optimum condition of NCC isolation from kapok fiber was obtained at 54.46% (b/b) H2SO4 with hydrolysis time of 48.96 minutes, resulting in a maximum degree of crystallinity of 71.8%. The hydrolysis process with H2SO4 caused a change in the NCC functional group. NCC had a diameter of about 11.2 nm and high thermal stability that potential for various composite materials

Keywords
acid hydrolysis, kapok fibre, nanocellulose, Response Surface Methodology

Topic
Biophysics engineering

Link: https://ifory.id/abstract/WzKepHbTwyYX

Corresponding Author
Abu Bakar Tawali

Institutions
a) Department of Food Science and Technology, Hasanuddin University, Indonesia
*andi.rahmayanti28[at]gmail.com
b) Department of Nutrition, Health Institute of Helvetia, Indonesia
c) Department of Public Health, Hasanuddin University, Indonesia
d) Department of Marine Science and Fisheries, Hasanuddin University, Indonesia

Abstract
Empek-empek is one of signatured food from Indonesia which made from fish paste, tapioca starch, and other additional ingredients. The objective of this present work was to develop premix flour for making empek-empek using mackerel surimi and to evaluate their chemical characteristic and sensory attributes of the product. The mackerel fish was made into surimi, powdered, then mixed with tapioca starch and other additional ingredients. The following aspect were characterized including moisture, fat, protein, ash, carbohydrate content, and sensory acceptability of the premix product. The results showed that mackerel surimi flour at level of 66,67% is the recommended formula. The empek-empek which made from this premix flour presented hedonic score like moderately for all sensory attributes. In conclusion, our premix can be used for preparing empek-empek with less complicated process and the product did not have any negative results on sensory acceptability.

Keywords
Empek-empek; Premix flour; Mackerel; Surimi

Topic
Biophysics engineering

Link: https://ifory.id/abstract/V674pJNzDnXh

Corresponding Author
Rizki Maftukhah

Institutions
Departement of Agricultural and Biosystem Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jl. Flora No. 1, Bulaksumur, Yogyakarta 55281, Indonesia

Abstract
Shallow water depth (SWD) and intermittent irrigation are methods design to reduce water use of rice plant and maintain rice yield. The objective of this study was to characterize the rice plant growth behavior of four different local rice varieties cultivated in continuous flooding (CF) and intermittent with shallow water depth (SWD) irrigation. Rice varieties i.e. Ciherang, IR64, Hitam, and Merah were grown in pot experiment with CF and SWD irrigation. Rice growth parameters such as plant height, number of tillers, SPAD, and steam hardness were observed during a season. Different rice varieties resulted different response to irrigation treatment, where Ciherang and Merah varieties under SWD irrigation were significantly improve number of tillers. However, IR64 and Hitam varieties were different. In addition, plant height, SPAD, and stem hardness were not significantly different among treatment. Rice cultivation under SWD irrigation of different local rice varieties in this experiment shows that not significantly different from CF irrigation, indicated that rice varieties can be adapted in areas with limited water availability.

Keywords
irrigation, water use, rice varieties, plant growth

Topic
Biophysics engineering

Link: https://ifory.id/abstract/Tn4GU8xMce2Z

Corresponding Author
Byoung-Kwan Cho

Institutions
Department of Biosystems Machinery Engineering, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, South Korea

Abstract
Wireless magnetoelastic (ME) biosensor was designed to detect one of the most popular foodborne pathogen, Escherichia coli (E. coli) O157H7. Binding of the bacteria to the antibody on the gold-coated ME sensor surface changed the resonance frequency of the sensor under the magnetic field, which was quantified by a network analyzer. The response of the sensor to the increment of the concentration of E. coli was investigated. A detection limit of 4.5x105 CFU/mL with a sensitivity of 4.7 kHz were achieved by the sensor with the dimension of 1x0.2x0.023 mm3. The immobilization of antibody-antigen was proven with the fluorescence microscopy which measured the fluorescence dye at the antibody to confirm the successful performance of the immune response on the sensor surface. The results demonstrate that the wireless ME biosensor has good potential to detect E.coli rapidly and efficiently.

Keywords
Food safety, Biosensor, Foodborne pathogen, E.coli

Topic
Biophysics engineering

Link: https://ifory.id/abstract/xgw8BuTEJ2Ha