bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microbiological profile of fresh goat milk: Impact of goat farmer practices in “Taruna Mukti” goat farmer group, Sragen, Central Java
Authors: Nuhriawangsa A D M , Kartikasari L R , Hadi R F , Wati A K , Hertanto B S 
Published: October 2019

Abstract
Goat milk is susceptible to be contaminated by many microorganisms including microbial pathogens responsible for causing diseases. Various contaminations come from every stage of goat milk produce including feeding, milking, and milk treatments. The aim of this study was to assess the practice of dairy goat farmer and evaluate the microbiological profile of raw goat milk in dairy goat farmer group. The study showed that row milk had high total plate count (7, 8x106 CFU/ml). Thus, Coliform and E. coli were detected in the samples of fresh goat milk. Overall, it can be seen that fresh goat milk was relatively poor hygienic quality and was not conformed to the Indonesian Nasional Standard.
The utilizing of zeolite and manures for increasing potassium availability, uptake, and yield on soybean in Alfisols
Authors: Haniati I L , Minardi S , Nastiti A H L , Harieni S , Syamsiyah J , Hartati S 
Published: October 2019

Abstract
Enhancement soybean production is needed to fulfill its high demand in Indonesia by utilizing the widespread potential land, such as Alfisols. Zeolite and manure addition used to overcome the nutrient availability in Alfisols and decrease the use of inorganic fertilizer. This study was conducted in field condition in a factorial randomized complete block design with three replicates in an Alfisols aimed to assess the effect of applying three rates of zeolites (Z0: 0 t.ha−1, Z1: 2.5 t.ha−1 and Z2: 5 t.ha−1) and three types of 5 t.ha−1 manures (P0: 0 No Manure, P1: quail manure (5 t.ha−1), P2: cattle manure (5 t.ha−1)) on K availability, its uptake, number of pods and seed weight/plot on soybean [Glycine max. (L) Merrill]. Zeolites showed a significant result of potassium availability at the rate 5 t.ha−1. The similar result is given by cattle manure for potassium uptake in soybean. An interaction between zeolites at the rate 5 t.ha−1 and cattle manure showed the significant result on a number of pods.plant−1, 100-seeds weight and seed yield.
Efficacy of betaine as carcass modifier in female broiler chickens to produce leaner carcass for human consumption
Authors: Ratriyanto A , Prastowo S , Widyas N 
Published: October 2019

Abstract
Betaine is a methyl group donor which involved in protein and energy metabolism, offering an opportunity to the poultry producers to satisfy consumer needs by producing leaner carcass. This study was conducted to investigate the efficacy of betaine as carcass modifier in female broiler chickens fed diet containing sufficient methyl group donor. Two hundred female day-old chicks (DOC) were allotted to four assay diets with 5 replicates of 10 birds. The starter and finisher diets contained 0.50 and 0.38% methionine as methyl group donor, respectively. The basal diets were fed without supplementation or supplemented with 0.10, 0.20 and 0.30% betaine. The assay diets were fed from the age 8–42 days. Two birds per replicate were slaughtered at the age of 42 days to measure the carcass characteristics. The fat content was derived from breast meat samples. Supplementation of betaine did not influence the slaughter weight, carcass and breast yield, indicating similar growth and carcass production. Furthermore, administration of betaine produced 29.8–42.5% lower abdominal fat pad deposition and 9.2 – 35.9% lower meat fat content than those without betaine administration (P<0.05). It can be concluded that betaine can modify carcass characteristic in female broiler chickens by lowering fat deposition.
Predicting yolk and albumen weight using egg weight of quails (Coturnix coturnix japonica) fed diet supplemented with betaine
Authors: Ratriyanto A , Amirullah Y H , Prastowo S , Widyas N 
Published: October 2019

Abstract
Betaine as a methyl donor is proven to increase the synthesis of egg components which presence in poultry diet is suspected to modify the composition of the eggs. Eggs are multipurpose animal product. It is utilized in various ways; either as a whole or separated between its yolk and albumen. For the later purpose, the knowledge about egg composition is essential. This study aimed to build models to predict the yolk and albumen weight using egg weight of quails (Coturnix coturnix japonica) fed diet supplemented with betaine. In total, 239 data obtained from 3 assay diets were subjected to analysis of variance, correlation, regression and cross validation. The assay diets consisted of a basal diet containing 16.5% protein fed without or with supplementation of 0.06 and 0.12% betaine. The supplementation of 0.12% betaine increased egg, yolk and albumen weight (p<0.01). The correlation of egg weight∼yolk weight and egg weight∼albumen weight ranged between 0.65–0.69 and 0.69–0.79, respectively. The regression models showed high predictability between 92.7–94.5% for yolk weight prediction and 96.0 – 97.2% for egg weight prediction based on egg weight. Thus, egg weight is a good predictor to predict the yolk and albumen weight of quail eggs.
Egg production patterns of quails given diets with different nutrient density
Authors: Widyas N , Nugroho T , Hidayat B F , Masykur A , Prastowo S , Ratriyanto A 
Published: October 2019

Abstract
Energy and protein ratio in the diet plays an important role in laying quails production. High nutrient density could expose the quails into heat stress due to inefficient metabolic process and nutrient absorption. On the other hand, lower density possesses the risk of nutrient insufficiency. Both cases are potential in affecting the egg production. This study aimed to investigate the egg production patterns of quails fed different nutrient density with constant ratio of metabolizable energy (ME) and crude protein (CP). Egg production data was obtained from two hundred laying quails (Coturnix coturnix japonica) which were randomly assigned into two distinct experimental diets. Dietary treatments were given for eight weeks and replicated five times each with 20 quails. Two diets were formulated to contain High ME-CP (2,800 kcal/kg ME and 18.7% CP) and Low ME-CP (2, 600 kcal/kg ME and 17.3% CP). The data were analysed using t-test and egg production patterns were plotted. Quails fed with different nutrient density yielded similar egg production values and patterns. We fit non-linear mathematical model into the datasets; similar trends and fitness were also observed (R2 = 0.96). It is concluded that quail fed with different nutrient density exhibited minor difference in egg production pattern.
The consistency of quail’s egg production supplemented with vitamin C in the diets
Authors: Ratriyanto A , Nugroho T , Masykur A , Hidayat B F , Prastowo S , Sunarto  , Widyas N 
Published: October 2019

Abstract
In tropical area, animals are prone to stress due to high environmental temperature hence affecting the production. Vitamin C has been offered as an agent to help animal to cope with heat stress. This paper aimed to estimate the consistency of quail’s egg production supplemented with vitamin C through repeatability estimates. A total of 136 quails (Coturnix coturnix japonica) were randomly allotted into 2 dietary treatments with 4 replicates each containing 17 quails. The dietary treatments were basal diet (T0) and basal diet + 250 mg/kg vitamin C (T1). Dietary treatments were given for 8 weeks in laying phase. In total we obtained 56 days of egg production data. Data were analysed using t-test to infer the differences between the treatments and analysis of variance (ANOVA) to obtain the repeatability value. The results showed that the supplementation of vitamin C increased egg production up to 14.3% (P<0.01). Repeatability value of T0 was higher (0.33) than T1 (-0.13). Quails given T0 has a high egg production consistency but produce lower egg production than T1. It is concluded that supplementation of vitamin C increased egg production but were not yet able to produce the optimal consistency.
Postharvest application of an edible coating based on chitosan and gum Arabic for controlling respiration rate and vitamin C content of chilli (Capsicum frustecens L.)
Authors: Muthmainnah N , Suratman  , Solichatun  
Published: October 2019

Abstract
Chili (Capsicum frutescens L.) is the most important vegetable cum spice grown in tropical and sub tropical regions of the world. The post-harvest handling of chilli must be done well so that the quality is maintained. One way of handling post-harvest is to use edible coating such as chitosan and gum Arabic. The research was aimed to find out the effects of chitosan and gum Arabic coating to control of respiration rate and vitamin C content of post-harvest chilli. The research was conducted using a Completely Randomized Design (CRD) factorial consisting of two factors. The first factor consisted of various concentration of chitosan (0%, 1%, 1.5%, 2%) and the second factor consisted of various concentration of gum Arabic (0%, 5%, 10%, 15%) with three replications for each treatment. The coated fruits were then stored at room temperature (28°C) for 15 days. The observed data included respiration rate and vitamin C content. Data were analyzed using Analysis of Varians (ANOVA) and followed by Duncan’s Multiple Range Test (DMRT) at a 5% confidence level. The results showed that the application of chitosan and gum Arabic coating significantly affected the respiration rate and maintained vitamin C content.
Color and texture analyses of meatballs made from beef, pork, rat, dog meats, and their mixtures
Authors: Tathma F R , Wibowo T , Taufik I M , Cahyadi M 
Published: October 2019

Abstract
The aim of this study was to evaluate color and texture of meatballs made from beef, pork, rat, dog meats, and their mixtures. A total of 32 meatballs have been made and they were grouped into eight treatments containing four meatballs, respectively. Color intensity consisting of lightness(L*), redness (a*), and yellowness (b*) has been tested using chromameter CR-400. Additionally, texture of meatballs consisting hardness, gumminess, springiness, chewiness was analyzed using AMETEX test and calibration instrument. The data obtained from this study was furthermore analyzed using one-way analysis of variance (ANOVA) and the pairwise differences among treatments were tested by Duncan’s multiple range test (DMRT). The results showed that L*, a*, b* were significantly different among treatments (P<0.01). The L* value of dog meat was different with beef, pork, and rat meat. Also, the a* value of beef was similar to pork and significant different with dog and rat meats, while b* value of dog meat was different with other meats. The L*, a*, b* scores in mixture samples consistently represented the average value of color scores of samples consisting various species. Moreover, texture analysis indicated highly significant effect of treatments on hardness, gumminess, springiness, and chewiness (P<0.05). Highest hardness, gumminess, and chewinessscores were found in meatballs made from beefand rat, respectively. In addition, springiness of meatballs was relatively similar among treatments. This study concluded that meatballs made from different species and mixtures had different color and texture. Further study should be conducted to test whether color and texture analysis could be utilized for checking meat-based food adulteration and halalness.
Effect of different solvents and extraction conditions on fiber contents of local corns silk powders
Authors: Haslina  , Praseptiangga D , Bintoro V P , Pujiasmanto B 
Published: October 2019

AbstractThe aim of this study was to optimize the different solvents and extraction conditions on fiber contents of local corn silk powders. Each sample of corn silk powder extract was analyzed by enzymatic method for fiber content including soluble fiber, insoluble fiber and total fiber. Design using Factorial Randomized Block Design (RBD) with 4 factors are local varieties of cornsilk (Bisma, Arjuna and Srikandi Putih), different solvents (water, methanol, ethanol and ethyl acetate), different concentration of solvents ( methanol (60%, 70% and 80%), ethanol (60%, 70% and 80%), ethyl acetate (60%, 70% and 80%) and water), and ratio of material and solvent (1:5 (w/v), 1:10 (w/v), 1:15 (w/v) and 1:20 (w/v)). Response Surface Methodology (RSM) technique for optimum condition determination was used. Results showed that the difference in experimental conditions affects the content of soluble fiber, insoluble fiber, and total fiber produced by optimization analysis using the DX11.0® Program with RSM-Central Composite Design (CCD). In conclusion, Bisma variety, solvent of methanol, concentration of 80% solvent and ratio of (1:20) was selected as the optimum condition of which resulted in soluble fiber content of 0.85%, insoluble fiber of 0.60% and total fiber of 1.45%.
Utilization of carrageenan and chitosan as coating material in phycocyanin encapsulation
Authors: Hadiyanto  , Sutanto H , Suzery M , Adetya N P , Nilamsari A M , Yunanda A 
Published: October 2019

Abstract
Phycocyanin is one of the pigments found in Spirulina platensis. Phycocyanin has potential as natural blue dye and antioxidant. The application of phycocyanin as food ingredient is still limited due to its vulnerability to environment. Microencapsulation can keep phycocyanin from environmental influences such as temperature, light and pH. This research aimed to determine the antioxidant activity of phycocyanin microencapsulation with carrageenan and chitosan coating material caused by the effect of thermal degradation overtime and its influence on the physical characteristics of the microencapsulation. The highest antioxidant activity of 61.48% was found in chitosan coating material that occurred at temperature of 40° with 30 minutes heat treatment.Phycocyanin microcapsule with chitosan has more vibrant blue color compared to carrageenan.Phycocyanin microencapsulation either by using carrageenan or chitosan have functional groups such as alkane, alcohol, ether and ester.
Effect of various heat treatment on physical and chemical characteristics of red rice bran (Oryza nivara L.) Rojolele
Authors: Siswanti  , Anandito R B K , Nurhartadi E , Iskandar B D 
Published: October 2019

Abstract
This research aims to study the effect of various heat treatment on physical and chemical characteristics of red rice bran (Oryza nivara L.) Rojolele. This study used a Completely Randomized Design (CRD) with one-factor variations of heat treatment applied on the bran. The various heat treatments use Oven an hour (80ºC and 100ºC), Microwave maximum temperature (2 and 5 minutes), and Autoclave 1500C (5 and 10 minutes). Results showed that all heat treatment methods decrease L value. The highest moisture level is on heating by microwave for 2 min. There were no significant difference in the level of ash, fat, and antioxidant activity. The FFA content was decreased by all heating treatment. The fenol level with heating with Oven 80ºC an hour was the highest. Among the treatments, Oven an hour at 80ºC is the best method. This method produces red rice bran with characteristics of lightness, water content, ash, fat, protein, total phenol, antioxidant activity, crude fiber, and free fatty acid content respectively 49.78; 5.51%; 8.37%; 27.11%; 10.50%; 0.25%; 75.88%; 9.30%; and 13.48%. Red rice bran Rojolele also contains anthocyanin and thiamin obtained from spectroscopy FTIR.
Household consumption of broilers meat in Kudus Central Java
Authors: Zulkarnain M B , Rahayu W , Antriyandartiand E , Ani S W 
Published: October 2019

Abstract
Broilers meat is one of protein intake sources from meat in Indonesia, but the consumption still very low compared to the standard set by Food and Agriculture Organization (FAO). This study investigates the pattern of animal food consumption, examines the determinants of broilers meat consumption and analyzes the demand elasticity in the household. This study uses Panel Data Analysis with Random Effect Model to estimate the factors influencing broilers meat consumption. The determinants are the number of family members, household income, the price of broilers meat, egg, rice, beef, fish, and the residential area. The results show that the most influential factor is the price of broilers meat, with inelastic demand elasticity.
Farming occupation in the views of farmer families in rural area
Authors: Widiyanti E , Karsidi R , Wijaya M , Utari P 
Published: October 2019

Abstract
As main actors in food production system, farmers receive much of the world’s attention due to the food crisis phenomenon happening all over the world. However, the attention to small-scale farmers tends to be neglected, especially regarding to the crisis of farmer regeneration. Thus it is interesting to understand how small-scale farmers and their families think of farming occupations. To comprehend the meanings underlying the farmer families’ views on farming occupations, the researchers applied Hebert Blumer’s symbolic interactionism in descriptive qualitative study using paradigm construction. The data were collected by interviews with a number of farmers and their families in Tegalmade Village, Mojolaban District, Sukoharjo Regency. The results showed that there are different views among older generation (farmers) and younger generation (farmers’ children). The identified views were positive, neutral and negative. The differences in their views are caused by different interaction processes, leading to different action orientations. The young generation has positive views when interacting with their families and youth community engaged in agriculture especially in agriculture entrepreneurship. These positive views result in action orientations to work on the farming occupations. The older generation has positive views when interacting with fellow farmers, views that they want to continue to make farming as their main livelihood.
Using Deep Neural Networks to Predict the Tensile Property of Ceramic Matrix Composites Based on Incomplete Small Dataset
Authors: Xiang GAO , Guanghui LI , Rong TAN , Leijiang YAO 
Published: October 2019

Abstract
It has been a hot spot in the area of material science that how to design an experiment to produce a kind of ceramic matrix composites (CMCs) which possesses ideal performances. An approach is to build models with data from previous experiments recorded in published papers and predict the experiment parameters needed by the ideal CMCs. According to the database of CMCs funded by the National Material Genome Engineering, 8 factors were considered to affect the tensile property of CMCs, which were the basis, the reinforcement fiber type, the reinforcement fiber volume content, the perform type, the porosity, the interface type, the interface thickness and the density. Among the data we collected from papers, however, only few of pieces contained all the 8 factors, most were incomplete, some of them even lacked multiple factors. This paper’s work mainly researched how to take advantage of the incomplete data to build an effective model to predict the tensile property of CMCs. We proposed a model to predict the tensile property of CMCs based on a 1-D convolution neural network (CNN), the training data of which were all from papers. To decrease the influences of the incompleteness of data, we tried several methods to process the missing data, such as the mean imputation, the K-Means clustering imputation, the Hot-Deck Imputation and the regression imputation. The results showed that the regression imputation with a dual-hidden-layer feedforward network performed better and improved the performance of the CNN tensile property prediction model.
Mechanism and Research on Preparation of AlN Powder by Carbon Thermal Reduction Method
Authors: Wang L Y , Zhang N 
Published: October 2019

Abstract
The alumina and activated carbon used as raw materials were prepared by chemical precipitation method. The uniformed aluminum nitride precursor was synthesized by mechanical mixing process. The effects of nitride temperature and time on the diameter of the particle were studied in detail. Ultrafined aluminum nitride powder was prepared by carbon-thermal reduction method. The results show that the precursor has better activity and nitride reaction proceeds rapidly. The complete conversion can be got at 1600°C for 2h. After calcination, it can be seen from the XRD graph that the powder with uniform size distribution has high AlN content.
A Reliable Defect Detection Method for Patterned Wafer Image Using Convolutional Neural Networks with the Transfer Learning
Authors: Lee Ji-Hee , Lee Jee-Hyong 
Published: October 2019

Abstract
In the semiconductor manufacturing process, wafer inspection images have valuable information on defects and wafer yield. It is worthy to analysis these images and there are many algorithms for this. Whenever new product designs are introduced, the algorithms are used to detect defects. Most new product designs have new types of defects. Hence, it is important to update the algorithms to cope with new types of defects. To update the algorithms, engineers collect the data and adjust a parameter values, such as threshold, to detect defects. It is time-consuming to collect enough data and only a knowledgeable engineer can find an appropriate parameter value. However, there is always a lack of engineer resources and time in the manufacturing industry. Due to these reasons, many algorithms can’t be used reliably and have disappeared. Therefore, we propose the advanced method to update an algorithm easily using a deep learning model. Deep learning models achieve high accuracy with less engineer knowledge than traditional algorithms. But it also needs a lot of data to train the model, so we apply an advanced method of updating with a small amount of data in a short time. This is called as transfer learning. Once we train a deep learning model with high accuracy, we can update the model with a small amount of data. Transfer learning uses the information gained during the training. As a result, we make a model that is easy to update with high accuracy. In the experiments, we obtained 99% accuracy with sufficient training data. To update the model for the new data, we did transfer learning and got 97% accuracy. It was lower, but we only used 10% of the training data and 5% of the training time. Also, the accuracy we have obtained is enough to be used for defect analysis. Our approach outperformed and executed faster than traditional algorithms.