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Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)
Published by Universitas Brawijaya
ISSN : -     EISSN : 26225921     DOI : https://doi.org/10.21776/ub.afssaae
Core Subject : Science, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Engineering Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering
The Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering is aimed to diseminate the results and the progress in research, science and technology relevant to the area of food sciences, agricultural engineering and agroindustrial engineering. The development of green food production, agricultural and agroindustrial practices to reduce the ecological footprint to the environment is also the key focus of the journal.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 198 Documents
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Edamame caspian sea soygurt as plant-based yogurt alternatives Kusnadi, Joni; Septi, Nur Diana; Fibrianto, Kiki
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 6, No 4 (2023)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2023.006.04.10

Abstract

Caspian sea soygurt is made by fermenting edamame milk with Lactococcus lactis ssp. cremoris and Acetobacter orientalis as microbial cultures. To produce good soygurt, edamame milk fermentation requires ideal conditions, such as an optimum carbon source and starter concentration. This study aimed to determine the effect of the proportion of sucrose:skim and concentration of starter on the physical, chemical, microbiological, and sensory characteristics of Caspian sea soygurt. This study used a randomized block design with 2 factors: sucrose:skim proportion (2.5:7.5, 5:5 7.5:2.5) and starter concentration (8, 10, 12% of pasteurized edamame milk) repeated three times. Data were analyzed using ANOVA and continued with the Tukey test. These results was used to select the best treatment using the Zeleny Multiple Attribute Method. The best Caspian soygurt treatment was found in the proportion of sucrose:skim 5:5 (% w/v of pasteurized edamame milk) and starter concentration 12 (% v/v of pasteurized edamame milk), which produced a color (L*) 78.98, (a*) -2.86 ( b*) 23.79, viscosity 516.67 cP, protein 3.38%, antioxidant activity 43.12%, pH 4.35, total lactic acid bacteria 9.85 log CFU/mL with a preference level of 3.45 and an acceptance level of 3.55 for the greenness, a preference level of 3.79 and an acceptance level of 3.80 for the brightness, a preference level of 3.15 and an acceptance level 3.21 on the sour aroma, preference level of 3.04 and acceptance level of 3.11for the beany aroma, preference level of 3.04 and acceptance level of 3.18 for the beany flavor, preference level of 3.02 and acceptance level of 3.19 for the sour taste, preference level of 2.98 and acceptance level of 3.09 for sweet taste, preference level of 3.49 and acceptance level of 3.60 for the viscosity.
Effect of concentration of sugar and dried Dayak onion (Eleutherine palmifolia) on the quality of Dayak onion kombucha Permatasari, Vitta Rizky; Widayanti, Vindhya Tri; Falasifah, Ratu; Sunyoto, Nimas Mayang Sabrina; Suhartini, Sri
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 3 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.03.2

Abstract

Kombucha is one example of a health drink product that falls under the category of functional drinks. Dayak onions are one of the ingredients with many bioactive components. This study aimed to determine the optimal combination of treatments to yield the highest quality Dayak onion kombucha by assessing the effects of variations in sugar concentration and dried Dayak onion concentration on the quality of Dayak onion kombucha (i.e., pH, total acid, and organoleptic). The study employed a randomized block design (RBD) with three replications to produce 27 experimental units. The two factors were dried Dayak onion concentrations of 2%, 4%, and 6% (w/v) and sugar concentrations of 5%, 7.5%, and 10% (w/v). The data was then subjected to a two-way ANOVA using IBM SPSS Statistics 26 software, and the Multiple Attribute method was used to determine the best treatment. The results demonstrated that the concentration of sugar and dried Dayak onions had a significant effect (α<0.05) on the pH value, total acid.  the higher the concentration of sugar, the higher the total acid content with a lower pH, and the higher the concentration of dried Dayak onions, the lower the total pH. The best treatment combination was using dried Dayak onion concentration of 6% (w/v) and sugar concentration of 7.5% (w/v). The test results obtained were pH 3.173, total acid 0.105%, organoleptic color 3.867, and organoleptic aroma 2.867.
Designing a sustainability monitoring system for the food and beverage industry in Indonesia using multidimensional scaling (MDS) Barus, Wan Habibi Rahman; Sriwana, Iphov Kumala; Prambudia, Yudha
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 2 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.02.2

Abstract

The decline in the performance of the food and beverage sector by -3% for the food sector and -26.39% for the beverage sector in the second quarter of 2020 due to the outbreak of Covid-19 necessitated an analysis of the sustainability of the food and beverage industry. This research aimed to analyze the sustainability of the industry. A monitoring system for the sustainability of the food and beverage industry was an essential tool to ensure that the sector operated sustainably and contributed positively to the environment and society. Multidimensional Scaling (MDS) could be used to analyze and visualize the sustainability performance of the food and beverage industry based on various relevant dimensions or factors. The simulation results of Rapid Assessment of Food and Beverages (RAP-FB) indicated an overall high level of sustainability at 64.89%. In summary, the research showed that the food and beverage (F&B) industry's sustainability could be assessed through various dimensions and factors (such as Gross Domestic Product (GDP), energy efficiency, and workplace safety) contributed significantly to its overall sustainability. The monitoring system based on MDS could provide valuable insights to enhance the industry's performance and ensure its continued positive impact on the environment and society.
Validations of sensory overall acceptability optimizations on response surface methodology through just-about-right technique for coffee-leaf tea at different brewing methods Fibrianto, Kiki; Bimo, Igoy Arya; Sofa, Atika Muna; Putri, Azalea; Amelia, Devia; Lalilika, Ovirista Rachma; Genbrovit, Irha Putri; Haq, Ahmad Izzul
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 1 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.01.3

Abstract

Response Surface Methodology (RSM) has been widely employed for optimizing processes. However, the implementation of RSM in sensory studies is still limited. Moreover, most publications implementing RSM on sensory disregarded the validation stage as normally applied for process optimization. In this study, validating sensory overall acceptability with RSM was proposed by the Just-About-Right (JAR) technique. Coffee-leaf tea has great commercial potential as an ethnic beverage with unique sensory attributes but is still underutilized. Optimizing sensory acceptability level by modifying temperature and duration of brewing using the RSM was expected to obtain well-accepted coffee-leaf tea.  Robusta coffee leaf tea is brewed using combined Decoction - V60, French Press, combined French Press - V60, and V60 at 90oC to 100oC for 2 to 10 minutes. Evaluated by 110 untrained panelists, it was observed that the ideal brewing parameters for each technique were 96.6oC for 6.5 minutes for Decoction – V60, 96oC and 6.5 minutes for French Press, 90oC and 2 minutes for French Press - V60, and 90oC and 2 minutes for V60. All optimum brewing conditions based on RSM were successfully validated by overall acceptability on JAR (p-value 0.05). Thus, the JAR technique can enhance the overall sensory acceptability analysis and optimization.
Robusta coffee processing productivity analysis using objective matrix (OMAX) method (Case study at PT Tinkerbels Permata Indah, Bogor, West Java) Deoranto, Panji; Hilal, Abiyyu Yazid; Purwaningsih, Isti
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 6, No 4 (2023)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2023.006.04.3

Abstract

PT Tinkerbels Permata Indah is one of the companies engaged in the coffee processing industry. The high market demand for coffee products made from robusta coffee requires PT Tinkerbels Permata Indah to continuously produce more coffee effectively and efficiently. Therefore, companies need to measure productivity to determine the performance of using several inputs to produce output. This research aimed to analyze the productivity level of robusta coffee bean production and to make a proposed improvement plan for PT Tinkerbels Permata Indah. The method used to measure productivity was the objective matrix (OMAX) method. The weight of each criterion was obtained with the help of the pairwise comparison method by filling out a questionnaire by the three experts involved. The results show that the company's highest productivity achievement was 5.893 in April 2022, and the lowest was in September 2022, with a current value of 0.880. Proposed improvements include companies needing to pay attention to their warehouses by maintaining temperature and humidity so that materials are not damaged by warehouse pests, implementing flexible daily hours to reduce wastage of employee work time, implementing an energy-saving culture, conducting energy audits, and implementing machinery maintenance management.
Characterisation of honey using high-frequency ohmic heating based on image segmentation Hartono, Elvianto Dwi; Lastriyanto, Anang; Zubaidah, Elok; Hendrawan, Yusuf
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 3 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.03.8

Abstract

In the field of computer vision, image segmentation using a clustering approach was employed. This non-destructive method was applied to process ohmic heating in honey, aiming to achieve an efficient and time-saving mass production process. The K-means clustering algorithm converted RGB color data to Lab color space for effective segmentation. The validation of outcomes was conducted through the evolution of RMSE values and regression analysis for each frequency. Notably, at a precision frequency of 1 kHz, the results were as follows: RMSE Red 1.4902, RMSE Green 0.7017, RMSE Blue 0.3328, Regression Red 0.0792, Regression Green 0.5782, Regression Blue 0.202, and heat penetration regression 0.658. This proposed method was benchmarked against the conventional heat penetration analysis in ohmic heating.
Optimization of maltodextrin concentration and spray drying temperature on physicochemical characteristics of powdered edamame milk Ali, Dego Yusa; Pramita, Hera Sisca; Widyaningsih, Tri Dewanti; Jayanti, Theresia Vania
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 2 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.02.1

Abstract

Peeled edamame can be processed into a product that will increase added value, including edamame milk. The perishable nature of milk requires further processing, such as drying it into powder. One of the commonly used fillers is maltodextrin because it can improve the product’s physical properties. With this treatment process, the physicochemical characteristics could be changed. Therefore, this study aimed to optimize the treatment of the physicochemical characteristics of edamame milk powder. Response Surface Methodology (RSM) with Central Composite Design (CCD) experiment with maltodextrin concentration factor (5.71%-10.00%) and spray drying temperature (160°C-215°C) was used in this study. Analysis of physicochemical characteristics carried out included water content, water activity, solubility, hygroscopicity, and color (a(-)). The results showed that treatment with the combination of 6.00% maltodextrin and 215 °C of drying temperature offer the optimum condition in producing a high-quality edamame milk powder.
The influence of seed separation techniques and drying temperature in a dehumidified drying machine for tomato seed production Hermanto, Mochamad Bagus; Susilo, Bambang; Lutfi, Mustofa; Damayanti, Retno; Yanti, Yanti; Irshafiyah, Irshafiyah
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 1 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.01.7

Abstract

Tomato (Lycopersicon esculentum Mill.) is a horticultural plant with high economic value, consumed as fresh fruit or a processed product. However, this plant still requires serious handling, especially in tomato seeds. The seeds are coated with quite slimy flesh and need to be separated using a suitable method so that the flesh layer can be cleaned optimally. Tomato seeds have a high water content, causing the seeds to easily damaged and quickly decrease their viability. Therefore, it is necessary to dry the seeds properly to lower the water content while maintaining the seed’s quality. This research aimed to calculate the time needed to reduce the water content of tomato seeds in a dehumidified drying machine, analyze the germination percentage of tomato seeds resulting from dehumidified drying using various separation techniques, and measure the effect of separation techniques. The temperature of dehumidified drying affects the germination and vigor of tomato seeds. The experiment was carried out using a two factorial Completely Randomized Design (CRD) method, namely separation technique (i.e., left for 24 hours, using 2% HCl, and using 10% Na2CO3) and temperature in a dehumidified drying machine (i.e., 30, 40, 50, and 60 °C). The highest germination percentage and vigor index were produced in the treatment with 2% HCl for 2 hours with a drying temperature of 40°C. The separation technique and drying temperature influenced the germination percentage and vigor index, but the interaction between separation techniques had no effect.
Enzyme dosage detection to degrade feathers in edible bird’s nests: A comparative convolutional neural networks study Liana, Verianti; Arifiandika, Rizal; Rohmatulloh, Bagas; Nafi’ah, Riris Waladatun; Hidayat, Arif; Hendrawan, Yusuf; Al-Riza, Dimas Firmanda; Mahatmanto, Tunjung; Nugroho, Hermawan
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 6, No 4 (2023)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2023.006.04.6

Abstract

Edible Bird’s Nest (EBN), a costly food product made from swiftlet’s saliva, has encountered a longstanding problem of plucking the swiftlet’s feather from the nests. The destructive and inefficient manual process of plucking the feathers can be substituted with a serine protease enzyme alternative. Accurate detection of enzyme dosage is crucial for ensuring efficient feather degradation with cost-effective enzyme usage. This research employed the transfer learning method using pretrained Convolutional Neural Networks (Pt-CNN) to detect enzyme dosage based on EBN’s images. This study aimed to compare the image classification mechanisms, architectures, and performance of three Pt-CNN: Resnet50, InceptionResnetV2, and EfficientNetV2S. InceptionResnetV2, using parallel convolutions and residual networks, significantly contributes to learning rich informative features. Consequently, the InceptionResnetV2 model achieved the highest accuracy of 96.18%, while Resnet50 and EfficientNetV2S attained only 30.44% and 17.82%, respectively. The differences in architecture complexity, parameter count, dataset characteristics, and image resolution also play a role in the performance disparities among the models. The study’s findings aid future researchers in streamlining model selection when facing limited datasets by understanding the reasons for the model’s performance and contributing to a non-destructive and quick solution for EBN’s cleaning process.  
Analysis of apple chips business development strategies using business model canvas approach and SOAR-AHP method Mustaniroh, Siti Asmaul; Putri, Salma Rana; Maligan, Jaya Mahar
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 3 (2024)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2024.007.03.3

Abstract

The study focuses on SMEs X, a producer of various processed fruit products, primarily apple chips. The business experienced a 90% decline in revenue due to an 8-month market closure during the Covid-19 pandemic, with ongoing challenges such as reduced revenue and production capacity post-pandemic. This study aims to identify business models in SMEs using the Business Model Canvas (BMC) approach, develop alternative business strategies through SOAR analysis of BMC elements, prioritize these strategies using the Analytical Hierarchy Process (AHP) method, and enhance their BMC. Four expert respondents participated in the study. The research results highlight the current business conditions across the 9 BMC elements. The SOAR matrix produced eight alternative strategies, prioritized using the AHP method, including optimal production planning and scheduling (OR2), strengthening apple chips brand awareness (OA2), disseminating freeze-drying production technology innovations (OA1), developing business unit production (SA2), expanding the marketplace (SA1), maximizing the use of social media (OR1), product quality standardization (SR1), and forming partnerships with other fruit chip SMEs to innovate freeze-dried products (SR2). The BMC was further developed by integrating SR2 and OA1 into the key partnerships element, SA2 into the key resources element, OA2, OR1, and OA2 into the key activities element, SR1 into the value proposition element, and SA1 into the channel element.

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