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Research Detail

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Md Rahmatuzzaman Rana
Department of Food Engineering and Tea Technology, Shahjalal University of Science and Technology, Sylhet, 3100, Bangladesh

Majharulislam Babor
Department of Food Engineering and Tea Technology, Shahjalal University of Science and Technology, Sylhet, 3100, Bangladesh

Ashfak Ahmed Sabuz
Postharvest Technology Division, Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

The present study was aimed to design and develop the consumer-accepted soy yogurt using different sweeteners and investigate the possibility of tracing these sweeteners by implementing a classification algorithm. The effects of three types of sweeteners on the physicochemical properties, sensory properties, and prediction of sweeteners in soymilk-based yogurt were investigated using linear discriminant analysis (LDA). Yogurts were prepared by inoculating lactic acid cultures into soymilk containing 0.3% gelatin, one of the selected sweeteners [sucrose, honey, and sucralose (an artificial sugar)], and strawberry flavor. Freshly prepared soy yogurts were then analyzed for their physicochemical and sensory characteristics. The results revealed that the honey samples had a higher protein content (4.69%–4.71%) compared to that in plain yogurt (3.83%). Soy yogurts containing the sweeteners had a relatively reduced fat content, with the lowest fat content exhibited by the honey samples (1.88%–1.91%). Furthermore, the addition of sweeteners resulted in final products with varying ash content and total soluble solids (TSS). In contrast, the least effect was found on lactic acid and pH. The overall sensory results revealed that the strawberry-flavored soy yogurt with honey as a sweetener could attain acceptable quality upon processing. LDA with two components based on the partial chemical composition of soy yogurts could identify the sweetener source in unknown soy yogurt samples. The discriminatory ability of the LDA model was further validated using unknown soy yogurt samples to predict the sweeteners, and an accuracy level ranging from 80% to  100% was attained in 1000 test runs. Moreover, the model could distinguish the presence of artificial sweeteners from the other sweeteners in the samples with 100% accuracy. 

  Soy yogurt, Sweeteners, Discrimination analysis, Acceptability
  In Bangladesh
  
  
  Food Safety and Security
  Nutrition, Yogurt

To design and develop the consumer-accepted soy yogurt using different sweeteners and investigate the possibility of tracing these sweeteners by implementing a classification algorithm.

Materials: Soybean (Glycine max) of BARI-5 variety was obtained from Bangladesh Agricultural Research Institute (BARI), Bangladesh, and stored at 4 ?C until use. Sucrose, honey, artificial sugar (sucralose), and strawberry flavor were obtained from the local market. All chemicals were of analytical grade. Commercial fresh yogurt was used for the isolation of the starter culture, which contained Streptococcus saliferous subsp. thermophilus (108 CFU/mL) and Lactobacillus delbrueckii (108 CFU/mL). Preparation of soymilk: The soymilk was prepared following the method described by Mei et al. [30] with slight modification. Briefly, 500 g of dry, mature, whole soybeans were soaked in 0.3% NaHCO3 (1:3 w/v) at 25 ?C for 12 h. After proper decantation, the seeds were dehulled manually and then blended with distilled water (1:8 w/v) for 5 min. The slurry was sieved through a double-layer cheesecloth. The supernatant portion was collected and simmered for 10 min, followed by cooling and storing at 4 ?C until use. Preparation of soy yogurt: Into the freshly prepared soymilk, any of the sweeteners and the flavor were added according to the formulations indicated. Subsequently, the mixture was pasteurized in a water bath at 85 ?C for 30 min and then cooled to 42 ?C. Afterward, the mixture was inoculated with 4% (w/v) yogurt starter culture, with a minimum count of approximately 7 log CFU/mL. The inoculated samples were incubated at 42?C for 7 h. After processing, the soy yogurts were subjected to physicochemical and sensory analysis. Physicochemical characteristics: The proximate composition of soy yogurt samples was determined using the standard methods. Moisture, protein, ash, and fat contents were determined using the gravimetric method (AOAC method 934.01), micro-Kjeldahl method (AOAC method 991.20), (AOAC method 923.03), and Gerber method, respectively. The acidity was determined by the samples titrating against 0.1 M sodium hydroxide and was expressed as % lactic acid. The pH of soybean, soymilk and soy yogurt was measured using a calibrated pH meter (Hanna 201A, Germany). TSS were determined using a hand refractometer (Master-53S, Atago, Japan) and expressed as ?Brix. The specific gravity of soy yogurt was estimated at room temperature using a standard specific-gravity bottle of 50 mL capacity. Sensory analysis: Analysis of the sensory characteristics was conducted by 25 semi-trained panelists in isolated cabins with the same lighting and temperature conditions. The evaluation was performed on a nine-point Hedonic scale, in which 1 corresponded to ‘dislike extremely’ and 9 corresponded to ‘like extremely’. The panelists evaluated the soy yogurt samples for the attributes of color, flavor, taste, texture, and overall acceptability. Statistical and chemometric procedures for data analysis: In all assays, final result values were calculated by averaging the results for nine different batches of soy yogurt samples and were expressed as mean and standard deviation. In the chemometric analysis, a subset of chemical parameters, i.e., moisture, protein, fat, and lactic acid, were considered. In the data analysis, Linear discriminant analysis (LDA) was implemented using Python 3.7 to trace and predict the sweeteners in the soy yogurt samples. 

  Journal of Agriculture and Food Research 5 (2021) 100155
  
Funding Source:
1.   Budget:  
  

The present study was aimed to determine the effect on the quality of soy yogurt due to the change of sweeteners. The results of the present study revealed that there was a significant impact on the nutritive value and consumer preference. It was demonstrated that the yogurt samples containing honey had higher protein and ash contents and lower fat content. Moreover, honey with strawberry flavor was the most preferred combination among the panelists in the sensory analysis. Therefore, it is suggested further to study the combination of honey and other flavoring agents to produce a marketable and consumer-accepted plant-based alternative to cow milk-based yogurt. Using the proposed strategy, it was observed that the LDA model could assess the information conveyed by the chemical composition of soy yogurt to trace the sweeteners in the soy yogurt samples with a high level of accuracy. The artificial sweeteners could be differentiated from the other sweeteners in the soy yogurt samples or other similar food products. Therefore, the proposed strategy could be implemented in the food sector to identify different sweetening agents added to the food system without having to measure several parameters to maintain quality and safety. 

  Journal
  


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