scholarly journals Production and quality evaluation of soy cheese (tofu) using various coagulants

2021 ◽  
Vol 13 (1) ◽  
pp. 36-42
Author(s):  
Joel Ndife ◽  
Itohan Imade ◽  
James Samaila

Food formulations that incorporate soy ingredients are being exploited as veritable alternatives. Cheese analogues are healthy alternatives to obtain the benefits of consuming functional foods. There is a need to enhance the production and quality of soy cheese. In this study, soy cheese (tofu) samples were prepared from soybean using four selected coagulants - Moringa oleifera seed extract (MC), tamarind seed extract (TC), lime juice (LC) and alum (AC). The effects of the coagulants on the physicochemical, microbial and sensory qualities of the soy cheese samples were evaluated. The results of the physical properties of the samples showed that MC had higher yield (12.84%) and acidity (0.37%), while AC had the highest values in hardness (84.55%) and dry matter (36.72%) content. The result of the proximate composition revealed that MC had the lowest moisture content (60.52 %) and the highest protein content (22.51%). The ash content of the soy cheese samples from plant coagulants MC (3.00%), TC (2.80%) and LC (3.5%) were lower than that of the alum coagulant AC (3.89%). The cheese from alum coagulant (AC) had more minerals than those from plant coagulants. TC had the highest vitamin C (2.69 mg/100 g), while MC had the highest vitamin B1 (6.07 mg/100 g) and B2 (29.21 mg/100 g) contents. There was no detection of coliform in the soy cheese samples. There were no significant differences (p>0.05) in the appearance and overall acceptability of MC sample and LC sample MC sample from Moringa oleifera seed extract coagulant had the highest sensory scores for flavour (8.35), texture (8.40) and overall acceptability (8.63). The results of quality properties of the cheese samples differed with the coagulants used. Moringa Oleifera coagulated cheese (MC) had superiority in nutrients and sensory qualities Hence, it is recommended for tofu production.

2017 ◽  
Vol 329 ◽  
pp. 102-109 ◽  
Author(s):  
William K. Garde ◽  
Steven G. Buchberger ◽  
David Wendell ◽  
Margaret J. Kupferle

2020 ◽  
Vol 48 (1) ◽  
pp. 114-120
Author(s):  
José Maria Carrera-Chávez ◽  
Edson Eduardo Jiménez-Aguilar ◽  
Theisy Patricia Acosta-Pérez ◽  
José Alberto Núñez-Gastélum ◽  
Andrés Quezada-Casasola ◽  
...  

RSC Advances ◽  
2016 ◽  
Vol 6 (31) ◽  
pp. 25918-25926 ◽  
Author(s):  
Saumyadeb Dasgupta ◽  
Naga Siva Kumar Gunda ◽  
Sushanta K. Mitra

We have provided a detailed antimicrobial study of the seed extract ofMoringa oleifera, a common medicinal plant.


2020 ◽  
Vol 11 (2) ◽  
pp. 130-133
Author(s):  
Shalini Devi ◽  
Rajni Modgil

The present study was conducted to prepare and evaluate the nutritional quality of millet cake. Millet flours were incorporated at 70 per cent level in cakes and their sensory and nutritional properties were evaluated. The results revealed that, incorporation of millet flours in cake significantly increased the contents of ash (1.27 to 4.32%), protein (10.45 to 11.13%) and fibre (2.18 to 6.95%). The cake supplemented with Kodra (Eleusine coracana) flour showed maximum overall acceptability after control. From the study it can be concluded that a maximum of 70 per cent millet flours can be incorporated to prepare acceptable quality of cake.


Author(s):  
Slamet Widodo ◽  
Muhammad Kalili

Some studies show that melinjo (Gnetum gnemon L.) seed extract contains various active ingredients that are beneficial to human health; even it has been commercialized as a health supplement product. Quality of seeds as raw material becomes one of key factors that determine the quality of product derived from melinjo seed extract. Therefore sorting becomes a critical process. However the sorting of good quality and broken seeds (moldy, chalky and perforated/infected insects) is still done manually with visual observations that tend to be inaccurate and inconsistent. This study aims to develop a new method for evaluation of quality of melinjo seeds based on digital image processing. The image is taken using two lighting systems i.e. frontlight and backlight. The results show that using color features (RGB and HSV) and certain threshold values, good quality and broken seeds can be distinguished by 92.5% and 100% accuracy using frontlight and backlight image respectively. It indicates that digital image processing can be used as an alternative for quality evaluation of melinjo seed.


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