2014
DOI: 10.15406/jnhfe.2014.01.00030
|View full text |Cite
|
Sign up to set email alerts
|

Process Optimization for Producing Cowpea Added Instant Kheer Mix Using Response Surface Methodology

Abstract: Abbreviations: RSM, response surface methodology; ANOVA, analysis of variance; SMP, skimmed milk powder; CCD, central composite design; R 2 , regression coefficient; CV, coefficient of variation IntroductionAn estimated 50 to 55% of milk produced in India is converted into various traditional milk products including numerous dairy desserts. A variety of sweet desserts to suit different festive occasions are manufactured, mainly in unorganized sector across the country. One of the most common traditional dairy … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
7
0

Year Published

2016
2016
2024
2024

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 8 publications
(7 citation statements)
references
References 20 publications
0
7
0
Order By: Relevance
“…RSM was used to determine the optimum process parameters that yield high malting characteristics. For numerical optimisation, the goals (none, maximum, minimum, target, or range) should be set for both the independent and response variables where all goals are combined into one desirable function [37]. Maximum values were set for the responses (i.e., Brix, FAN, and diastatic power).…”
Section: Resultsmentioning
confidence: 99%
“…RSM was used to determine the optimum process parameters that yield high malting characteristics. For numerical optimisation, the goals (none, maximum, minimum, target, or range) should be set for both the independent and response variables where all goals are combined into one desirable function [37]. Maximum values were set for the responses (i.e., Brix, FAN, and diastatic power).…”
Section: Resultsmentioning
confidence: 99%
“…To meet the intended target requirement placed on each response variable and independent factor in this experiment, a goal was set for each independent and dependent variable. An-uar, Adnan, Saat, Aziz, and Taha (2013), Gupta, Verma, Jain, and Jain (2014) and Danbaba et al (2016) reported that for locating optimum conditions using numerical methods, there was a need to set goals, which may either be none, maximum, minimum, target or range for both response and independent variables that could be combined into one desirable function. In this work, the barrel temperature, feed moisture content and feed soybean composition were all set within range (100 to 140 o C; 15 to 25%; 8 to 24%) as defined by the preliminary study (Table 1), while the goal for the response variables of bulk density, expansion index and lightness chroma levels were set at maximum, and a* and b* set at minimum (Table 6).…”
Section: Optimization Process Variablesmentioning
confidence: 99%
“…Also, the ready‐to‐consume puddings often have a very limited shelf life, often spanning just a few hours to a day (Gupta et al . 2014; Pahwa and Khamrui 2020), which stresses the need to explore technologies for extended shelf life products in this category.…”
Section: Introductionmentioning
confidence: 99%
“…Several mathematical and statistical approaches have been reported in literature for optimisation. Among the reported methodologies, response surface methodology (RSM) has been widely applied as a mathematical tool to optimise the processing parameters during the production of several ready-to-eat and ready-to-reconstitute products (Gupta et al 2014;Jha et al 2015;Jain et al 2019;Pahwa et al 2020).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation