Sensory evaluation of aromatic foods packed in developed starch based films using fuzzy logic

Chowdhury, Trinath; Das, Madhusweta

doi:10.7455/ijfs/4.1.2015.a3

Cited by 11 publications

(1 citation statement)

References 38 publications

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“…Basak et Fuzzy logic systems are efficient and simple designs for fast analysis and problemsolving with a highly accurate approach. As a result, these systems have been widely used in industry [94,100,102,103]. In the food industry, fuzzy logic techniques are also applied.…”

Section: R Peer Reviewmentioning

confidence: 99%

The Application of Artificial Intelligence and Big Data in the Food Industry

Ding,

Tian,

et al. 2023

Foods

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Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

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Section: R Peer Reviewmentioning

confidence: 99%

The Application of Artificial Intelligence and Big Data in the Food Industry

Ding,

Tian,

et al. 2023

Foods

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Self‐supporting‐film from starch, poly(vinyl alcohol), and glutaraldehyde: Optimization of composition using response surface methodology

Sen

Das

2016

J of Applied Polymer Sci

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Use of starch based biodegradable packaging film can partially reduce the landfilling problem from non-biodegradable petroleum based alternatives. The aim of this work was to optimize raw material blend composition containing corn-starch (CS), and low amount of poly(vinylalcohol) (PVA) and glutaraldehyde (GA) to produce self-supporting-film (SSF), using response surface methodology. Rotatable central composite design was used to evaluate the effect of CS (6.25-7.50), PVA (0.00-1.25), and GA (0.00-1.25), in g/100 mL of the blend, on tensile strength (TS), percent elongation (%El), and water vapor permeability (WVP) of the film. The most significant (p < 0.01/0.05) factors were: CS and GA for TS, CS and PVA for El, and PVA for WVP. The SSFs were thin, flexible and transparent; the optimum composition (g/100 mL) to maximize TS and El, and minimize WVP was 7.50 (CS), 0.875 (PVA), and 0.125 (GA), which produced SSF showing TS: 11.66 MPa, %El: 8.56, and WVP: 0.13 g mm/m 2 /kPa/h. V C 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44436.

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Flavor quality evaluation system of Xinjiang milk knots by using SOM neural network and the fuzzy AHP

Wei

Zhan

et al. 2020

Food Science & Nutrition

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Self-made milk knots in Xinjiang Kazakh ethnic group were used as material to establish the quality assessment system of flavor quality. The fuzzy analytic hierarchy process based on the optimal consistency matrix was used to evaluate the quality of the samples qualitatively and quantitatively. Its result is consistent with the cluster analysis of the SOM neural network. The results showed that the milk knot samples of Altay had differences with the milk knot samples of Yili. The comprehensive evaluation system is feasible and can evaluate the quality of milk knot samples by flavor characteristics. This can provide a reference for further research on the origin of differences between two types of milk knot samples. K E Y W O R D Sfuzzy analytic hierarchy process, sensory evaluation, SOM neural network, Xinjiang traditional milk knots

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Sensory evaluation of aromatic foods packed in developed starch based films using fuzzy logic

Cited by 11 publications

References 38 publications

The Application of Artificial Intelligence and Big Data in the Food Industry

The Application of Artificial Intelligence and Big Data in the Food Industry

Self‐supporting‐film from starch, poly(vinyl alcohol), and glutaraldehyde: Optimization of composition using response surface methodology

Flavor quality evaluation system of Xinjiang milk knots by using SOM neural network and the fuzzy AHP

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