AI-Driven Software Framework for Intelligent Optimization of Sugar Reduction Strategies in Confectionery Using Polyols and High-Intensity Sweeteners
Abstract
Growing consumer awareness regarding health and nutrition has increased the demand for reduced-sugar confectionery products.
However, sugar performs multiple functional roles in confectionery systems, including sweetness, bulking, texture formation,
crystallization control, and shelf stability, making its reduction a complex formulation challenge. This study proposes an AI-driven
software framework designed to intelligently optimize sugar reduction strategies in confectionery formulations using polyols and high-intensity sweeteners. The developed framework integrates machine learning algorithms, ingredient property databases, and predictive
modeling techniques to support researchers and product developers in designing optimized reduced-sugar formulations. The software architecture consists of modules for ingredient selection, sweetness equivalence prediction, physicochemical property estimation, and multi-objective optimization. Polyols such as sorbitol, xylitol, and maltitol are incorporated to provide bulking effects and desirablemouthfeel, while high-intensity sweeteners including steviol glycosides and sucralose are used to achieve the required sweetness intensity. A structured dataset comprising formulation ratios, sweetness intensity, water activity, texture parameters, and sensory evaluation scores is used to train supervised learning models for prediction and optimization. The framework applies multi-objective optimization algorithms to balance key formulation constraints including sweetness profile, caloric reduction, crystallization behavior, and storage stability. The proposed AI-enabled approach demonstrates significant potential in improving formulation efficiency and guiding intelligent sugar substitution strategies. This study highlights the interdisciplinary integration of software engineering, machine learning, and food product development for designing healthier next-generation confectionery products.
Keywords:
rtificial Intelligence, Sugar Reduction, Confectionery Optimization, Polyols, High-Intensity Sweeteners, Predictive Food FormulationPublished
Issue
Section
License
Copyright (c) 2026 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Juby Mathew, Maria Jojo, Neha Ann Samson, Noell Biju Michael, Ron T Alumkal, PulseSync: IoT-Enabled Monitoring and Predictive Analytics for Healthcare , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- K Sooraj, Yasim Khan M, A High Speed Low Power 10T SRAM with high Robustness , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Dr nitha C Vellayudan, Akshay K.P, Muhamed Adhil P.M, C.A Sivasankar , Crop Yield and Price Prediction , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Sreyas George, Gregan George, Ruth Tennyson, Rishil Shajan, Dr. Juby Mathew, MindPulse: Employee Mental Health Detection and Attrition Prediction App , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Eric Biji Varghese, MediLens: An AI-Powered Medicine Information and Assistance System , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Albin Thomas Lalu, Resmara S, Alen A Thankachen, Sneha Priya Sebastian, Dany Jennez , Lirin Blesson, Kesia Sunny, Fault Detection of Transmission Lines Using Unmanned Aerial Vehicle (UAV) , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Rony Sebastian Tomson, Alan Leejoy, Nandagopan L, Althaf Rahman, Angitha George, Reson Studio: An AI Integrated Digital Audio Workstation for Intelligent and Collaborative Music Production , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- NITHYA M V, ADIL SIYAD K.M, AFINSHA P.B, GAUTHAM T.S, ABHIJITH K.P, SALIH SUDHEER, ARJUN SANKAR R.S, C.S ADHITHYAN, JEWELLERY SHOPPING WITH FACIAL RECOGNITION , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Anishamol Abraham, Elbin Santhosh, Diliya Saji, Edwin Roy, Catherine Achu Punnoose, AI Revolutionizing Fashion: A Review of Algorithms and Applications , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Honey Joseph, Aaron M Vinod, Abin Mathew varghese, Aby Alex, Aleena Sain, Crop Yield Prediction Using ML , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
You may also start an advanced similarity search for this article.
