A Nutritional Quality-Driven Food Processing Framework for Sustainability

Thesis Abstract

This study addresses the urgent need to harmonize nutritional quality with sustainability in food processing, recognizing that conventional processing often degrades micronutrients and bioactive compounds while consuming excessive energy and water. The research aims to develop and validate a Nutritional Quality-Driven Food Processing Framework (NQ-FPF) that optimizes processing parameters to preserve or enhance nutrient density, functional properties, and sensory acceptability while minimizing environmental footprints. Specific objectives are (1) to identify critical control points where processing interventions most influence nutrient retention (e.g., vitamins, minerals, phenolics) and energy-water-use efficiency; (2) to formulate a framework linking product quality targets with process design variables (time, temperature, moisture, pH, and mitigation of nutrient losses) and sustainability indicators (energy use, water footprint, waste valorization); (3) to empirically evaluate the framework across diverse staple commodities (maize, cassava, and legumes) subjected to pilot-scale processing; (4) to develop decision-support tools incorporating life cycle assessment (LCA) and nutritional profiling for process optimization; and (5) to propose policy and industry adoption pathways for nutrient-preserving, low-impact processing technologies. Methodologically, the study adopts a mixed-methods design anchored in the Theory of Planned Behavior and the Systems Theory of sustainability. The population comprises purposively selected pilot facilities and small-to-medium scale processing plants, with collaborations involving two industrial partners and three academic laboratories. A total of 36 experimental trials per commodity are conducted in a factorial design to isolate the effects of processing variables on nutrient retention (e.g., ascorbic acid, folates, carotenoids, minerals) and energy and water use. Analytical measurements include high-performance liquid chromatography (HPLC) for micronutrients, spectrophotometric assays for antioxidant activity, proximate composition analysis, and near-infrared spectroscopy for rapid quality assessment. Environmental performance is assessed through cradle-to-gate life cycle assessments using a standardized LCA framework (ISO 14040/44) with impact categories including global warming potential, eutrophication, and water scarcity. Sensory evaluation employs trained panels and consumer acceptability tests to ensure market viability. Data analysis utilizes multivariate regression to quantify relationships between process variables and nutrient/energy outcomes, ANOVA for treatment effects, and structural equation modeling (SEM) to test the hypothesized framework links between processing decisions, nutritional quality, and sustainability metrics. Thematic analysis of expert interviews informs framework refinement and practical implementation challenges. Expected findings indicate that targeted processing modifications—such as optimized thermal blanching with controlled moisture, enzyme-assisted decontamination, and rapid cooling protocols—can significantly reduce nutrient losses by 25–40% relative to conventional methods while achieving energy reductions of 10–25% and water savings of 15–30%. The NQ-FPF is anticipated to yield robust relationships between processing parameters and composite sustainability scores, enabling prioritization of interventions with the greatest nutrient-sustainability gains. The research is expected to identify commodity-specific optimization pathways and elucidate trade-offs between sensory quality and nutrient preservation, offering a scalable framework adaptable to diverse processing contexts. The study contributes to knowledge by integrating nutrition science, process engineering, and life cycle thinking into a cohesive decision-support framework for sustainable food processing. It provides validated models and a practical toolset for processors to optimize nutrient retention without compromising environmental performance, supported by empirical data across multiple commodity systems. The findings have policy relevance for defining nutrient-preservation standards, informing funding for energy- and water-efficient technologies, and guiding industry best practices for sustainable product reformulation. Theoretical contributions include operationalizing the Nutritional Quality-Driven Processing model within a systems-based sustainability paradigm and extending application of SEM to link granular processing choices with macro-environmental outcomes. The main conclusion is that nutritionally prioritized processing decisions, when embedded within an LCA-informed framework, can simultaneously advance public health and sustainability goals. Recommendations emphasize scalable adoption of nutrient-preserving technologies, routine integration of nutritional profiling into process design, development of industry-wide guidelines for energy and water optimization, and further research into region-specific crops and consumer-driven quality attributes.