Balunkeswar Nayak

Antinutrients in plant foods must be removed or reduced during processing before they can be consumed safely. The study evaluated the effectiveness of various processing methods in reducing antinutrient levels in yam flour. The treatments included soaking for varying durations (4, 8, and 12 h), boiling for different time intervals (5, 15, and 25 min), and autoclaving at 100°C for corresponding durations (5, 15, and 25 min). Post‐treatment, the yam slices were dehydrated in a hot air oven at 50°C for 10 h and then milled into flour. The study quantitatively assessed the reduction in phytate, oxalate, tannin, saponin, trypsin, and α‐amylase inhibitors. The findings demonstrated reduction ranges of 15%–35%, 20%–45%, 50%–82%, 16%–43%, 11%–78%, and 16%–51% across the different pretreatment methods. Additionally, the study investigated the effects of these pretreatments on antioxidant activity, structural modifications (via XRD and FTIR analyses), morphological changes, and thermal properties. A statistically significant impact (p ≤ 0.05) was observed on total phenolics, flavonoids, and antioxidant levels. The crystallinity index and granule particle size varied between 9.82% and 9.61% and 10–140 μm, respectively. Notably, boiling for 25 min emerged as the most efficacious pretreatment for antinutrient reduction, though it also induced considerable alterations in granule size and morphology, as evidenced by SEM micrographs. However, it may be proposed that a combination of boiling followed by soaking could be explored for potentially improved results and warrant further investigation.

With growing awareness of the environmental, economic, and social costs associated with food waste, there is a concerted effort on multiple scales to recover the nutrient value of discarded food. These developments are positive, but the rapid movement toward alternatives and the complexity of solving problems located at the intersection of economic, social, and environmental systems also have the potential to produce unanticipated risks. This paper draws upon long-term stakeholder-engaged research throughout New England, with a focus on Maine, to develop a transdisciplinary, systems-based model of the potential social, economic, and environmental risks of food waste nutrient cycling. Our effort is intended to help inform the creation of safe, functional, and environmentally benign circular food systems.

Thermophysical properties such as thermal conductivity (k), bulk density (ρ), specific heat (C), and thermal diffusivity (D) are crucial for simulating dynamic thermal processes such as drying and temperature-controlled storage. In this study, the effects of product temperatures (T) and moisture contents (MC) on different thermophysical properties of kelp were studied. The thermal conductivity and thermal diffusivity of the samples were measured using a KD2 Pro dual-needle sensor for a temperature range of 30–70° C and moisture content varying from 6 to 90 g (100 g sample)⁻¹. The particle density and the bulk densities of the samples were estimated using a pycnometer with toluene as a working liquid. The k, C, and D values were fitted with a regression equation considering the individual and interaction factors (MC × T). Moisture content and temperature of the sample have significant effects (p < 0.05) on its thermophysical properties. The thermophysical properties calculated using the Choi and Okos' model based on the mass fraction of individual components present in sugar kelp and temperature were significantly (p < 0.05) different as compared to the experimental values. An artificial neural network (ANN) model evaluated eight different configurations of neurons in a single hidden layer for 180 data. The prediction performances of the ANN were evaluated in terms of mean absolute error (MAE), mean relative error (MRE), standard error (SE) and coefficient of determination in MATLAB. Overall, the ANN model’s performance was superior to the Choi and Okos empirical model in predicting the thermophysical properties with a relatively high coefficient of determination and low MAE, MRE, and SE.