Worldwide, a massive amount of agriculture and food waste is a major threat to the environment, the economy and public health. However, these wastes are important sources of phytochemicals (bioactive), such as polyphenols, carotenoids, carnitine, coenzymes, essential oils and tocopherols, which have antioxidant, antimicrobial and anticarcinogenic properties. Hence, it represents a promising opportunity for the food, agriculture, cosmetics, textiles, energy and pharmaceutical industries to develop cost effective strategies. The value of agri-food wastes has been extracted from various valuable bioactive compounds such as polyphenols, dietary fibre, proteins, lipids, vitamins, carotenoids, organic acids, essential oils and minerals, some of which are found in greater quantities in the discarded parts than in the parts accepted by the market used for different industrial sectors. The value of agri-food wastes and by-products could assure food security, maintain sustainability, efficiently reduce environmental pollution and provide an opportunity to earn additional income for industries. Furthermore, sustainable extraction methodologies like ultrasound-assisted extraction, pressurized liquid extraction, supercritical fluid extraction, microwave-assisted extraction, pulse electric field-assisted extraction, ultrasound microwave-assisted extraction and high hydrostatic pressure extraction are extensively used for the isolation, purification and recovery of various bioactive compounds from agri-food waste, according to a circular economy and sustainable approach. This review also includes some of the critical and sustainable challenges in the valorisation of agri-food wastes and explores innovative eco-friendly methods for extracting bioactive compounds from agri-food wastes, particularly for food applications. The highlights of this review are providing information on the valorisation techniques used for the extraction and recovery of different bioactive compounds from agricultural food wastes, innovative and promising approaches. Additionally, the potential use of these products presents an affordable alternative towards a circular economy and, consequently, sustainability. In this context, the encapsulation process considers the integral and sustainable use of agricultural food waste for bioactive compounds that enhance the properties and quality of functional food.

The need to feed 9.9 billion people by 2050 will require the coordination of farming practices and water utilization by nutrient-dense plants and crops. High levels of lead (Pb), a toxic element that can accumulate in plants, can lead to toxicity in humans. With the development of novel treatment technologies, such as atmospheric cold plasma (ACP) and engineered nanoparticles (NPs), the time to germination and levels of heavy metals in food and feed commodities can be reduced. This study provides insight into the impact of plasma-activated water (PAW) on the germination rates and effects of soybean seeds, and the resultant combination effects of zinc oxide uptake in the presence of lead. Soybean seedlings were watered with PAW (treated for 3, 5, and 7 min at 30, 50, and 70 kV), and the germination and growth rate were monitored for 10 days. The germinated seedlings were then grown hydroponically in a nutrient solution, and the biomass of each example was measured. The PAW treatment that resulted in the best growth of soybean seeds was then exposed to Pb and zinc-oxide nanoparticles (ZnONPs) to investigate heavy metal uptake in the presence of nanoparticles. After acid digestion, the rate of heavy metal uptake by the soybean plants was evaluated using inductively coupled plasma-mass spectrometry. The PAW seeds grew and germinated more quickly, demonstrating that the plasma therapy had an effect. The rate of heavy metal uptake by the plants was also shown to be 5x lower in the presence of ZnONP.

Heavy metal concentrations that must be maintained in aquaponic environments for plant growth have been a source of concern for many decades, as they cannot be completely eliminated in a commercial set-up. Our goal was to create a low-cost real-time smart sensing and actuation system for controlling heavy metal concentrations in aquaponic solutions. Our solution entails sensing the nutrient concentrations in the hydroponic solution, specifically calcium, sulfate, and phosphate, and sending them to a Machine Learning (ML) model hosted on an Android application. The ML algorithm used in this case was a Linear Support Vector Machine (Linear-SVM) trained on top three nutrient predictors chosen after applying a pipeline of Feature Selection methods namely a pairwise correlation matrix, ExtraTreesClassifier and Xgboost classifier on a dataset recorded from three aquaponic farms from South-East Texas. The ML algorithm was then hosted on a cloud platform which would then output the maximum tolerable levels of iron, copper and zinc in real time using the concentration of phosphorus, calcium and sulfur as inputs and would be controlled using an array of dispensing and detecting equipments in a closed loop system.

In this study, we combined atmospheric pressure cold plasma, a novel treatment technology, with an absorption technique with soybean husk to remove Pb and Cd from milk. Different combinations of treatment duration, voltage, and post treatment retention time were used to determine the effectiveness of cold plasma. Soybean husk was used for metal extraction, and it was observed that when the milk samples were plasma treated with a discharge voltage of 50 kV for 2 min and held for 24 h, the highest mean elimination of about 27.37% for Pb and 14.89% for Cd was obtained. Reactive oxygen and nitrogen species produced from plasma treatment were identified using Optical Emission Spectra analysis. A high voltage of 50 kV plasma for a 2 min duration could produce 500 ± 100 ppm of ozone concentration inside the treated package. The value of ΔE, which indicates overall color difference measurement, was significantly (p < 0.05) higher in all the treated samples than control samples. However, in the frequency range from 0.01 to 100 Hz, there was not much difference between the control and treated sample in the frequency sweep test. The identified functional groups at different wavenumbers (cm⁻¹) in the treated samples were found to be similar compared to the control samples.