Mashua (Tropaeolum tuberosum), a resilient and underutilized Andean tuber, is a high-potential nutritional and functional food innovation resource. This review surveys information on the nutritional composition, bioactive profile, and functional properties of the tuber based on a comprehensive literature search conducted in the Scopus database. The search strategy employed eight Boolean operators combining the following terms: (“Tropaeolum tuberosum” OR “mashua”) AND (“bioactive compounds” OR “functional properties” OR “glucosinolates” OR “antioxidant activity” OR “food processing”). The review included English-language research articles published between 2000 and 2025. Its diverse constituents, such as glucosinolates, phenolics, and anthocyanins, have antioxidant, anti-inflammatory, and antimicrobial activities. Technologies such as freeze-drying, microencapsulation, and 3D printing make it easier to preserve these bioactive components and ensure their use in novel food products. Although Mashua has potential, its widespread adoption remains limited by its distinct sensory characteristics and the lack of clinical validation regarding its effect on human health. To extract the full potential of mashua as a functional ingredient for the global food industry, consensus evidence exists around the need for standardized analytical methodologies, technological innovation, and sustainable value chain development.

The sustainable processing of coffee requires not only improving the efficiency of conventional operations but also advancing the recovery and valorization of bioactive compounds across the coffee value chain. In this context, emerging technologies offer eco-efficient alternatives to conventional extraction methods. This review summarizes recent advances in ultrasound-assisted extraction (UAE), high-pressure extraction (HPE), cold atmospheric plasma (CAP), and microwave-assisted extraction (MAE) applied to coffee beans and major coffee side streams, including pulp, husk, parchment, silverskin, and spent coffee grounds. The physicochemical principles of each technology, the main operating parameters, and their influence on extraction yield, phenolic composition, antioxidant capacity, and heat-sensitive compound preservation are discussed. Furthermore, potential synergies between combined techniques (UAE-MAE or HPE-UAE) and trends toward industrial scaling and integral valorization within a circular economy framework are highlighted. Overall, the evidence indicates that emerging technologies can intensify coffee extraction processes, increase phenolic recovery (often achieving up to two-fold improvements in total phenolic content compared to conventional techniques), and significantly reduce processing times (commonly reaching 2.5–15 min), supporting more sustainable and industrially relevant value chains.

Modified tuber starches have gained relevance as innovative and versatile materials for the encapsulation of bioactive compounds, distinguishing themselves from synthetic polymers due to their biocompatibility, biodegradability, and tunable functionality. This review analyzes the effects of physical, chemical, and biochemical modifications on the composition and morphological, rheological, thermal, and techno-functional properties of tuber starches, as well as their development prospects as coating materials in encapsulation techniques such as spray drying, freeze-drying, electrospinning, and emulsification. The evidence reviewed indicates that modified tuber starches exhibit reduced retrogradation, higher thermal resistance, improved solubility, and better digestibility, facilitating their application as protective agents. The main challenges for their industrial implementation are identified and analyzed, including the standardization of processes, scalability, and the ambiguous regulatory framework. In the future, research in this area should be directed toward the optimization of “clean-label” methodologies and the valorization of non-conventional tuber sources, thereby consolidating the development of safer, more effective, and more sustainable encapsulation systems for the food industry.

The growing demand for fresh fruit, coupled with high postharvest losses, highlights the need for sustainable and effective preservation technologies. In this context, polymeric biocoatings are emerging as a promising alternative to conventional synthetic packaging, thanks to their biodegradability, film-forming capacity, and potential to incorporate bioactive compounds. This review article summarizes recent advances in the development of coatings based on polysaccharides, proteins, and nanomaterials, analyzing their physicochemical, functional, and sensory properties, and the main conventional and emerging application methods used in fresh fruit. It also highlights the role of phenolic compounds and essential oils as antioxidant and antimicrobial agents, along with the valorization of agro-industrial by-products under circular economy schemes. Finally, it discusses the challenges associated with standardization, industrial scaling, and consumer acceptance, proposing future perspectives aimed at designing multifunctional systems that extend the shelf life and improve the quality of fresh products, in line with environmental sustainability objectives. Unlike recent reviews, this work unifies structure–function relationships with quantitative comparisons of coating performance across fruits. It further contributes a critical evaluation of emerging application technologies and their technological and regulatory readiness, offering a distinctly more integrated perspective.

Edible roots and tubers, such as potato, sweetpotato, cassava, and carrot, are vital to global food security; however, postharvest quality control still relies largely on costly, subjective manual inspection. Computer vision and machine learning applied to multiple imaging modalities have emerged as non-destructive approaches for automated inspection and quality assessment. This review synthesizes 141 studies (2016–2026) that applied these methods to the non-destructive quality assessment of edible roots and tubers. The reviewed studies span eight species, with potato (77.3%) and sweetpotato (17.0%) being dominant. RGB imaging is the most common acquisition modality (79%), alongside the growing use of hyperspectral and near-infrared spectroscopy. Deep learning is now the default approach, with its share rising from 18% (2016–2020) to 71% (2024–2026). YOLO-family detectors lead real-time sorting and defect detection, while classical image processing and machine learning remain competitive for narrowly defined tasks such as size grading. Several gaps stand out. Evidence beyond potato and sweetpotato remains thin. Public benchmarks are almost nonexistent, with only 5 of 141 studies using a public dataset. Foundation and zero-/few-shot models were almost absent from the reviewed studies, and most studies measure benchtop accuracy rather than the full inspection-to-actuation pipeline. This review maps where the field has matured and where it has not, offering a structured reference point and a research agenda for non-destructive quality evaluation of these crops.