Yellow or sour passion fruit is a climacteric fruit with a high rate of respiration and ethylene production, and postharvest technology is needed to extend its shelf life. This study investigated the properties of a biocomposite film with chitosan (CH) incorporated with beeswax (BW) and graphene oxide (GO) nanoparticles for use as an edible coating to extend the shelf life of yellow passion fruit at 22 °C and 70% RH for eight days. CH films associated with BW showed lower water vapor permeability (WVP) than films with CH alone. However, adding GO to the CH + BW biopolymer matrix improved the WVP, decreased the solubility (12.8%), and increased the opacity of the film by 9% compared to those of the CH film. Fruits coated with CH + BW or CH + BW + GO exhibited a reduction in respiration rate, a slower ripening process by approximately 3 days, and a significant decrease in weight loss. This also resulted in a higher soluble solids content and increased antioxidative capacity of the pulp. The incorporation of GO into the CH + BW matrix resulted in a more pronounced delay of fruit ripening, as evidenced by the lower depigmentation of the peel at eight days, with a lightness approximately 10.7% lower at 54.92, a chroma value 16.5% lower at 49.33, a hue angle 7.2% higher at 92.56, a soluble solid (SS) content 16.7% higher at 11.32°Brix, and an acidity 31.9% higher at 4.18% compared to the control. Furthermore, the biopolymer packaging led to a higher consumer acceptance score for the fruit.

Artificial intelligence (AI) is emerging as a transformative force in education, driving personalized teaching and mitigating educational inequalities. This study aims to analyze, through a bibliometric approach, the main trends in the application of AI in education, with an emphasis on scientific production associated with developing countries and contexts with limited infrastructure, and to identify advances, challenges, and opportunities. The methodology used was bibliographic research, characterized by systematic analysis of the literature. Data were collected from the Scopus and Web of Science (WoS) databases, covering the period from 2014 to 2024. After screening and applying inclusion and exclusion criteria, 634 documents were selected. Reference management was performed using Zotero, and data organization and cleaning was conducted on the Rayyan platform. Bibliometric analysis was conducted using the Bibliometrix package in RStudio software, and VOSviewer was employed for the scientific mapping and analysis of co-authorship and co-occurrence networks. The results revealed an increase in scientific production of AI in education from 2019 onwards, intensified by the COVID-19 pandemic. China, the United States, and India stood out as the countries with the most significant scientific production and academic impact in the field. Despite these advances, the study highlighted several challenges, including infrastructural barriers, algorithmic bias, a lack of teacher training, and ethical risks associated with the collection and use of sensitive data. It is concluded that the ethical, equitable, and contextualized use of AI in education requires public policies committed to digital inclusion, ongoing teacher training, and investments in accessible technologies that are sensitive to local realities.