The limited nutritional quality of conventional cereals has prompted the search for more complete alternatives from native Andean sources. In this context, a systematic review of recent studies was conducted to compare the characteristics of Lupinus mutabilis and Amaranthus spp., two crops with potential as functional ingredients in the food industry. Data reported in multiple studies were analyzed, considering the variability attributed to origin, processing, and genetic conditions, as well as the influence of different transformation techniques. The results show that Lupinus mutabilis has a protein content ranging from 41% to 53% in dry matter, along with up to 17% fat and fiber levels above 10%. Amaranthus spp., on the other hand, offers 13% to 17% protein, 6% to 8% fat, and up to 10% fiber and is notable for providing up to 180 mg of polyphenols per 100 g. Processing, such as debittering, may decrease the antioxidant capacity of Lupinus mutabilis by 52.9%, while germination enhances this indicator in Amaranthus spp. The inclusion of these flours in bakery and extrusion formulations allows for protein and fiber content enhancements ranging from 10% to 50%, achieving texture and acceptability improvements in up to 80% of reported sensory tests. This scenario supports the strategic use of these grains to optimize nutritional and functional profiles in innovative food developments.

The pre-university course established at the Universidad Politécnica Estatal del Carchi (UPEC) after the disappearance of the Sistema Nacional de Nivelación y Admisión (National Equalization and Admissions System, known by its Spanish acronym as the SNNA) posed new challenges for the organizational and academic structure of this university. To start with, the challenge began with the adaptation of a curricular structure according to the educational needs of the nine undergraduate degrees offered at the university. It was followed by the implementation of the program, and finally its evaluation. The present research was designed and carried out as part of the latter goal. Its main objective was to determine the sociocultural and demographic factors that influence the academic performance of the students in the course. For the purposes of this investigation, from a methodological perspective, academic performance was associated with the number of subjects passed by the student. Using multivariate dependency techniques, a logistic regression was performed, which determined the degree of incidence of sociocultural and demographics factors on academic success. After applying the model, the results indicated that the demographic factors in this case do not influence academic success, while variables such as the educational level of the student’s parents, the student’s grade on university entrance exams and work status are significant when it comes to establishing a cause and effect relationship in this case study.

Reducing the carbon footprint of higher education institutions has become a global trend in recent years, as they are the axis of society's scientific and technological transformation that must be carried out with a sustainable approach. Among the many approaches that can contribute to this problem are the digital transformation of academic and administrative processes and its impact on reducing paper use. This study details the statistical analysis of the digital transformation process based on the modules and computer services implemented by the ICT department in a higher education institution and its incidence in reducing the use of paper by its teaching and administrative staff. For this purpose, an initial instrument was proposed, consisting of 18 ordinal, three categorical and two numerical variables. After applying statistical data processing and validation techniques, it was reduced to 13 ordinal variables, three categorical and two influential numerical variables. In addition, this study has proposed an appropriate statistical protocol for the design and extraction of information applicable in the context of higher education institutions, consisting of the techniques: Mahalanobis distances, confirmatory factor analysis, Kruskal-Wallis, Mann-Whitney's U and Wilcoxon tests. The results showed the power of confirmatory factor analysis as a technique for obtaining models to measure indirectly observed latent variables, such as perceptions of digital transformation and paper reduction. In addition, it was found that the modules, systems, and computer tools implemented in the institution significantly reduced the execution times for performing administrative and teaching tasks in the institution, and significant differences were identified in the perception of digital transformation and reduction of paper use among staff.

The limited nutritional quality of conventional cereals has prompted the search for more complete alternatives from native Andean sources. In this context, a systematic review of recent studies was conducted to compare the characteristics of Lupinus mutabilis and Amaranthus spp., two crops with potential as functional ingredients in the food industry. Data reported in multiple studies were analyzed, considering the variability attributed to origin, processing, and genetic conditions, as well as the influence of different transformation techniques. The results show that Lupinus mutabilis has a protein content ranging from 41% to 53% in dry matter, along with up to 17% fat and fiber levels above 10%. Amaranthus spp., on the other hand, offers 13% to 17% protein, 6% to 8% fat, and up to 10% fiber, and is notable for providing up to 180 mg of polyphenols per 100 grams. Processing, such as debittering, may decrease the antioxidant capacity of Lupinus mutabilis by 52.9%, while germination enhances this indicator in Amaranthus spp. The inclusion of these flours in bakery and extrusion formulations allows for protein and fiber content enhancements ranging from 10% to 50%, achieving texture and acceptability improvements in up to 80% of reported sensory tests. This scenario supports the strategic use of these grains to optimize nutritional and functional profiles in innovative food developments.

En esta investigación se ha caracterizado uno de los productos agrícolas con mayor proyec- ción para su transformación agroindustrial en la parroquia de Chical, como lo es el borojó (Borojoa patinoi). La fama de este producto agrícola trasciende la línea de los conocimien- tos y costumbres gastronómicas de los pobladores de esta región, reconociéndose al mismo como una fuente alta de energía y como un fruto con potencial medicinal. Sin embargo la información de su composición física, química y bromatológica no es bibliográficamente muy conocida, ya que otros autores han caracterizado al fruto tomando como referencia muestras de otros sectores geográficos del país, lo cual es importante señalar si se conoce que la composición del mismo varía de lugar a lugar. Para el presente estudio se tomaron muestras provenientes de las zonas más representativas y en donde se encuentra con mayor abundancia al borojó y se sometieron a los diversos análisis como lo son determinación de humedad, cenizas, fibra, proteína, grasa y pH bajo las diferentes normativas sugeridas por la FAO, AOAC y el INEN para este tipo de produc- tos. Con este mismo fin se ha trabajado experimentalmente con un ensayo conformado por 4 repeticiones para cada variable.

The growing demand for sustainable development has exposed significant limitations in how Higher Education Institutions (HEIs) evaluate sustainability-oriented research, particularly due to fragmented indicators, descriptive approaches, and the absence of robust data-driven assessment frameworks. This study proposes a comprehensive framework for evaluating the sustainability orientation of university research models, integrating validated measurement instruments with advanced analytical and predictive techniques to support evidence-based decision-making in higher education governance. The framework is based on a multidimensional instrument comprising 26 indicators across environmental, social, economic, and institutional dimensions, developed through expert judgment using the Delphi method and statistically validated through Confirmatory Factor Analysis (CFA). The instrument was applied to 260 researchers from four public HEIs located in the Colombia–Ecuador border region, and perceived performance was contrasted with actual institutional indicators, revealing significant nonlinear discrepancies. To address this complexity, an artificial neural network model was developed to estimate real sustainability performance based on survey data, achieving a predictive accuracy of 90.92%. Beyond institutional diagnosis, the proposed framework functions as a decision-support tool that enables HEIs to identify critical gaps, prioritize interventions, and guide continuous improvement strategies in research management. Due to its methodological rigor, scalability, and transferability, the framework can be adapted to diverse higher education contexts, contributing to the advancement of sustainability assessment methods and governance practices in universities.