Aquaculture uses large volumes of water, which is generally discharged without treatment, possibly causing scarcity and contamination. A sustainable aquaculture option is biofloc technology (BFT), which recycles food residues and toxic organic and inorganic compounds from the system through microorganisms, avoiding excessive use of water and serving as natural food for cultured aquatic organisms. The aim of this study was to identify the main factors that limit a Mexican aquaculture producer from adopting biofloc technology in their aquaculture production units (APUs). Strengths and weaknesses were methodologically analyzed through 248 questionnaires, applied to fish farmers in 16 states of the country with a mixed approach (quantitative and qualitative). Findings reveal that the main obstacles in the use of BFT are due to the following: low academic level, limited administrative capacity, scarce technological equipment in facilities, diversified productive activity, and obsolete regulations. Other factors that promote the adoption of BTFs for aquaculturists are production experience, favorable weather conditions, and abundant availability of water and energy. In conclusion, the use of BTF is a sustainable option for APUs despite the limiting factors identified in this research which slow down the growth of the sector. It is advisable to study Mexican producers with BFT, in order to spread their benefits to other APUs, and further evaluate the productivity of the aquaculture sector. This study considers production aspects, and also sustainable use of its resources, specifically, surface, energy, water, and food.

In the educational field, reading comprehension is connected to learning achievement, and through it, one can interpret, retain, organize and value what has been read. It is an essential ability for the understanding and processing of information in learning. Furthermore, it is an essential skill to developing sustainable education. In this sense, sustainable development needs an advanced reading comprehension ability at elementary school in order to teach and learn future knowledge areas such as climate change, disaster risk reduction, biodiversity, poverty reduction, and sustainable consumption. Nevertheless, there have been few works focused on analyzing reading comprehension, particularly in Mexico, where the reference is the Programme for International Student Assessment (PISA) test on how well the Mexican students have developed this skill. Hence, this article shows the usefulness of employing Bayesian techniques in the analysis of reading comprehension at elementary school. The Bayesian network model allows for the determination of the language and communication level of achievement based on parameters such as learning style, learning pace, speed, and reading comprehension, obtaining an 85.36% precision. Moreover, the results confirm that teachers could determine changes in lesson planning and implement new pedagogical mechanisms to improve the level of learning and understanding contents.