For more than a century, agricultural mechanization encouraged larger fields with more uniform management and increasing impacts on the environment. The trajectory of agricultural technology is now at an inflection point where information technology, including remote sensing, simulation modeling, decision support systems, precision agricultural technologies, and automation, enables site-specific management at small spatial scales with the potential to simultaneously enhance food and bioenergy production, farm profitability, and environmental quality. To achieve these economic and environmental benefits of transforming agricultural landscape design and cropping system management, agricultural producers need increased access to both enabling technologies and engineering expertise. Government policies and programs are also needed to incentivize changes in cropping systems that promote soil health and improve water quality, for example, payments to cover much or all of the cost of transitioning land use to perennials and nutrient trading programs in which agricultural producers contract with industrial and municipal wastewater generators to reduce nutrient loading at a reduced cost. Information technology is providing the tools to target, quantify, and document this re-coupling of economic, environmental, and social sustainability in food–energy–water systems.

This study proposes a performance appraisal framework for agricultural water distribution systems based on the Water-Food-Energy Nexus perspective. To analyze and evaluate agricultural water distribution systems with this framework, various methods of improving the operational management were developed and tested under the conventional and water shortages in operational scenarios. The Water-Food-Energy Nexus indicators were then calculated for performance appraisal of the water distribution systems in a study area, located in central Iran. The results indicated that by upgrading the manual operation to an automatic control system, gave the best results from the nexus indicators perspectives. The Bayesian Network model was used to present a probabilistic approach that could assist managers and decision-makers in evaluating the performance of the system, based on the nexus perspective. For this purpose, various configurations of the Bayesian Network structures were developed based on an export-oriented approach, and the most appropriate model was determined for the test case. The calibration and validation process of the selected configuration approved a high accuracy in fulfilling the objective of the study. The developed framework can be employed as a decision support model to prioritize options for modernizing agricultural water distribution systems.

This comprehensive review explores aquaponics as an environmentally friendly solution aligned with SDGs and food sovereignty, assessing various aspects from system design to automation, and weighing social, economic, and environmental benefits through literature and case studies. However, challenges persist in obtaining organic certification and legislative recognition, hindering its growth. Achieving remarkable water use efficiency, up to 90%, relies on adaptable fish species like Nile tilapia and carp. Nutrient-rich fish feeds notably benefit low-nutrient-demanding greens. Ensuring water quality and efficient nitrification are pivotal, supported by IoT systems. Despite its efficiency, integrating Industry 4.0 involves complexity and cost barriers, necessitating ongoing innovation. Economies of scale and supportive horticultural policies can bolster its viability. Aquaponics, known for its efficiency in enhancing crop yields while minimizing water use and waste, is expanding globally, especially in water-scarce regions. Aquaponics, pioneered by the University of the Virgin Islands, is expanding in Europe, notably in Spain, Denmark, Italy, and Germany. Asia and Africa also recognize its potential for sustainable food production, especially in water-limited areas. While it offers fresh produce and cost savings, challenges arise in scaling up, managing water quality, and meeting energy demands, particularly for indoor systems. Egypt’s interest in desert and coastal regions highlights aquaponics’ eco-friendly food production potential. Despite the associated high costs, there is a quest for practical and affordable designs for everyday integration. Research in arid regions and industry advancements are crucial for aquaponics’ global food production potential. Deeper exploration of intelligent systems and automation, particularly in large-scale setups, is essential, highlighting the industry’s promise. Practical application, driven by ongoing research and local adaptations, is a key to fully harnessing aquaponics for sustainable food production worldwide.

The objective of this study was evaluate the efficiency in water and food use in sheep production, using two new traits (residual water intake - RWI; residual feed and residual water intake - RFRWI). For this purpose, we evaluated the relationships between the traits total water intake, RWI and RFRWI with water measures, productive performance and carcass traits (ultrasound). We used 32 lambs with age of 3 months: 16 Santa Ines breed (8 males and 8 females) and 16 crossbred 7/8 Dorper x Santa Ines (8 males and 8 females). They were fed at an automated feed and water station (Intergado®), where the food and water intake by each animal was measured automatically. Residual water intake (RWI), residual feed intake (RFI) and residual body weight gain (RWG) were calculated using the MIXED procedure in SAS®. Correlation coefficients between total water intake (TWI), RWI and all traits (water measures, performance and carcass traits) were calculated using the CORR procedure (P ≤ 0.05). Total water intake showed mean 3.15 L/day during the study and the RWI ranged from 0.66 L to -0.89 L, which represents a difference of 1.55 L between the most and least efficient animal. There was positive correlation between less efficient animals in water consumption (positive RWI) and water intake (r = 0.31); total water intake in relation to dry matter intake (r = 0.36); total water intake in relation to mid-trial metabolic body weight (r = 0.26); residual feed and residual water intake (r = 0.99) and gain/feed ratio (r = 0.44). There was negative correlation between less efficient animal and dry matter intake in relation to body weight (r= -0.33) and feed conversion ratio (r= -0.44). The evaluation of the new variables, RWI and RFRWI, proved effective in identifying the most efficient animals in water use. Moreover, these findings open the possibility of considering the traits RWI and RFRWI in sheep selection, because performance and carcass traits are not adversely affected by selecting for these new traits.

Overreporting of dietary intake in infants is a problem when using food records (FR), distorting possible relationships between diet and health outcomes. Image-assisted dietary assessment may improve the accuracy, but to date, evaluation in the pediatric setting is limited. The aim of the study was to compare macronutrient and energy intake by using an active image-assisted five-day FR against a regular five-day FR, and to validate image-assistance with total energy expenditure (TEE), was measured using doubly labeled water. Participants in this validation study were 22 healthy infants randomly selected from the control group of a larger, randomized intervention trial. The parents reported the infants’ dietary intake, and supplied images of main course meals taken from standardized flat-surfaced plates before and after eating episodes. Energy and nutrient intakes were calculated separately using regular FR and image-assisted FRs. The mean (± standard deviations) energy intake (EI) was 3902 ± 476 kJ/day from the regular FR, and 3905 ± 476 kJ/day from the FR using active image-assistance. The mean EI from main-course meals when image-assistance was used did not differ (1.7 ± 55 kJ, p = 0.89) compared to regular FRs nor did the intake of macronutrients. Compared to TEE, image-assisted FR overestimated EI by 10%. Without validation, commercially available software to aid in the volume estimations, food item identification, and automation of the image processing, image-assisted methods remain a more costly and burdensome alternative to regular FRs in infants. The image-assisted method did, however, identify leftovers better than did regular FR, where such information is usually not readily available.

Germ-free (GF) mice are useful models for the examination of host–microbe interactions in health and disease. We recently reported on the maintenance of individual GF mice for more than 1 year in a sealed positive-pressure cage. However, no useful system exists to automatically record basic behavioral patterns, such as activity and the intake of water and food, under GF status. In this study, we examined basic behavior by combining the sealed positive-pressure cage with a behavioral monitoring system and observed the gross morphology of GF mice at 4 weeks and 8 months of age. GF mice exhibited cecal enlargement and had lower body and adipose tissue weights compared with age-matched specific pathogen–free (SPF) mice. Although both strains had similar circadian rhythms, GF mice exhibited decreased activity compared with age-matched SPF mice. GF mice also exhibited increased levels of water intake compared with age-matched SPF mice. Although GF mice demonstrated decreased food intake levels at the age of 4 weeks, they exhibited increased food intake levels compared with age-matched SPF mice at the age of 8 months. The present research indicates that automated measurement systems that record the basic behaviors of GF mice for long periods are useful for the acceleration of the study of metabolic functions and host–microbe interactions.

La industria 4.0, conocida como cuarta revolución industrial, es responsable de la transformación en la forma de producir alimento, de manera eficiente y sostenible. Este estudio tiene como objetivo presentar los indicadores de productividad científica relacionadas con las nuevas tecnologías implementadas para la automatización de alimentación y medición de calidad de agua en tilapia y salmónidos. Para ello, se realizó un análisis bibliométrico usando la base de datos de Scopus de artículos publicados durante el 2018-2024. Los hallazgos muestras que la productividad científica empieza a tener más impulso en el año 2022. Sin embargo, persisten los desafíos relacionados con la falta de inversión y poco interés sobre el tema. En cuento a los parámetros de calidad de agua en salmónidos, los países más influyentes son Canadá, China, Noruega y Estados Unidos; mientras que en tilapia son Filipinas, Indonesia y Tailandia los artículos publicados están enfocados en el uso de herramientas tecnológicas para monitorizar y controlar parámetros de calidad de agua en tiempo real. En comparación con los países más influyentes en la automatización de la alimentación en salmónidos son Estados unidos, China y Noruega, mientras que, en el caso de la tilapia son Filipinas, China e Indonesia, los artículos publicados se centran en la automatización de la alimentación, resaltando beneficios como la precisión en la cantidad de ración, programación de horarios, mejorando el crecimiento homogéneo, la eficiencia en conversión alimenticia. Aunque Noruega es el principal país productor de salmónidos, no ocupa el primer lugar en la publicación de científicas, lo que refleja el enfoque gubernamental para el financiamiento de proyectos de investigación y el intercambio de conocimiento. Se puede concluir la importancia de monitorizar los parámetros de calidad de agua y los sistemas de automatización de alimentación para mitigar riesgos sanitarios, reducir la alta mortalidad, mejorar el bienestar animal, minimizar el impacto ambiental y mejorar la eficiencia de las prácticas de manejo sostenible y productivo. | Industry 4.0, known as the fourth industrial revolution, is responsible for the transformation in the way food is produced, efficiently and sustainably. This study aims to present the indicators of scientific productivity related to the new technologies implemented for the automation of feeding and water quality measurement in tilapia and salmonids. For this purpose, a bibliometric analysis was performed using the Scopus database of articles published during 2018-2024. The findings show that scientific productivity starts to have more momentum in the year 2022. However, challenges related to lack of investment and little interest in the subject persist. However, there are still challenges related to lack of investment and little interest in the subject. In terms of water quality parameters in salmonids, the most influential countries are Canada, China, Norway and the United States; while in tilapia, the Philippines, Indonesia and Thailand are the most influential countries. In comparison, the most influential countries in salmonid feed automation are the United States, China and Norway, while in the case of tilapia it is the Philippines, China and Indonesia, the published articles focus on feed automation, highlighting benefits such as precision in ration quantity, scheduling, improving homogeneous growth, feed conversion efficiency. Although Norway is the leading producer of salmonids, it does not rank first in the publication of scientific papers, reflecting the government's approach to funding research projects and knowledge sharing. We can conclude the importance of monitoring water quality parameters and feeding automation systems to mitigate health risks, reduce high mortality, improve animal welfare, minimize environmental impact and improve the efficiency of sustainable and productive management practices. | 1. Introducción. -- 2. Planteamiento problema. -- 3. Justificación. -- 4. Objetivos. -- 4.1. Objetivo general. -- 4.2. Objetivos específicos. -- 5. Marco conceptual. -- 5.1. Acuicultura inteligente. -- 5.2. Descripción de las especies en estudio. -- 5.2.1 Cíclidos. -- 5.2.2. Caracterización. -- 5.2.3 Salmón. -- 5.2.4. Caracterización. -- 5.3. Sensores. -- 5.3.1. Sensores inalámbricos-redes. -- 5.4. Internet de las cosas (IoT). -- 5.5. Inteligencia artificial. -- 5.5.1. Aprendizaje de máquinas. -- 5.6. Visión artificial. -- 5.7 Calidad de agua. -- 5.7.1 Parámetros fisicoquímicos. -- 5.8. Automatización de alimento. -- 5.9 Raciones de alimento. -- 5.10. Manejo de alimento. -- 6. Marco Normativo. -- 7. Estado del arte. -- 8. Metodología. -- 9. Análisis bibliométrico. -- 9.1. Red de desempeño por años de publicación. -- 9.2. Países más influyentes de automatización en parámetros de calidad de agua. -- 9.3 Países más influyentes en automatización de la alimentación. -- 9.4. Autores influyentes. -- 9.5. Instituciones influyentes en calidad de agua. -- 9.6. Instituciones influyentes en automatización de la alimentación. -- 10. Discusión. -- 10.1. Impacto de las tendencias de publicaciones. -- 10.2. Desafíos y limitaciones. -- 11. Conclusiones. -- 12. Bibliografía. | Pregrado | Médico veterinario

In this study, a new metal-organic framework-monolith composite for in-tube solid phase microextraction phase (IT-SPME) of fluoroquinolones (FQs) was prepared. 4-Vinylbenzoic acid was copolymerized with ethylenedimethacrylate in a fused silica capillary to form porous monolith. After that, zeolitic imidazolate frameworks (ZIF-8) were synthesized in situ within the pores and the surface of the monolith by controlled layer-by-layer self-assembly of Zn2+ and imidazole. The introduction of ZIF-8 enhanced the surface area of monolith composite, and thus, improving the extraction performance of IT-SPME for FQs obviously. Under the optimized conditions, a highly sensitive method for the monitoring of FQs residue in water and honey samples was developed by the on-line combination of IT-SPME with high-performance liquid chromatography with fluorescence detection (HPLC-FLD). The limits of detection (S/N = 3) for the targeted FQs in water and honey samples were as low as 0.14–0.61 ng/L and 0.39–1.1 ng/L, respectively. The relative standard deviations (RSDs) for intra-day and inter-day assay variability were less than 10% in all samples. The established on-line IT-SPME-HPLC-FLD was successfully used to detect ultra-trace FQs in environmental water and honey samples. Recoveries at different spiked concentrations ranged from 80.1% to 119% and 80.2–117% for water and honey samples, respectively, with satisfactory reproducibility. Compared to up-to-date reported methods, the proposed approach exhibits some features such as high sensitivity, convenience, partial automation, low consumptions of sample and solvent.