The integration of fish farming in intensive system and plant production, called "aquaponics" is practiced successfully in countries like the USA, Australia and Europe. In Brazil, this integration has attracted the attention of researchers and producers. In this context, the aim of this study was to evaluate the effect of two substrates (crushed stone number 3, CS III and flexible polyurethane foam, FPF) on the production of aquaponic lettuce, moreover, to show that the residual water from intensive tilapia production provides sufficient qualitative characteristics for competitive production of lettuce without adding commercial fertilizers. The treatment in which FPF was used provided higher concentrations of macro and micronutrients in the shoots, higher production of fresh matter of shoots (95.48 g plant-1) and a larger number of leaves (14.90) relative to CS III. These results were attributed to the lower post-transplanting stress and the higher water retention time provided by the FPF. The residual water from tilapia intensive farming can provide sufficient nutrients for the production of lettuce, making the supplementary fertilization with commercial products unnecessary. Thus, the FPF presents the most suitable conditions to be used as substrate in aquaponics system with recirculation of the residual water from the intensive tilapia farming.

Evaluation of the comfort and animal welfare parameters enables determining the best environmental conditions for livestock creation. The present study was aimed to determine the thermal comfort index for beef cattle using interpolation techniques for the State of Mato Grosso do Sul during extreme summer and winter seasons for a period of 10 years. The analysis was performed on the climatic variables data provided by the National Institute of Meteorology, Brazil. The maximum (THImax) and minimum (THImin) temperature and humidity indices (THIs) of 28 weather stations distributed across the state were calculated, and the thematic maps of the THIs (maximum and minimum) calculated for the summer and winter seasons were prepared. The results revealed a state of emergency in the two largest animal-producing cities in the state; namely, Corumbá and Ribas do Rio Pardo, while two other cities, Chapadão do Sul and Costa Rica emerged as favorable regions for the production of beef cattle. The Spline method used in the present study, therefore, proved to be a suitable tool for analyzing a small number of weather stations distributed over a large territorial area.

In the aquaponic system, the characteristics of the materials used as substrate directly affect plant development, because besides acting as a support base, they must present a surface to fix microorganisms, responsible for the conversion of nutrients into forms more easily available to plants. Thus, the objective of this study was to evaluate the effect of four growing substrates on the yield of lettuce grown in aquaponic system. The experimental design was randomized blocks with four treatments, which corresponded to the substrates, and six replicates. Plants were grown using the nutrient film technique (NFT) system. The substrates used in the experiment were: coconut shell fiber with crushed stone #3, expanded vermiculite, zeolite and phenolic foam. The treatment with phenolic foam was considered as the least suitable for lettuce cultivation in aquaponic system, because it caused lower yield (20.8 t ha^-1). The treatment using coconut shell fiber with crushed stone #3 was considered as the most adequate, since it led to higher yield (39.9 t ha^-1) compared with the other substrates analyzed.

Brazilian agriculture production requires new types of rural buildings that are more sustainable, economical, and well adapted to their environment. Furthermore, these buildings are no longer simple living quarters, but a way of valuing rural workers. Thus, this study aimed to create a linear programming model for optimizing decision-making when different techniques and construction materials are combined to build rural housing dwellings, thereby enabling an assessment of both the cost and comfort of such buildings. The research considered localizing network facilities via analogies in order to adapt a budget matrix. Three main criteria were applied: cost, runtime, and the environmental comfort provided. The model comprised six construction systems, three types of sealing masonry, two types of roofing, and four types of tiles. Simulations were performed for two Brazilian states, considering the same reference date of validation and comparison. Each input variable resulted in a different construction model. It was demonstrated that the new industrialized construction technologies are advantageous since they provide faster execution, competitive prices, and sustainable raw materials, whilst the application of the criteria to the traditional system of reinforced concrete is also feasible. The linear programming model offers its users an additional decision-making tool for construction systems, enabling time and resource optimization.

Owing to the exponential growth of the human population and problems related to food supply, research focused on finding the most suitable approach to manage and geographically explore the environment using sustainable technologies stand out. The present study aims to produce a consistent interpolation of historical series of enthalpy (H) resulting in a thematic map of enthalpy, using the spline method as a kriging option in areas with few sampling points. The thematic map considers thermal comfort conditions to produce broiler chickens, that could be used as a management tool to reduce power consumption due to the cooling process of the facilities. It was verified that spline is an efficient method to create a suitable thematic maps representations of areas presenting a few sampled units. The geographical representation of enthalpy allowed the evaluation of the environments, concluding that the state of Mato Grosso do Sul, Brazil is inadequate for broiler chickens production without suitable thermal cooling systems. Evidence suggests introduction of aviculture in areas still unexplored, e.g., Chapadão do Sul and Sete Quedas.

Increasing population and demand for animal-derived products has raised the need for improved efficiency in managing and controlling animal production. Given this context, the project aimed to develop a device that aids decision-making in animal production. A hardware system was designed for instant measurement of thermal well-being levels, light intensity, and air gas concentration. This hardware integrated DHT11 sensors, an LDR photoresistor, and an MQ-135 sensor. To validate the system, a 30-day experimental study was conducted in an industrial pig farming setting. The collected data was sent to the Thingspeak server using the HTTP protocol. Data management, filtering, and organization were optimized using developed treatment algorithms. The system presented information on air humidity, temperature, ammonia concentration, CO₂ levels, luminosity, and enthalpy through interactive images on a dashboard. In the case of a risk situation, the system automatically notified users with an "ALERT" message, facilitating prompt and efficient management response, and minimizing losses. The sensor calibration process yielded a high coefficient of determination (r² = 0.98). Thus, the developed IoT device represents a viable solution, providing precise environmental conditions to support producers and enhance their efficiency and sustainability.