Compost barn (CB), although recent in Brazil, is increasingly gaining popularity among the intensive breeding systems in the dairy sector. This system promises to offer several advantages to producers and animals: such as providing an environment in which milk production is increased and the physical integrity of cattle is improved, reducing mastitis episodes, and promoting thermal comfort for animals. Another factor that highlights CB concerning other intensive systems is the composting process, generated by the deposition of carbon-rich materials (bedding) with nitrogen sources (urine and feces) from animals. For the full benefits of this composting to be achieved, management, especially of bedding, must be carried out correctly, considering the development requirements of the compost, the use of quality organic material, adequate ventilation, and an ideal rate of animal capacity, so that the generation of heat occurs efficiently. However, there is a general lack of information about the CB system. Hence, there is an increasing need for data surveys of Brazilian regions to compare the diversity of materials used in bedding, assessing energy efficiency and performance over time. Therefore, this bibliographical review addressed the main points of the CB system approach, considering that studies such as this are consistently relevant for rural producers, facilitating decisions regarding the implementation and management of the CB system on their farms.

Animal welfare and zootechnical performance are compromised when animals are housed in environments which place them outside their thermal comfort zone. However, the identification of thermal stress, when based on air properties, suggests the use of outdated and generic indices. The objective of this work was to develop and validate a methodology for classifying and diagnosing heat stress in production animals based on psychrometric air relations. The model was created for broilers, pigs, dairy cattle, and laying birds, categorized into a total of 21 breeding phases. For each phase, a bibliographic search was carried out for the psychrometric parameters of the air - dry bulb temperature (AT) and relative humidity (RH) - that satisfied the animals' critical and ideal thermoneutral zones. Adding the local atmospheric pressure (AP), the parameters were used to calculate the enthalpy (h), resulting in five comfort ranges. Based on this, a decision tree was elaborated, consisting of three attributes (AT, RH, and h) and seven diagnostic classes, based on the psychrometric principles of air. The proposed methodology was used in a case study, with a database extracted from an individual shelter for calves. For the evaluation of the decision tree, two induction algorithms, ID3, and c4.5, were compared, both of which presented high accuracy and proposed simpler tree models than the one theoretically developed for the methodology. In conclusion, the methodology represents a great potential to characterize the thermal comfort of the animals, diagnose the causes of stress and recommend possible corrective actions. The study revealed that decision trees can be adapted and simplified for each creation phase.

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