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This study investigated the feasibility of using easy-to-measure phenotypic traits to predict sheep resistant, resilient, and susceptible to gastrointestinal nematodes, compared the classification performance of multinomial logistic regression (MLR), linear discriminant analysis (LDA), random forest (RF), and artificial neural network (ANN) methods, and evaluated the applicability of the best classification model on each farm. The database comprised 3654 records of 1250 Santa Inês sheep from 6 farms. The animals were classified into resistant (2605 records), resilient (939 records), and susceptible (110 records) according to fecal egg count and packed cell volume. A random oversampling method was performed to balance the dataset. The classification methods were fitted using the information of age class, the month of record, farm, sex, Famacha© degree, body weight, and body condition score as predictors, and the resistance, resilience, and susceptibility to gastrointestinal nematodes as the target classes to be predicted considering data from all farms randomly. An additional leave-one-farm-out cross-validation technique was used to assess prediction quality across farms. The MLR and LDA models presented good performances in predicting susceptible and resistant animals. The results suggest that the use of readily available records and easily measurable traits may provide useful information for supporting management decisions at the farm level.

This study evaluated the influence of environmental temperature on thermoregulation, hormonal, and hematological characteristics in Caracu cattle. Blood samples, hair length, coat and muzzle colors, rectal (RT), and surface temperatures were collected from 48 males and 43 females before (morning) and after sun exposure for eight hours (afternoon). Infrared thermography (IRT) was used to identify superficial temperature that exhibits a high correlation with RT. Hematological parameters, hormone concentrations, RT, and the superficial temperature obtained by IRT that exhibited the highest correlation with RT were evaluated by variance analysis. Regarding IRT, the lower left side of the body (LS) showed the highest correlation with the RT. Interaction between period and sex was observed for LS, cortisol, and eosinophils. Cortisone, progesterone, and RT were influenced by period and sex. Neutrophils and segmented neutrophils were influenced by the period, which showed the highest concentrations after sun exposure. Platelets, leukocytes, lymphocytes, and monocytes were influenced by sex. Heat stress changes several physiological characteristics where males and females exhibited differences in their responses to heat stress. Furthermore, most characteristics evaluated remained within the regular values observed for taurine Creole breeds, showing that Caracu is adapted to tropical climates.

Feed and water efficiency are important traits to improve beef cattle production’s economic and environmental sustainability. This study evaluated residual feed intake (RFI) and residual water intake (RWI) and their relationship with performance, ingestive behavior, and carcass traits in Caracu beef cattle. The data were analyzed using a generalized linear model with least squares means. The ingestive behavior, performance, and carcass traits were influenced by sex (p < 0.05). Males showed higher dry matter intake (DMI), average daily gain (ADG), mid-test metabolic weight (BW0.75), rib eye area, and rump fat thickness than females, besides spending more time drinking and eating. Low RFI animals exhibited higher DMI than high RFI animals. Low RWI animals ingested 3.89 L/d of water further than high RWI animals. The interaction between sex and RWI influenced the DMI, BW0.75, and backfat thickness. The ingestive behavior of low and high RFI animals was similar, although high RWI animals visited a smaller number of drinkers than low RWI animals. Water intake positively affects productive efficiency, and the combined use of RWI and RFI may help improve the selection of more efficient animals contributing to reducing the costs of beef cattle production and improving environmental sustainability.