The objective of this study was to develop and validate equations for estimating growth of dairy heifers using measures of withers height, body weight (BW), and age. Measures of BW and withers height of 207 Holstein heifers raised in a tropical climate were taken from birth to calving, totaling to 2,047 observations. To be included in the database, the heifer had to have at least 4 measures recorded. After that, 4 models were built and evaluated as follows: (1) a linear model of BW as function of age (BW~A), (2) a linear model of the BW-to-height ratio as function of age (BW: H ~A), (3) a quadratic model, adjusted for a defined plateau, to describe height as function of age (H~A), and ( 4) an exponential growth model of BW as function of height (BW~H). A cross-validation procedure was performed to evaluate accuracy and precision of the models. The linear relationship of BW~A and BW: H ~A were estimated, respectively, by the equations: BW = 42.65 + 0.62 × A and BW:H = 0.70 + 0.0041 × A, where BW is in kilograms, BW:H = BW-to-height ratio (kg/ cm), and A = age (d). Using the quadratic plateau for the model H~A, a critical "x" value of ~806 d and a height plateau of 138.6 cm were identified. Therefore, the following equations for estimating the height of animals younger and older than 806 d, respectively, were developed: H = 78.15 + 0.150 × A -0.00009 × A 2 and H = 78.15 + 0.150 × cvx -0.00009 × cvx 2 , where H = height (cm) and cvx = 806 (critical "x" value; given in days). Additionally, the exponential model of W~H was estimated by the following equation: BW = 4.25 × exp (0.034 × H) , where BW is in kilograms and H = height (cm). A cross validation demonstrated that all equations had very high accuracy and precision. Overall, these models demonstrated that BW and BW-to-height ratio increase linearly as a function of age, while BW follows an exponential growth pattern as a function of height. Additionally, the H~A model predicted that heifers achieve a maximum height of 138.6 cm at 806 d of age.

The effect of the flood pulse directs productivity and interactions of biota in abandoned oxbow lakes, as these habitats provide refuge from predators and serve as nurseries and feeding grounds for many fish species. The present study was conducted in twelve oxbow lakes with varying degrees of connectivity, located in the floodplain of the Middle Purus River in Brazil. 8.647 individuals were collected among 157 species. Lakes with high hydrological connectivity were shown to have the largest richness of species (131 species), while lakes with medium connectivity had slightly smaller richness (123 species), and lakes with low connectivity had even less (113 species). The results show high diversity in lakes that are attributed different connectivity, thereby indicating the importance of studies focused on oxbow lakes that contribute with relevant information on the composition of fish species in the Middle Purus River.

This study aimed to describe the application of the management tool GUT matrix in a family dairy farm in the state of Acre to identify the main weaknesses and propose adequate tools to allow better management of the causes of the three biggest identified problems. This is a case study carried out on a single property located in the municipality of Rio Branco - Acre in May 2022. Information was collected by applying a semi-structured form with 267 questions. The GUT matrix allowed ranking the three main weaknesses of the property, namely: “lack of zootechnical bookkeeping,” “long calving interval,” and “failure in feeding management.” The management tools proposed to the producer, seeking to guide and organize the activities of the property, consisted of 5W2H and Ishikawa diagram.

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