Crescimento corporal e sistema digestivo em frangos de corte.

Foram analisados dados do peso corporal e do sistema digestivo em função da idade em frangos de corte de linhagem Pilch, de um a 70 dias de idade

Growth patterns in broilers

Regressões polinomiais e não-lineares (Gompertz, Richards, Logística e Bertalanffy) foram ajustadas a dados peso e idade de frangos e frangas, do nascimento aos 68 dias. O experimento foi realizado em Concórdia, SC, entre agosto e outubro de 1981. As rações ministradas ad libitum, eram isocalóricas e isoprotóicas; no período inicial (1 a 28 dias), continham 2.970 kcal/kg de energia metabolizável (EM) e 22,8% de proteína bruta (PB) e, na fase final (29 a 68 dias), 3.050 kcal/kg de EM e 19,8% de PB. Os modelos Gompertz, Logístico e Bertalanffy, apresentaram valores mais altos para os coeficientes de determinação corrigidos (R2), superiores a 0,98, e médias de erros de predição (EP) em valor absoluto, estatisticamente inferiores (P<0,05). A regressão cúbica apresentou, igualmente, valor alto para R2 ; porém para frangos, o valor absoluto de EP foi maior (P<0,05), que os três últimos modelos. A função linear, seguida da Richards e quadrática, apresentaram estimativas inadequadas do peso observado em todo o período estudado. As funções Gompertz e Logística apresentaram estimativas adequadas ao peso e idade à inflexão e da taxa de ganho diário. A Logística apresentou uma taxa de maturidade superior 30% à Gompertz, e a Bertalanffy superestimou o peso à maturidade.Polynomial regressions and nonlinear (Gompertz, Richards, Logistic and Bertalanffy) were fitted to age-weight data of male and female broilers from birth to 68 days. The experiment was carried out in Concórdia, SC, Brazil, from August to October 1981. The rations, supplied ad libitum, were isocaloric and isoproteic containing 2,970 kcal/kg of metabolizable energy (ME) and 22.8% of crude protein (CP) in the initial phase (first to 28th days) and 3,050 kcal/kg of EM and 19.8% CP in the final phase (29 to 68 days). The Gompertz, Logistic and Bertalanffy models showed the best corrected coefficient of determination (R2), over 0.98, and mean prediction errors (PE) were lower statistycally (P<0.05), in absolute value. The cubic regression provided also a high R-2, however, for male broilers the absolute value of PE was higher than the last three regressions (P<0.05). The linear followed by Richards and quadratic functions, provided poor estimates of observed weight in all studied periods. The Logistic and Gompertz functions provided adequate estimates of weigh and age at inflection point and daily gain rate. The Logistic function showed a 30% greater maturing rate than Gompertz, and the Bertalanffy over estimated the weight at maturity

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio