Desempenho de ovinos em confinamento recebendo dietas com torta de cupuaçu (Theobroma grandiflorum schum., sterculiaceae)

Esse estudo avaliou o efeito da inclusão da torta de cupuaçu (Theobroma grandiflorum Schum.) na alimentação de ovinos em confinamento. Foram avaliados o consumo (em kg dia-1, % PV e kg PV-0, 75), ganho de peso, conversão alimentar, medidas morfométricas da carcaça, características de carcaça, comportamento ingestivo e qualidade da carne. Foram utilizados vinte e cinco ovinos castrados, sem raça definida (SRD), com peso médio vivo inicial de 17,4 (±1,90) kg, mantidos em confinamento até que atingissem 35 kg de peso vivo (PV). As dietas experimentais eram compostas por 26 % de silagem de capim-elefante (Pennisetum purpureum, Schum) e 74 % de concentrado, composto de milho moído, farelo de soja, farelo de trigo, calcário calcítico e torta de cupuaçu, e consistiram na substituição do milho e do farelo de trigo pela torta de cupuaçu nos níveis 0 (controle), 7,4, 14,8, 22,2 e 29,6 % da matéria seca total. O delineamento experimental foi inteiramente casualizado, com cinco tratamentos e cinco repetições.  A substituição dos alimentos padrões pela torta de cupuaçu não influenciaram (P>0,05) nas variáveis avaliadas, indicando que a torta pode ser utilizada em dietas para ovinos em confinamento em até 30 % da matéria seca total, sem comprometer consumo, características da carcaça e qualidade da carne

Effects of dietary palm oil supplementation on ruminal degradation and apparent digestibility of nutrients in sheep

Abstract The aim of this study was to evaluate the effects of the inclusion of palm oil on the ruminal environment and nutrient digestibility of sheep diets. Twenty rumen-cannulated sheep were kept in individual stalls equipped with feeding and drinking troughs The animals were fed five diets based on Elephant grass (Pennisetum purpureum Schum. cv. Roxo) silage and supplemented with 0, 25, 50, 75, or 100 g kg-1 of palm oil (based on total DM). The Elephant grass was harvested at 90 days of regrowth and the concentrate was based on ground corn grain, soybean meal and mineral mix (20 g kg-1 DM), offered to the sheep at a ratio of 1.5 g kg-1d-1 of body weight (restricted intake) to maintain a forage-to-concentrate ratio of 1:1, based on DM. There were no differences (P = 0.324) in ruminal disappearance and degradability parameters with up to 75 g of oil per kg of DM. Organic matter showed a linear reduction in apparent digestibility, while ether extract increased linearly. Palm oil affected the digestibility and nutritional parameters in ruminant diets

Utilização de redes bayesianas através do algoritmo naïve bayes para classificação de carcaças de ovinos / Use of bayesian networks through the na dove bayes algorithm for the classification of sheep carcases

Este trabalho apresenta uma aplicação do algoritmo Naïve Bayes com capacidade para classificar carcaças ovinas usando duas classes de saída (conformac?a?o e acabamento). Por meio de diversos parâmetros, que são recolhidos a partir da mensurac?a?o das carcaças dos animais para determinar duas classificações: uma para conformação e outra para acabamento. Para fins de concretização deste trabalho, ale?m da aplicac?a?o do algoritmo Naïve Bayes, foi desenvolvido o software Frame Mining, responsa?vel por fazer as mensurac?o?es automatizadas dos animais. Tambe?m foi desenvolvida uma arquitetura que realiza cadastro de base de dados, ale?m de um algoritmo capaz de realizar converso?es de dados nume?ricos para nominais. Todos esses recursos foram fundamentais para a obtenção dos resultados e o algoritmo apresentou uma taxa de classificação adequada em vários exemplos durante os teste

Nutrient intake, digestibility, performance, carcass traits and sensory analysis of meat from lambs fed with co-products of Amazon oilseeds

Introduction:The increase in availability and nutritional composition of oilseed co-products has made it essential to study the use of this biomass.Methods:The objective of this work was to investigate the effects of including oilseed cakes on intake and digestibility, performance, carcass characteristics and meat sensory in feedlot lambs. Twenty-four crossbred Dorper × Santa Inês lambs, with initial body weight of 30 ± 1.3 kg, male, castrated, aged 4–5 months, were distributed in a completely randomized experimental design with four treatments (diets) and six replications (animals), confined in individual stalls for 70 days.Results:The inclusion of tucuma cake (Tuc) reduced dry matter intake (p < 0.01) and diets with cupuassu cake (Cup) and palm kernel cake (Palm) reduced dry matter digestibility (p < 0.05). The Tuc diet also provided the lowest final body weight (p = 0.02); lower average daily gain (p = 0.03); lower feed efficiency (p = 0.03) and lower carcass weight (p < 0.01). However, diets did not influence carcass yield (%), fat thickness (mm) and loin eye area (cm2; p > 0.05). Meat from lambs on the control diet was rated as less fibrous and more tender (p < 0.05).Conclusion:The inclusion of tucuma cake does not influence digestibility, but reduces intake, performance and influences carcass characteristics and meat texture. Diets with cupuassu cake or palmiste cake reduced digestibility, however, intake, performance and carcass characteristics were similar to the control diet

Methane emission, intake, digestibility, performance and blood metabolites in sheep supplemented with cupuassu and tucuma cake in the eastern Amazon

The use of co-products as a feed supplement for ruminants makes livestock sustainable and optimizes the use of available areas and animal performance. Furthermore, when cakes are used, the residual fat composition can influence ruminal metabolism and methane (CH4) production. This study aimed to assess the effects of a diet containing cupuassu (CUP; Theobroma grandiflorum) and tucuma (TUC; Astrocaryum vulgare Mart.) cakes on intake, digestibility, serum metabolites, performance, and CH4 emissions in confined sheep in the Amazon. Approximately 28 animals, Dorper-Santa Inês, castrated, with an average initial live weight (ILW) of 35 ± 2.3 kg, were distributed in metabolic cages, in a completely randomized design, with four treatments and seven replications: (1) Control (C40), without the addition of Amazonian cake and with 40 g of ether extract (EE)/kg of dietary dry matter (DM); (2) CUP, the inclusion of the CUP cake and 70 g of EE/kg; (3) TUC, the inclusion of the TUC cake and 70 g of EE/kg; and (4) Control (C80), without the addition of Amazonian cake and with 80 g of EE/kg of dietary DM, with roughage to concentrate ratio of 40:60. The use of the TUC cake as a feed supplement reduced the intake of DM, crude protein (CP), and EE compared to the inclusion of the CUP cake (p < 0.05); however, it increased the intake of neutral detergent fiber (NDF) by 32% (p < 0.01). The highest averages of DM (732 g/kg) and CP (743 g/kg) digestibility were presented in C40, while the highest digestibility of NDF was presented in TUC (590 g/kg). Albumin levels stayed above and protein levels were below the reference values, and the C40 diet also obtained below results for cholesterol, triglycerides and High Density Lipoprotein (HDL) (P < 0.05). Sheep fed CUP (91 g) and TUC (45 g) had lower daily weight gains (DWGs) than those fed with diets without the inclusion of cakes (C40 = 119 g; C80 = 148 g), and feed efficiency (FE) was also lower in CUP (84) and TUC (60) diets than in C40 (119) and C80 (137) diets. CH4 emissions were lower in animals fed TUC (26 L/day) and higher in C40 (35 L/day); however, TUC resulted in higher CH4 emissions in grams/body live weight (BW) gain/day (353 g/BW/day) vs. 183 g/BW/day (C40), 157 g/BW/day (C80), and 221 g/BW/day (CUP). The supplementation with cakes did not improve intake, digestibility and performance, did not compromise blood metabolites and did not reduce the enteric CH4 emission in confined sheep in the Amazon; however, the use of CUP cake showed similar results to the control treatments and did not increase CH4 emissions, as occurred with the inclusion of TUC cake

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

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost