3 research outputs found

    Effects of different levels of cassava fibre and traditional fibre sources on extrusion, kibble characteristics, and palatability of dog diets

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    Pet food companies often use fibres in extruded diets as a strategy to improve intestinal functionality and reduce energy density, but studies evaluating the effect of fibres on the extrusion process, kibble characteristics, and palatability of dog diets are scarce. Thus, the objective of this study was to evaluate the effect of cassava fibre (CA) levels and conventional fibre sources on the extrusion process, kibble characteristics, and palatability of diets. Seven diets were evaluated: control diet (CO), without the inclusion of fibre sources; three diets with increasing levels of CA—4, 8, and 12% (totalling 6.1, 7.2, and 8.3% total dietary fibre—TDF, respectively); diet with 3.8% cellulose (CE); diet with 6% beet pulp (BP); and diet with 3.8% lignocellulose (LC). Diets 12% CA, CE, BP, and LC presented approximately 8.0% TDF. Diet palatability was evaluated in 16 adult beagle dogs in a completely randomised design. Seven paired tests were conducted, with two consecutive days per test, totalling 32 repetitions. Diets with fibre sources had lower kibble density than the CO diet (p = .004). The inclusion of increasing dietary CA levels resulted in a linear increase in the kibble expansion index (p = .0001). Dogs preferred the 12% CA diet to the CO (p = .032) or BP diets (p = .0001). The evaluated insoluble fibre sources resulted in greater expansion and lower density kibbles than the CO diet. Furthermore, 12% of CA positively affected diet palatability in dogs.HIGHLIGHTS Cassava fibre linearly increased the expansion of kibbles. 12% cassava fibre positively affected diet palatability. Diets with fibre sources changed the physical characteristics of kibbles

    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

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    Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data
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