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Dietary chia (Salvia hispanica L.) improves the nutritional quality of broiler meat
Mendonça Nicole Batelli de Souza Nardelli,Sobrane Filho Sérgio Turra,Oliveira David Henrique de,Lima Eduardo Machado Costa,Rosa Priscila Vieira e,Faria Peter Bitencourt,Naves Luciana de Paula,Rodrigue 아세아·태평양축산학회 2020 Animal Bioscience Vol.33 No.8
Objective: The current study was conducted to evaluate the quality and profile of fatty acid in the breast and thigh, and the performance of broilers fed diets containing seed or oil of chia (Salvia hispanica L.) as a replacement for soybean, in the rearing period from 29 to 42 days of age. Methods: On the 29th day of age, 120 broilers were distributed in four treatments evaluated in five replicates of six birds. The grain or oil of soybean was respectively replaced on a weight-to-weight basis in the formulation by the seed or oil of chia, constituting the experimental diets. The roasted whole soybean and chia seed were included in the feed at 16.4%, whereas the soybean and chia oils were included at 2.5%. Results: The dietary chia oil increased the lipid peroxidation in the thigh meat, and the dietary chia seed increased the cooking loss of the thigh. However, for the other physicochemical parameters evaluated and for the proximate composition of the breast and thigh, in general, the inclusion of chia seed or oil in the diet provided similar or better results than those observed when the diets contained soybean oil or roasted whole soybean. With regard to the fatty acid profile and associated parameters, dietary chia increased the concentrations of α-linolenic, eicosapentaenoic, and docosahexaenoic acids and reduced the Σω-6:Σω-3 ratio and the atherogenicity and thrombogenicity indices of the broiler meat. However, the dietary chia seed worsened the feed conversion ratio. Conclusion: Diet containing 2.5% chia oil supplied to broilers during the period from 29 to 42 days of age improves the feed conversion ratio, increases the deposition of the ω-3 fatty acids in the breast and thigh, in addition to reducing the Σω-6:Σω-3 ratio and the atherogenicity and thrombogenicity indices, thereby resulting in meat with higher nutritional quality.
R.R. Alvarenga,P.B. Rodrigues,M.G. Zangeronimo,E.C. Oliveira,F.C.M.Q. Mariano,E.M.C. Lima,L.P. Naves,N.B.S. Nardelli,N.B.S. Nardelli 아세아·태평양축산학회 2015 Animal Bioscience Vol.28 No.9
A set of prediction equations to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of individual ingredients and diets used in the poultry feed industry was evaluated. The AMEn values of three energy ingredients (maize, sorghum and defatted maize germ meal), four protein ingredients (soybean meal, maize gluten meal 60% crude protein, integral micronized soy and roasted whole soybean) and four diets (three containing four feedstuffs, complex diets, and one containing only corn-soybean meal, basal diet) were determined using a metabolism assay with male broilers from 1 to 7, 8 to 21, 22 to 35, and 36 to 42 days old. These values were compared to the AMEn values presented in the tables of energy composition or estimated by equation predictions based on chemical composition data of feedstuffs. In general, the equation predictions more precisely estimated the AMEn of feedstuffs when compared to the tables of energy composition. The equation AMEn (dry matter [DM] basis) = 4,164.187+51.006 ether extract (% in DM basis)–197.663 ash–35.689 crude fiber (% in DM basis)–20.593 neutral detergent fiber (% in DM basis) (R2 = 0.75) was the most applicable for the prediction of the energy values of feedstuffs and diets used in the poultry feed industry.
The 2019 materials by design roadmap
Alberi, Kirstin,Nardelli, Marco Buongiorno,Zakutayev, Andriy,Mitas, Lubos,Curtarolo, Stefano,Jain, Anubhav,Fornari, Marco,Marzari, Nicola,Takeuchi, Ichiro,Green, Martin L,Kanatzidis, Mercouri,Toney, M IOP 2019 Journal of Physics. D, Applied Physics Vol.52 No.1
<P>Advances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesis and characterization. The increased use of computational tools, the generation of materials databases, and advances in experimental methods have substantially accelerated these activities. It is therefore an opportune time to consider future prospects for materials by design approaches. The purpose of this Roadmap is to present an overview of the current state of computational materials prediction, synthesis and characterization approaches, materials design needs for various technologies, and future challenges and opportunities that must be addressed. The various perspectives cover topics on computational techniques, validation, materials databases, materials informatics, high-throughput combinatorial methods, advanced characterization approaches, and materials design issues in thermoelectrics, photovoltaics, solid state lighting, catalysts, batteries, metal alloys, complex oxides and transparent conducting materials. It is our hope that this Roadmap will guide researchers and funding agencies in identifying new prospects for materials design.</P>
Lee, Seunghun,Wang, Haihang,Gopal, Priya,Shin, Jongmoon,Jaim, H. M. Iftekhar,Zhang, Xiaohang,Jeong, Se-Young,Usanmaz, Demet,Curtarolo, Stefano,Fornari, Marco,Buongiorno Nardelli, Marco,Takeuchi, Ichir American Chemical Society 2017 Chemistry of materials Vol.29 No.21
<P>By combining high-throughput experiments and first-principles calculations based on the DFT-ACBN0 approach, we have investigated the energy band gap of Sr-, Pb-, and Bi-substituted BaSnO<SUB>3</SUB> over wide concentration ranges. We show that the band gap energy can be tuned from 3 to 4 eV by chemical substitution. Our work indicates the importance of considering the mixed-valence nature and clustering effects upon substitution of BaSnO<SUB>3</SUB> with Pb and Bi. Starting from the band gap of ∼3.4 eV for pure BaSnO<SUB>3</SUB>, we find that Pb substitution changes the gap in a nonmonotonic fashion, reducing it by as much as 0.3 eV. Bi substitution provides a monotonic reduction but introduces electronic states into the energy gap due to Bi clustering. Our findings provide new insight into the ubiquitous phenomena of chemical substitutions in perovskite semiconductors with mixed-valence cations that underpin their physical properties.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/cmatex/2017/cmatex.2017.29.issue-21/acs.chemmater.7b03381/production/images/medium/cm-2017-03381d_0005.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/cm7b03381'>ACS Electronic Supporting Info</A></P>
Alvarenga, R.R.,Rodrigues, P.B.,Zangeronimo, M.G.,Oliveira, E.C.,Mariano, F.C.M.Q.,Lima, E.M.C.,Garcia, A.A.P. Jr,Naves, L.P.,Nardelli, N.B.S. Asian Australasian Association of Animal Productio 2015 Animal Bioscience Vol.28 No.9
A set of prediction equations to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of individual ingredients and diets used in the poultry feed industry was evaluated. The AMEn values of three energy ingredients (maize, sorghum and defatted maize germ meal), four protein ingredients (soybean meal, maize gluten meal 60% crude protein, integral micronized soy and roasted whole soybean) and four diets (three containing four feedstuffs, complex diets, and one containing only corn-soybean meal, basal diet) were determined using a metabolism assay with male broilers from 1 to 7, 8 to 21, 22 to 35, and 36 to 42 days old. These values were compared to the AMEn values presented in the tables of energy composition or estimated by equation predictions based on chemical composition data of feedstuffs. In general, the equation predictions more precisely estimated the AMEn of feedstuffs when compared to the tables of energy composition. The equation AMEn (dry matter [DM] basis) = 4,164.187+51.006 ether extract (% in DM basis)-197.663 ash-35.689 crude fiber (% in DM basis)-20.593 neutral detergent fiber (% in DM basis) ($R^2=0.75$) was the most applicable for the prediction of the energy values of feedstuffs and diets used in the poultry feed industry.