986 resultados para prediction equations


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This study aimed to analyse several factors of variation of slurry composition and to establish prediction equations for potential methane (CH4) and ammonia (NH3) emissions. Seventy-nine feed and slurry samples were collected at two seasons (summer and winter) from commercial pig farms sited at two Spanish regions (Centre and Mediterranean). Nursery, growing-fattening, gestating and lactating facilities were sampled. Feed and slurry composition were determined, and potential CH4 and NH3 emissions measured at laboratory. Feed nutrient contents were used as covariates in the analysis. Near infrared reflectance spectroscopy (NIRS) was evaluated as a predicting tool for slurry composition and potential gaseous emissions. A wide variability was found both in feed and slurry composition. Mediterranean farms had a higher pH (p<0.001) and ash (p=0.02) concentration than those located at the Centre of Spain. Also, type of farm affected ether extract content of the slurry (p=0.02), with highest values obtained for the youngest animal facilities. Results suggested a buffer effect of dietary fibre on slurry pH and a direct relationship (p<0.05) with fibre constituents of manure. Dietary protein content did not affect slurry nitrogen content but decreased (p=0.003) total and volatile solids concentration. Prediction models of potential NH3 emissions (R2=0.89) and CH4 yield (R2=0.61) were obtained from slurry composition. Predictions from NIRS showed a high accuracy for most slurry constituents (R2>0.90) and similar accuracy of prediction of potential NH3 and CH4 emissions (R2=0.84 and 0.68, respectively) to models using slurry characteristics, which can be of interest to estimate emissions from commercial farms and establish mitigation strategies or optimize biogas production.

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Esta Tesis doctoral fue desarrollada para estudiar las emisiones de amoniaco (NH3) y metano (CH4) en purines de cerdos, y los efectos ocasionados por cambios en la formulación de la dieta. Con este propósito, fueron llevados a cabo tres estudios. El experimento 1 fue realizado con el objetivo de analizar los factores de variación de la composición de purines y establecer ecuaciones de predicción para emisiones potenciales de NH3 y CH4. Fueron recogidas setenta y nueve muestras de piensos y purines durante dos estaciones del año (verano y invierno) de granjas comerciales situadas en dos regiones de España (Centro y Mediterráneo). Se muestrearon granjas de gestación, maternidad, lactación y cebo. Se determinó la composición de piensos y purines, y la emisión potencial de NH3 y CH4. El contenido de nutrientes de los piensos fue usado como covariable en el análisis. La espectroscopia de reflectancia del infrarrojo cercano (NIRS) se evaluó como herramienta de predicción de la composición y potencial emisión de gases del purín. Se encontró una amplia variabilidad en la composición de piensos y purines. Las granjas del Mediterráneo tenían mayor pH (P<0,001) y concentración de cenizas (P =0,02) en el purín que las del Centro. El tipo de granja también afectó al contenido de extracto etéreo (EE) del purín (P =0,02), observando los valores más elevados en las instalaciones de animales jóvenes. Los resultados sugieren un efecto tampón de la fibra de la dieta en el pH del purín y una relación directa (P<0,05) con el contenido de fibra fecal. El contenido de proteína del pienso no afectó al contenido de nitrógeno del purín, pero disminuyó (P=0,003) la concentración de sólidos totales (ST) y de sólidos volátiles (SV). Se obtuvieron modelos de predicción de la emisión potencial de NH3 (R2=0,89) y CH4 (R2=0,61) partir de la composición del purín. Los espectros NIRS mostraron una buena precisión para la estimación de la mayor parte de los constituyentes, con coeficientes de determinación de validación cruzada (R2cv) superiores a 0,90, así como para la predicción del potencial de emisiones de NH3 y CH4 (R2cv=0,84 y 0,68, respectivamente). El experimento 2 fue realizado para investigar los efectos del nivel de inclusión de dos fuentes de sub-productos fibrosos: pulpa de naranja (PN) y pulpa de algarroba (PA), en dietas iso-fibrosas de cerdos de cebo, sobre la composición del purín y las emisiones potenciales de NH3 y CH4. Treinta cerdos (85,4±12,3 kg) fueron alimentados con cinco dietas iso-nutritivas: control comercial trigo/cebada (C) y cuatro dietas experimentales incluyendo las dos fuentes de sub-productos a dos niveles (75 y 150 g/kg) en una estructura 2 × 2 factorial. Después de 14 días de periodo de adaptación, heces y orina fueron recogidas separadamente durante 7 días para medir la digestibilidad de los nutrientes y el nitrógeno (N) excretado (6 réplicas por dieta) en cerdos alojados individualmente en jaulas metabólicas. Las emisiones de NH3 y CH4 fueron medidas después de la recogida de los purínes durante 11 y 100 días respectivamente. La fuente y el nivel de subproductos fibrosos afectó a la eficiencia digestiva de diferentes formas, ya que los coeficientes de digestibilidad total aparente (CDTA) para la materia seca (MS), materia orgánica (MO), fracciones fibrosas y energía bruta (EB) aumentaron con la PN pero disminuyeron con la inclusión de PA (P<0,05). El CDTA de proteína bruta (PB) disminuyó con la inclusión de las dos fuentes de fibra, siendo más bajo al mayor nivel de inclusión. La concentración fecal de fracciones fibrosas aumentó (P<0,05) con el nivel de inclusión de PA pero disminuyó con el de PN (P<0,01). El nivel más alto de las dos fuentes de fibra en el pienso aumentó (P<0,02) el contenido de PB fecal pero disminuyó el contenido de N de la orina (de 205 para 168 g/kg MS, P<0,05) en todas las dietas suplementadas comparadas con la dieta C. Adicionalmente, las proporciones de nitrógeno indigerido, nitrógeno soluble en agua, nitrógeno bacteriano y endógeno excretado en heces no fueron afectados por los tratamientos. Las características iniciales del purín no difirieron entre las diferentes fuentes y niveles de fibra, excepto para el pH que disminuyó con la inclusión de altos niveles de sub-productos. La emisión de NH3 por kg de purín fue más baja en todas las dietas suplementadas con fibras que en la dieta C (2,44 vs.1,81g de promedio, P<0,05). Además, purines de dietas suplementadas con alto nivel de sub-productos tendieron (P<0,06) a emitir menos NH3 por kg de nitrógeno total y mostraron un potencial más bajo para emitir CH4, independientemente de la fuente de fibra. El experimento 3 investigó los efectos de la fuente de proteína en dietas prácticas. Tres piensos experimentales fueron diseñados para sustituir una mescla de harina y cascarilla de soja (SOJ) por harina de girasol (GIR) o por DDGS del trigo (DDGST). La proporción de otros ingredientes fue modificada para mantener los contenidos de nutrientes similares a través de las dietas. El cambio en la fuente de proteína dio lugar a diferencias en el contenido de fibra neutro detergente ligada a proteína bruta (FNDPB), fibra soluble (FS) y lignina ácido detergente (LAD) en la dieta. Veinticuatro cerdos (ocho por dieta), con 52,3 o 60,8 kg en la primera y segunda tanda respectivamente, fueron alojados individualmente en jaulas metabólicas. Durante un periodo de 7 días fue determinado el balance de MS, el CDTA de los nutrientes y la composición de heces y orina. Se realizó el mismo procedimiento del experimento 2 para medir las emisiones de NH3 y CH4 de los purines de cada animal. Ni la ingestión de MS ni el CDTA de la MS o de la energía fueron diferentes entre las dietas experimentales, pero el tipo de pienso afectó (P<0.001) la digestibilidad de la PB, que fue mayor para GIR (0,846) que para SOJ (0,775), mientras que la dieta DDGST mostró un valor intermedio (0,794). La concentración fecal de PB fue por tanto influenciada (P<0,001) por el tratamiento, observándose la menor concentración de PB en la dieta GIR y la mayor en la dieta SOJ. La proporción de N excretado en orina o heces disminuyó de 1,63 en la dieta GIR hasta 0,650 en la dieta SOJ, como consecuencia de perdidas más bajas en orina y más altas en heces, con todas las fracciones de nitrógeno fecales creciendo en paralelo a la excreción total. Este resultado fue paralelo a una disminución de la emisión potencial de NH3 (g/kg purín) en la dieta SOJ con respecto a la dieta GIR (desde 1,82 a 1,12, P<0,05), dando valores intermedios (1,58) para los purines de la dieta DDGST. Por otro lado, el CDTA de la FS y de la fibra neutro detergente (FND) fueron afectados (P<0,001 y 0,002, respectivamente) por el tipo de dieta, siendo más bajas en la dieta GIR que en la dieta SOJ; además, se observó un contenido más alto de FND (491 vs. 361g/kg) en la MS fecal para la dieta GIR que en la dieta SOJ, presentando la dieta DDGST valores intermedios. El grado de lignificación de la FND (FAD/FND x 100) de las heces disminuyó en el orden GIR>DDGST>SOJ (desde 0,171 hasta 0,109 y 0,086, respectivamente) en paralelo a la disminución del potencial de emisión de CH4 por g de SV del purín (desde 301 a 269 y 256 mL, respectivamente). Todos los purines obtenidos en estos tres experimentos y Antezana et al. (2015) fueron usados para desarrollar nuevas calibraciones con la tecnología NIRS, para predecir la composición del purín y el potencial de las emisiones de gases. Se observó una buena precisión (R2cv superior a 0,92) de las calibraciones cuando muestras de los ensayos controlados (2, 3 y Antezana et al., 2015) fueron añadidas, aumentando el rango de variación. Una menor exactitud fue observada para TAN y emisiones de NH3 y CH4, lo que podría explicarse por una menor homogeneidad en la distribución de las muestras cuando se amplía el rango de variación del estudio. ABSTRACT This PhD thesis was developed to study the emissions of ammonia (NH3) and methane (CH4) from pig slurry and the effects caused by changes on diet formulation. For these proposes three studies were conducted. Experiment 1 aimed to analyse several factors of variation of slurry composition and to establish prediction equations for potential CH4 and NH3 emissions. Seventy-nine feed and slurry samples were collected at two seasons (summer and winter) from commercial pig farms sited at two Spanish regions (Centre and Mediterranean). Nursery, growing-fattening, gestating and lactating facilities were sampled. Feed and slurry composition were determined, and potential CH4 and NH3 emissions measured. Feed nutrient contents were used as covariates in the analysis. Near infrared reflectance spectroscopy (NIRS) was evaluated as a predicting tool for slurry composition and potential gaseous emissions. A wide variability was found both in feed and slurry composition. Mediterranean farms had a higher pH (P<0.001) and ash (P=0.02) concentration than those located at the centre of Spain. Also, type of farm affected ether extract (EE) content of the slurry (P=0.02), with highest values obtained for the youngest animal facilities. Results suggested a buffer effect of dietary fibre on slurry pH and a direct relationship (P<0.05) with fibre constituents of manure. Dietary protein content did not affect slurry nitrogen content (N) but decreased (P=0.003) in total solid (TS) and volatile solids (VS) concentration. Prediction models of potential NH3 emissions (R2=0.89) and biochemical CH4 potential (B0) (R2=0.61) were obtained from slurry composition. Predictions from NIRS showed a high accuracy for most slurry constituents with coefficient of determination of cross validation (R2cv) above 0.90 and a similar accuracy of prediction of potential NH3 and CH4 emissions (R2cv=0.84 and 0.68, respectively) thus models based on slurry composition from commercial farms. Experiment 2 was conducted to investigate the effects of increasing the level of two sources of fibrous by-products, orange pulp (OP) and carob meal (CM), in iso-fibrous diets for growing-finishing pig, slurry composition and potential NH3 and CH4 emissions. Thirty pigs (85.4±12.3 kg) were fed five iso-nutritive diets: a commercial control wheat/barley (C) and four experimental diets including two sources of fibrous by-products OP and CM and two dietary levels (75 and 150 g/kg) in a 2 × 2 factorial arrangement. After a 14-day adaptation period, faeces and urine were collected separately for 7 days to measure nutrient digestibility and the excretory patterns of N from pigs (6 replicates per diet) housed individually in metabolic pens. For each animal, the derived NH3 and CH4 emissions were measured in samples of slurry over an 11 and 100-day storage periods, respectively. Source and level of the fibrous by-products affected digestion efficiency in a different way as the coefficients of total tract apparent digestibility (CTTAD) for dry matter (DM), organic matter (OM), fibre fractions and gross energy (GE) increased with OP but decreased with CM (P<0.05). Crude protein CTTAD decreased with the inclusion of both sources of fibre, being lower at the highest dietary level. Faecal concentration of fibre fractions increased (P<0.05) with the level of inclusion of CM but decreased with that of OP (P<0.01). High dietary level for both sources of fibre increased (P<0.02) CP faecal content but urine N content decreased (from 205 to 168 g/kg DM, P<0.05) in all the fibre-supplemented compared to C diet. Additionally, the proportions of undigested dietary, water soluble, and bacterial and endogenous debris of faecal N excretion were not affected by treatments. The initial slurry characteristics did not differ among different fibre sources and dietary levels, except pH, which decreased at the highest by-product inclusion levels. Ammonia emission per kg of slurry was lower in all the fibre-supplemented diets than in C diet (2.44 vs. 1.81g as average, P<0.05). Additionally, slurries from the highest dietary level of by-products tended (P<0.06) to emit less NH3 per kg of initial total Kjeldahl nitrogen (TKN) and showed a lower biochemical CH4 potential , independently of the fibre source. Experiment 3 investigated the effects of protein source in practical diets. Three experimental feeds were designed to substitute a mixture of soybean meal and soybean hulls (SB diet) with sunflower meal (SFM) or wheat DDGS (WDDGS). The proportion of other ingredients was also modified in order to maintain similar nutrient contents across diets. Changes in protein source led to differences in dietary content of neutral detergent insoluble crude protein (NDICP), soluble fibre (SF) and acid detergent lignin (ADL). Twenty-four pigs (eight per diet), weighing 52.3 or 60.8 kg at the first and second batch respectively, were housed individually in metabolic pens to determine during a 7-day period DM balance, CTTAD of nutrients, and faecal and urine composition. Representative slurry samples from each animal were used to measure NH3 and CH4 emissions over an 11 and or 100-day storage period, respectively. Neither DM intake, nor DM or energy CTTAD differed among experimental diets, but type of feed affected (P<0.001) CP digestibility, which was highest for SFM (0.846) than for SB (0.775) diet, with WDDGS-based diet giving an intermediate value (0.794). Faecal DM composition was influenced (P<0.001) accordingly, with the lowest CP concentration found for diet SFM and the highest for SB. The ratio of N excreted in urine or faeces decreased from SFM (1.63) to SB diet (0.650), as a consequence of both lower urine and higher faecal losses, with all the faecal N fractions increasing in parallel to total excretion. This result was parallel to a decrease of potential NH3 emission (g/kg slurry) in diet SB with respect to diet SFM (from 1.82 to 1.12, P<0.05), giving slurry from WDDGS-based diet an intermediate value (1.58). Otherwise, SF and insoluble neutral detergent fibre (NDF) CTTAD were affected (P<0.001 and P=0.002, respectively) by type of diet, being lower for SFM than in SB-diet; besides, a higher content of NDF (491 vs. 361 g/kg) in faecal DM was observed for SFM with respect to SB based diet, with WDDGS diet being intermediate. Degree of lignification of NDF (ADL/NDF x 100) of faeces decreased in the order SFM>WDDGS>SB (from 0.171 to 0.109 and 0.086, respectively) in parallel to a decrease of biochemical CH4 potential per g of VS of slurry (from 301 to 269 and 256 ml, respectively). All slurry samples obtained from these three experiments and Antezana et al. (2015) were used to develop new calibrations with NIRS technology, to predict the slurry composition and potential gaseous emissions of samples with greater variability in comparison to experiment 1. Better accuracy (R2cv above 0.92) was observed for calibrations when samples from controlled trials experiments (2, 3 and Antezana et al., 2015) were included, increasing the range of variation. A lower accuracy was observed for TAN, NH3 and CH4 gaseous emissions, which might be explained by the less homogeneous distribution with a wider range of data.

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Los objetivos de esta tesis fueron 1) obtener y validar ecuaciones de predicción para determinar in vivo la composición corporal y de la canal de conejos en crecimiento de 25 a 77 días de vida utilizando la técnica de la Impedancia Bioeléctrica (BIA), y 2) evaluar su aplicación para determinar diferencias en la composición corporal y de la canal, así como la retención de nutrientes de animales alimentados con diferentes fuentes y niveles de grasa. El primer estudio se realizó para determinar y después validar, usando datos independientes, las ecuaciones de predicción obtenidas para determinar in vivo la composición corporal de los conejos en crecimiento. Se utilizaron 150 conejos a 5 edades distintas (25, 35, 49, 63 y 77 días de vida), con un rango de pesos entre 231 y 3138 g. Para determinar los valores de resistencia (Rs,) and reactancia (Xc,) se usó un terminal (Model BIA-101, RJL Systems, Detroit, MI USA) con cuatro electrodos. Igualmente se registró la distancia entre electrodos internos (D), la longitud corporal (L) y el peso vivo (PV) de cada animal. En cada edad, los animales fueron molidos y congelados (-20 ºC) para su posterior análisis químico (MS, grasa, proteína, cenizas y EB). El contenido en grasa y energía de los animales se incrementó, mientras que los contenidos en proteína, cenizas y agua de los animales disminuyeron con la edad. Los valores medios de Rs, Xc, impedancia (Z), L y D fueron 83.5 ± 23.1 , 18.2 ± 3.8 , 85.6 ± 22.9 , 30.6 ± 6.9 cm y 10.8 ± 3.1 cm. Se realizó un análisis de regresión lineal múltiple para determinar las ecuaciones de predicción, utilizando los valores de PV, L and Z como variables independientes. Las ecuaciones obtenidas para estimar los contenidos en agua (g), PB (g), grasa (g), cenizas (g) and EB (MJ) tuvieron un coeficiente de determinación de (R2) de 0.99, 0.99, 0.97, 0.98 y 0.99, y los errores medios de predicción relativos (EMPR) fueron: 2.79, 6.15, 24.3, 15.2 y 10.6%, respectivamente. Cuando el contenido en agua se expresó como porcentaje, los valores de R2 y EMPR fueron 0.85 and 2.30%, respectivamente. Al predecir los contenidos en proteína (%MS), grasa (%MS), cenizas (%MS) y energía (kJ/100 g MS), se obtuvieron valores de 0.79, 0.83, 0.71 y 0.86 para R2, y 5.04, 18.9, 12.0 y 3.19% para EMPR. La reactancia estuvo negativamente correlacionada con el contenido en agua, cenizas y PB (r = -0.32, P < 0.0001; r = -0.20, P < 0.05; r = -0.26, P < 0.01) y positivamente correlacionada con la grasa y la energía (r = 0.23 y r = 0.24; P < 0.01). Sin embargo, Rs estuvo positivamente correlacionada con el agua, las cenizas y la PB (r = 0.31, P < 0.001; r = 0.28, P < 0.001; r = 0.37, P < 0.0001) y negativamente con la grasa y la energía (r = -0.36 y r = -0.35; P < 0.0001). Igualmente la edad estuvo negativamente correlacionada con el contenido en agua, cenizas y proteína (r = -0.79; r = -0.68 y r = -0.80; P < 0.0001) y positivamente con la grasa y la energía (r = 0.78 y r = 0.81; P < 0.0001). Se puede concluir que el método BIA es una técnica buena y no invasiva para estimar in vivo la composición corporal de conejos en crecimiento de 25 a 77 días de vida. El objetivo del segundo estudio fue determinar y validar con datos independientes las ecuaciones de predicción obtenidas para estimar in vivo la composición de la canal eviscerada mediante el uso de BIA en un grupo de conejos de 25 a 77 días, así como testar su aplicación para predecir la retención de nutrientes y calcular las eficacias de retención de la energía y del nitrógeno. Se utilizaron 75 conejos agrupados en 5 edades (25, 35, 49, 63 y 77 días de vida) con unos pesos que variaron entre 196 y 3260 g. Para determinar los valores de resistencia (Rs, ) y reactancia (Xc, ) se usó un terminal (Model BIA-101, RJL Systems, Detroit, MI USA) con cuatro electrodos. Igualmente se registró la distancia entre electrodos internos (D), la longitud corporal (L) y el peso vivo (PV) del cada animal. En cada edad, los animales fueron aturdidos y desangrados. Su piel, vísceras y contenido digestivo fueron retirados, y la canal oreada fue pesada y molida para posteriores análisis (MS, grasa, PB, cenizas y EB). Los contenidos en energía y grasa aumentaron mientras que los de agua, cenizas y proteína disminuyeron con la edad. Los valores medios de Rs, Xc, impedancia (Z), L y D fueron 95.9±23.9 , 19.5±4.7 , 98.0±23.8 , 20.6±6.3 cm y 13.7±3.1 cm. Se realizó un análisis de regresión linear múltiple para determinar las ecuaciones de predicción, utilizando los valores de PV, L and Z como variables independientes. Los coeficientes de determinación (R2) de las ecuaciones obtenidas para estimar los contenidos en agua (g), PB (g), grasa (g), cenizas (g) and EB (MJ) fueron: 0.99, 0.99, 0.95, 0.96 y 0.98, mientras que los errores medios de predicción relativos (EMPR) fueron: 4.20, 5.48, 21.9, 9.10 y 6.77%, respectivamente. Cuando el contenido en agua se expresó como porcentaje, los valores de R2 y EMPR fueron 0.79 y 1.62%, respectivamente. Cuando se realizó la predicción de los contenidos en proteína (%MS), grasa (%MS), cenizas (%MS) y energía (kJ/100 g MS), los valores de R2 fueron 0.68, 0.76, 0.66 and 0.82, y los de RMPE: 3.22, 10.5, 5.82 and 2.54%, respectivamente. La reactancia estuvo directamente correlacionada con el contenido en grasa (r = 0.24, P < 0.05), mientras que la resistencia guardó una correlación positiva con los contenidos en agua, cenizas y proteína (r = 0.55, P < 0.001; r = 0.54, P < 0.001; r = 0.40, P < 0.005) y negativa con la grasa y la energía (r = -0.44 y r = -0.55; P < 0.001). Igualmente la edad estuvo negativamente correlacionada con los contenidos en agua, cenizas y PB (r = -0.94; r = -0.85 y r = -0.75; P < 0.0001) y positivamente con la grasa y la energía (r = 0.89 y r = 0.90; P < 0.0001). Se estudió la eficacia global de retención de la energía (ERE) y del nitrógeno (ERN) durante todo el periodo de cebo (35-63 d), Los valores de ERE fueron 20.4±7.29%, 21.0±4.18% and 20.8±2.79% en los periodos 35 a 49, 49 a 63 y 35 a 63 d, respectivamente. ERN fue 46.9±11.7%, 34.5±7.32% y 39.1±3.23% para los mismos periodos. La energía fue retenida en los tejidos para crecimiento con una eficiencia del 52.5% y la eficiencia de retención de la energía como proteína y grasa fue de 33.3 y 69.9% respectivamente. La eficiencia de utilización del nitrógeno para crecimiento fue cercana al 77%. Este trabajo muestra como el método BIA es técnica buena y no invasiva para determinar in vivo la composición de la canal y la retención de nutrientes en conejos en crecimiento de 25 a 77 días de vida. En el tercer estudio, se llevaron a cabo dos experimentos con el fin de investigar los efectos del nivel de inclusión y de la fuente de grasa, sobre los rendimientos productivos, la mortalidad, la retención de nutrientes y la composición corporal total y de la canal eviscerada de conejos en crecimiento de 34 a 63 d de vida. En el Exp. 1 se formularon 3 dietas con un diseño experimental factorial 3 x 2 con el tipo de grasa utilizada: Aceite de Soja (SBO), Lecitinas de Soja (SLO) y Manteca (L) y el nivel de inclusión (1.5 y 4%) como factores principales. El Exp. 2 también fue diseñado con una estructura factorial 3 x 2, pero usando SBO, Aceite de Pescado (FO) y Aceite de Palmiste como fuentes de grasa, incluidas a los mismos niveles que en el Exp. 1. En ambos experimentos 180 animales fueron alojados en jaulas individuales (n=30) y 600 en jaulas colectivas en grupos de 5 animales (n=20). Los animales alimentados con un 4% de grasa añadida tuvieron unos consumos diarios y unos índices de conversión más bajos que aquellos alimentados con las dietas con un 1.5% de grasa. En los animales alojados en colectivo del Exp. 1, el consumo fue un 4.8% más alto en los que consumieron las dietas que contenían manteca que en los animales alimentados con las dietas SBO (P = 0.036). La inclusión de manteca tendió a reducir la mortalidad (P = 0.067) en torno al 60% y al 25% con respecto a las dietas con SBO y SLO, respectivamente. La mortalidad aumentó con el nivel máximo de inclusión de SLO (14% vs. 1%, P < 0.01), sin observarse un efecto negativo sobre la mortalidad con el nivel más alto de inclusión de las demás fuentes de grasa utilizadas. En los animales alojados colectivo del Exp. 2 se encontró una disminución del consumo (11%), peso vivo a 63 d (4.8%) y de la ganancia diaria de peso (7.8%) con la inclusión de aceite de pescado con respecto a otras dietas (P < 0.01). Los dos últimos parámetros se vieron especialmente más reducidos cuando en las dietas se incluyó el nivel más alto de FO (5.6 y 9.5%, respectivamente, (P < 0.01)). Los animales alojados individualmente mostraron unos resultados productivos muy similares. La inclusión de aceite pescado tendió (P = 0.078) a aumentar la mortalidad (13.2%) con respecto al aceite de palmiste (6.45%), siendo intermedia para las dietas que contenían SBO (8.10%). La fuente o el nivel de grasa no afectaron la composición corporal total o de la canal eviscerada de los animales. Un incremento en el nivel de grasa dio lugar a una disminución de la ingesta de nitrógeno digestible (DNi) (1.83 vs. 1.92 g/d; P = 0.068 en Exp. 1 y 1.79 vs. 1.95 g/d; P = 0.014 en Exp. 2). Debido a que el nitrógeno retenido (NR) en la canal fue similar para ambos niveles (0.68 g/d (Exp. 1) y 0.71 g/d (Exp. 2)), la eficacia total de retención del nitrógeno (ERN) aumentó con el nivel máximo de inclusión de grasa, pero de forma significativa únicamente en el Exp. 1 (34.9 vs. 37.8%; P < 0.0001), mientras que en el Exp. 2 se encontró una tendencia (36.2 vs. 38.0% en Exp. 2; P < 0.064). Como consecuencia, la excreción de nitrógeno en heces fue menor en los animales alimentados con el nivel más alto de grasa (0.782 vs. 0.868 g/d; P = 0.0001 en Exp. 1, y 0.745 vs. 0.865 g/d; P < 0.0001 en Exp.2) al igual que el nitrógeno excretado en orina (0.702 vs. 0.822 g/d; P < 0.0001 en Exp. 1 y 0.694 vs. 0.7999 g/d; P = 0.014 en Exp.2). Aunque no hubo diferencias en la eficacia total de retención de la energía (ERE), la energía excretada en heces disminuyó al aumentar el nivel de inclusión de grasa (142 vs. 156 Kcal/d; P = 0.0004 en Exp. 1 y 144 vs. 154 g/d; P = 0.050 en Exp. 2). Sin embargo, la energía excretada como orina y en forma de calor fue mayor en el los animales del Exp. 1 alimentados con el nivel más alto de grasa (216 vs. 204 Kcal/d; P < 0.017). Se puede concluir que la manteca y el aceite de palmiste pueden ser considerados como fuentes alternativas al aceite de soja debido a la reducción de la mortalidad, sin efectos negativos sobre los rendimientos productivos o la retención de nutrientes. La inclusión de aceite de pescado empeoró los rendimientos productivos y la mortalidad durante el periodo de crecimiento. Un aumento en el nivel de grasa mejoró el índice de conversión y la eficacia total de retención de nitrógeno. ABSTRACT The aim of this Thesis is: 1) to obtain and validate prediction equations to determine in vivo whole body and carcass composition using the Bioelectrical Impedance (BIA) method in growing rabbits from 25 to 77 days of age, and 2) to study its application to determine differences on whole body and carcass chemical composition, and nutrient retention of animals fed different fat levels and sources. The first study was conducted to determine and later validate, by using independent data, the prediction equations obtained to assess in vivo the whole body composition of growing rabbits. One hundred and fifty rabbits grouped at 5 different ages (25, 35, 49, 63 and 77 days) and weighing from 231 to 3138 g were used. A four terminal body composition analyser was used to obtain resistance (Rs, ) and reactance (Xc, ) values (Model BIA-101, RJL Systems, Detroit, MI USA). The distance between internal electrodes (D, cm), body length (L, cm) and live BW of each animal were also registered. At each selected age, animals were slaughtered, ground and frozen (-20 ºC) for later chemical analyses (DM, fat, CP, ash and GE). Fat and energy body content increased with the age, while protein, ash, and water decreased. Mean values of Rs, Xc, impedance (Z), L and D were 83.5 ± 23.1 , 18.2 ± 3.8 , 85.6 ± 22.9 , 30.6 ± 6.9 cm and 10.8 ± 3.1 cm. A multiple linear regression analysis was used to determine the prediction equations, using BW, L and Z data as independent variables. Equations obtained to estimate water (g), CP (g), fat (g), ash (g) and GE (MJ) content had, respectively, coefficient of determination (R2) values of 0.99, 0.99, 0.97, 0.98 and 0.99, and the relative mean prediction error (RMPE) was: 2.79, 6.15, 24.3, 15.2 and 10.6%, respectively. When water was expressed as percentage, the R2 and RMPE were 0.85 and 2.30%, respectively. When prediction of the content of protein (%DM), fat (%DM), ash (%DM) and energy (kJ/100 g DM) was done, values of 0.79, 0.83, 0.71 and 0.86 for R2, and 5.04, 18.9, 12.0 and 3.19% for RMPE, respectively, were obtained. Reactance was negatively correlated with water, ash and CP content (r = -0.32, P < 0.0001; r = -0.20, P < 0.05; r = -0.26, P < 0.01) and positively correlated with fat and GE (r = 0.23 and r = 0.24; P < 0.01). Otherwise, resistance was positively correlated with water, ash and CP (r = 0.31, P < 0.001; r = 0.28, P < 0.001; r = 0.37, P < 0.0001) and negatively correlated with fat and energy (r = -0.36 and r = -0.35; P < 0.0001). Moreover, age was negatively correlated with water, ash and CP content (r = -0.79; r = -0.68 and r = -0.80; P < 0.0001) and positively correlated with fat and energy (r = 0.78 and r = 0.81; P < 0.0001). It could be concluded that BIA is a non-invasive good method to estimate in vivo whole body composition of growing rabbits from 25 to 77 days of age. The aim of the second study was to determine and validate with independent data, the prediction equations obtained to estimate in vivo carcass composition of growing rabbits by using the results of carcass chemical composition and BIA values in a group of rabbits from 25 to 77 days. Also its potential application to predict nutrient retention and overall energy and nitrogen retention efficiencies was analysed. Seventy five rabbits grouped at 5 different ages (25, 35, 49, 63 and 77 days) with weights ranging from 196 to 3260 g were used. A four terminal body composition analyser (Model BIA-101, RJL Systems, Detroit, MI USA) was used to obtain resistance (Rs, ) and reactance (Xc, ) values. The distance between internal electrodes (D, cm), body length (L, cm) and live weight (BW, g) were also registered. At each selected age, all the animals were stunned and bled. The skin, organs and digestive content were removed, and the chilled carcass were weighed and processed for chemical analyses (DM, fat, CP, ash and GE). Energy and fat increased with the age, while CP, ash, and water decreased. Mean values of Rs, Xc, impedance (Z), L and D were 95.9±23.9 , 19.5±4.7 , 98.0±23.8 , 20.6±6.3 cm y 13.7±3.1 cm. A multiple linear regression analysis was done to determine the equations, using BW, L and Z data as parameters. Coefficient of determination (R2) of the equations obtained to estimate water (g), CP (g), fat (g), ash (g) and GE (MJ) content were: 0.99, 0.99, 0.95, 0.96 and 0.98, and relative mean prediction error (RMPE) were: 4.20, 5.48, 21.9, 9.10 and 6.77%, respectively. When water content was expressed as percentage, the R2 and RMPE were 0.79 and 1.62%, respectively. When prediction of protein (%DM), fat (%DM), ash (%DM) and energy (kJ/100 g DM) content was done, R2 values were 0.68, 0.76, 0.66 and 0.82, and RMPE: 3.22, 10.5, 5.82 and 2.54%, respectively. Reactance was positively correlated with fat content (r = 0.24, P < 0.05) while resistance was positively correlated with water, ash and protein carcass content (r = 0.55, P < 0.001; r = 0.54, P < 0.001; r = 0.40, P < 0.005) and negatively correlated with fat and energy (r = -0.44 and r = -0.55; P < 0.001). Moreover, age was negatively correlated with water, ash and CP content (r = -0.97, r = -0.95 and r = -0.89, P < 0.0001) and positively correlated with fat and GE (r = 0.95 and r = 0.97; P < 0.0001). In the whole growing period (35-63 d), overall energy retention efficiency (ERE) and nitrogen retention efficiency (NRE) were studied. The ERE values were 20.4±7.29%, 21.0±4.18% and 20.8±2.79%, from 35 to 49, 49 to 63 and from 35 to 63 d, respectively. NRE was 46.9±11.7%, 34.5±7.32% and 39.1±3.23% for the same periods. Energy was retained in body tissues for growth with an efficiency of approximately 52.5% and efficiency of the energy for protein and fat retention was 33.3 and 69.9%, respectively. Efficiency of utilization of nitrogen for growth was near to 77%. This work shows that BIA it’s a non-invasive and good method to estimate in vivo carcass composition and nutrient retention of growing rabbits from 25 to 77 days of age. In the third study, two experiments were conducted to investigate the effect of the fat addition and source, on performance, mortality, nutrient retention, and the whole body and carcass chemical composition of growing rabbits from 34 to 63 d. In Exp. 1 three diets were arranged in a 3 x 2 factorial structure with the source of fat: Soybean oil (SBO), Soya Lecithin Oil (SLO) and Lard (L) and the dietary fat inclusion level (1.5 and 4%) as the main factors. Exp. 2 had also arranged as a 3 x 2 factorial design, but using SBO, Fish Oil (FO) and Palmkernel Oil (PKO) as fat sources, and included at the same levels than in Exp. 1. In both experiments 180 animals were allocated in individual cages (n=30) and 600 in collectives cages, in groups of 5 animals (n=20). Animals fed with 4% dietary fat level showed lower DFI and FCR than those fed diets with 1.5%. In collective housing of Exp. 1, DFI was a 4.8% higher in animals fed with diets containing lard than SBO (P = 0.036), being intermediate for diet with SLO. Inclusion of lard also tended to reduce mortality (P = 0.067) around 60% and 25% with respect SBO and SLO diets, respectively. Mortality increased with the greatest level of soya lecithin (14% vs. 1%, P < 0.01). In Exp. 2 a decrease of DFI (11%), BW at 63 d (4.8%) and DWG (7.8%) were observed with the inclusion of fish oil with respect the other two diets (P < 0.01). These last two traits impaired with the highest level of fish oil (5.6 and 9.5%, respectively, (P < 0.01)). Animals housed individually showed similar performance results. The inclusion of fish oil also tended to increase (P = 0.078) mortality (13.2%) with respect palmkernel oil (6.45%), being mortality of SBO intermediate (8.10%). Fat source and level did not affect the whole body or carcass chemical composition. An increase of the fat sources addition led to a decrease of the digestible nitrogen intake (DNi) (1.83 vs. 1.92 g/d; P = 0.068 in Exp. 1 and 1.79 vs. 1.95 g/d; P = 0.014 in Exp. 2). As the nitrogen retained (NR) in the carcass was similar for both fat levels (0.68 g/d (Exp. 1) and 0.71 g/d (Exp. 2)), the overall efficiency of N retention (NRE) increased with the highest level of fat, but only reached significant level in Exp. 1 (34.9 vs. 37.8%; P < 0.0001), while in Exp. 2 a tendency was found (36.2 vs. 38.0% in Exp. 2; P < 0.064). Consequently, nitrogen excretion in faeces was lower in animals fed with the highest level of fat (0.782 vs. 0.868 g/d; P = 0.0001 in Exp. 1, and 0.745 vs. 0.865 g/d; P < 0.0001 in Exp.2). The same effect was observed with the nitrogen excreted as urine (0.702 vs. 0.822 g/d; P < 0.0001 in Exp. 1 and 0.694 vs. 0.7999 g/d; P = 0.014 in Exp.2). Although there were not differences in ERE, the energy excreted in faeces decreased as fat level increased (142 vs. 156 Kcal/d; P = 0.0004 in Exp. 1 and 144 vs. 154 g/d; P = 0.050 in Exp. 2). In Exp. 1 the energy excreted as urine and heat production was significantly higher when animals were fed with the highest level of dietary fat (216 vs. 204 Kcal/d; P < 0.017). It can be concluded that lard and palmkernel oil can be considered as alternative sources to soybean oil due to the reduction of the mortality, without negative effects on performances or nutrient retention. Inclusion of fish impaired animals´ productivity and mortality. An increase of the dietary fat level improved FCR and overall protein efficiency retention.

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Achievement of steady state during indirect calorimetry measurements of resting energy expenditure (REE) is necessary to reduce error and ensure accuracy in the measurement. Steady state is often defined as 5 consecutive min (5-min SS) during which oxygen consumption and carbon dioxide production vary by +/-10%. These criteria, however, are stringent and often difficult to satisfy. This study aimed to assess whether reducing the time period for steady state (4-min SS or 3-min SS) produced measurements of REE that were significantly different from 5-min SS. REE was measured with the use of open-circuit indirect calorimetry in 39 subjects, of whom only 21 (54%) met the 5-min SS criteria. In these 21 subjects, median biases in REE between 5-min SS and 4-min SS and between 5-min SS and 3-min SS were 0.1 and 0.01%, respectively. For individuals, 4-min SS measured REE within a clinically acceptable range of +/-2% of 5-min SS, whereas 3-min SS measured REE within a range of -2-3% of 5-min SS. Harris-Benedict prediction equations estimated REE for individuals within +/-20-30% of 5-min SS. Reducing the time period of steady state to 4 min produced measurements of REE for individuals that were within clinically acceptable, predetermined limits. The limits of agreement for 3-min SS fell outside the predefined limits of +/-2%; however, both 4-min SS and 3-min SS criteria greatly increased the proportion of subjects who satisfied steady state within smaller limits than would be achieved if relying on prediction equations.

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Detailed analysis of body composition in children has helped to understand changes that occur in growth and disease. Bioelectrical impedance analysis (BIA) has gained popularity as a simple, non-invasive and inexpensive tool of body composition assessment. Being an indirect technique, prediction equations have to be used in the assessment of body composition. There are many prediction equations available in the literature for the assessment of body composition from BIA. This study aims to cross-validate some of those prediction equations to determine the suitability of their use on Australian children of white Caucasian and Sri Lankan origins. Height, weight and BIA were measured. Total body water was measured using the isotope dilution method (D2O). Fat-mass (FM) and %FM were estimated from BIA using ten prediction equations described in the literature. Five to 14.99-year-old healthy, 96 white Caucasians and 42 Sri Lankan children were studied. The equation of Schaefer et al was the most suitable prediction equation for this group with the lowest mean bias for %FM assessment in both Caucasian (–1.0±9.6%) and Sri Lankan (1.6±5.2%) children and the fat content of the individuals did not influence the predictions by this equation. Impedance index (height2/impedance) explained for 80% of TBW in white Caucasians and 93% in Sri Lankans and figures were similar for the prediction of FFM. We conclude that BIA can be used effectively in the assessment of body composition in children. However, for the assessment of body composition using BIA, either prediction equations should be derived to suit the local populations or existing equations should be cross-validated to determine their suitability before their application.

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Resting energy expenditure (REE) is lower than predicted in persons taking atypical antipsychotic medication, and weight management is a significant clinical challenge for some of them. However, to date there have been no published guidelines to assist clinicians in choosing appropriate prediction equations to estimate energy expenditure in persons taking atypical antipsychotic medications. The objectives of this study were to measure REE in a group of men taking the atypical antipsychotic clozapine and to determine whether REE can be accurately predicted for this population using previously published regression equations. REE was measured using indirect calorimetry via a ventilated hood on eight men who had completed at least 6 months of treatment with clozapine. Comparisons between measured REE and predicted REE using five different equations were undertaken. The commonly-used Harris-Benedict and Schofield equations systematically overestimated REE. Predictions of REE from other equations were too variable for clinical use. When estimating energy requirements as part of a weight-management program in men who have been taking clozapine for 6 months, predictions of REE from the equations of Harris-Benedict and Schofield should be reduced by 280 kcal/day.

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Veterinary medicines (VMs) from agricultural industry can enter the environment in a number of ways. This includes direct exposure through aquaculture, accidental spillage and disposal, and indirect entry by leaching from manure or runoff after treatment. Many compounds used in animal treatments have ecotoxic properties that may have chronic or sometimes lethal effects when they come into contact with non-target organisms. VMs enter the environment in mixtures, potentially having additive effects. Traditional ecotoxicology tests are used to determine the lethal and sometimes reproductive effects on freshwater and terrestrial organisms. However, organisms used in ecotoxicology tests can be unrepresentative of the populations that are likely to be exposed to the compound in the environment. Most often the tests are on single compound toxicity but mixture effects may be significant and should be included in ecotoxicology testing. This work investigates the use, measured environmental concentrations (MECs) and potential impact of sea lice treatments on salmon farms in Scotland. Alternative methods for ecotoxicology testing including mixture toxicity, and the use of in silico techniques to predict the chronic impact of VMs on different species of aquatic organisms were also investigated. The Scottish Environmental Protection Agency (SEPA) provided information on the use of five sea lice treatments from 2008-2011 on Scottish salmon farms. This information was combined with the recently available data on sediment MECs for the years 2009-2012 provided by SEPA using ArcGIS 10.1. In depth analysis of this data showed that from a total of 55 sites, 30 sites had a MEC higher than the maximum allowable concentration (MAC) as set out by SEPA for emamectin benzoate and 7 sites had a higher MEC than MAC for teflubenzuron. A number of sites that were up to 16 km away from the nearest salmon farm reported as using either emamectin benzoate or teflubenzuron measured positive for the two treatments. There was no relationship between current direction and the distribution of the sea lice treatments, nor was there any evidence for alternative sources of the compounds e.g. land treatments. The sites that had MECs higher than the MAC could pose a risk to non-target organisms and disrupt the species dynamics of the area. There was evidence that some marine protected sites might be at risk of exposure to these compounds. To complement this work, effects on acute mixture toxicity of the 5 sea lice treatments, plus one major metabolite 3-phenoxybenzoic acid (3PBA), were measured using an assay using the bioluminescent bacteria Aliivibrio fischeri. When exposed to the 5 sea lice treatments and 3PBA A. fischeri showed a response to 3PBA, emamectin benzoate and azamethiphos as well as combinations of the three. In order to establish any additive effect of the sea lice treatments, the efficacy of two mixture prediction equations, concentration addition (CA) and independent action ii(IA) were tested using the results from single compound dose response curves. In this instance IA was the more effective prediction method with a linear regression confidence interval of 82.6% compared with 22.6% of CA. In silico molecular docking was carried out to predict the chronic effects of 15 VMs (including the five used as sea lice control). Molecular docking has been proposed as an alternative screening method for the chronic effects of large animal treatments on non-target organisms. Oestrogen receptor alpha (ERα) of 7 non-target bony fish and the African clawed frog Xenopus laevis were modelled using SwissModel. These models were then ‘docked’ to oestradiol, the synthetic oestrogen ethinylestradiol, two known xenoestrogens dichlorodiphenyltrichloroethane (DDT) and bisphenol A (BPA), the antioestrogen breast cancer treatment tamoxifen and 15 VMs using Auto Dock 4. Based on the results of this work, four VMs were identified as being possible xenoestrogens or anti-oestrogens; these were cypermethrin, deltamethrin, fenbendazole and teflubenzuron. Further investigation, using in vitro assays, into these four VMs has been suggested as future work. A modified recombinant yeast oestrogen screen (YES) was attempted using the cDNA of the ERα of the zebrafish Danio rerio and the rainbow trout Oncorhynchus mykiss. Due to time and difficulties in cloning protocols this work was unable to be completed. Use of such in vitro assays would allow for further investigation of the highlighted VMs into their oestrogenic potential. In conclusion, VMs used as sea lice treatments, such as teflubenzuron and emamectin benzoate may be more persistent and have a wider range in the environment than previously thought. Mixtures of sea lice treatments have been found to persist together in the environment, and effects of these mixtures on the bacteria A. fischeri can be predicted using the IA equation. Finally, molecular docking may be a suitable tool to predict chronic endocrine disrupting effects and identify varying degrees of impact on the ERα of nine species of aquatic organisms.

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AIMS: Renal dysfunction is a powerful predictor of adverse outcomes in patients hospitalized for acute coronary syndrome. Three new glomerular filtration rate (GFR) estimating equations recently emerged, based on serum creatinine (CKD-EPIcreat), serum cystatin C (CKD-EPIcyst) or a combination of both (CKD-EPIcreat/cyst), and they are currently recommended to confirm the presence of renal dysfunction. Our aim was to analyse the predictive value of these new estimated GFR (eGFR) equations regarding mid-term mortality in patients with acute coronary syndrome, and compare them with the traditional Modification of Diet in Renal Disease (MDRD-4) formula. METHODS AND RESULTS: 801 patients admitted for acute coronary syndrome (age 67.3±13.3 years, 68.5% male) and followed for 23.6±9.8 months were included. For each equation, patient risk stratification was performed based on eGFR values: high-risk group (eGFR<60ml/min per 1.73m2) and low-risk group (eGFR⩾60ml/min per 1.73m2). The predictive performances of these equations were compared using area under each receiver operating characteristic curves (AUCs). Overall risk stratification improvement was assessed by the net reclassification improvement index. The incidence of the primary endpoint was 18.1%. The CKD-EPIcyst equation had the highest overall discriminate performance regarding mid-term mortality (AUC 0.782±0.20) and outperformed all other equations (ρ<0.001 in all comparisons). When compared with the MDRD-4 formula, the CKD-EPIcyst equation accurately reclassified a significant percentage of patients into more appropriate risk categories (net reclassification improvement index of 11.9% (p=0.003)). The CKD-EPIcyst equation added prognostic power to the Global Registry of Acute Coronary Events (GRACE) score in the prediction of mid-term mortality. CONCLUSION: The CKD-EPIcyst equation provides a novel and improved method for assessing the mid-term mortality risk in patients admitted for acute coronary syndrome, outperforming the most widely used formula (MDRD-4), and improving the predictive value of the GRACE score. These results reinforce the added value of cystatin C as a risk marker in these patients.

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Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

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Objectives The purpose of the study was to establish regression equations that could be used to predict muscle thickness and pennation angle at different intensities from electromyography (EMG) based measures of muscle activation during isometric contractions. Design Cross-sectional study. Methods Simultaneous ultrasonography and EMG were used to measure pennation angle, muscle thickness and muscle activity of the rectus femoris and vastus lateralis muscles, respectively, during graded isometric knee extension contractions performed on a Cybex dynamometer. Data form fifteen male soccer players were collected in increments of approximately 25% intensity of the maximum voluntary contraction (MVC) ranging from rest to MVC. Results There was a significant correlation (P < 0.05) between ultrasound predictors and EMG measures for the muscle thickness of rectus femoris with an R2 value of 0.68. There was no significant correlation (P > 0.05) between ultrasound pennation angle for the vastus lateralis predictors for EMG muscle activity with an R2 value of 0.40. Conclusions The regression equations can be used to characterise muscle thickness more accurately and to determine how it changes with contraction intensity, this provides improved estimates of muscle force when using musculoskeletal models.

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Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing Light gauge Steel Frame (LSF) wall systems made of 1.15 mm G500 steel studs and varying plasterboard and insulation configurations (cavity and external insulation) using full scale fire tests. Suitable finite element models of LSF walls were then developed and validated by comparing with test results. In this study, the validated finite element models of LSF wall panels subject to standard fire conditions were used in a detailed parametric study to investigate the effects of important parameters such as steel grade and thickness, plasterboard screw spacing, plasterboard lateral restraint, insulation materials and load ratio on their performance under standard fire conditions. Suitable equations were proposed to predict the time–temperature profiles of LSF wall studs with eight different plasterboard-insulation configurations, and used in the finite element analyses. Finite element parametric studies produced extensive fire performance data for the LSF wall panels in the form of load ratio versus time and critical hot flange (failure) temperature curves for eight wall configurations. This data demonstrated the superior fire performance of externally insulated LSF wall panels made of different steel grades and thicknesses. It also led to the development of a set of equations to predict the important relationship between the load ratio and the critical hot flange temperature of LSF wall studs. Finally this paper proposes a simplified method to predict the fire resistance rating of LSF walls based on the two proposed set of equations for the load ratio–hot flange temperature and the time–temperature relationships.

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Objectives Currently, there are no studies combining electromyography (EMG) and sonography to estimate the absolute and relative strength values of erector spinae (ES) muscles in healthy individuals. The purpose of this study was to establish whether the maximum voluntary contraction (MVC) of the ES during isometric contractions could be predicted from the changes in surface EMG as well as in fiber pennation and thickness as measured by sonography. Methods Thirty healthy adults performed 3 isometric extensions at 45° from the vertical to calculate the MVC force. Contractions at 33% and 100% of the MVC force were then used during sonographic and EMG recordings. These measurements were used to observe the architecture and function of the muscles during contraction. Statistical analysis was performed using bivariate regression and regression equations. Results The slope for each regression equation was statistically significant (P < .001) with R2 values of 0.837 and 0.986 for the right and left ES, respectively. The standard error estimate between the sonographic measurements and the regression-estimated pennation angles for the right and left ES were 0.10 and 0.02, respectively. Conclusions Erector spinae muscle activation can be predicted from the changes in fiber pennation during isometric contractions at 33% and 100% of the MVC force. These findings could be essential for developing a regression equation that could estimate the level of muscle activation from changes in the muscle architecture.

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In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.