Optimizing rabbit production under heat stress: cage density and cage size during fattening, and breeding system and water quality on rabbit does

The aim of this work was to evaluate different management strategies to optimize rabbit production under chronic heat stress. To achieve it, three trials were conducted. In the first trial, to find the optimal cage density in tropical very dry forest condition, were measured growth performance, mortality rate, injured animals and carcass performance over an initial population of 300 cross-breed rabbits of New Zealand, California, Butterfly, Dutch and Satin, weaned at 30 days (535 ± 8 g, standard error). Treatments evaluated were: 6, 12, 18 and 24 rabbits/m2 (3, 6, 9 and 12 rabbits/cage, respectively, each cage of 0.5 m2). The maximal temperature-humidity index indicated a severe heat stress from weaning to 2.2 kg body weight (experimental time). At the end of experimental period 10, 20, 30 and 30 rabbits from the treatments of 6, 12, 18 and 24 rabbits/m2, respectively, were slaughtered and carcass performance recorded. Average daily gain and feed intake decreased by 0.31 ± 0.070 and 1.20 ± 0.25 g, respectively, per each unit that the density increased at the beginning of the experiment (P = 0.001). It increased the length of the fattening period by 0.91 ± 0.16 d (P = 0.001) per each unit of increment of density. However, rabbit production (kg/m2) increased linear and quadratically with the density (P < 0.008). Animals housed at the highest density compared to the lower one tended to show a higher incidence of ringworm (68.9 vs 39.4%; P = 0.075), injured animals (16.8 vs 3.03%; P = 0.12) and mortality (20.5 vs 9.63%; P = 0.043). The proportion of scapular fat (P = 0.042) increased linearly with increasing levels of density. Increasing density reduced linearly dorsal length (P = 0.001), and reduced linear and quadratically drip loss percentage (P = 0.097 and 0.018, respectively). In the second trial, 46 nulliparous rabbit does (23 clipped and 23 unclipped) with a BW of 3.67 ± 0.05 kg (s.e.) were used to evaluate heat stress and circadian rhythms comparing unclipped and clipped rabbit does, and to study if a more extensive breeding system increase litters performance at weaning without impairing rabbit doe performance,. Rectal temperature, feed and water 4 intake were recorded for 24 h. Rabbit does were mated 7 d after circadian measurements, and randomly assigned to two breeding systems. Control (C): mated at 14 d after parturition + litter weaned at 35 d of age. Extensive (E): mate at 21 after parturition + litter weaned at 42 d of age. The first three cycles were evaluated concerning to rabbit doe and litter performance. Two hundred twenty eight weaned rabbits, were divided into two cage sizes: 0.5 and 0.25 m2 with same density (16 rabbit/m2) and growing performance was recorded. Farm and rectal temperatures were minimal and feed and water intake maximal during the night (P < 0.001). Unclipped rabbit does showed higher rectal temperature (P = 0.045) and lower feed intake respect to clipped does (P = 0.019) which suggest a lower heat stress in the latter. Kits weaned per litter was reduced by 33% (P=0.038) in C group. This reduction was more important in the 2nd and 3rd cycles compared to the first (P ≤ 0.054). Rabbit doe feed efficiency tended to decrease in E respect C group (P = 0.093), whereas it was impaired from the first to the third cycle by 48% (P = 0.014). Growing rabbits from the E group were heavier at weaning (by 38%. P < 0.001), showed a higher feed intake (+7.4%) and lower feed efficiency (-8.4%) throughout the fattening period (P ≤ 0.056) respect to C group. Cage size had minor influence in growing performance. In the third trial, forty five non pregnant and non lactating rabbit does (21 nulliparous and 24 multiparous) were assigned randomly to farm water and to potable water to study if a water quality improvement can affect positively rabbit doe response to heat stress during pregnancy and lactation. A transponder was implanted in each animal to record subcutaneous temperature at 07:30 and 14:30 h. Experimental period extended from pregnancy (with no lactation) to the next lactation (until day 28). Body temperature and milk production were recorded daily, and body condition, feed and water intake weekly. Water quality did not affect any trait (P ≥ 0.15). Pregnant rabbit does were classified as does that weaned (W: 47%), not weaned (NW: 44%) or those pregnant that did not deliver (NB: 9%). Body temperature and feed intake decreased during pregnancy (P ≤ 0.031), but water intake remained constant. In this period body temperature decreased with metabolic weight (P ≤ 0.009). In W and NW does, 5 from mating to birth energy and protein balance impaired (P≤0.011). Body temperature of W does tended to be the lowest (P ≤ 0.090). Pregnancy length and total number of kits born tended to be longer and higher in NW than in W does (P = 0.10 and 0.053, respectively). Kit mortality at birth and from birth to 14 d of lactation was high, being worse for NW than for W does (97 vs. 40%; P<0.001). Body temperature during lactation was maximal at day 12, and milk production increased it (P ≤ 0.025). . In conclusion, in our heat stress conditions densities higher than 18 rabbits/m2 (34 kg/m2) at the end of fattening, are not recommended despite cage size, gestation and lactation productivity impaired not only when lactation is extended and along successive reproductive cycles but also due to a reduced embryo/kit survival and finally water quality improvement did not attenuate negative effect of heat stress. RESUMEN El propósito de éste trabajo fue evaluar diferentes estrategias de manejo para optimizar la producción de conejos bajo estrés térmico. Para lo cual se desarrollaron tres experimentos. En el primer experimento, para encontrar el número óptimo de gazapos por m2 de jaula durante el cebo en condiciones de bosque muy seco tropical, se estudiaron los rendimientos durante el cebo, mortalidad, animales lesionados y rendimiento de la canal sobre una población inicial de 300 conejos mestizos de Nueva Zelanda, California, Mariposa, Holandés y Satin, destetados a los 30 días de edad (535 ± 8g, error estándar). Los tratamientos evaluados fueron: 6, 12, 18 y 24 conejos/m2 (3, 6, 9 y 12 conejos/jaula, respectivamente, en jaulas de 0.5 m2). Durante el período experimental (destete a 2.2 kg de peso vivo), se observaron valores de THI correspondientes con un estrés térmico severo (THI max. De 31 a 35). Al final del período experimental, 10, 20, 30, y 30 conejos de los tratamientos con densidades de 6, 12, 18 y 24 conejos/m2, respectivamente, fueron sacrificados y su canal fue valorada. El promedio de la ganancia diaria y el consumo de alimento disminuyeron en 0.31 ± 0.070 y 1.20 ± 0.25 g, respectivamente, por cada unidad de incremento en la densidad al inicio del experimento (P=0.001). Esto alargó el período de engorde en 0.91 ± 0.16 d (P=0.001) por cada unidad de incremento de la densidad. Sin embargo, la producción de conejos (kg/m2) aumentó lineal y cuadráticamente con la densidad (P<0.008). Los animales alojados en las mayores densidades en comparación con el resto tendieron a mostrar una mayore incidencia de tiña (68.9 vs 39.4%; P=0.075), de cantidad de animales heridos (16.8 vs 3.03%; P=0.12), así como de mortalidad (20.5 vs 9.63%; P=0.043). El aumento en la densidad aumentó linealmente la proporción de grasa escapular (P=0.042) y redujo linealmente la longitud dorsal (P=0.001), y lineal y cuadráticamente el porcentaje de pérdida por goteo (P=0.018). En el segundo experimento, 46 conejas nulliparas (23 rasuradas y 23 no rasuradas) con un peso vivo de 3.67 ± 0.05 kg (e.e.) fueron usadas para evaluar el estrés 8 térmico y los ritmos circadianos comparando conejas rasuradas o no, y estudiar si un sistema de crianza más extensivo mejora el desempeño de la camada al destete sin perjudicar la productividad de la coneja. Durante 24 h se midió la temperatura rectal, consumo de alimento y de agua. Las conejas fueron montadas 7 días después, y distribuidas en dos sistemas de crianza. El control (C): monta a 14 días posparto y destete a 35 d de edad. El extensivo (E): monta a 21 días posparto y destete a 42 d de edad. Se controló la productividad de la coneja y la camada durante los tres primeros ciclos. Doscientos veintiocho gazapos fueron distribuidos en dos tamaños de jaulas (0.5 y 0.25 m2) con la misma densidad (16 conejos/m2) y se controlaron sus rendimientos productivos. Durante la noche se observaron los valores mínimos para la temperatura ambiental y rectal, y los máximos para consumo de alimento y agua (P< 0.001). Las conejas no rasuradas mostraron mayor temperatura rectal (P=0.045) y menores valores de consumo de alimento con respecto a las conejas rasuradas (P=0.019), lo que sugiere un menor estrés térmico en las últimas. El número de gazapos destetados por camada se redujo en 33% (P=0.038) en el grupo C. Este comportamiento se acentuó en el 2do y 3er ciclo en comparación con el primero (P≤0.054). La eficiencia alimenticia de las conejas tendió a disminuir en el grupo E con respecto al grupo C (P=0.093), dicha tendencia se acentúa del primer al tercer ciclo en un 48% (P=0.014). Los gazapos en fase de crecimiento provenientes del grupo E fueron más pesados al momento del destete (en 38% P<0.001), mostrando un mayor consumo de alimento (+7.4%) y menor eficiencia alimenticia (-8.4%) a lo largo del engorde (P≤0.056) con respecto al grupo C. El tamaño de la jaula tuvo una mínima influencia en el comportamiento durante el crecimiento de éstos gazapos. En el tercer experimento, cuarenta y cinco conejas no gestantes ni lactantes (21 nulíparas y 24 multíparas) se les asignó al azar agua dos tipos de agua: común de la granja y agua potable, con el fin de estudiar si una mejora en la calidad del agua puede afectar positivamente la respuesta de la coneja al estrés térmico durante la gestación y la lactancia. Se les implantó un transponder para registrar la temperatura subcutánea a las 7:30 y a las 14:30 h. El período experimental se extendió desde la gestación (sin 9 lactancia) hasta la lactanción consecutiva (hasta los 28 días). La temperatura corporal y la producción de leche se controlaron diariamente, y la condición corporal, consumo de agua y alimento, semanalmente. La calidad del agua no afectó a ninguna variable (P≥0.15). Las conejas preñadas fueron clasificadas como conejas que destetaron (W: 47%), que no destetaron (NW:44%) o aquellas que no parieron (NB: 9%). La temperatura corporal y consumo de alimento disminuyeron durante la gestación (P≤0.031), mientras que el consumo de agua se mantuvo constante. La temperatura corporal descendió con el peso metabólico durante la gestación (P≤0.009). El balance de energía y proteína disminuyó desde la monta al parto para las conejas W y NW (P≤0.011). Durante la gestación la temperatura corporal tendió a ser menor en las conejas W (P≤0.090). La longitud de la gestación y el número total de gazapos nacidos tendieron a ser mayores en conejas NW que en conejas W (P=0.10 y 0.053, respectivamente). La mortalidad de los gazapos al parto y del parto a los 14 días de lactancia fue alta, siendo peor para las conejas NW que para las W (97 vs 40%; P<0.001). Durante la lactancia la temperatura corporal alcanzó su valor máximo para el día 12, y la producción de leche indujo un incremento en la misma (P≤0.025). En conclusión, en nuestras condiciones de estrés térmico y sin importar el tamaño de la jaula, no se recomiendan densidades mayores a 18 conejos/m2 (34 kg/m2) al final del engorde. La productividad de la gestación y la lactancia disminuyen cuando la lactancia es mayor y se suceden varios ciclos reproductivos seguidos. Esto se debe al efecto negativo del estrés térmico sobre la vitalidad y supervivencia del embrión/gazapo. La mejora de la calidad del agua atenuó el efecto negativo del estrés térmico. Las conejas más productoras parece que son aquéllas que consiguen manejar mejor el estrés térmico.

New non-reorientational, non-thermal optical nonlinear effect in MBBA

It is widely known the anular-shaped beam divergence produced by the optical reorientation induced in nematics by a Gaussian beam. Recent works have found a new effect in colored liquid crystal (MBBA, Phase V,...) showing a similar spatial distribution. A new set of random-oscillating rings appears for light intensities over a certain threshold. The beam divergence due to that effect is greater than the molecular reorientation induced one.

UWB doublet generation employing non-linear effects of a Semiconductor Optical Amplifier Mach-Zehnder inteferometer

In this article, a novel method to generate an ultra-wideband (UWB) doublet using the cross-phase modulation (XPM) effect is proposed and experimentally demonstrated. The main component of the submitted architecture is a SOA-Mach-Zehnder interferometer (MZI) pumped with a modulated Gaussian pulse. Maximum and minimum conversion points are analyzed through the systems transfer function in order to determinate the most effective operation stage. By tuning different values for the SOAs currents, it is possible to identify a conversion step in which the input pulse is enough large to saturate the SOAMZI, leading to the generation of a UWB doublet pulse.

Analysis of the behavior of multijunction solar cells under high irradiance Gaussian light profiles showing chromatic aberration with emphasis on tunnel junction performance

In this work, we explain the behavior of multijunction solar cells under non-uniform (spatially and in spectral content) light profiles in general and in particular when Gaussian light profiles cause a photo-generated current density, which exceeds locally the peak current density of the tunnel junction. We have analyzed the implications on the tunnel junction's limitation, that is, in the loss of efficiency due to the appearance of a dip in the I–V curve. For that, we have carried out simulations with our three-dimensional distributed model for multijunction solar cells, which contemplates a full description of the tunnel junction and also takes into account the lateral resistances in the tunnel junction. The main findings are that the current density photo-generated spreads out through the lateral resistances of the device, mainly through the tunnel junction layers and the back contact. Therefore, under non-uniform light profiles these resistances are determinant not only to avoid the tunnel junction's limitation but also for mitigating losses in the fill factor. Therefore, taking into account these lateral resistances could be the key for jointly optimizing the concentrator photovoltaic system (concentrator optics, front grid layout and semiconductor structure)

Orientation of biological cells using plane-polarized gaussian beam optical tweezers

Optical tweezers are widely used for the manipulation of cells and their internal structures. However, the degree of manipulation possible is limited by poor control over the orientation of the trapped cells. We show that it is possible to controllably align or rotate disc-shaped cells-chloroplasts of Spinacia oleracea-in a plane-polarized Gaussian beam trap, using optical torques resulting predominantly from circular polarization induced in the transmitted beam by the non-spherical shape of the cells.

Non-positivity of Groenewold operators

A central feature in the Hilbert space formulation of classical mechanics is the quantisation of classical Lionville densities, leading to what may be termed Groenewold operators. We investigate the spectra of the Groenewold operators that correspond to Gaussian and to certain uniform Lionville densities. We show that when the classical coordinate-momentum uncertainty product falls below Heisenberg's limit, the Groenewold operators in the Gaussian case develop negative eigenvalues and eigenvalues larger than 1. However, in the uniform case, negative eigenvalues are shown to persist for arbitrarily large values of the classical uncertainty product.

Initiation of fungal epizootics in diamondback moth populations within a large field cage: proof of concept for auto-dissemination

Adult diamondback moths (DBM), Plutella xylostella L. (Lepidoptera: Plutellidae), inoculated with the fungus Zoophthora radicans, were released within a large field cage containing DBM-infested potted broccoli plants. Larvae and pupae on exposed and caged control plants were examined on five occasions over the next 48 days for evidence of Z. radicans infection. Infected larvae were first detected on exposed plants 4 days after the initial release of adults, and after 48 days the infection level reached 79%. Aerially borne conidia were a factor in transmission of the fungus. Infection had no effect on possible losses of larval and adult cadavers due to scavengers in field crops. In a trial to measure the influence of infection on dispersal, twice as many non-infected as infected males were recaptured in pheromone traps, although the difference in cumulative catch only became significant 3 days after release of the males. In a separate experiment, when adult moths were inoculated with Beauveria bassiana conidia and released into the field cage, DBM larvae collected from 37 of 96 plants sampled 4 days later subsequently died from B. bassiana infection. The distribution of plants from which the infected larvae were collected was random, but the distribution of infected larvae was clustered within the cage. These findings suggest that the auto-dissemination of fungal pathogens may be a feasible strategy for DBM control, provided that epizootics can be established and maintained when DBM population densities are low.

Regression with input-dependent noise: A Gaussian process treatment

Gaussian processes provide natural non-parametric prior distributions over regression functions. In this paper we consider regression problems where there is noise on the output, and the variance of the noise depends on the inputs. If we assume that the noise is a smooth function of the inputs, then it is natural to model the noise variance using a second Gaussian process, in addition to the Gaussian process governing the noise-free output value. We show that prior uncertainty about the parameters controlling both processes can be handled and that the posterior distribution of the noise rate can be sampled from using Markov chain Monte Carlo methods. Our results on a synthetic data set give a posterior noise variance that well-approximates the true variance.

Upper and lower bounds on the learning curve for Gaussian processes

In this paper we introduce and illustrate non-trivial upper and lower bounds on the learning curves for one-dimensional Gaussian Processes. The analysis is carried out emphasising the effects induced on the bounds by the smoothness of the random process described by the Modified Bessel and the Squared Exponential covariance functions. We present an explanation of the early, linearly-decreasing behavior of the learning curves and the bounds as well as a study of the asymptotic behavior of the curves. The effects of the noise level and the lengthscale on the tightness of the bounds are also discussed.

Gaussian processes:iterative sparse approximations

In recent years there has been an increased interest in applying non-parametric methods to real-world problems. Significant research has been devoted to Gaussian processes (GPs) due to their increased flexibility when compared with parametric models. These methods use Bayesian learning, which generally leads to analytically intractable posteriors. This thesis proposes a two-step solution to construct a probabilistic approximation to the posterior. In the first step we adapt the Bayesian online learning to GPs: the final approximation to the posterior is the result of propagating the first and second moments of intermediate posteriors obtained by combining a new example with the previous approximation. The propagation of em functional forms is solved by showing the existence of a parametrisation to posterior moments that uses combinations of the kernel function at the training points, transforming the Bayesian online learning of functions into a parametric formulation. The drawback is the prohibitive quadratic scaling of the number of parameters with the size of the data, making the method inapplicable to large datasets. The second step solves the problem of the exploding parameter size and makes GPs applicable to arbitrarily large datasets. The approximation is based on a measure of distance between two GPs, the KL-divergence between GPs. This second approximation is with a constrained GP in which only a small subset of the whole training dataset is used to represent the GP. This subset is called the em Basis Vector, or BV set and the resulting GP is a sparse approximation to the true posterior. As this sparsity is based on the KL-minimisation, it is probabilistic and independent of the way the posterior approximation from the first step is obtained. We combine the sparse approximation with an extension to the Bayesian online algorithm that allows multiple iterations for each input and thus approximating a batch solution. The resulting sparse learning algorithm is a generic one: for different problems we only change the likelihood. The algorithm is applied to a variety of problems and we examine its performance both on more classical regression and classification tasks and to the data-assimilation and a simple density estimation problems.

Statistical mechanics analysis of LDPC coding in MIMO Gaussian channels

Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under low-density parity-check (LDPC) network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and symmetric and asymmetric interference. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases. © 2007 IOP Publishing Ltd.

Non-normally distributed data and non-parametric statistics

Different types of numerical data can be collected in a scientific investigation and the choice of statistical analysis will often depend on the distribution of the data. A basic distinction between variables is whether they are ‘parametric’ or ‘non-parametric’. When a variable is parametric, the data come from a symmetrically shaped distribution known as the ‘Gaussian’ or ‘normal distribution’ whereas non-parametric variables may have a distribution which deviates markedly in shape from normal. This article describes several aspects of the problem of non-normality including: (1) how to test for two common types of deviation from a normal distribution, viz., ‘skew’ and ‘kurtosis’, (2) how to fit the normal distribution to a sample of data, (3) the transformation of non-normally distributed data and scores, and (4) commonly used ‘non-parametric’ statistics which can be used in a variety of circumstances.

Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions

In this paper we develop set of novel Markov Chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. The novel diffusion bridge proposal derived from the variational approximation allows the use of a flexible blocking strategy that further improves mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample applications the algorithm is accurate except in the presence of large observation errors and low to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient. © 2011 Springer-Verlag.