Modelling of sinkage tests in tilled soils for mobility study

The study of the mechanical behaviour of breached surface soils allows the optimization of the running gear of the vehicles for the off-road mobility.The sinkage of the running gear causes a motion resistance which is opposed to the tractive capacity of the vehicle. In a homogeneous soil, the sinkage is predicted by the interpretation of plate sinkage tests. In order to make possible and easier the sinkage prediction of a vehicle going in a tilled soil, the article has for objective to present a method to model pressure–sinkage curve for a tilled soil with the pressure–sinkage curve of the same soil before tillage.The tilled soil is considered as two layers of the same soil whose density is lower for the upper layer than for the sub-base. The two-layered soil behaviour is modelled as the combination of the behaviour of the loose soil layer and the behaviour of the dense soil. The link between these two behaviours is a critical depth defined as the depth of the plate when the layer of soil in a critical density reaches the limit between the two layers.Sinkage tests with circular plates were carried out on four soils chosen to represent the mechanical properties of a range of soils: a sand for frictional soils, a silt for cohesive soils and a silty sand and a sandy loam for cohesive frictional soils predominant in the agricultural soils. The soils were tested in one-layered and two-layered configurations in small and large bins with well-known and controlled soil conditions.A theoretical approach allows the calculation of the critical depth with a deformation process of the soil below the plate. The critical depth depends on the density of the soil, the tillage depth, the diameter of the plate and the angle of friction of the soil.The critical depth allows the modelling of the pressure–sinkage curve for the tilled soils using the one-layered soil data. The comparison with the experimental tests in tilled soil validate the approach.     

Meningoencephalomyelitis in a foal due to Salmonella agona infection

CASE HISTORY: A neonatal Thoroughbred foal was presented with rib fractures and left forelimb lameness secondary to dystocia.

CLINICAL FINDINGS: The foal developed a head tilt, seizures and watery diarrhoea during hospitalisation and died at 7 days of age. Histological examination of the brain and spinal cord revealed a suppurative meningoencephalomyelitis with vasculitis, and numerous intralesional, gram-negative bacilli. Similar microscopic lesions were noted in the lungs, renal medullary interstitium, and umbilicus. Bacilli in the brain, spinal cord and umbilicus were identified immunohistochemically as Salmonella group B. Salmonella agona was isolated in pure culture from the brain, lung, liver, kidney, and intestine.

CONCLUSION: This is the first report of meningoencephalomyelitis and septicaemia due to Salmonella infection in an equine neonate.     

Listeria monocytogenes gastroenteritis in sheep

Extract

Listeria monocytogenes is widely distributed in the environment of farm animals. It is found in soil, faeces and nasal secretions of healthy animals, water troughs and animal feeds. Under certain conditions it becomes pathogenic, causing serious disease in cattle and sheep. Most commonly it causes meningoencephalitis but, on occasion, septicaemic listeriosis results in abortion, and more recently it has been associated with gastroenteritis.     

Multivariate global sensitivity analysis for dynamic crop models

Dynamic crop models are frequently used in ecology, agronomy and environmental sciences for simulating crop and environmental variables at a discrete time step. They often include a large number of parameters whose values are uncertain, and it is often impossible to estimate all these parameters accurately. A common practice consists in selecting a subset of parameters by global sensitivity analysis, estimating the selected parameters from data, and setting the others to some nominal values. For a discrete-time model, global sensitivity analyses can be applied sequentially at each simulation date. In the case of dynamic crop models, simulations are usually computed at a daily time step and the sequential implementation of global sensitivity analysis at each simulation date can result in several hundreds of sensitivity indices, with one index per parameter per simulation date. It is not easy to identify the most important parameters based on such a large number of values. In this paper, an alternative method called multivariate global sensitivity analysis was investigated. More precisely, the purposes of this paper are (i) to compare the sensitivity indices and associated parameter rankings computed by the sequential and the multivariate global sensitivity analyses, (ii) to assess the value of multivariate sensitivity analysis for selecting the model parameters to estimate from data. Sequential and multivariate sensitivity analyses were compared by using two dynamic models: a model simulating wheat biomass named WWDM and a model simulating N₂O gaseous emission in crop fields named CERES-EGC. N₂O measurements collected in several experimental plots were used to evaluate how parameter selection based on multivariate sensitivity analysis can improve the CERES-EGC predictions.The results showed that sequential and multivariate sensitivity analyses provide modellers with different types of information for models which exhibit a high variability of sensitivity index values over time. Conversely, when the parameter influence is quite constant over time, the two methods give more similar results. The results also showed that the estimation of the parameters with the highest sensitivity indices led to a strong reduction of the prediction errors of the model CERES-EGC.     

Testosterone serum profile,semen characteristics and testicular biometry of Mangalarga Marchador stallions in a tropical environment

This study was conducted to characterize the daily profile of testosterone secretion and its mean concentrations in the four seasons as well as to evaluate the semen characteristics and testicular biometry of Mangalarga Marchador stallions throughout the year in a tropical region. Three stallions were submitted to semen collections and evaluation of testicular biometry every 14 days along a year. Blood samples were collected once at the middle of each season, in a 20‐min interval during 24 hr in order to evaluate the testosterone secretion profiles among seasons. Testosterone concentrations along the day were higher at the beginning of the afternoon (from 12:00 to 15:00 hr), but a circadian secretion was not clearly observed. Mean testosterone concentrations did not differ among seasons (p > .05), but a pattern of secretion along the day showed variations with higher concentrations in the afternoon during the winter. Ejaculate volume was higher during summer; however, sperm motility decreased in summer and spring. Total sperm in ejaculate, sperm morphology and testicular biometry kept constant along the year showing no differences among the seasons. The results demonstrated that in a tropical region, reproductive aspects of stallions did not show a clearly defined seasonal variation, and months of autumn and winter were not unsuitable for reproduction of the males.     

A general method to filter out defective spatial observations from yield mapping datasets

Yield maps are recognized as a valuable tool with regard to managing upcoming crop production but can contain a large amount of defective data that might result in misleading decisions. These anomalies must be removed before further processing to ensure the quality of future decisions. This paper proposes a new holistic methodology to filter out defective observations likely to be present in yield datasets. The notion of spatial neighbourhood has been refined to embrace the specific characteristics of such on-the-go vehicle based datasets. Observations are compared with their newly-defined spatial neighbourhood and the most abnormal ones are classified as defective observations based on a density-based clustering algorithm. The approach was conceived to be as non-parametric and automated as far as possible to pre-process a growing number of datasets without supervision. The proposed approach showed promising results on real yield datasets with the detection of well-known sources of errors such as filling and emptying times, speed changes and non-fully used cutting bar.     

Fleets of robots for environmentally-safe pest control in agriculture

Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. Within this context, this research strived to design, develop, test and assess a new generation of automatic and robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced end-effectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.     

Influence of a long-term storage in anaerobic conditions on Norway spruce (Picea abies,L. Karst.) physical and mechanical wood properties

Timber storage is a key aspect of storm damage management. After huge storms, sprinkling storage is usually the most used conservation process but anaerobic storage in sealed silos appears as good alternative to preserve wood quality over long periods. This paper investigates the impact of long-term (57 months) storage of Norway spruce logs in anaerobic atmosphere on wood properties. Tests were performed on clear wood specimens and on lumbers to determine the modulus of elasticity (E), the static bending strength (σ_f) and the dynamic bending strength (K). Storage effects on impregnability and colour variation were also studied. Results show no effect of storage on E, σ_f and K. The naturally poor impregnability of Norway spruce is not improved by the anaerobic conditions, compared to traditional wet storage. Triangle tests reveal no discernible colour variation between logs that underwent anaerobic storage and the control sample. As a conclusion, despite a mould (Gliocladium solani) frequently observed on logs surface after the storage, the process offers ideal conservation conditions. While overall cost remains the main drawback for using anaerobic storage at large scale, the process can be recommended for high value logs, especially since it has few environmental impacts.