Interactions between genes involved in growth and muscularity in pigs: IGF-2, myostatin, ryanodine receptor 1, and melanocortin-4 receptor

In the swine breeding industry, two economical traits are of particular importance in sires, namely, muscle growth and average daily gain (ADG). These traits are quantitative, which implies that they are under the control of multiple genes. Mutations in these genes, associated with either muscularity or growth, are useful quantitative trait nucleotides (QTN) for unraveling genetic variation of these traits and can be used in marker-assisted selection. Until now, QTN involved in muscle growth and/or ADG in pigs were identified in porcine ryanodine receptor 1 (RYR1), insulin-like growth factor-2 (IGF-2), and melanocortin-4 receptor (MC4R). Recently, a fourth possible QTN was found in porcine myostatin (MSTN). All four QTN have an influence on muscle growth and/or somatic growth, so an influence of one mutation on one or more of the other mutations should not be excluded. However, although the polymorphisms in the RYR1 and the MC4R gene affect the function of the respective protein, the polymorphisms of the IGF-2 and MSTN gene influence the mRNA expression of the respective gene. Therefore, this study investigated possible interactions between the genotypes of MSTN, IGF-2, and MC4R (population 1) or the RYR1, IGF-2, and MSTN QTN (population 2) on IGF-2 and MSTN expression in different muscle types in pigs. In both skeletal muscle and heart muscle growth, the IGF-2:MSTN ratio seems to play an important role. Also, the RYR1 genotype had a significant effect on IGF-2 expression in m. longissimus dorsi. No effect of the MC4R QTN could be seen.     

Expert judgement in a risk assessment model for Salmonella spp. in pork: The performance of different weighting schemes

A structured expert judgement study was carried out in order to obtain input parameters for a quantitative microbial risk assessment (QMRA) model. This model aimed to estimate the risk of human Salmonella infections associated with the consumption of minced pork meat. Judgements of 11 experts were used to derive subjective probability density functions (PDFs) to quantify the uncertainty on the model input parameters.The performance of experts as probability assessors was measured by the experts’ ability to correctly and precisely provide estimates for a set of seed variables (=variables from the experts’ area of expertise for which the true values were known to the analyst). Subsequently different weighting schemes or “decision makers” (DMs) were applied using Cooke's classical model in order to obtain combined PDFs as a weighted linear combination of the expert's individual PDFs.The aim of this study was to compare the performance of four DMs namely the equal weight DM (each expert's opinion received equal weight), the user weight DM (weights are determined by the expert's self-perceived level of expertise) and two performance-based DMs: the global weight DM and the item weight DM. Weights in the performance-based DMs were calculated based on the expert's calibration and information performance as measured on the set of seed variables.The item weight DM obtained the highest performance with a calibration score of 0.62 and an information score of 0.52, as compared to the other DMs. The weights of the performance-based DMs outperformed those of the best expert in the panel. The correlation between the scores for self-rating of expertise and the weights based on the experts’ performance on the calibration variables was low and not significant (r = 0.37, p = 0.13).The applied classical model provided a rational basis to use the combined distributions obtained by the item weight DM as input in the QMRA model since this DM yielded generally more informative distributions for the variables of interest than those obtained by the equal weight and user weight DM. Attention should be paid to find adequate and relevant seed variables, since this is important for the validation of the results of the weighting scheme.     

Optimisation of a semiochemical slow-release alginate formulation attractive towards Aphidius ervi Haliday parasitoids

BACKGROUND: Optimisation of alginate formulations is described in order to develop semiochemical (E-β-farnesene and E-β-caryophyllene) slow-release devices in biological control approaches by attracting predators and parasitoids of aphids. Various formulation criteria were optimised with respect to semiochemical encapsulation capacity. Moreover, the optimised formulation was characterised by texturometry and confocal microscopy. The slow-release rates of semiochemicals were calculated in laboratory controlled conditions. The attractiveness of semiochemical formulations towards Aphidius ervi was demonstrated by olfactometry. RESULTS: Two major parameters were highlighted in encapsulation optimisation: the type of alginate (Sigma L) and the type of crosslinker ion (Ca²⁺). Other formulation parameters were optimised: ionic strength (0.5 M), Ca²⁺ (0.2 M) and alginate (1.5%) concentrations and the maturation time of beads in CaCl₂ solution (48 h). After physical characterisation of beads, semiochemical slow-release measurements showed that alginate formulations were efficient sesquiterpene releasers, with 503 µg of E-β-farnesene and 1791 µg of E-β-caryophyllene totally released in 35 days. The efficiency of semiochemical alginate beads as attractants for female parasitoids was demonstrated, with high percentages of attraction for semiochemical odours (88 and 90% for E-β-farnesene and E-β-caryophyllene respectively) and significant statistical results. CONCLUSION: Semiochemical alginate beads can be considered as efficient slow-release systems in biological control. These formulations could be very useful to attract aphid parasitoids on crop fields. Copyright © 2011 Society of Chemical Industry     

Regional simulation of long-term organic carbon stock changes in cropland soils using the DNDC model: 2. Scenario analysis of management options

The development of successful agricultural policies in response to the Kyoto Protocol is aided by the identification of regions where the effects of soil organic carbon (SOC) sequestration measures can be maximized. We describe a modelling approach which incorporates a spatial analysis of the results from regional simulation under different management alternatives. SOC stock changes in Flemish cropland soils, simulated with the DNDC model, were previously fitted to a large data set of SOC measurements for the period 1990–2000. Using the results of this study, simulations with DNDC of SOC stock changes during the period 2006–2012 including the Kyoto commitment period were carried out at the community level for a business‐as‐usual (BAU) scenario and seven alternative agricultural management options for SOC sequestration. The baseline SOC stock decreased during that period by 0.15 t OC ha⁻¹ year⁻¹ compared with 0.48 t OC ha⁻¹ year⁻¹ in the 1990s. All alternative scenarios resulted in net SOC storage compared with the BAU scenario, but none of the individual scenarios were able to increase the average absolute SOC stock. Overall, spatial variability in SOC storage for the selected management options was strongly dependent on the current distribution of crops and associated management. The modelling approach used in this study provides a case study in regional scale modelling of SOC sequestration and is applicable to other regions in Europe with comparable intensive agriculture.     

Research on some characters in black currant progenies

Populations derived from selfs and crosses of a small number of black currant varieties with the variety Consort were analysed for various characters, viz. vigour, number of flowers, flowering time, ripening time, fruit-set, strig-length and berry size. Flowering began in the third growing year. In the next year the bushes could be assessed to best advantage. The results of the evaluations are:

1. 1.
   The vigour of the selfed progenies showed, with the exception of Consort, a clear inbreeding depression as compared with the hybrid populations.     

The free-water pond under a trickle source: A field test of existing theories

  The size of the free-water ponds under drippers is an important field characteristic of trickle irrigation. Here we review four existing analytical theories that purport to describe 3-D infiltration. We show how they can be used to predict the extent of the pond from basic soil parameters, and the dripper discharge rate. Via a numerical example it is shown that the different theories give significantly different free-water pond radii, especially for high drip discharge rates when the flow is dominated by gravity. We then describe field experiments that were carried out to permit a comparison of the measured and predicted values using independently-measured soil parameters. This test of the different theories was conducted on a loamy soil. Raats' (1971) solution gave the best estimates of the free-water pond radius, across the range of discharge rates. The free-water pond radius, a determinant of the lateral spread away from the dripper, was found to vary only weakly with drip discharge in the range of practical applications. Consequences for management are discussed. Received: 24 September 1995     

Influence of subsoiling on the yield of sugar-beets

Root growth and yield of sugar-beets were studied on two Belgian silt loam soils and one alluvial clay soil after subsoiling to a depth of 60 cm. The removal of the plough sole layer, characterized by penetration resistances > 3 MPa, resulted in an increase of the root quantity and a higher availability of water. As a consequence, a mean yield increase of 5 tons/ha for sugar-beets was found on the subsoiled plots in drier years. The yield increase was accompanied by a higher uptake of nutritive elements.     

Development and comparison of four real-time polymerase chain reaction systems for specific detection and quantification of Zea mays L

Four real-time polymerase chain reaction systems aiming at the specific detection and quantification of maize DNA are described. They have been developed in four independent laboratories targeting different maize sequences, i.e., alcohol dehydrogenase (Adh1), high mobility group protein (hmga), invertase A (ivr1), and zein, respectively. They were all fully specific, showing a very similar quantification accuracy along a number of distantly related maize cultivars and being either single or low copy number genes. They were highly sensitive and exhibited limits of quantification below 100 maize genomic copies. In consequence, they are considered suitable for use as maize specific endogenous reference genes in DNA analyses, including GMO quantitative tests.     

Regional simulation of long-term organic carbon stock changes in cropland soils using the DNDC model: 1. Large-scale model validation against a spatially explicit data set

Because of the large spatial and temporal variability of soil organic carbon (SOC) dynamics, a modelling approach is crucial in detailed regional analyses. Several estimates of regional scale SOC sequestration potential have been made using dynamic soil organic matter (SOM) models which have been linked to spatial databases contained within a Geographic Information System. In all these previous studies, a large‐scale model validation, which provides information on the general model performance for the study area under concern, was impossible because of lack of data. A data set of over 190 000 SOC measurements, grouped as means per community and covering the period 1989–2000 was available for Flanders in northern Belgium. In order to validate the DNDC model at a large spatial scale, we used this data set along with detailed pH, soil texture and crop areas which were all available at the municipality scale to simulate SOC stocks for the entire study area during the period 1990–2000. A minor adjustment of the initial distribution of SOC in the model's SOC pool was necessary to fit the simulated SOC stock changes to the measured decrease of −475 kg OC ha⁻¹ year⁻¹ (0–30 cm). Although DNDC was able to simulate the SOC stock changes well for the whole study area, the simulated decrease in the SOC stocks was overestimated for communities predominantly having sandy textures and underestimated for communities with silt loam to silt textures. This study also urges caution with the application of SOM models at regional scales after limited validation or calibration at the field scale as these do not guarantee good simulation of spatial variation in SOC changes.