Effect of pea bacterial blight (Pseudomonas syringae pv. pisi) on the yield of spring sown combining peas (Pisum sativum)

Field trials to examine the effect of pea bacterial blight (Pseudomonas syringae pv. pisi) (Psp) on the yield of combining peas were carried out at five sites (HRI Wellesbourne, ADAS Rosemaund, ADAS Terrington, PGRO, SASA East Craigs) in the UK in 1990, 1991 and 1992. Healthy seed, cv. Solara, and seed naturally infected with Psp Race 2 was sown in large plots (c. 200 m²) in the open or under nets to prevent bird damage by pigeons. Despite relatively low disease severity levels (< 15% leaf area) and separation by at least 12 m of cv. Consort (resistant to Race 2) between plots there was considerable spread of disease into plots sown with healthy seed. Regression analysis demonstrated a significant relationship between yield and disease. Of the disease measurements examined, disease severity on the leaves (stipules) at growth stage 208 was found to be the best predictor of yield. A model containing environmental and bird damage terms, in addition to disease, suggested that a yield loss of 0.98 t/ha would be expected for a disease severity score of 1, equivalent to 5% leaf area affected, at growth stage 208.     

Aspects Affecting Biosynthesis and Biotransformation of Secondary Metabolites in Plant Cell Cultures

Abstract

Biosensors are useful analytical devices that can be integrated with on-line process monitoring schemes. In this article, the principles and applications of these devices for bioprocess monitoring are considered. Several different types of biosensors are described, and the applications and limitations of flow injection analysis (FIA) for these applications are discussed. It is hoped that the background provided here can be useful to researchers in this area.     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel

The purpose of this article is to compare Principal Component Analysis (PCA) and a much less used method, i.e. MCA (Multiple Correspondence Analysis) with data being first changed into membership values to fuzzy space windows. For such a comparison, data from an experimental study about turning the steering wheel is used. In a didactic perspective, this article only considers one multidimensional signal with 5 components: 3 linked to the steering wheel angle and hand positions and 2 to hand effort variables. A discussion weighs out the pros and the cons of both methods with criteria such as the possibility to show complex relational phenomena, the analysis/computing time or the information loss inherent to the averaging stage (in the perspective to analyze several hundreds of large multidimensional signals).     

Expression patterns and association analysis of the porcine DHX58 gene

RIG-1 signalling is responsible for the detection of cytoplasmic viral RNA molecules. DEXH (Asp-Glu-X-His) box polypeptide 58 (encoded by DHX58) is a negative regulator of the RIG-1 signalling pathway. In human, the DHX58 gene can be upregulated and can inhibit the RIG-1 signalling pathway during viral infection. In this study, porcine DHX58 gene expression patterns were studied. According to our results, the porcine DHX58 gene was upregulated not only by the stimulation of Poly I:C but also by the stimulation of 1ipopolysaccharides (LPS). One polymorphism (g.4919G>C), detected in the ninth intron, was significantly associated with some blood parameters including the red cell distribution width of 1-day-old pigs and white blood cell counts, lymphocyte absolute counts, and platelet distribution width of 17-day-old pigs (P < 0.05). Moreover, the individuals with the genotype GG have a significantly higher mean white blood cell count than individuals with genotype CC or GC (P < 0.05). Our study indicates that DHX58 is an important gene that is associated with the immune response in swine.     

Determination of adenosine triphosphate in human semen to estimate the fertilizing potential and to quantify sperm antibodies

The measurement of the ATP content of fresh semen is as accurate as the estimation of sperm motility by conventional methods in discriminating between semen of fertile versus subfertile men. The ATP content of frozen thawed donor semen is correlated with the probability of conception per cycle of insemination. Exact quantification of cytotoxic sperm antibodies in serum is possible with the adenosine-triphosphate-release-cytotoxicity test, since measurement is free of the bias of microscopic examination. The procedure has been simplified by testing only one serum dilution and calculating the ‘sperm toxicity index’.     

Some New Aspects of 2 × 2 Table Measures and Their Applications

The paper deals with the analysis of 2 × 2 table measures and describes several new possibilities for applying them. An estimate is given for HELLMICH's asymmetric K-measure and a possible extension of the contingency concept in a special 2×2 case is presented. The concept introduced and the recommended computer application of the 2×2 table measures is supported by new results obtained for the relationship between jaw joint pains and noises examined earlier by F. SCHMID and C. ZSCHEGE. With a larger number of observations the opportunity arises for a deeper analysis of this dental problem using path analysis. The plan of evaluation and the conncetion between the variables examined is illustrated by a path-diagram. The association tables determined on the basis of the (C) values introduced during the examination of jaw joint disturbances using association analysis draw attention to the special role of the left side of mastication. The paper raises ideas for further generalisations and indicates where further research is needed.