PCR-based detection of Xanthomonas campestris pathovars in Brassica seed

Xanthomonas campestris is a seedborne bacterium that causes black rot of crucifers. Substantial crop losses may result from the rapid spread of the bacteria under favourable conditions, especially those occurring during seedling production. A PCR-based method has been developed for the rapid and sensitive detection of the pathovars of X. campestris that affect crucifers. Primers were designed to specifically amplify a 619 bp fragment of the hrpF gene from X. campestris . Amplification products were not detected from other Xanthomonas species, or from other pathogenic or epiphytic bacteria occurring on these plants. To avoid false-negative results arising from the presence of amplification inhibitors in plant extracts, primers targeting a 360 bp section of the internal transcribed spacer (ITS) region from Brassica spp. were included in a multiplex PCR. The assay readily detected X. campestris pv. campestris infections in diseased plants and from bacterial colonies isolated on growth media, and was more sensitive and specific than traditional plating methods and a commercially available ELISA. A seed-washing protocol was optimized to allow the detection of a single artificially infected seed among 10 000 healthy seeds using the multiplex PCR.     

Evaluation of optical sensor measurements of canopy reflectance and of leaf flavonols and chlorophyll contents to assess crop nitrogen status of muskmelon

Nitrogen losses from intensive vegetal production systems are commonly associated with contamination of water bodies. Sustainable and optimal economic N management requires correct and timely on-farm assessment of crop N status to detect N deficiency or excess. Optical sensors are promising tools for the assessment of crop N status throughout a crop or at critical times. We evaluated optical sensor measurement of canopy reflectance and of leaf flavonols and chlorophyll contents to assess crop N status weekly throughout a muskmelon crop. The Crop Circle ACS 470 was used for reflectance measurement, the SPAD 502 for leaf chlorophyll, and the DUALEX 4 Scientific for leaf chlorophyll and flavonols. Four indices of canopy reflectance (NDVI, GNDVI, RVI, GVI), leaf flavonols and chlorophyll contents and the nitrogen balance index (NBI), the ratio of chlorophyll to flavonols contents, were linearly related to crop N content and to crop Nitrogen Nutrition Index (NNI) throughout most of the crop. NBI most accurately predicted crop N status; in five consecutive weekly measurements, R² values were 0.80–0.95. For NDVI during the same period, R² values were 0.76–0.87 in the first three measurements but R² values in the last two measurements were 0.39–0.45. Similar relationships were found with the three other reflectance indices. Generally, the relationships with NNI were equal to or slightly better than those with crop N content. These optical sensor measurements provided (i) estimation of crop N content in the range 1.5–4.5%, and (ii) an assessment of whether crop N content was sufficient or excessive for optimal crop growth for NNI ranges of 0.8–2.0. Composite equations that integrated the relationships between successive measurements with the optical sensors and crop N content or NNI for periods of ≥2 weeks (often 2–3 weeks) were derived for most indices/parameters. Overall, these results demonstrated the potential for the use of these optical sensor measurements for on-farm monitoring of crop N status in muskmelon.     

Analysing disease incidence data from designed experiments by generalized linear mixed models

As a result of aggregation or clustering of sampling units, disease incidence data from designed experiments frequently show overdispersion relative to the binomial distribution. This paper discusses generalized linear mixed models (GLMM) suitable for analysing overdispersed disease incidence data. The methods are exemplified using data from a randomized complete block experiment on the incidence of downy mildew ( Plasmopara viticola ) of grape ( Vitis lambrusca ). Hints are given regarding implementation of the methods using the %GLIMMIX macro for the SAS system.     

An Intermediate-Technology Pattern Matching Model of Veterinary Diagnosis

An intermediate-technology pattern matching model and decision support system for veterinary diagnosis is described. Six diseases of cattle occurring in the tropics are used to illustrate the model. The pattern matching model is composed of a series of transparent overlays and a template. Each transparent overlay represents a sign state and contains sign frequency information for the diseases on the template. By superimposing multiple transparent overlays upon the disease template, a ranked list of differential diagnoses can be obtained. Ranking is by summation of disease sign frequencies. Modifications to accommodate observational uncertainty are presented. Disease prevalences can be represented in the model.     

Spatial patterns of spear rot in oil palm plantations in Surinam

As the aetiology of spear rot of oil palm is unknown, indirect methods were applied to study its putative infectiousness by analysing data from commercial oil palm plantations in Surinam. Geostatistics and gradient analysis were used to examine the spatial variation of spear rot disease in 13 blocks at two plantations. In two blocks, which had low spear rot incidence initially, the variogram indicated that affected trees were not spatially related, suggesting that infection came from various distant sources. Later, the semivariances in one of these two blocks and in seven others, calculated for successive dates, showed a linear increase with distance. The variograms for four blocks showed a nonlinear increase in variance. Over the years, the variograms suggested that the variation in spear rot was anisotropic, with more spatial dependence in a westerly direction. Classical analysis of disease gradients over time confirmed that there was a preferential direction of disease spread. The data are compatible with the following hypotheses: (1) spear rot is an infectious disease; (2) the causal agent of spear rot is vector-borne, the vector being displaceable by wind; and (3) spear rot appears in two distinct phases, phase 1 being characterized by few randomly scattered trees, phase 2 by focal spread of disease starting from such scattered trees. The trigger of the change from phase 1 to phase 2 remains unknown.     

Identification of feline polycystic kidney disease mutation using fret probes and melting curve analysis

We developed and validated a real-time polymerase chain reaction (PCR) assay using fluorescent hybridization probes and melting curve analysis to identify the PKD1 exon 29 (C → A) mutation, which is implicated in polycystic kidney disease of cats. DNA was isolated from peripheral blood of 20 Persian cats. The employ of the new real-time PCR and melting curve analysis in these samples indicated that 13 cats (65%) were wild type homozygotes and seven cats (35%) were heterozygotes. Both PCR-RFLP and sequencing procedures were in full agreement with real-time PCR test results. Sequence analysis showed that the mutant gene had the expected base change compared to the wild type gene.The new procedure is not only very reliable but also faster than the techniques currently applied for diagnosis of the mutation.