Analysis of long-term light-trap data for Helicoverpa spp. (Lepidoptera : Noctuidae) in Australia: the effect of climate and crop host plants

Regression analyses of a long series of light-trap catches at Narrabri, Australia, were used to describe the seasonal dynamics of Helicoverpa armigera (Hubner). The size of the second generation was significantly related to the size of the first generation, to winter rainfall, which had a positive effect, and to spring rainfall which had a negative effect. These variables accounted for up to 96% of the variation in size of the second generation from year to year. Rainfall and crop hosts were also important for the size of the third generation. The area and tonnage of many potential host crops were significantly correlated with winter rain. When winter rain was omitted from the analysis, the sizes of both the second and third generations could be expressed as a function of the size of the previous generation and of the areas planted to lucerne, sorghum and maize. Lucerne and maize always had positive coefficients and sorghum a negative one. We extended our analysis to catches of H. punctigera (Wallengren), which declines in abundance after the second generation. Winter rain had a positive effect on the sizes of the second and third generations, and rain in spring or early summer had a negative effect. Only the area grown to lucerne had a positive effect on abundance. Forecasts of pest levels from a few months to a few weeks in advance are discussed, along with the improved understanding of the seasonal dynamics of both species and the significance of crops in the management of insecticide resistance for H. armigera.

Microsatellite allele sequencing in population analyses of the South American cactophilic species Drosophila antonietae (Diptera: Drosophilidae)

Drosophila antonietae belongs to the Drosophila buzzatii cluster, a cactophilic group of species naturally endemic to South America. Morphological and genetic analyses indicate that its populations are the most homogenous in the cluster and that the diversity observed is mainly a result of variation within populations. Seven polymorphic microsatellite loci were described for this species and used in the present study to investigate the genetic diversity of natural populations of D. antonietae by both length and sequence variation. The study aimed to understand how homoplasy and null alleles affect inferences about the population history of this species and to obtain an accurate interpretation of population inferences where these loci could be applied. The results provide useful information on the interpretation of genetic data derived from the microsatellite loci described for D. antonietae and on evolutionary aspects of cactophilic Drosophila. Importantly, the results indicate that size homoplasy and null alleles do not represent significant problems for the population genetics analyses because the large amount of variability at microsatellite loci compensate the low frequency of these problems in the populations. (C) 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 100, 573-584.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

Leishmania sp identification by PCR associated with sequencing of target SSU rDNA in paraffin-embedded skin samples stored for more than 30 years

Paraffin-embedded samples commonly stored at educational and research institutions constitute tissues banks for follow-up or epidemiological studies; however, the paraffin inclusion process involves the use of substances that can cause DNA degradation. In this study, a PCR protocol was applied to identify Leishmania strains in 33 paraffin-embedded skin samples of patients with American cutaneous leishmaniasis. DNA was obtained by the phenol-chloroform protocol following paraffin removal and then used in PCR or nested PCR based on the nucleotide sequence of the small subunit ribosomal RNA (SSU rDNA). The amplicons obtained were cloned and sequenced to determine the single nucleotide polymorphism that distinguishes between different Leishmania species or groups. This assay allowed to distinguish organisms belonging to the subgenus Viannia and identify L. (Leishmania) amazonensis and L. (L.) chagasi of the Leishmania subgenus. Of the 33 samples, PCR and nested PCR identified 91% of samples. After sequencing the PCR product of 26 samples, 16 were identified as L. (L.) amazonensis, the other 10 contain organisms belonging to the L. (Viannia) sub-genus. These results open a huge opportunity to study stored samples and promote relevant contributions to epidemiological studies.

Molecular cloning, sequencing, and expression analysis of presenilin cDNA from Schistosoma mansoni

Presenilins (PS) are integral membrane proteins involved, among other functions, in regulated intramembrane proteolysis. In this study, we report the identification and characterization of a complementary DNA from Schistosoma mansoni exhibiting a significant homology to human and nonvertebrate presinilins. S. mansoni contained a 1,485 bp open reading frame encoding a predicted protein of 494 amino acids. Alignment of predicted amino acid sequence of S. mansoni with PS (SmPS) from other species revealed up to 40% similarity shared among the investigated organisms. In addition, phylogenetic analyses demonstrated SmPS being closely related to its orthologues found in Schistosoma japonicum and Caenorhabditis elegans. Expression analysis of SmPS using quantitative real-time PCR revealed that the transcript is up-regulated in the egg stage. We hypothesize that the high level of SmPS in the S. mansoni embryo correlates to an important role during cellular signaling associated to larval development. To our knowledge, this study represents the first attempt to investigate the existence and abundance of PS from a helminth parasite.

Differentiation of field isolates and vaccine strains of infectious laryngotracheitis virus by DNA sequencing

Two different regions of the infected cell protein 4 (ICP4) gene of infectious laryngotracheitis virus (ILTV) were amplified and sequenced for characterization of field isolates and tissue culture-origin (TCO) and chicken embryo-origin (CEO) vaccine strains. Phylogenetic analysis of the two regions showed differences in nucleotide and amino acid sequences between field isolates and attenuated vaccines. The PCR-RFLP results were identical to those obtained by DNA sequencing and validated their use to differentiate ILTV strains. The approach using the sequencing of the two fragments of the ICP4 gene showed to be an efficient and practical procedure to differentiate between field isolates and vaccine strains of ILTV. (C) 2009 Elsevier Ltd. All rights reserved.

Fate of urea nitrogen applied to a banana crop in the wet tropics of Queensland

This paper reports a study in the wet tropics of Queensland on the fate of urea applied to a dry or wet soil surface under banana plants. The transformations of urea were followed in cylindrical microplots (10.3 cm diameter x 23 cm long), a nitrogen (N) balance was conducted in macroplots (3.85 m x 2.0 m) with N-15 labelled urea, and ammonia volatilization was determined with a mass balance micrometeorological method. Most of the urea was hydrolysed within 4 days irrespective of whether the urea was applied onto dry or wet soil. The nitrification rate was slow at the beginning when the soil was dry, but increased greatly after small amounts of rain; in the 9 days after rain 20% of the N applied was converted to nitrate. In the 40 days between urea application and harvesting, the macroplots the banana plants absorbed only 15% of the applied N; at harvest the largest amounts were found in the leaves (3.4%), pseudostem (3.3%) and fruit (2.8%). Only 1% of the applied N was present in the roots. Sixty percent of the applied N was recovered in the soil and 25% was lost from the plant-soil system by either ammonia volatilization, leaching or denitrification. Direct measurements of ammonia volatilization showed that when urea was applied to dry soil, and only small amounts of rain were received, little ammonia was lost (3.2% of applied N). In contrast, when urea was applied onto wet soil, urea hydrolysis occurred immediately, ammonia was volatilized on day zero, and 17.2% of the applied N was lost by the ninth day after that application. In the latter study, although rain fell every day, the extensive canopy of banana plants reduced the rainfall reaching the fertilized area under the bananas to less than half. Thus even though 90 mm of rain fell during the volatilization study, the fertilized area did not receive sufficient water to wash the urea into the soil and prevent ammonia loss. Losses by leaching and denitrification combined amounted to 5% of the applied N.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.