Effects of foliar application of potassium nitrate on suppression of Alternaria leaf blight of cotton (Gossypium hirsutum) in northern Australia

Alternaria leaf blight is the most prevalent disease of cotton in northern Australia. A trial was conducted at Katherine Research Station, Northern Territory, Australia, to determine the effects of foliar application of potassium nitrate (KNO3) on the suppression of Alternaria leaf blight of cotton. Disease incidence, severity and leaf shedding were assessed at the bottom (1-7 nodes), middle (8-14 nodes) and the top (15+ nodes) of plants at weekly intervals from 7 July to 22 September 2004. Disease incidence, severity and shedding at the middle canopy level were significantly higher for all treatments than those from bottom and top canopies. Foliar KNO3, applied at 13 kg/ha, significantly (P < 0.05) reduced the mean disease incidence, severity and leaf shedding assessed during the trial period. KNO 3 significantly (P < 0.001) reduced the disease severity and leaf shedding at the middle canopy level. Almost all leaves in the middle canopy became infected in the first week of July in contrast to infection levels of 50-65% at the bottom and top of the canopy. Disease severity and leaf shedding in the middle canopy were significantly (P < 0.05) lower in KNO 3-treated plots than the control plots from the second and third weeks of July to the second and third weeks of August. This study demonstrates that foliar application of KNO3 may be effective in reducing the effect of Alternaria leaf blight of cotton in northern Australia.

Isolation and characterization of novel microsatellite markers and their application for diversity assessment in cultivated groundnut (Arachis hypogaea)

Background: Cultivated peanut or groundnut (Arachis hypogaea L.) is the fourth most important oilseed crop in the world, grown mainly in tropical, subtropical and warm temperate climates. Due to its origin through a single and recent polyploidization event, followed by successive selection during breeding efforts, cultivated groundnut has a limited genetic background. In such species, microsatellite or simple sequence repeat (SSR) markers are very informative and useful for breeding applications. The low level of polymorphism in cultivated germplasm, however, warrants a need of larger number of polymorphic microsatellite markers for cultivated groundnut. Results: A microsatellite- enriched library was constructed from the genotype TMV2. Sequencing of 720 putative SSR-positive clones from a total of 3,072 provided 490 SSRs. 71.2% of these SSRs were perfect type, 13.1% were imperfect and 15.7% were compound. Among these SSRs, the GT/CA repeat motifs were the most common (37.6%) followed by GA/CT repeat motifs (25.9%). The primer pairs could be designed for a total of 170 SSRs and were optimized initially on two genotypes. 104 (61.2%) primer pairs yielded scorable amplicon and 46 (44.2%) primers showed polymorphism among 32 cultivated groundnut genotypes. The polymorphic SSR markers detected 2 to 5 alleles with an average of 2.44 per locus. The polymorphic information content (PIC) value for these markers varied from 0.12 to 0.75 with an average of 0.46. Based on 112 alleles obtained by 46 markers, a phenogram was constructed to understand the relationships among the 32 genotypes. Majority of the genotypes representing subspecies hypogaea were grouped together in one cluster, while the genotypes belonging to subspecies fastigiata were grouped mainly under two clusters. Conclusion. Newly developed set of 104 markers extends the repertoire of SSR markers for cultivated groundnut. These markers showed a good level of PIC value in cultivated germplasm and therefore would be very useful for germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships in cultivated groundnut as well as related Arachis species.

No-tillage and nitrogen application affects the decomposition of 15N-labelled wheat straw and the levels of mineral nitrogen and organic carbon in a Vertisol

No-tillage (NT) practice, where straw is retained on the soil surface, is increasingly being used in cereal cropping systems in Australia and elsewhere. Compared to conventional tillage (CT), where straw is mixed with the ploughed soil, NT practice may reduce straw decomposition, increase nitrogen immobilisation and increase organic carbon in the soil. This study examined 15N-labelled wheat straw (stubble) decomposition in four treatments (NT v. CT, with N rates of 0 and 75 kg/ha.year) and assessed the tillage and fertiliser N effects on mineral N and organic C and N levels over a 10-year period in a field experiment. NT practice decreased the rate of straw decomposition while fertiliser N application increased it. However, there was no tillage practice x N interaction. The mean residence time of the straw N in soil was more than twice as long under the NT (1.2 years) as compared to the CT practice (0.5 years). In comparison, differences in mean residence time due to N fertiliser treatment were small. However, tillage had generally very little effect on either the amounts of mineral N at sowing or soil organic C (and N) over the study period. While application of N fertiliser increased mineral N, it had very little effect on organic C over a 10-year period. Relatively rapid decomposition of straw and short mean residence time of straw N in a Vertisol is likely to have very little long-term effect on N immobilisation and organic C level in an annual cereal cropping system in a subtropical, semiarid environment. Thus, changing the tillage practice from CT to NT may not necessitate additional N requirement unless use is made of additional stored water in the soil or mineral N loss due to increased leaching is compensated for in N supply to crops.

Refined Global Analysis of Bemisia tabaci (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae) Mitochondrial Cytochrome Oxidase 1 to Identify Species Level Genetic Boundaries.

Identifying species boundaries within morphologically indistinguishable cryptic species complexes is often contentious. For the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae), the lack of a clear understanding about the genetic limits of the numerous genetic groups and biotypes so far identified has resulted in a lack of consistency in the application of the terms, the approaches use to apply them and in our understanding of what genetic structure within B. tabaci means. Our response has been to use mitochondrial gene cytochrome oxidase one to consider how to clearly and consistently define genetic separation. Using Bayesian phylogenetic analysis and analysis of sequence pairwise divergence we found a considerably higher to number of genetic groups than had been previously determined with two breaks in the distribution, one at 11% and another at 3.5%. At >11% divergence, 11 distinct groups were resolved, whereas at >3.5% divergence 24 groups were identified. Consensus sequences for each of these groups were determined and were shown to be useful in the correct assignment of sequences of unknown origin. The 3.5% divergence bound is consistent with species level separations in other insect taxa and Suggests that B. tabaci is it cryptic species composed of at least 24 distinct species. We further show that the placement of Bemesia atriplex (Froggatt) within the B. tabaci in, group adds further weight to the argument for species level separation within B. tabaci. This new analysis, which constructs consensus sequences and uses these its a standard against which unknown sequences call be compared, provides for the first time it consistent means of identifying the genetic hounds of each species with it high degree of certainty.

Application of a model to assess aflatoxin risk in peanuts.

When exposed to hot (22-35 degrees C) and dry climatic conditions in the field during the final 4-6 weeks of pod filling, peanuts (Arachis hypogaea L.) can accumulate highly carcinogenic and immuno-suppressing aflatoxins. Forecasting of the risk posed by these conditions can assist in minimizing pre-harvest contamination. A model was therefore developed as part of the Agricultural Production Systems Simulator (APSIM) peanut module, which calculated an aflatoxin risk index (ARI) using four temperature response functions when fractional available soil water was <0.20 and the crop was in the last 0.40 of the pod-filling phase. ARI explained 0.95 (P <= 0.05) of the variation in aflatoxin contamination, which varied from 0 to c. 800 mu g/kg in 17 large-scale sowings in tropical and four sowings in sub-tropical environments carried out in Australia between 13 November and 16 December 2007. ARI also explained 0.96 (P <= 0.01) of the variation in the proportion of aflatoxin-contaminated loads (>15 mu g/kg) of peanuts in the Kingaroy region of Australia during the period between the 1998/99 and 2007/08 seasons. Simulation of ARI using historical climatic data from 1890 to 2007 indicated a three-fold increase in its value since 1980 compared to the entire previous period. The increase was associated with increases in ambient temperature and decreases in rainfall. To facilitate routine monitoring of aflatoxin risk by growers in near real time, a web interface of the model was also developed. The ARI predicted using this interface for eight growers correlated significantly with the level of contamination in crops (r=095, P <= 0.01). These results suggest that ARI simulated by the model is a reliable indicator of aflatoxin contamination that can be used in aflatoxin research as well as a decision-support tool to monitor pre-harvest aflatoxin risk in peanuts.

Identifying risk-efficient strategies using stochastic frontier analysis and simulation: An application to irrigated cropping in Australia

In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.