Ergovaline does not alter the severity of ryegrass staggers induced by lolitrem B

AIM: To investigate a possible interaction between lolitrem B and ergovaline by comparing the incidence and severity of ryegrass staggers in sheep grazing ryegrass (Lolium perenne) containing lolitrem B or ryegrass containing both lolitrem B and ergovaline.

METHODS: Ninety lambs, aged approximately 6 months, were grazed on plots of perennial ryegrass infected with either AR98 endophyte (containing lolitrem B), standard endophyte (containing lolitrem B and ergovaline) or no endophyte, for up to 42 days from 2 February 2010. Ten lambs were grazed on three replicate plots per cultivar. Herbage samples were collected for alkaloid analysis and lambs were scored for ryegrass staggers (scores from 0–5) weekly during the study. Any animal which was scored ≥4 was removed from the study.

RESULTS: Concentrations of lolitrem B did not differ between AR98 and standard endophyte-infected pastures during the study period (p=0.26), and ergovaline was present only in standard endophyte pastures. Ryegrass staggers was observed in sheep grazing both the AR98 and standard endophyte plots, with median scores increasing in the third week of the study. Prior to the end of the 42-day grazing period, 22 and 17 animals were removed from the standard endophyte and AR98 plots, respectively, because their staggers scores were ≥4. The cumulative probability of lambs having scores ≥4 did not differ between animals grazing the two pasture types (p=0.41).

CONCLUSIONS AND CLINICAL RELEVANCE: There was no evidence for ergovaline increasing the severity of ryegrass staggers induced by lolitrem B. In situations where the severity of ryegrass staggers appears to be greater than that predicted on the basis of concentrations of lolitrem B, the presence of other tremorgenic alkaloids should be investigated.     

Identification of resistance to Aspergillus flavus infection in cotton germplasm

Natural resistance in cottonseed to Aspergillus flavus infection has not been explored to date. A green fluorescent protein (GFP) expressing A. flavus strain was used to assess the resistance of seed from 35 cotton varieties from Gossypium arboreum, G. barbadense, and G. hirsutum. Mature cotyledons devoid of seed coat were wounded, inoculated, and assessed for innate resistance to A. flavus infection. Of the initial 35 varieties tested, we observed a range of resistance to infection in representatives of all three species. A subset of 15 representatives was further analyzed. Within this group, G. arboreum cultivar A2 186 and G. hirsutum cultivar SA 1582 were most resistant to fungal infection. The most susceptible cultivar in this group was G. hirsutum SA 1595. The remaining 12 representatives tested in the secondary screen (3 G. arboreum, 3 G. barbadense, and 6 G. hirsutum lines) exhibited intermediate resistance. We did not observe any relationship between species and resistance. Within each species, there was a range of responses to fungal infection. Future studies using this methodology to screen additional diploid and tetraploid cotton lines may enable us to identify naturally resistant germplasm that can be used to develop cotton with enhanced resistance to fungal infection.     

Comparison of the Sensitivity of Landscape-fire-succession Models to Variation in Terrain, Fuel Pattern, Climate and Weather

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer & wetter, and warmer & drier) and weather (year-to-year variability) was determined for four existing landscape-fire-succession models (EMBYR, FIRESCAPE, LANDSUM and SEM-LAND) and a new model implemented in the LAMOS modelling shell (LAMOS(DS)). Sensitivity was measured as the variance in area burned explained by each of the four factors, and all of the interactions amongst them, in a standard generalised linear modelling analysis. Modelled area burned was most sensitive to climate and variation in weather, with four models sensitive to each of these factors and three models sensitive to their interaction. Models generally exhibited a trend of increasing area burned from observed, through warmer and wetter, to warmer and drier climates with a 23-fold increase in area burned, on average, from the observed to the warmer, drier climate. Area burned was sensitive to terrain for FIRESCAPE and fuel pattern for EMBYR. These results demonstrate that the models are generally more sensitive to variation in climate and weather as compared with terrain complexity and fuel pattern, although the sensitivity to these latter factors in a small number of models demonstrates the importance of representing key processes. The models that represented fire ignition and spread in a relatively complex fashion were more sensitive to changes in all four factors because they explicitly simulate the processes that link these factors to area burned. The US Government's and the Canadian Government's right to retain a non-exclusive, royalty-free license is acknowledged