Genetic erosion and changes in distribution of sorghum (Sorghum bicolor L. (Moench)) landraces in north-eastern Ethiopia

Ethiopia is believed to be the centre of origin and domestication for sorghum, where sorghum remains one of the main staple crops. Loss of biodiversity is occurring at an alarming rate in Ethiopia and crops, including sorghum, have long been recognized as vulnerable to genetic erosion. A major collection of sorghum germplasm was made in 1973 by Gebrekidan and Ejeta from north-eastern Ethiopia. A new collection of landraces was made in 2003, and these were field evaluated at Sirinka in 2004 along with representative samples from the 1973 collection. Farmer surveys and soil and climate surveys were also performed. Preliminary analysis demonstrated that some important landraces have disappeared either locally or regionally in the past 30 years and many other landraces have become marginalized. Landraces which are less preferred in terms of agronomic value and end use, and introductions, have become increasingly important. Late maturing landraces were found to be particularly vulnerable, with a number disappearing altogether. Farmers have become more risk averse, and factors such as declining soil fertility, more frequent drought and unreliable rainfall, and increased pest infestation have contributed to a change in farmer landrace selection. Data are presented on the variability and unique characters of some of the Ethiopian landraces, and implications for conservation are discussed.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Defining and predicting the 'break of the season' for north-east Queensland grazing areas

For pasture growth in the semi-arid tropics of north-east Australia, where up to 80% of annual rainfall occurs between December and March, the timing and distribution of rainfall events is often more important than the total amount. In particular, the timing of the 'green break of the season' (GBOS) at the end of the dry season, when new pasture growth becomes available as forage and a live-weight gain is measured in cattle, affects several important management decisions that prevent overgrazing and pasture degradation. Currently, beef producers in the region use a GBOS rule based on rainfall (e. g. 40mm of rain over three days by 1 December) to define the event and make their management decisions. A survey of 16 beef producers in north-east Queensland shows three quarters of respondents use a rainfall amount that occurs in only half or less than half of all years at their location. In addition, only half the producers expect the GBOS to occur within two weeks of the median date calculated by the CSIRO plant growth days model GRIM. This result suggests that in the producer rules, either the rainfall quantity or the period of time over which the rain is expected, is unrealistic. Despite only 37% of beef producers indicating that they use a southern oscillation index (SOI) forecast in their decisions, cross validated LEPS (linear error in probability space) analyses showed both the average 3 month July-September SOI and the 2 month August-September SOI have significant forecast skill in predicting the probability of both the amount of wet season rainfall and the timing of the GBOS. The communication and implementation of a rigorous and realistic definition of the GBOS, and the likely impacts of anthropogenic climate change on the region are discussed in the context of the sustainable management of northern Australian rangelands.

Multilevel load frequency control (a perturbational approach)

A two-level control scheme for the load frequency control of a multi-area power system utilizing certain possible beneficial aspects of interconnections is described in this paper. The problem is identified as the determination of the necessary equivalent perturbation on the control distribution matrix to provide the corrective control.

On the breakdown of the most probable distribution for mayer clusters

We present an analysis of the breakdown of the most probable approximation to the Mayer cluster size distribution for clusters of size comparable to the size of the system. This failure is illustrated by considering an ideal Bose gas for which exact volume dependent reducible cluster integrals are available.

The potential geographic distribution of the invasive weed Senna obtusifolia in Australia

Senna obtusifolia (sicklepod) is an invasive weed of northern Australia, where it significantly impacts agricultural productivity and alters natural ecosystem structure and function. Although currently restricted to northern regions, the potential for S. obtusifolia to spread south is not known. Using the eco-climatic model CLIMEX, this study simulated the potential geographic distribution of S. obtusifolia in Australia under two scenarios. Model parameters for both scenarios were derived from the distribution of S. obtusifolia throughout North and Central America. The first scenario used these base model parameters to predict the distribution of S. obtusifolia in Australia, whilst the second model predicted the distribution of a cold susceptible S. obtusifolia ecotype that is reported to occur in the USA. Both models predicted the potential for an extensive S. obtusifolia distribution, with the first model indicating suitable climatic conditions occurring predominantly in coastal regions from the Northern Territory, to far north Queensland and into northern Victoria. The cold susceptible ecotype displayed a comparatively reduced distribution in the southern parts of Australia, where inappropriate temperatures, a lack of thermal accumulation and cold stress restrict the invasion south to the coastal regions of central New South Wales. The extent of the predicted distribution of both ecotypes of S. obtusifolia reinforces the need for strategic management at a national scale.

Is the distribution of Fiji leaf gall in Australian sugarcane explained by variation in the vector Perkinsiella saccharicida?

Fiji leaf gall (FLG) is an important virally induced disease in Australian sugarcane. It is confined to southern canegrowing areas, despite its vector, the delphacid planthopper Perkinsiella saccharicida, occurring in all canegrowing areas of Queensland and New South Wales. This disparity between distributions could be a result of successful containment of the disease through quarantine and/or geographical barriers, or because northern Queensland populations of Perkinsiella may be poorer vectors of the disease. These hypotheses were first tested by investigating variation in the ITS2 region of the rDNA fragment among eastern Australian and overseas populations of Perkinsiella. The ITS2 sequences of the Western Australian P. thompsoni and the Fijian P. vitiensis were distinguishable from those of P. saccharicida and there was no significant variation among the 26 P. saccharicida populations. Reciprocal crosses of a northern Queensland and a southern Queensland population of P. saccharicida were fertile, so they may well be conspecific. Single vector transmission experiments showed that a population of P. saccharicida from northern Queensland had a higher vector competency than either of two southern Queensland populations. The frequency of virus acquisition in the vector populations was demonstrated to be important in the vector competency of the planthopper. The proportion of infected vectors that transmitted the virus to plants was not significantly different among the populations tested. This study shows that the absence of FLG from northern Queensland is not due to a lack of vector competency of the northern population of P. saccharicida.

The distribution and spread of citrus canker in Emerald, Australia

Citrus canker is a disease of citrus and closely related species, caused by the bacterium Xanthomonas citri subsp. citri. This disease, previously exotic to Australia, was detected on a single farm [infested premise-1, (IP1). IP is the terminology used in official biosecurity protocols to describe a locality at which an exotic plant pest has been confirmed or is presumed to exist. IP are numbered sequentially as they are detected] in Emerald, Queensland in July 2004. During the following 10 months the disease was subsequently detected on two other farms (IP2 and IP3) within the same area and studies indicated the disease first occurred on IP1 and spread to IP2 and IP3. The oldest, naturally infected plant tissue observed on any of these farms indicated the disease was present on IP1 for several months before detection and established on IP2 and IP3 during the second quarter (i.e. autumn) 2004. Transect studies on some IP1 blocks showed disease incidences ranged between 52 and 100% (trees infected). This contrasted to very low disease incidence, less than 4% of trees within a block, on IP2 and IP3. The mechanisms proposed for disease spread within blocks include weather-assisted dispersal of the bacterium (e.g. wind-driven rain) and movement of contaminated farm equipment, in particular by pivot irrigator towers via mechanical damage in combination with abundant water. Spread between blocks on IP2 was attributed to movement of contaminated farm equipment and/or people. Epidemiology results suggest: (i) successive surveillance rounds increase the likelihood of disease detection; (ii) surveillance sensitivity is affected by tree size; and (iii) individual destruction zones (for the purpose of eradication) could be determined using disease incidence and severity data rather than a predefined set area.