Climatic regulation of seed dormancy and emergence of diverse Malva parviflora populations from a Mediterranean-type environment

Malva parviflora L. (Malvaceae) is rapidly becoming a serious weed of Australian farming systems. An understanding of the variability of its seed behaviour is required to enable the development of integrated weed management strategies. Mature M. parviflora seeds were collected from four diverse locations in the Mediterranean-type climatic agricultural region of Western Australia. All of the seeds exhibited physical dormancy at collection; manual scarification or a period of fluctuating summer temperatures (50/20 degrees C or natural) were required to release dormancy. When scarified and germinated soon (1 month) after collection, the majority of seeds were able to germinate over a wide range of temperatures (5-37 degrees C) and had no light requirement. Germination was slower for seeds stored for 2 months than seeds stored for 2 years, suggesting the presence of shallow physiological dormancy. Seed populations from regions with similar annual rainfall exhibited similar dormancy release patterns; seeds from areas of low rainfall (337-344mm) were more responsive to fluctuating temperatures, releasing physical dormancy earlier than those from areas of high rainfall (436-444mm). After 36 months, maximum seedling emergence from soil in the field was 60%, with buried seeds producing 13-34% greater emergence than seeds on the surface. Scanning electron microscopy of the seed coat revealed structural differences in the chalazal region of permeable and impermeable seeds, suggesting the importance of this region in physical dormancy breakdown of M. parviflora seeds. The influence of rainfall during plant growth in determining dormancy release, and hence, germination and emergence timing, must be considered when developing management strategies for M. parviflora.

Diagnosis and Correction of Nutritional Disorders in Ginger

This booklet contains descriptions and photographs of symptoms of deficiencies and toxicities of nutrients, including nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, iron, boron, manganese, zinc, copper and molybdenum, and advice on treatment of affected crops.

Modelling broccoli development, yield and quality

Broccoli is a vegetable crop of increasing importance in Australia, particularly in south-east Queensland and farmers need to maintain a regular supply of good quality broccoli to meet the expanding market. A predictive model of ontogeny, incorporating climatic data including frost risk, would enable farmers to predict harvest maturity date and select appropriate cultivar – sowing date combinations. To develop procedures for predicting ontogeny, yield and quality, field studies using three cultivars, ‘Fiesta’, ‘Greenbelt’ and ‘Marathon’, were sown on eight dates from 11 March to 22 May 1997, and grown under natural and extended (16 h) photoperiods at the University of Queensland, Gatton Campus. Cultivar, rather than the environment, mainly determined head quality attributes of head shape and branching angle. Yield and quality were not influenced by photoperiod. A better understanding of genotype and environmental interactions will help farmers optimise yield and quality, by matching cultivars with time of sowing. The estimated base and optimum temperature for broccoli development were 0°C and 20 °C, respectively, and were consistent across cultivars, but thermal time requirements for phenological intervals were cultivar specific. Differences in thermal time requirement from floral initiation to harvest maturity between cultivars were small and of little importance, but differences in thermal time requirement from emergence to floral initiation were large. Sensitivity to photoperiod and solar radiation was low in the three cultivars used. This research has produced models to assist broccoli farmers in crop scheduling and cultivar selection in south-east Queensland.

Towards developing reliable models of leaf area on grapevines (Vitis vinifera L.)

A field study in three vineyards in southern Queensland (Australia) was carried out to develop predictive models for individual leaf area and shoot leaf area of two cultivars (Cabernet Sauvignon and Shiraz) of grapevines (Vitis Vinifera L.). Digital image analysis was used to measure leaf vein length and leaf area. Stepwise regressions of untransformed and transformed models consisting of up to six predictor variables for leaf area and three predictor variables for shoot leaf area were carried out to obtain the most efficient models. High correlation coefficients were found for log10 transformed individual leaf and shoot leaf area models. The significance of predictor variables in the models varied across vineyards and cultivars, demonstrating the discontinuous and heterogeneous nature of vineyards. The application of this work in a grapevine modeling environment and in a dynamic vineyard management context are discussed. Sample sizes for quantification of individual leaf areas and areas of leaves on shoots are proposed based on target margins of errors of sampled data.