Time filter

Source Type

Indooroopilly, Australia

Basnayake J.,Sugar Research Australia | Jackson P.A.,CSIRO | Inman-Bamber N.G.,Crop Science Consulting | Lakshmanan P.,Sugar Research Australia Ltd
Journal of Experimental Botany

Stomatal conductance (g s) and canopy temperature have been used to estimate plant water status in many crops. The behaviour of g s in sugarcane indicates that the internal leaf water status is controlled by regular opening and closing of stomata. A large number of g s measurements obtained across varying moisture regimes, locations, and crop cycles with a diverse sugarcane germplasm composed of introgression, and commercial clones indicated that there is a high genetic variation for g s that can be exploited in a breeding programme. Regardless of the environmental influences on the expression of this trait, moderate heritability was observed across 51 sets of individual measurements made on replicated trials over 3 years. The clone×water status interaction (G×E) variation was smaller than the clone (G) variation on many occasions. A wide range of genetic correlations (r g= -0.29 to 0.94) between g s and yield were observed across test environments in all three different production regions used. Canopy conductance (g c) based on g s and leaf area index (LAI) showed a stronger genetic correlation than the g s with cane yield (tonnes of cane per hectare; TCH) at 12 months (mature crop). The regression analysis of input weather data for the duration of measurements showed that the predicted values of r g correlated with the maximum temperature (r=0.47) during the measurements and less with other environmental variables. These results confirm that the g c could have potential as a criterion for early-stage selection of clones in sugarcane breeding programmes. © 2015 The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com. Source

Everingham Y.,James Cook University | Sexton J.,James Cook University | Skocaj D.,James Cook University | Skocaj D.,Sugar Research Australia | Inman-Bamber G.,James Cook University
Agronomy for Sustainable Development

Foreknowledge about sugarcane crop size can help industry members make more informed decisions. There exists many different combinations of climate variables, seasonal climate prediction indices, and crop model outputs that could prove useful in explaining sugarcane crop size. A data mining method like random forests can cope with generating a prediction model when the search space of predictor variables is large. Research that has investigated the accuracy of random forests to explain annual variation in sugarcane productivity and the suitability of predictor variables generated from crop models coupled with observed climate and seasonal climate prediction indices is limited. Simulated biomass from the APSIM (Agricultural Production Systems sIMulator) sugarcane crop model, seasonal climate prediction indices and observed rainfall, maximum and minimum temperature, and radiation were supplied as inputs to a random forest classifier and a random forest regression model to explain annual variation in regional sugarcane yields at Tully, in northeastern Australia. Prediction models were generated on 1 September in the year before harvest, and then on 1 January and 1 March in the year of harvest, which typically runs from June to November. Our results indicated that in 86.36 % of years, it was possible to determine as early as September in the year before harvest if production would be above the median. This accuracy improved to 95.45 % by January in the year of harvest. The R-squared of the random forest regression model gradually improved from 66.76 to 79.21 % from September in the year before harvest through to March in the same year of harvest. All three sets of variables—(i) simulated biomass indices, (ii) observed climate, and (iii) seasonal climate prediction indices—were typically featured in the models at various stages. Better crop predictions allows farmers to improve their nitrogen management to meet the demands of the new crop, mill managers could better plan the mill’s labor requirements and maintenance scheduling activities, and marketers can more confidently manage the forward sale and storage of the crop. Hence, accurate yield forecasts can improve industry sustainability by delivering better environmental and economic outcomes. © 2016, INRA and Springer-Verlag France. Source

Reeves S.,Information Technology and Innovation | Wang W.,Information Technology and Innovation | Wang W.,Griffith University | Salter B.,Sugar Research Australia
Atmospheric Environment

Nitrous oxide (N2O) emissions from soil are often measured using the manual static chamber method. Manual gas sampling is labour intensive, so a minimal sampling frequency that maintains the accuracy of measurements would be desirable. However, the high temporal (diurnal, daily and seasonal) variabilities of N2O emissions can compromise the accuracy of measurements if not addressed adequately when formulating a sampling schedule. Assessments of sampling strategies to date have focussed on relatively low emission systems with high episodicity, where a small number of the highest emission peaks can be critically important in the measurement of whole season cumulative emissions. Using year-long, automated sub-daily N2O measurements from three fertilised sugarcane fields, we undertook an evaluation of the optimum gas sampling strategies in high emission systems with relatively long emission episodes. The results indicated that sampling in the morning between 09:00-12:00, when soil temperature was generally close to the daily average, best approximated the daily mean N2O emission within 4-7% of the 'actual' daily emissions measured by automated sampling. Weekly sampling with biweekly sampling for one week after >20 mm of rainfall was the recommended sampling regime. It resulted in no extreme (>20%) deviations from the 'actuals', had a high probability of estimating the annual cumulative emissions within 10% precision, with practicable sampling numbers in comparison to other sampling regimes. This provides robust and useful guidance for manual gas sampling in sugarcane cropping systems, although further adjustments by the operators in terms of expected measurement accuracy and resource availability are encouraged. By implementing these sampling strategies together, labour inputs and errors in measured cumulative N2O emissions can be minimised. Further research is needed to quantify the spatial variability of N2O emissions within sugarcane cropping and to develop techniques for effectively addressing both spatial and temporal variabilities simultaneously. © 2016 Elsevier Ltd. Source

Jackson P.,CSIRO | Wei X.M.,Sugar Research Australia
37th Annual Conference of the Australian Society of Sugar Cane Technologists, ASSCT 2015

SELECTION IN SUGARCANE breeding programs is complicated by measured traits being affected greatly by non-genetic effects, especially in early stage selection trials, and because clones vary for multiple traits affecting industry profitability which need to be selected for simultaneously. Selection index theory is a method which accounts for these issues, and has been progressively applied within the Australian sugarcane breeding program. In this paper, the selection index framework is briefly reviewed, and this is used to consider two issues in early stage selection trials. These are (i) adjusting index coefficients for presence of competition effects and genotype × environment interactions and (ii) incorporating traits which have no direct economic impact by themselves (e.g. DNA marker predictions or physiological traits) but which are correlated with other traits of high value (e.g. yield). Hypothetical but realistic examples are given to illustrate the methods. In addition, the economic weighting for fibre is considered. Economic weightings for fibre have recently been reviewed and the impact of different realistic weightings on selection in diverse populations typical of those in early stage trials is considered. Selection indices reflecting value of fibre based on some contrasting prices for electricity were derived and an example set of data presented in this paper. An overall conclusion from analysis of several data sets was that future progress in breeding programs for a range of realistic production systems and assumptions about product prices (e.g. for electricity or biofuel) is unlikely to be sensitive to the relative value of fibre, even at upper ends of likely potential value. Recommendations for dealing with uncertain future fibre values in breeding programs are made. Source

Bhuiyan S.A.,Sugar Research Australia | Croft B.J.,Sugar Research Australia
37th Annual Conference of the Australian Society of Sugar Cane Technologists, ASSCT 2015

SMUT CAUSED BY the fungus, Sporisorium scitamineum, is an important disease of sugarcane in Australia. A trial was conducted in Bundaberg on a silicon-deficient sandy soil to determine the efficacy of soil-applied silicon for control of smut in two susceptible (Q157 and Q205φ), one intermediate (Q208φ) and two resistant (Q151 and Q200φ) varieties. Silicon was applied as air-cooled blast furnace slag (14-18% silicon) at 6 t/ha (8.1 kg/9 m row) to selected plots and incorporated using a rotary hoe. Test varieties were planted between spreader rows of smut-infected Q205φ. The trial was maintained for three years until second ratoon. Disease assessments were carried out prior to harvesting, and yield data were collected only in the second ratoon. The silicon levels in leaf tissue were significantly higher in silicon-treated plots compared to untreated controls. The highly resistant variety Q151 showed no smut in either silicon or untreated plots throughout the experiment. The intermediate to resistant variety Q208 had 3% smut in the silicon treatment and 6% smut in the untreated plots in the second ratoon crop and the moderately resistant variety Q200φ had 12% smut in the silicon treatment and 8% smut in the untreated. These differences were not significant. At the final inspection in the second ratoon crop there were no significant differences in smut incidence between the silicon-treated and untreated plots of the susceptible variety Q157 (99 and 100% respectively), but significance differences were observed in Q205φ (86 and 93% respectively). Tonnes of cane per hectare (TCH) and tonnes of sugar per hectare (TSH) were significantly higher in the silicon-treated Q208φ compared with the untreated Q208φ. The highest TCH and TSH in this trial were obtained from Q208φ with silicon (150 and 26 t/ha respectively). Silicon did not significantly increase TCH or TSH in the other varieties and no differences in commercial cane sugar (CCS) were observed between silicon treated and untreated varieties. This experiment showed that resistant and intermediate varieties are effective in controlling smut with no addition of silicon under very high inoculum pressure from the disease. Silicon did not control smut in highly susceptible varieties, but possibly minimised the adverse stress response in Q208φ. Source

Discover hidden collaborations