Understanding and Managing the Late Time of Ratooning Effect on Cane Yield

Each year growers are faced with the decision of when to harvest individual blocks of sugarcane throughout the harvest season. This decision influences the yield of the current crop and can affect the yield in the following season. Growers must therefore decide which blocks to harvest early and which to harvest later in the harvest season. Usually, the latest harvested cane is the lowest yielding the following year (the �late harvest� effect). Block productivity data from Tully were used to determine the effects of harvest timing on cane yield of the current and subsequent crop. The results are tabulated to provide a ready reference to these time of harvest effects on the current and future crop in either a single year or over the full crop cycle for the Tully district.

Improved methods for predicting individual leaf area and leaf senescence in maize (Zea mays)

The ability to predict leaf area and leaf area index is crucial in crop simulation models that predict crop growth and yield. Previous studies have shown existing methods of predicting leaf area to be inadequate when applied to a broad range of cultivars with different numbers of leaves. The objectives of the study were to (i) develop generalised methods of modelling individual and total plant leaf area, and leaf senescence, that do not require constants that are specific to environments and/or genotypes, (ii) re-examine the base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence, and (iii) assess the method of calculation of individual leaf area from leaf length and leaf width in experimental work. Five cultivars of maize differing widely in maturity and adaptation were planted in October 1994 in south-eastern Queensland, and grown under non-limiting conditions of water and plant nutrient supplies. Additional data for maize plants with low total leaf number (12-17) grown at Katumani Research Centre, Kenya, were included to extend the range in the total leaf number per plant. The equation for the modified (slightly skewed) bell curve could be generalised for modelling individual leaf area, as all coefficients in it were related to total leaf number. Use of coefficients for individual genotypes can be avoided, and individual and total plant leaf area can be calculated from total leaf number. A single, logistic equation, relying on maximum plant leaf area and thermal time from emergence, was developed to predict leaf senescence. The base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence were 8, 34, and 40 degrees C, and apply for the whole crop-cycle when used in modelling of leaf senescence. Thus, the modelling of leaf production and senescence is simplified, improved, and generalised. Consequently, the modelling of leaf area index (LAI) and variables that rely on LAI will be improved. For experimental purposes, we found that the calculation of leaf area from leaf length and leaf width remains appropriate, though the relationship differed slightly from previously published equations.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - II. Testing simulation capabilities of wheat growth

To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

Radiation use efficiency increases when the diffuse component of incident radiation is enhanced under shade

Theoretical analyses have shown the radiation use efficiency of maize, soybean, and peanut to increase with a decrease in the level of incident radiation and an increase in the proportion of diffuse radiation. This study compared the growth and radiation use efficiency of Panicum maximum cv. Petrie (green panic) and Bothriochloa insculpta cv. Bisset (creeping bluegrass) beneath shading treatments (birdguard and solarweave shadecloths) with that in full sunlight. A level of incident radiation reduced by 25% under birdguard shadecloth decreased final yield and final leaf area index, but increased canopy leaf nitrogen concentration and radiation use efficiency (19-14%) (compared with the full sun treatment). A similar level of reduced incident radiation under solarweave shadecloth (which provided an increased proportion of diffuse radiation), increased final yield and radiation use efficiency (46-50%). An understanding of the effects of composition of incident radiation on radiation use efficiency of tropical grasses enables more accurate estimation of potential pasture growth in shaded environments. It also has impact upon crop production in glasshouses and greenhouses.

Some factors affecting white stem borer Scirpophaga innotata (Walker) (Lepidoptera : Pyralidae) injury to rice

The amount of injury to rice caused by white stem borer Sciryophaga innotata depends on cultivar, and stage of plant and insect development, as well as insect abundance. Of the cultivars tested, IR64, IR42, Cisadane and Ketan. IR64 were the most susceptible and Ketan the least susceptible to feeding damage. Third and fourth instars consumed more stem dry matter than other stages, although yield reduction depended on the number of tillers injured. On the wider stemmed Ketan, fewer tillers were injured than the narrower IR64. Larvae are more likely to move among tillers in the third instar stage, which tends to coincide with maximum tillering and may result in more tillers injured and in yield reduction. Later instar larvae burrow downwards to the internode where they pupate. Larvae appear to move less among tillers in 'resistant' cultivars. Management strategies should target this pest at third instar and when its abundance in the field warrants control. Fewer than 10% of the neonates establish successfully on stems, and this mortality needs to be taken into account when deciding on control, as does the ability of rice plants to compensate for injury. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

Analysis of long-term light-trap data for Helicoverpa spp. (Lepidoptera : Noctuidae) in Australia: the effect of climate and crop host plants

Regression analyses of a long series of light-trap catches at Narrabri, Australia, were used to describe the seasonal dynamics of Helicoverpa armigera (Hubner). The size of the second generation was significantly related to the size of the first generation, to winter rainfall, which had a positive effect, and to spring rainfall which had a negative effect. These variables accounted for up to 96% of the variation in size of the second generation from year to year. Rainfall and crop hosts were also important for the size of the third generation. The area and tonnage of many potential host crops were significantly correlated with winter rain. When winter rain was omitted from the analysis, the sizes of both the second and third generations could be expressed as a function of the size of the previous generation and of the areas planted to lucerne, sorghum and maize. Lucerne and maize always had positive coefficients and sorghum a negative one. We extended our analysis to catches of H. punctigera (Wallengren), which declines in abundance after the second generation. Winter rain had a positive effect on the sizes of the second and third generations, and rain in spring or early summer had a negative effect. Only the area grown to lucerne had a positive effect on abundance. Forecasts of pest levels from a few months to a few weeks in advance are discussed, along with the improved understanding of the seasonal dynamics of both species and the significance of crops in the management of insecticide resistance for H. armigera.

Toxicity of biorational insecticides to Helicoverpa spp. (Lepidoptera : Noctuidae) and predators in cotton field

Field trials on upland cotton (Gossypium hirstum L.) during its reproductive phase were used to assess the toxicity of several biorational pesticides and chemicals to Helicoverpa armigera (Hubner) and H. puntigera Wallengren, as well as major predators at Dalby, Queensland, Australia. Moderate rate-dependent control was obtained in plots treated with neem (Azadirachta indica A. Juss) seed extract-azadirachtin (Aza) at rates of 30, 60 and 90 g/ha. Plots treated with Talstar EC (bifenthrin) applications achieved the best results, followed by treatment with alternation of chemicals (methomyl, bifenthrin, thiodicarb and endosulfan) and biorational insecticides (neem oil, azadirachtin and Bacillus thuringiensis kurstaki var. Berliner). Predators, including lady beetles, lacewings, spiders and predatory bugs, were insensitive to Aza, tooseendanin (Tsdn) and BT applications. In contrast, chemicals were very destructive of predators. All treatments provided some protection from infestation of H. armigera and H. puntigera. The effect of Aza on Helicoverpa spp. was reflected in a relatively higher yield of seed cotton harvested from Aza-treated plots compared with the control, but chemical control achieved significantly higher yields than any other treatment.

Does maintaining green leaf area in sorghum improve yield under drought? II. Dry matter production and yield

Retention of green leaf area at maturity (GLAM), known as stay-green, is used as an indicator of postanthesis drought resistance in sorghum [Sorghum bicolor (L.) Moench] breeding programs in the USA and Australia. The critical issue is whether maintaining green leaves under postanthesis drought increases grain yield in stay-green compared with senescent hybrids. Field studies were undertaken in northeastern Australia on a cracking and self-mulching gay clay. Nine closely related hybrids varying in rate of leaf senescence were grown under two water-limiting regimes, post-flowering water deficit and terminal (pre- and postflowering) water deficit, and a fully irrigated control. Under terminal water deficit, grain yield tvas correlated positively with GLAM (r = 0.75**) and negatively with rate of leaf senescence (r = -0.74**). Grain yield also increased by approximate to 0.35 Mg ha(-1) for every day that onset of leaf senescence was delayed beyond 76 DAE in the water-limited treatments. Stay-green hybrids produced 47% more postanthesis biomass than their senescent counterparts (920 vs. 624 g m(-2)) under the terminal water deficit regime. No differences in grain yield were found among eight of the nine hybrids under fully irrigated conditions, suggesting that the stay-green trait did not constrain yield in the well-watered control. The results indicate that sorghum hybrids possessing the stay-green trait have a significant yield advantage under postanthesis drought compared with hybrids not possessing this trait.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.