Phenology of Carpophilus spp. (Coleoptera: Nitidulidae)in stone fruit orchards as determined by pheromone trapping: Implications for prediction of crop damage

Traps baited with synthetic aggregation pheromone and fermenting bread dough were used to monitor seasonal incidence and abundance of the ripening fruit pests, Carpophilus hemipterus (L.), C. mutilatus Erichson and C. davidsoni Dobson in stone fruit orchards in the Leeton district of southern New South Wales during five seasons (1991-96). Adult beetles were trapped from September-May, but abundance varied considerably between years with the amount of rainfall in December-January having a major influence on population size and damage potential during the canning peach harvest (late February-March). Below average rainfall in December-January was associated with mean trap catches of < 10 beetles/trap/week in low dose pheromone traps during the harvest period in 1991/92 and 1993/94 and no reported damage to ripening fruit. Rainfall in December-January 1992/93 was more than double the average and mean trap catches ranged from 8-27 beetles/week during the harvest period with substantial damage to the peach crop. December-January rainfall was also above average in 1994/95 and 1995/96 and means of 50-300 beetles/trap/week were recorded in high dose pheromone traps during harvest periods. Carpophilus spp. caused economic damage to peach crops in both seasons. These data indicate that it may be possible to predict the likelihood of Carpophilus beetle damage to ripening stone fruit in inland areas of southern Australia, by routine pheromone-based monitoring of beetle populations and summer temperatures and rainfall.

Assessing the relationship between shire winter crop yield and seasonal variability of the MODIS NDVI and EVI images

Australian researchers have been developing robust yield estimation models, based mainly on the crop growth response to water availability during the crop season. However, knowledge of spatial distribution of yields within and across the production regions can be improved by the use of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, available since 1999, have the potential to contribute to crop yield estimation. The objective of this study was to analyse the relationship between winter crop yields and the spectral information available in MODIS vegetation index images at the shire level. The study was carried out in the Jondaryan and Pittsworth shires, Queensland , Australia . Five years (2000 to 2004) of 250m resolution, 16-day composite of MODIS Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images were used during the winter crop season (April to November). Seasonal variability of the profiles of the vegetation index images for each crop season using different regions of interest (cropping mask) were displayed and analysed. Correlation analysis between wheat and barley yield data and MODIS image values were also conducted. The results showed high seasonal variability in the NDVI and EVI profiles, and the EVI values were consistently lower than those of the NDVI. The highest image values were observed in 2003 (in contrast to 2004), and were associated with rainfall amount and distribution. The seasonal variability of the profiles was similar in both shires, with minimum values in June and maximum values at the end of August. NDVI and EVI images showed sensitivity to seasonal variability of the vegetation and exhibited good association (e.g. r = 0.84, r = 0.77) with winter crop yields.

Modelling Leaf Production and Crop Development in Maize (Zea mays L.) After Tassel Initiation Under Diverse Conditions of Temperature and Photoperiod

Prediction of the initiation, appearance and emergence of leaves is critically important to the success of simulation models of crop canopy development and some aspects of crop ontogeny. Data on leaf number and crop ontogeny were collected on five cultivars of maize differing widely in maturity and genetic background grown under natural and extended photoperiods, and planted on seven sowing dates from October 1993 to March 1994 at Gatton, South-east Queensland. The same temperature coefficients were established for crop ontogeny before silking, and the rates of leaf initiation, leaf tip appearance and full leaf expansion, the base, optimum and maximum temperatures for each being 8, 34 and 40 degrees C. After silking, the base temperature for ontogeny was 0 degrees C, but the optimum and maximum temperatures remained unchanged. The rates of leaf initiation, appearance of leaf tips and full leaf expansion varied in a relatively narrow range across sowing times and photoperiod treatments, with average values of 0.040 leaves (degrees Cd)-1, 0.021 leaves (degrees Cd)-1, and 0.019 leaves (degrees Cd)-1, respectively. The relationships developed in this study provided satisfactory predictions of leaf number and crop ontogeny (tassel initiation to silking, emergence to silking and silking to physiological maturity) when assessed using independent data from Gatton (South eastern Queensland), Katherine and Douglas Daly (Northern Territory), Walkamin (North Queensland) and Kununurra (Western Australia).

Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: An integrated modelling approach in maize.

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

Validation of in silico-predicted genic SNPs in white clover (Trifolium repens L.), an outbreeding allopolyploid species

White clover (Trifolium repens L.) is an obligate outbreeding allotetraploid forage legume. Gene-associated SNPs provide the optimum genetic system for improvement of such crop species. An EST resource obtained from multiple cDNA libraries constructed from numerous genotypes of a single cultivar has been used for in silico SNP discovery and validation. A total of 58 from 236 selected sequence clusters (24.5%) were fully validated as containing polymorphic SNPs by genotypic analysis across the parents and progeny of several two-way pseudo-testcross mapping families. The clusters include genes belonging to a broad range of predicted functional categories. Polymorphic SNP-containing ESTs have also been used for comparative genomic analysis by comparison with whole genome data from model legume species, as well as Arabidopsis thaliana. A total of 29 (50%) of the 58 clusters detected putative ortholoci with known chromosomal locations in Medicago truncatula, which is closely related to white clover within the Trifolieae tribe of the Fabaceae. This analysis provides access to translational data from model species. The efficiency of in silico SNP discovery in white clover is limited by paralogous and homoeologous gene duplication effects, which are resolved unambiguously by the transmission test. This approach will also be applicable to other agronomically important cross-pollinating allopolyploid plant species.

Simulating crop-parasitic weed interactions using APSIM: Model evaluation and application

The parasitic weed Orobanche crenata inflicts major damage on faba bean, lentil, pea and other crops in Mediterranean environments. The development of methods to control O. crenata is to a large extent hampered by the complexity of host-parasite systems. Using a model of host-parasite interactions can help to explain and understand this intricacy. This paper reports on the evaluation and application of a model simulating host-parasite competition as affected by environment and management that was implemented in the framework of the Agricultural Production Systems Simulator (APSIM). Model-predicted faba bean and O. crenata growth and development were evaluated against independent data. The APSIM-Fababean and -Parasite modules displayed a good capability to reproduce effects of pedoclimatic conditions, faba bean sowing date and O. crenata infestation on host-parasite competition. The r(2) values throughout exceeded 0.84 (RMSD: 5.36 days) for phenological, 0.85 (RMSD: 223.00 g m(-2)) for host growth and 0.78 (RMSD: 99.82 g m(-2)) for parasite growth parameters. Inaccuracies of simulated faba bean root growth that caused some bias of predicted parasite number and host yield loss may be dealt with by more flexibly simulating vertical root distribution. The model was applied in simulation experiments to determine optimum sowing windows for infected and non-infected faba bean in Mediterranean environments. Simulation results proved realistic and testified to the capability of APSIM to contribute to the development of tactical approaches in parasitic weed control.

Domestication to crop improvement: Genetic resources for Sorghum and Saccharum (Andropogoneae).

Background: Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources: The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

Integrating grazing and forage systems on marginal cropping lands

Planned grazing systems are being introduced to beef cattle enterprises across the marginal cropping lands of Queensland, as they are on more extensive grazing properties. Systems range from continuous grazing with opportunistic summer rest periods to cell systems with more than 60 paddocks. The aim of planned grazing is to increase production, improve sustainability and increase economic viability from both the pastured and cropping lands of a property. Managing the more intensive grazing systems on native or sown pastures with strategic summer and winter forage crops is a challenge under the variable rainfall conditions. Under favourable conditions, integrating summer and winter crops with summer-growing grass-based pastures offers a wider range of options for breeding, finishing and marketing cattle. The integration of pasture grazing systems with opportunistic forage cropping systems on marginal cropping lands is discussed, and a current research project assessing grazing systems is described.

Crop and environmental attributes underpinning genotype by environment interaction in synthetic-derived bread wheat evaluated in Mexico and Australia

Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the north-west of Mexico (CIANO) and sites across Australia during 3 seasons. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. Previously, we have evaluated both the performance of genotypes across environments and the genotype x environment interaction (G x E). The objective of this study was to interpret the G x E for yield in terms of crop attributes measured at individual sites and to identify the potential environmental drivers of this interaction. Groups of SBWs with consistent yield performance were identified, often comprising closely related lines. However, contrasting performance was also relatively common among sister lines or between a recurrent parent and its SBWs. Early flowering was a common feature among lines with broad adaptation and/or high yield in the northern Australian wheatbelt, while yields in the southern region did not show any association with the maturity type. Lines with high yields in the southern and northern regions had cooler canopies during flowering and early grain filling. Among the SBWs with Australian genetic backgrounds, lines best adapted to CIANO were tall (>100 cm), with a slightly higher ground cover. These lines also displayed a higher concentration of water-soluble carbohydrates in the stem at flowering, which was negatively correlated with stem number per unit area when evaluated in southern Australia (Horsham). Possible reasons for these patterns are discussed. Selection for yield at CIANO did not specifically identify the lines best adapted to northern Australia, although they were not the most poorly adapted either. In addition, groups of lines with specific adaptation to the south would not have been selected by choosing the highest yielding lines at CIANO. These findings suggest that selection at CIMMYT for Australian environments may be improved by either trait based selection or yield data combined with trait information. Flowering date, canopy temperature around flowering, tiller density, and water-soluble carbohydrate concentration in the stem at flowering seem likely candidates.

High subsoil chloride concentrations reduce soil water extraction and crop yield on Vertosols in north-eastern Australia

Salinity, sodicity, acidity, and phytotoxic levels of chloride (Cl) in subsoils are major constraints to crop production in many soils of north-eastern Australia because they reduce the ability of crop roots to extract water and nutrients from the soil. The complex interactions and correlations among soil properties result in multi-colinearity between soil properties and crop yield that makes it difficult to determine which constraint is the major limitation. We used ridge-regression analysis to overcome colinearity to evaluate the contribution of soil factors and water supply to the variation in the yields of 5 winter crops on soils with various levels and combinations of subsoil constraints in the region. Subsoil constraints measured were soil Cl, electrical conductivity of the saturation extract (ECse), and exchangeable sodium percentage (ESP). The ridge regression procedure selected several of the variables used in a descriptive model, which included in-crop rainfall, plant-available soil water at sowing in the 0.90-1.10 m soil layer, and soil Cl in the 0.90-1.10 m soil layer, and accounted for 77-85% of the variation in the grain yields of the 5 winter crops. Inclusion of ESP of the top soil (0.0-0.10 m soil layer) marginally increased the descriptive capability of the models for bread wheat, barley and durum wheat. Subsoil Cl concentration was found to be an effective substitute for subsoil water extraction. The estimates of the critical levels of subsoil Cl for a 10% reduction in the grain yield were 492 mg cl/kg for chickpea, 662 mg Cl/kg for durum wheat, 854 mg Cl/kg for bread wheat, 980 mg Cl/kg for canola, and 1012 mg Cl/kg for barley, thus suggesting that chickpea and durum wheat were more sensitive to subsoil Cl than bread wheat, barley, and canola.

Analysis of high yielding maize production - A study based on a commercial crop

This paper reports on the use of APSIM - Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004-05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004-05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004-05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

Subsoil constraints in Vertosols: Crop water use nutrient concentration, and grain yields of bread wheat, durum wheat, barley, chickpea and canola

Single or multiple factors implicated in subsoil constraints including salinity, sodicity, and phytotoxic concentrations of chloride (Cl) are present in many Vertosols including those occurring in Queensland, Australia. The variable distribution and the complex interactions that exist between these constraints limit the agronomic or management options available to manage the soil with these subsoil constraints. The identification of crops and cultivars adapted to these adverse subsoil conditions and/or able to exploit subsoil water may be an option to maintain productivity of these soils. We evaluated relative performance of 5 winter crop species, in terms of grain yields, nutrient concentration, and ability to extract soil water, grown on soils with various levels and combinations of subsoil constraints in 19 field experiments over 2 years. Subsoil constraints were measured by levels of soil Cl, electrical conductivity of the saturation extract (ECse), and exchangeable sodium percentage (ESP). Increasing levels of subsoil constraints significantly decreased maximum depth of water extraction, grain yield, and plant-available water capacity for all the 5 crops and more so for chickpea and durum wheat than bread wheat, barley, or canola. Increasing soil Cl levels had a greater restricting effect on water availability than did ECse and ESP. We developed empirical relationships between soil Cl, ECse, and ESP and crop lower limit (CLL) for estimating subsoil water extraction by 5 winter crops. However, the presence of gypsum influenced the ability to predict CLL based on the levels of ECse. Stronger relationships between apparent unused plant-available water (CLL - LL15; LL15 is lower limit at -1.5 MPa) and soil Cl concentrations than ESP or ECse suggested that the presence of high Cl in these soils most likely inhibited the subsoil water extraction by the crops. This was supported by increased sodium (Na) and Cl concentration with a corresponding decrease in calcium (Ca) and potassium (K) in young mature leaf of bread wheat, durum wheat, and chickpea with increasing levels of subsoil constraints. Of the 2 ions, Na and Cl, the latter appears to be more damaging than the former, resulting in plant dieback and reduced grain yields.

Availability of soil potassium and diagnostic soil tests

Thirty-seven surface (0-0.10 or 0-0.20 m) soils covering a wide range of soil types (16 Vertosols, 6 Ferrosols, 6 Dermosols, 4 Hydrosols, 2 Kandosols, 1 Sodosol, 1 Rudosol, and 1 Chromosol) were exhaustively cropped in 2 glasshouse experiments. The test species were Panicum maximum cv. Green Panic in Experiment A and Avena sativa cv. Barcoo in Experiment B. Successive forage harvests were taken until the plants could no longer grow in most soils because of severe potassium (K) deficiency. Soil samples were taken prior to cropping and after the final harvest in both experiments, and also after the initial harvest in Experiment B. Samples were analysed for solution K, exchangeable K (Exch K), tetraphenyl borate extractable K for extraction periods of 15 min (TBK15) and 60 min (TBK60), and boiling nitric acid extractable K (Nitric K). Inter-correlations between the initial levels of the various soil K parameters indicated that the following pools were in sequential equilibrium: solution K, Exch K, fast release fixed K [estimated as (TBK15-Exch K)], and slow release fixed K [estimated as (TBK60-TBK15)]. Structural K [estimated as (Nitric K-TBK60)] was not correlated with any of the other pools. However, following exhaustive drawdown of soil K by cropping, structural K became correlated with solution K, suggesting dissolution of K minerals when solution K was low. The change in the various K pools following cropping was correlated with K uptake at Harvest 1 ( Experiment B only) and cumulative K uptake ( both experiments). The change in Exch K for 30 soils was linearly related to cumulative K uptake (r = 0.98), although on average, K uptake was 35% higher than the change in Exch K. For the remaining 7 soils, K uptake considerably exceeded the change in Exch K. However, the changes in TBK15 and TBK60 were both highly linearly correlated with K uptake across all soils (r = 0.95 and 0.98, respectively). The slopes of the regression lines were not significantly different from unity, and the y-axis intercepts were very small. These results indicate that the plant is removing K from the TBK pool. Although the change in Exch K did not consistently equate with K uptake across all soils, initial Exch K was highly correlated with K uptake (r = 0.99) if one Vertosol was omitted. Exchangeable K is therefore a satisfactory diagnostic indicator of soil K status for the current crop. However, the change in Exch K following K uptake is soil-dependent, and many soils with large amounts of TBK relative to Exch K were able to buffer changes in Exch K. These soils tended to be Vertosols occurring on floodplains. In contrast, 5 soils (a Dermosol, a Rudosol, a Kandosol, and 2 Hydrosols) with large amounts of TBK did not buffer decreases in Exch K caused by K uptake, indicating that the TBK pool in these soils was unavailable to plants under the conditions of these experiments. It is likely that K fertiliser recommendations will need to take account of whether the soil has TBK reserves, and the availability of these reserves, when deciding rates required to raise exchangeable K status to adequate levels.

Urana subterranean clover (Trifolium subterraneum L. var. subterraneum)

Urana is a hardseeded, moderately early flowering F-5-derived crossbred subterranean clover of var. subterraneum [( Katz. et Morley) Zohary and Heller] developed by the collaborating organisations of the National Annual Pasture Legume Improvement Program. It has been selected for release as a new cultivar on the basis of its high winter and spring herbage production and overall field performance relative to other subterranean clovers of similar maturity. Urana is recommended for sowing in Western Australia, New South Wales, Victoria, South Australia and Queensland. It is best suited to well-drained, moderately acidic soils in areas with a growing season of 5 - 7 months, which extends into mid-October. Urana is suited to phase farming and crop rotations. It has been granted Plant Breeders Rights in Australia.

Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts

We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.