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.

Sustaining productivity of a Vertosol at Warra, Queensland, with fertilisers, no-tillage or legumes. 9. Production and nitrogen benefits from mixed grass and legume pastures in rotation with wheat

Reduced supplies of nitrogen (N) in many soils of southern Queensland that were cropped exhaustively with cereals over many decades have been the focus of much research to avoid declines in profitability and sustainability of farming systems. A 45-month period of mixed grass (purple pigeon grass, Setaria incrassata Stapf; Rhodes grass, Chloris gayana Kunth.) and legume (lucerne, Medicago sativa L.; annual medics, M. scutellata L. Mill. and M. truncatula Gaertn.) pasture was one of several options that were compared at a fertility-depleted Vertosol at Warra, southern Queensland, to improve grain yields or increase grain protein concentration of subsequent wheat crops. Objectives of the study were to measure the productivity of a mixed grass and legume pasture grown over 45 months (cut and removed over 36 months) and its effects on yield and protein concentrations of the following wheat crops. Pasture production (DM t/ha) and aboveground plant N yield (kg/ha) for grass, legume (including a small amount of weeds) and total components of pasture responded linearly to total rainfall over the duration of each of 3 pastures sown in 1986, 1987 and 1988. Averaged over the 3 pastures, each 100 mm of rainfall resulted in 0.52 t/ha of grass, 0.44 t/ha of legume and 0.97 t/ha of total pasture DM, there being little variation between the 3 pastures. Aboveground plant N yield of the 3 pastures ranged from 17.2 to 20.5 kg/ha per 100 mm rainfall. Aboveground legume N in response to total rainfall was similar (10.6 - 13.2 kg/ha. 100 mm rainfall) across the 3 pastures in spite of very different populations of legumes and grasses at establishment. Aboveground grass N yield was 5.2 - 7.0 kg/ha per 100mm rainfall. In most wheat crops following pasture, wheat yields were similar to that of unfertilised wheat except in 1990 and 1994, when grain yields were significantly higher but similar to that for continuous wheat fertilised with 75 kg N/ha. In contrast, grain protein concentrations of most wheat crops following pasture responded positively, being substantially higher than unfertilised wheat but similar to that of wheat fertilised with 75 kg N/ha. Grain protein averaged over all years of assay was increased by 25 - 40% compared with that of unfertilised wheat. Stored water supplies after pasture were < 134mm (< 55% of plant available water capacity); for most assay crops water storages were 67 - 110 mm, an equivalent wet soil depth of only 0.3 - 0.45 m. Thus, the crop assays of pasture benefits were limited by low water supply to wheat crops. Moreover, the severity of common root rot in wheat crop was not reduced by pasture - wheat rotation.

Long-term response of corn to limited irrigation and crop rotations

Dwindling water supplies for irrigation are prompting alternative management choices by irrigators. Limited irrigation, where less water is applied than full crop demand, may be a viable approach. Application of limited irrigation to corn was examined in this research. Corn was grown in crop rotations with dryland, limited irrigation, or full irrigation management from 1985 to 1999. Crop rotations included corn following corn (continuous corn), corn following wheat, followed by soybean (wheat-corn-soybean), and corn following soybean (corn-soybean). Full irrigation was managed to meet crop evapotranspiration requirements (ETc). Limited irrigation was managed with a seasonal target of no more than 150 mm applied. Precipitation patterns influenced the outcomes of measured parameters. Dryland yields had the most variation, while fully irrigated yields varied the least. Limited irrigation yields were 80% to 90%> of fully irrigated yields, but the limited irrigation plots received about half the applied water. Grain yields were significantly different among irrigation treatments. Yields were not significantly different among rotation treatments for all years and water treatments. For soil water parameters, more statistical differences were detected among the water management treatments than among the crop rotation treatments. Economic projections of these management practices showed that full irrigation produced the most income if water was available. Limited irrigation increased income significantly from dryland management.

Soil properties and crop yields in a dryland Vertisol sown with cotton-based crop rotations

Information on the effects of growing cotton (Gossypium hirsutum L.)-based crop rotations on soil quality of dryland Vertisols is sparse. The objective of this study was to quantify the effects of growing cereal and leguminous crops in rotation with dryland cotton on physical and chemical properties of a grey Vertisol near Warra, SE Queensland, Australia. The experimental treatments, selected after consultations with local cotton growers, were continuous cotton (T1), cotton-sorghum (Sorghum bicolor (L.) Moench.) (T2), cotton-wheat (Triticum aestivum L.) double cropped (T3), cotton-chickpea (Cicer arietinum L.) double cropped followed by wheat (T4) and cotton-wheat (T5). From 1993 to 1996 land preparation was by chisel ploughing to about 0.2 m followed by two to four cultivations with a Gyral tyne cultivator. Thereafter all crops were sown with zero tillage except for cultivation with a chisel plough to about 0.07-0.1 m after cotton picking to control heliothis moth pupae. Soil was sampled from 1996 to 2004 and physical (air-filled porosity of oven-dried soil, an indicator of soil compaction; plastic limit; linear shrinkage; dispersion index) and chemical (pH in 0.01 M CaCl2, organic carbon, exchangeable Ca, Mg, K and Na contents) properties measured. Crop rotation affected soil properties only with respect to exchangeable Na content and air-filled porosity. In the surface 0.15 m during 2000 and 2001 lowest air-filled porosity occurred with T1 (average of 34.6 m3/100 m3) and the highest with T3 (average of 38.9 m3/100 m3). Air-filled porosity decreased in the same depth between 1997 and 1998 from 45.0 to 36.1 m3/100 m3, presumably due to smearing and compaction caused by shallow cultivation in wet soil. In the subsoil, T1 and T2 frequently had lower air-filled porosity values in comparison with T3, T4 and T5, particularly during the early stages of the experiment, although values under T1 increased subsequently. In general, compaction was less under rotations which included a wheat crop (T3, T4, T5). For example, average air-filled porosity (in m3/100 m3) in the 0.15-0.30 m depth from 1996 to 1999 was 19.8 with both T1 and T2, and 21.2 with T3, 21.1 with T4 and 21.5 with T5. From 2000 to 2004, average air-filled porosity (in m3/100 m3) in the same depth was 21.3 with T1, 19.0 with T2, 19.8 with T3, 20.0 with T4 and 20.5 with T5. The rotation which included chickpea (T4) resulted in the lowest exchangeable Na content, although differences among rotations were small. Where only a cereal crop with a fibrous root system was sown in rotation with cotton (T2, T3, T5) linear shrinkage in the 0.45-0.60 m depth was lower than in rotations, which included tap-rooted crops such as chickpea (T4) or continuous cotton (T1). Dispersion index and organic carbon decreased, and plastic limit increased with time. Soil organic carbon stocks decreased at a rate of 1.2 Mg/ha/year. Lowest average cotton lint yield occurred with T2 (0.54 Mg/ha) and highest wheat yield with T3 (2.8 Mg/ha). Rotations which include a wheat crop are more likely to result in better soil structure and cotton lint yield than cotton-sorghum or continuous cotton.

Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform

A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

New annual and short-lived perennial pasture legumes for Australian agriculture--15 years of revolution

Fifteen years ago subterranean clover (Trifolium subterraneum) and annual medics (Medicago spp.) dominated annual pasture legume sowings in southern Australia, while limited pasture legume options existed for cropping areas of subtropical Australia. Since then a number of sustainability and economic challenges to existing farming systems have emerged, exposing shortcomings in these species and the lack of legume biodiversity. Public breeding institutions have responded to these challenges by developing 58 new annual and short-lived perennial pasture legumes with adaptation to both existing and new farming systems. This has involved commercialisation of new species and overcoming deficiencies in traditional species. Traits incorporated in legumes of Mediterranean Basin origin for the Mediterranean, temperate and southern subtropical climates of Australia include deeper root systems, protection from false breaks (germination-inducing rainfall events followed by death from drought), a range of hardseed levels, acid-soil tolerant root nodule symbioses, tolerance to pests and diseases and provision of lower cost seed through ease of seed harvesting and processing. Ten new species, French serradella (Ornithopus sativus), biserrula (Biserrula pelecinus), sulla (Hedysarum coronarium), gland (Trifolium glanduliferum), arrowleaf (Trifolium vesiculosum), eastern star (Trifolium dasyurum) and crimson (Trifolium incarnatum) clovers and sphere (Medicago sphaerocarpos), button (Medicago orbicularis) and hybrid disc (Medicago tornata x Medicago littoralis) medics have been commercialised. Improved cultivars have also been developed of subterranean (T. subterraneum), balansa (Trifolium michelianum), rose (Trifolium hirtum), Persian (Trifolium resupinatum) and purple (Trifolium purpureum) clovers, burr (Medicago polymorpha), strand (M. littoralis), snail (Medicago scutellata) and barrel (Medicago truncatula) medics and yellow serradella (Ornithopus compressus). New tropical legumes for pasture phases in subtropical cropping areas include butterfly pea (Clitoria ternatea), burgundy bean (Macroptilium bracteatum) and perennial lablab (Lablab purpureus). Other species and cultivars of Mediterranean species are likely to be released soon. The contributions of genetic resources, rhizobiology, pasture ecology and agronomy, plant pathology, entomology, plant chemistry and animal science have been paramount to this success. A farmer survey in Western Australia has shown widespread adoption of the new pasture legumes, while adoption of new tropical legumes has also been high in cropping areas of the subtropics. This trend is likely to increase due to the increasing cost of inorganic nitrogen, the need to combat herbicide-resistant crop weeds and improved livestock prices. Mixtures of these legumes allows for more robust pastures buffered against variable seasons, soils, pests, diseases and management decisions. This paper discusses development of the new pasture legumes, their potential use and deficiencies in the current suite. 'Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

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.

How accurate are the marker orders in crop linkage maps generated from large marker datasets?

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R-2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping

Differences between the in vitro digestibility of extrusa collected from oesophageal fistulated steers and the forage consumed.

In a study that included C-4 tropical grasses, C-3 temperate grasses and C-3 pasture legumes, in vitro dry matter digestibility of extrusa, measured as in vitro dry matter loss (IVDML) during incubation, compared with that of the forage consumed, was greater for grass extrusa but not for legume extrusa. The increase in digestibility was not caused by mastication or by the freezing of extrusa samples during storage but by the action of saliva. Comparable increases in IVDML were achieved merely by mixing bovine saliva with ground forage samples. Differences were greater than could be explained by increases due to completely digestible salivary DM. There was no significant difference between animals in relation to the saliva effect on IVDML and, except for some minor differences, similar saliva effects on IVDML were measured using either the pepsin-cellulase or rumen fluid-pepsin in vitro techniques. For both C-4 and C-3 grasses the magnitude of the differences were inversely related to IVDML of the feed and there was little or no difference between extrusa and feed at high digestibilities (>70%) whereas differences of more than 10 percentage units were measured on low quality grass forages. The data did not suggest that the extrusa or saliva effect on digestibility was different for C-3 grasses than for C-4 grasses but data on C-3 grasses were limited to few species and to high digestibility samples. For legume forages there was no saliva effect when the pepsin-cellulase method was used but there was a small but significant positive effect using the rumen fluid-pepsin method. It was concluded that when samples of extrusa are analysed using in vitro techniques, predicted in vivo digestibility of the feed consumed will often be overestimated, especially for low quality grass diets. The implications of overestimating in vivo digestibility and suggestions for overcoming such errors are discussed.

Poor adoption of ley-pastures in south-west Queensland: biophysical, economic and social constraints.

The present review identifies various constraints relating to poor adoption of ley-pastures in south-west Queensland, and suggests changes in research, development and extension efforts for improved adoption. The constraints include biophysical, economic and social constraints. In terms of biophysical constraints, first, shallower soil profiles with subsoil constraints (salt and sodicity), unpredictable rainfall, drier conditions with higher soil temperature and evaporative demand in summer, and frost and subzero temperature in winter, frequently result in a failure of established, or establishing, pastures. Second, there are limited options for legumes in a ley-pasture, with the legumes currently being mostly winter-active legumes such as lucerne and medics. Winter-active legumes are ineffective in improving soil conditions in a region with summer-dominant rainfall. Third, most grain growers are reluctant to include grasses in their ley-pasture mix, which can be uneconomical for various reasons, including nitrogen immobilisation, carryover of cereal diseases and depressed yields of the following cereal crops. Fourth, a severe depletion of soil water following perennial ley-pastures (grass + legumes or lucerne) can reduce the yields of subsequent crops for several seasons, and the practice of longer fallows to increase soil water storage may be uneconomical and damaging to the environment. Economic assessments of integrating medium- to long-term ley-pastures into cropping regions are generally less attractive because of reduced capital flow, increased capital investment, economic loss associated with establishment and termination phases of ley-pastures, and lost opportunities for cropping in a favourable season. Income from livestock on ley-pastures and soil productivity gains to subsequent crops in rotation may not be comparable to cropping when grain prices are high. However, the economic benefits of ley-pastures may be underestimated, because of unaccounted environmental benefits such as enhanced water use, and reduced soil erosion from summer-dominant rainfall, and therefore, this requires further investigation. In terms of social constraints, the risk of poor and unreliable establishment and persistence, uncertainties in economic and environmental benefits, the complicated process of changing from crop to ley-pastures and vice versa, and the additional labour and management requirements of livestock, present growers socially unattractive and complex decision-making processes for considering adoption of an existing medium- to long-term ley-pasture technology. It is essential that research, development and extension efforts should consider that new ley-pasture options, such as incorporation of a short-term summer forage legume, need to be less risky in establishment, productive in a region with prevailing biophysical constraints, economically viable, less complex and highly flexible in the change-over processes, and socially attractive to growers for adoption in south-west Queensland.

Pest-damage relationships for Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) on soybean (Glycine max) and dry bean (Phaseolus vulgaris) during pod-fill.

The response of soybean (Glycine max) and dry bean (Phaseolus vulgaris) to feeding by Helicoverpa armigera during the pod-fill stage was studied in irrigated field cages over three seasons to determine the relationship between larval density and yield loss, and to develop economic injury levels. H. armigera intensity was calculated in Helicoverpa injury equivalent (HIE) units, where 1 HIE was the consumption of one larva from the start of the infestation period to pupation. In the dry bean experiment, yield loss occurred at a rate 6.00 ± 1.29 g/HIE while the rates of loss in the three soybean experiments were 4.39 ± 0.96 g/HIE, 3.70 ± 1.21 g/HIE and 2.12 ± 0.71 g/HIE. These three slopes were not statistically different (P > 0.05) and the pooled estimate of the rate of yield loss was 3.21 ± 0.55 g/HIE. The first soybean experiment also showed a split-line form of damage curve with a rate of yield loss of 26.27 ± 2.92 g/HIE beyond 8.0 HIE and a rapid decline to zero yield. In dry bean, H. armigera feeding reduced total and undamaged pod numbers by 4.10 ± 1.18 pods/HIE and 12.88 ± 1.57 pods/HIE respectively, while undamaged seed numbers were reduced by 35.64 ± 7.25 seeds/HIE. In soybean, total pod numbers were not affected by H. armigera infestation (out to 8.23 HIE in Experiment 1) but seed numbers (in Experiments 1 and 2) and the number of seeds/pod (in all experiments) were adversely affected. Seed size increased with increases in H. armigera density in two of the three soybean experiments, indicating plant compensatory responses to H. armigera feeding. Analysis of canopy pod profiles indicated that loss of pods occurred from the top of the plant downwards, but with an increase in pod numbers close to the ground at higher pest densities as the plant attempted to compensate for damage. Based on these results, the economic injury levels for H. armigera on dry bean and soybean are approximately 0.74 HIE and 2.31 HIE/m2, respectively (0.67 and 2.1 HIE/row-m for 91 cm rows).

Pest-damage relationships for Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) on vegetative soybean.

The response of vegetative soybean (Glycine max) to Helicoverpa armigera feeding was studied in irrigated field cages over three years in eastern Australia to determine the relationship between larval density and yield loss, and to develop economic injury levels. Rather than using artificial defoliation techniques, plants were infested with either eggs or larvae of H. armigera, and larvae allowed to feed until death or pupation. Larvae were counted and sized regularly and infestation intensity was calculated in Helicoverpa injury equivalent (HIE) units, where 1 HIE was the consumption of one larva from the start of the infestation period to pupation. In the two experiments where yield loss occurred, the upper threshold for zero yield loss was 7.51 ± 0.21 HIEs and 6.43 ± 1.08 HIEs respectively. In the third experiment, infestation intensity was lower and no loss of seed yield was detected up to 7.0 HIEs. The rate of yield loss/HIE beyond the zero yield loss threshold varied between Experiments 1 and 2 (-9.44 ± 0.80 g and -23.17 ± 3.18 g, respectively). H. armigera infestation also affected plant height and various yield components (including pod and seed numbers and seeds/pod) but did not affect seed size in any experiment. Leaf area loss of plants averaged 841 and 1025 cm2/larva in the two experiments compared to 214 and 302 cm2/larva for cohort larvae feeding on detached leaves at the same time, making clear that artificial defoliation techniques are unsuitable for determining H. armigera economic injury levels on vegetative soybean. Analysis of canopy leaf area and pod profiles indicated that leaf and pod loss occurred from the top of the plant downwards. However, there was an increase in pod numbers closer to the ground at higher pest densities as the plant attempted to compensate for damage. Defoliation at the damage threshold was 18.6 and 28.0% in Experiments 1 and 2, indicating that yield loss from H. armigera feeding occurred at much lower levels of defoliation than previously indicated by artificial defoliation studies. Based on these results, the economic injury level for H. armigera on vegetative soybean is approximately 7.3 HIEs/row-metre in 91 cm rows or 8.0 HIEs/m2.