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.

The limit to wheat water-use efficiency in eastern Australia. I. Gradients in the radiation environment and atmospheric demand

In the wheatbelt of eastern Australia, rainfall shifts from winter dominated in the south (South Australia, Victoria) to summer dominated in the north (northern New South Wales, southern Queensland). The seasonality of rainfall, together with frost risk, drives the choice of cultivar and sowing date, resulting in a flowering time between October in the south and August in the north. In eastern Australia, crops are therefore exposed to contrasting climatic conditions during the critical period around flowering, which may affect yield potential, and the efficiency in the use of water (WUE) and radiation (RUE). In this work we analysed empirical and simulated data, to identify key climatic drivers of potential water- and radiation-use efficiency, derive a simple climatic index of environmental potentiality, and provide an example of how a simple climatic index could be used to quantify the spatial and temporal variability in resource-use efficiency and potential yield in eastern Australia. Around anthesis, from Horsham to Emerald, median vapour pressure deficit (VPD) increased from 0.92 to 1.28 kPa, average temperature increased from 12.9 to 15.2°C, and the fraction of diffuse radiation (FDR) decreased from 0.61 to 0.41. These spatial gradients in climatic drivers accounted for significant gradients in modelled efficiencies: median transpiration WUE (WUEB/T) increased southwards at a rate of 2.6% per degree latitude and median RUE increased southwards at a rate of 1.1% per degree latitude. Modelled and empirical data confirmed previously established relationships between WUEB/T and VPD, and between RUE and photosynthetically active radiation (PAR) and FDR. Our analysis also revealed a non-causal inverse relationship between VPD and radiation-use efficiency, and a previously unnoticed causal positive relationship between FDR and water-use efficiency. Grain yield (range 1-7 t/ha) measured in field experiments across South Australia, New South Wales, and Queensland (n = 55) was unrelated to the photothermal quotient (Pq = PAR/T) around anthesis, but was significantly associated (r2 = 0.41, P < 0.0001) with newly developed climatic index: a normalised photothermal quotient (NPq = Pq . FDR/VPD). This highlights the importance of diffuse radiation and vapour pressure deficit as sources of variation in yield in eastern Australia. Specific experiments designed to uncouple VPD and FDR and more mechanistic crop models might be required to further disentangle the relationships between efficiencies and climate drivers.

A consensus genetic map of sorghum that integrates multiple component maps and high-throughput Diversity Array Technology (DArT) markers

Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

Hardness Methods for Testing Maize Kernels

Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and. to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Functional dynamics of the nitrogen balance of sorghum: I. N demand of vegetative plant parts.

Stay-green, an important trait for grain yield of sorghum grown under water limitation, has been associated with a high leaf nitrogen content at the start of grain filling. This study quantifies the N demand of leaves and stems and explores effects of N stress on the N balance of vegetative plant parts of three sorghum hybrids differing in potential crop height. The hybrids were grown under well-watered conditions at three levels of N supply. Vertical profiles of biomass and N% of leaves and stems, together with leaf size and number, and specific leaf nitrogen (SLN), were measured at regular intervals. The hybrids had similar minimum but different critical and maximum SLN, associated with differences in leaf size and N partitioning, the latter associated with differences in plant height. N demand of expanding new leaves was represented by critical SLN, and structural stem N demand by minimum stem N%. The fraction of N partitioned to leaf blades increased under N stress. A framework for N dynamics of leaves and stems is developed that captures effects of N stress and genotype on N partitioning and on critical and maximum SLN.

Simulating the evolution of glyphosate resistance in grains farming in northern Australia.

Background and Aims: The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods: The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results: Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions: This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

Potential of piperonyl butoxide-synergised pyrethrins against psocids (Psocoptera: Liposcelididae) for stored-grain protection.

BACKGROUND: Piperonyl butoxide (PB)-synergised natural pyrethrins (pyrethrin:PB ratio 1:4) were evaluated both as a grain protectant and a disinfestant against four Liposcelidid psocids: Liposcelis bostrychophila Badonnel, L. entomophila (Enderlein), L. decolor (Pearman) and L. paeta Pearman. These are key storage pests in Australia that are difficult to control with the registered grain protectants and are increasingly being reported as pests of stored products in other countries. Firstly, mortality and reproduction of adults were determined in wheat freshly treated at 0.0, 0.75, 1.5, 3 and 6 mg kg-1 of pyrethrins + PB (1:4) at 301C and 702% RH. Next, wheat treated at 0.0, 1.5, 3 and 6 mg kg-1 of pyrethrins + PB (1:4) was stored at 301C and 702% RH and mortality and reproduction of psocids were assessed after 0, 1.5, 3 and 4.5 months of storage. Finally, the potential of synergised pyrethrins as a disinfestant was assessed by establishing time to endpoint mortality for adult psocids exposed to wheat treated at 3 and 6 mg kg-1 of synergised pyrethrins after 0, 3, 6, 9 and 12 h of exposure. RESULTS: Synergised pyrethrins at 6 mg kg-1 provided 3 months of protection against all four Liposcelis spp., and at this rate complete adult mortality of these psocids can be achieved within 6 h of exposure. CONCLUSION: Piperonyl butoxide-synergised pyrethrins have excellent potential both as a grain protectant and as a disinfestant against Liposcelidid.

Analysis and Modelling of the Effects of Water Stress on Maize Growth and Yield in Dryland Conditions.

It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated until late canopy expansion followed by rainfed) was used to compare effects of water stress on crop production in two maize (Zea mays L.) cultivars (Pioneer 34N43 and Pioneer 31H50). Water stress affected growth and yield more in Pioneer 34N43 than in Pioneer 31H50. A crop model APSIM-Maize, after having been calibrated for the two cultivars, was used to simulate maize growth and development under water stress. The predictions on leaf area index (LAI) dynamics, biomass growth and grain yield under rain fed and irrigated followed by rain fed treatments was reasonable, indicating that stress indices used by APSIM-Maize produced appropriate adjustments to crop growth and development in response to water stress. This study shows that Pioneer 31H50 is less sensitive to water stress and thus a preferred cultivar in dryland conditions, and that it is feasible to provide sound predictions and risk assessment for crop production in drier, more variable conditions using the APSIM-Maize model.

Net radiation dynamics: performance of 20 daily net radiation models as related to model structure and intricacy in two climates.

We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

Temporal genetic structure patterns in tropical maize populations under reciprocal recurrent selection.

In order to investigate the effect of long term recurrent selection on the pattern of gene diversity, thirty randomly-selected individuals from the progenitors (p) and four selection cycles (C0, C3, C6 and C11) were sampled for DNA analysis from the tropical maize (Zea mays L.) breeding populations, Atherton 1 (AT1) and Atherton 2 (AT2). Fifteen polymorphic Simple Sequence Repeat markers amplified a total of 284 and 257 alleles in AT1 and AT2 populations, respectively. Reductions in the number of alleles were observed at advanced selection cycles. About 11 and 12% of the alleles in AT1 and AT2 populations respectively, were near to fixation. However, a higher number of alleles (37% in AT1 and 33% in AT2) were close to extinction. Fisher's exact test and analysis of molecular variance (AMOVA) showed significant population differentiations. Gene diversity estimates and AMOVA revealed increased genetic differentiations at the expense of loss of heterozygosity. Population differentiations were mainly due to fixation of complementary alleles at a locus in the two breeding populations. The estimates of effective population at an advanced selection cycle were close to the population size predicted by the breeding method.

Nutritional constraints on displacement of Fusarium pseudograminearum from cereal straw by antagonists.

Displacement of the fungus Fusarium pseudograminearum from stubble by antagonists is a potential means of biocontrol of crown rot in cereals. The role of carbon and nitrogen nutrition in interactions between the pathogen and the antagonists Fusarium equiseti, Fusarium nygamai, Trichoderma harzianum and the non-antagonistic straw fungus Alternaria infectoria was investigated. Sole carbon source utilization patterns on Biolog plates were similar among the three Fusarium species, suggesting a possible role for competition. However, carbon niche overlap was unlikely to be important in antagonism by T. harzianum. Straw medium supplemented with sugars generally reduced the inhibitory effect of antagonists on growth of F. pseudograminearum in dual culture, indicating that availability of simple carbon sources does not limit antagonism. Adding nitrogen as urea, nitrate or ammonium to straw medium had little effect on antagonism by F. equiseti and F. nygamai, but ammonium addition removed the inhibitory effect of T. harzianum on growth of F. pseudograminearum. Displacement of F. pseudograminearum from straw by all fungi in a Petri dish assay was greater when urea or nitrate was used as a nitrogen source than with ammonium. All forms of nitrogen significantly increased displacement of F. pseudograminearum from straw under simulated field conditions when straws were either inoculated with T. harzianum or exposed to resident soil microbes. However, in 2 out of 3 experiments urea and nitrate were more effective than ammonium. The results suggest that availability of nitrogen, but not carbon, is limiting the activities of antagonists of F. pseudograminearum in straw, and the way nitrogen is applied can influence the rate of displacement and mortality of the pathogen in host residues.

Screening of new lines of cereal grains for inclusion in Near Infra Red Scan calibrations

The project will provide enough data for a reliable and robust NIRs. It will more fully develop the in vitro method to enable less costly assessment of grains in the future. It will also provide a reliable assessment for DE which is the most expensive component of pig feed.

Improved Post Entry Quarantine Diagnostics

Develop a new diagnostic platform for Post Entry Plant Quarantine to support the detection of Emergency Plant Pests in the Australian Grains and Nursery Industries.

Size optimization of a cantilever beam under deformation-dependent loads with application to wheat stalks

In this paper, we consider the optimization of the cross-section profile of a cantilever beam under deformation-dependent loads. Such loads are encountered in plants and trees, cereal crop plants such as wheat and corn in particular. The wind loads acting on the grain-bearing spike of a wheat stalk vary with the orientation of the spike as the stalk bends; this bending and the ensuing change in orientation depend on the deformation of the plant under the same load.The uprooting of the wheat stalks under wind loads is an unresolved problem in genetically modified dwarf wheat stalks. Although it was thought that the dwarf varieties would acquire increased resistance to uprooting, it was found that the dwarf wheat plants selectively decreased the Young's modulus in order to be compliant. The motivation of this study is to investigate why wheat plants prefer compliant stems. We analyze this by seeking an optimal shape of the wheat plant's stem, which is modeled as a cantilever beam, by taking the large deflection of the stem into account with the help of co-rotational finite element beam modeling. The criteria considered here include minimum moment at the fixed ground support, adequate stiffness and strength, and the volume of material. The result reported here is an example of flexibility, rather than stiffness, leading to increased strength.