Australian Grain Research Articles

Machine vision solutions for monitoring pest snails in australian no-till cropping fields: An exploration of spectral characteristics and detectability

In the realm of Australian grain agriculture, the invasive presence of two round snail species, Cernuella virgata and Theba pisana, alongside two conical counterparts, Cochlicella acuta and Cochlicella Barbara, has inflicted substantial economic losses. Effective integrated pest management hinges on precise monitoring of snail populations, yet current manual sampling techniques prove labour-intensive and susceptible to errors. This study underscores the imperative for a machine vision system capable of accurately and efficiently surveilling snail populations in the diverse landscapes of Australian broadacre no-till cropping fields. The inherent challenges of varied plant residues, gravels and soil types in the fields demand a sophisticated optical system to detect small, clustered and camouflaged snails. Through a meticulous exploration of spectral features and detectability by employing different combinations of wavelengths and machine learning algorithms, this research yielded promising results that live round snails, dead round snails, live conical snails, dead conical snails and complex field materials can be classified with F1 scores range from 0.7 to 0.9. This paper not only highlights the potential of such a machine vision system but also delineates ongoing challenges that warrant further investigation. The insights derived from this study serve as a crucial guide for the development of a robust machine vision system aimed at mitigating the impact of pest snails in agricultural fields.

Assessing the sub‐lethal impacts of insecticides on aphid parasitoids through laboratory‐based studies

AbstractAphids are a major pest of cropping systems throughout the world. In most cases, crop aphids are controlled with broad‐spectrum insecticides; although generally very effective at preventing yield loss, this approach risks non‐target damage to beneficial organisms. In the last 20 years, a number of selective insecticides have become available to control aphids while minimising harm to other arthropods. Previous studies have found that two such insecticides, flonicamid and afidopyropen, cause only low‐level acute mortality impacts on aphid parasitoids in Australian grain crops. However, little research has examined the sub‐lethal effects of these chemicals, which could induce various physiological changes that impact pest control. We hypothesised that both flonicamid and afidopyropen have negative effects that extend beyond the immediate acute mortality previously published. To test this hypothesis, we undertook a series of experiments to determine the effects of flonicamid and afidopyropen, along with the synthetic pyrethroid gamma‐cyhalothrin, on aphid parasitism (mummification) rate, emergence rate of the next generation and the next generation sex ratio in three important aphid parasitoids, Aphidius colemani (Viereck), Diaeretiella rapae (M'Intosh) and Aphelinus abdominalis (Dalman). Analogous with previous research, our acute toxicity bioassays showed that all three insecticides had low (<30%) mortality impacts. Although sub‐lethal impacts could not be assessed for D. rapae due to the low level of aphid parasitism by that species, our findings showed negative impacts on fecundity in surviving A. abdominalis and A. colemani. Of particular note is the increase in International Organisation for Biological Control ratings to moderate (30%–80% mortality and/or reproductive reduction) when mortality and reduced fecundity effects were combined to determine overall fitness impacts. Gamma‐cyhalothrin typically resulted in higher negative impacts on A. abdominalis and A. colemani (compared with flonicamid and afidopyropen); however, quite surprisingly, these impacts were not rated as highly toxic. Taken together, our results suggest that, even when sub‐lethal impacts are considered, flonicamid and afidopyropen are useful tools for farmers targeting aphid populations while minimising the non‐target impacts on parasitoids. We recommend semi‐field and/or field trials to further assess the impacts of these insecticides on aphid parasitoid populations.

Indigenous Australian grass seeds as grains: macrostructure, microstructure and histochemistry.

Utilization of grains of local grasses by Australia's First Nations people for food and connection to Country has largely been lost due to colonization. Native Australian grain production has the potential to deliver environmental, economic, nutritional and cultural benefits to First Nations people and the wider community. Revitalization of the native grain food system can only be achieved if relevant properties of the grains are elucidated. This study aimed to characterize the grain structure and histochemistry of four Australian native grasses: Dactyloctenium radulans (Button Grass), Astrebla lappacea (Curly Mitchell Grass), Panicum decompositum (Native Millet) and Microlaena stipoides (Weeping Grass). For these species, as well as wheat and sorghum, whole-grain images were obtained via stereo microscopy, starch and the embryo were visualized, and sections of fixed grains were imaged via bright-field and fluorescence microscopy. The shape, size and colour of the whole native grains varied between the species. The aleurone layer was one-cell thick in the native species, as in the domesticated grains, except for Weeping Grass, which had a two-cell-thick aleurone. In the native grains, endosperm cell walls appeared thinner than in wheat and sorghum. Starch granules in Button Grass, Curly Mitchell Grass and Native Millet were found mainly in the central region of the starchy endosperm, with very few granules in the sub-aleurone layer, whereas Weeping Grass had abundant starch in the sub-aleurone. Protein appeared most abundant in the aleurone and sub-aleurone layers of the native grains, although in Button Grass, the starchy endosperm was observed to be rich in protein, as in wheat and sorghum. As a proportion of the whole grain, the embryo was larger in the native species than in wheat. The differences found in the grain properties among the four native Australian species have important implications for the agri-food industry in a changing climate.

Hybrid RNA sequencing of broad bean wilt virus 2 from faba beans.

High-throughput sequencing (HTS) is an important tool for plant virus detection and discovery. HTS technologies such as Nanopore sequencing has been rapidly developing in recent years, and offers new possibilities for fast routine diagnostic applications. This study compared MiSeq (Illumina) RNA-Seq with the MinION sequencer (Oxford Nanopore Technologies) (ONT) direct-RNA-Seq methods to detect and sequence the broad bean wilt virus 2 (BBWV2) genome. The Illumina BBWV2 RNA1 and RNA2 genome segments were intact and matched with ONT with 99.1% and 98.8% nucleotide identity (nt) match, respectively. The RNA1 genome derived from ONT had deletions within the nucleoside-triphosphate binding and protease factor open-reading frames, and the upstream of five untranslated regions. However, its RNA2 was intact, and no sequencing errors were observed. The ONT and Illumina RNA1 and RNA 2 BBWV2 genome segments clustered together phylogenetically along with other none-Fabaceae species, BBWV2 RNA1 NCBI accession KC790225, and RNA 2 MW556592 both from China. This is the first BBWV2 genome study reported in Australia and forms part of the strategy to integrate versatile diagnostic genomics tools at the border to safeguard the Australian grains industry. IMPORTANCE Globally, viral diseases impair the growth and vigor of cultivated crops such as grains, leading to a significant reduction in quality, marketability, and competitiveness. As an island nation, Australia has a distinct advantage in using its border to prevent the introduction of damaging viruses, which threaten the continental agricultural sector. However, breeding programs in Australia rely on imported seeds as new sources of genetic diversity. As such, it is critical to remain vigilant in identifying new and emerging viral pathogens, by ensuring the availability of accurate genomic diagnostic tools at the grain biosecurity border. High-throughput sequencing offers game-changing opportunities in biosecurity routine testing. Genomic results are more accurate and informative compared to traditional molecular methods or biological indexing. The present work contributes to strengthening accurate phytosanitary screening, to safeguard the Australian grains industry, and expedite germplasm release to the end users.

Enhancing biosecurity against virus disease threats to Australian grain crops: current situation and future prospects

Australia is a major grain exporter, and this trade makes an important contribution to its economy. Fortunately, it remains free of many damaging virus diseases and virus vectors found elsewhere. However, its crop biosecurity is under increasing pressure from global ecological, climatic, and demographic challenges. Stringent biosecurity and plant health programs safeguard Australian grain production from damaging virus and virus vector incursions entering via different pathways. These programs formerly relied upon traditional testing procedures (indicator hosts, serology, PCRs) to intercept incoming virus-contaminated plant material. Recently, the integration of rapid genomic diagnostics innovation involving High Throughput Sequencing (HTS) smart tools into sample testing schedules is under exploration to improve virus testing accuracy, efficiency, and cost effectiveness under diverse circumstances. This process includes evaluating deployment of Illumina and Oxford Nanopore Technology shotgun sequencing. It also includes evaluating targeted viral genome HTS and virus vector metabarcoding approaches. In addition, using machine learning and deep learning capacities for big data analyses and remote sensing technologies will improve virus surveillance. Tracking damaging virus variants will be improved by surveillance networks which combine virus genomic-surveillance systems with an interoperable virus database. Sequencing Australian virus specimen collections will help ensure the accuracy of virus identifications based solely on genetic information. Enhancing routine diagnosis and data collection using these innovations will improve post entry virus interception and background virus and vector surveillance. This will help reduce the frequency of new incursions, improve virus management during eradication, containment and other plant health activities, and achieve more profitable Australian grain production.

Looking beyond Glyphosate for Site-Specific Fallow Weed Control in Australian Grain Production

Summer annual weed species in northern Australian summer fallows are frequently present at low densities and, increasingly, are glyphosate-resistant, creating the need for alternative herbicides for site-specific weed control. Alternative non-selective herbicide treatments are effective on problematic summer fallow weeds; however, many are yet to be evaluated as site-specific (spot spraying) treatments. This study aimed to identify herbicides that could be used in place of glyphosate to control larger/mature Chloris virgata and Sonchus oleraceus plants. The response of these weed species to 12 herbicide treatments was evaluated in pot experiments conducted over summer/autumn 2022. Despite herbicide treatments not being consistently effective across both species, there were instances where control was achieved by some herbicide treatments. S. oleraceus was controlled (i.e., ≤10% plant survival) by glufosinate-ammonium, paraquat and also with protoporphyrinogen-oxidase (PPO)-inhibiting herbicides saflufenacil, tiafenacil and trifludimoxazin. However, these results were not consistent in repeated studies or for C. virgata. Glyphosate was the only herbicide that controlled C. virgata. A glyphosate replacement as a spot-spraying treatment was not identified, and until further studies are more successful, alternative approaches are needed to preserve the ongoing effectiveness of this herbicide.

Mining the Australian Grains Gene Bank for Rust Resistance in Barley.

Global barley production is threatened by plant pathogens, especially the rusts. In this study we used a targeted genotype-by-sequencing (GBS) assisted GWAS approach to identify rust resistance alleles in a collection of 287 genetically distinct diverse barley landraces and historical cultivars available in the Australian Grains Genebank (AGG) and originally sourced from Eastern Europe. The accessions were challenged with seven US-derived cereal rust pathogen races including Puccinia hordei (Ph-leaf rust) race 17VA12C, P. coronata var. hordei (Pch-crown rust) race 91NE9305 and five pathogenically diverse races of P. striiformis f. sp. hordei (Psh-stripe rust) (PSH-33, PSH-48, PSH-54, PSH-72 and PSH-100) and phenotyped quantitatively at the seedling stage. Novel resistance factors were identified on chromosomes 1H, 2H, 4H and 5H in response to Pch, whereas a race-specific QTL on 7HS was identified that was effective only to Psh isolates PSH-72 and PSH-100. A major effect QTL on chromosome 5HL conferred resistance to all Psh races including PSH-72, which is virulent on all 12 stripe rust differential tester lines. The same major effect QTL was also identified in response to leaf rust (17VA12C) suggesting this locus contains several pathogen specific rust resistance genes or the same gene is responsible for both leaf rust and stripe rust resistance. Twelve accessions were highly resistant to both leaf and stripe rust diseases and also carried the 5HL QTL. We subsequently surveyed the physical region at the 5HL locus for across the barley pan genome variation in the presence of known resistance gene candidates and identified a rich source of high confidence protein kinase and antifungal genes in the QTL region.

Segmentation of Sandplain Lupin Weeds from Morphologically Similar Narrow-Leafed Lupins in the Field

Narrow-leafed lupin (Lupinus angustifolius) is an important dryland crop, providing a protein source in global grain markets. While agronomic practices have successfully controlled many dicot weeds among narrow-leafed lupins, the closely related sandplain lupin (Lupinus cosentinii) has proven difficult to control, reducing yield and harvest quality. Here, we successfully trained a segmentation model to detect sandplain lupins and differentiate them from narrow-leafed lupins under field conditions. The deep learning model was trained using 9171 images collected from a field site in the Western Australian grain belt. Images were collected using an unoccupied aerial vehicle at heights of 4, 10, and 20 m. The dataset was supplemented with images sourced from the WeedAI database, which were collected at 1.5 m. The resultant model had an average precision of 0.86, intersection over union of 0.60, and F1 score of 0.70 for segmenting the narrow-leafed and sandplain lupins across the multiple datasets. Images collected at a closer range and showing plants at an early developmental stage had significantly higher precision and recall scores (p-value < 0.05), indicating image collection methods and plant developmental stages play a substantial role in the model performance. Nonetheless, the model identified 80.3% of the sandplain lupins on average, with a low variation (±6.13%) in performance across the 5 datasets. The results presented in this study contribute to the development of precision weed management systems within morphologically similar crops, particularly for sandplain lupin detection, supporting future narrow-leafed lupin grain yield and quality.

Using machine learning with case studies to identify practices that reduce greenhouse gas emissions across Australian grain production regions

It is difficult to identify farm management practices that consistently provide greenhouse gas (GHG) abatement at different locations because effectiveness of practices is greatly influenced by climates and soils. We address this knowledge gap by identifying practices that provide abatement in eight case studies located across diverse conditions in Australian’s grain-producing areas. The case studies focus on soil-based emissions of nitrous oxide (N2O) and changes in soil organic carbon (SOC), simulated over 100 years for 15 cropping management scenarios. Average changes in the balance of GHG from both N2O emissions and SOC sequestration (∆GHG balance) and gross margins compared to a high emissions baseline were determined over 25 and 100 simulated years. Because scenarios providing the greatest abatement varied across individual case studies, we aggregated the data over all case studies and analysed them with a random forest data mining approach to build models for predicting ∆GHG balance. Increased cropping intensity, achieved by including cover crops, additional grains crops, or crops with larger biomass in the rotation, was the leading predictor of ∆GHG balance across the scenarios and sites. Abatement from increased cropping intensity averaged 774 CO2-e ha−1 year−1 (25 years) and 444 kg CO2-e ha−1 year−1 (100 years) compared to the baseline, with reduced emissions from SOC sequestration offsetting increased N2O emissions for both time frames. Increased cropping intensity decreased average gross margins, indicating that a carbon price would likely be needed to maximise GHG abatement from this management. To our knowledge, this is the first time that the random forest approach has been applied to assess management practice effectiveness for achieving GHG abatement over diverse environments. Doing so provided us with more general information about practices that provide GHG abatement than would have come from qualitative comparison of the variable results from the case studies.

Non-destructive insect metabarcoding as a surveillance tool for the Australian grains industry: a first trial for the iMapPESTS smart trap

Surveillance and long-term monitoring of insect pest populations are of paramount importance to limit dispersal and inform pest management. Molecular methods have been employed in diagnostics, surveillance and monitoring for the past few decades, often paired with more traditional techniques relying on morphological examinations. Within this context, the ‘iMapPESTS: Sentinel Surveillance for Agriculture’ project was conceptualised to enhance on-farm pest management decision-making via development and deployment of smart traps, able to collect insects, as well as recording associated environmental data. Here, we compared an iMapPESTS ‘Sentinel’ smart trap to an alternative suction trap over a 10-week period. We used a non-destructive insect metabarcoding approach complemented by insect morphological diagnostics to assess and compare aphid species presence and diversity across trap samples and time. Furthermore, we paired this with environmental data recorded throughout the sampling period. This methodology recorded a total of 497 different taxa from 70 traps over a 10-week period in the grain-growing region in western Victoria. This included not only the 14 aphid target species, but an additional 12 aphid species, including a new record for Victoria. Ultimately, with more than 450 bycatch species detected, this highlighted the value of insect metabarcoding, not only for pest surveillance, but also at a broader ecosystem level, with potential applications in integrated pest management and biocontrol.

Use of digital technology for research data and information transfer within the Australian grains sector: A case study using Online Farm Trials

CONTEXTAgriculture is experiencing rapid change with the widespread availability of industry-specific technological and digital innovations. One example of this is Online Farm Trials (OFT), a user-facing web portal that systematises on-farm and field-based cropping research trial data for Australia's grains industry. The portal delivers access to research data, including legacy data, from thousands of grains trials projects that have been supplied by industry contributors. The portal is well established, having been informed by regular stakeholder input that has guided and informed the continued improvement of the portal from its development and implementation to continued operations. OBJECTIVEResearch was conducted across three time-points to assess the usage and application of OFT, and to examine its perceived impact on users to facilitate access to information supporting on-farm decision making and practice change within the Australian grains industry. METHODSQuantitative and qualitative data (portal usage and website analytics, surveys, in-depth interviews) were collected at three time points over 6 years with the aim of examining the usage and application of the portal. Portal users, data contributors, and other stakeholders from the grains and agriculture industries participated in this research. RESULTS AND CONCLUSIONSOver the three time points, a total of 89 surveys were completed and 49 interviews were conducted. Portal usage data confirms consistency in the number of visitors over time; most users of the portal were from Australia, with many accessing the portal on multiple occasions. Survey and interview data demonstrate that OFT is valued, widely used, and that the data on the portal are being broadly applied. Access to information and data through the portal (including legacy data) is used to support knowledge and to make sector-relevant decisions, and is assisting portal users in their workplace and work practices. The availability of data and information through the portal is increasing connections between industry and stakeholders across the grains sector. However, the trust and quality of contributor data has been consistently raised as a point of discussion by some portal users. SIGNIFICANCEThis research demonstrates the contribution that this data portal has on usage, adoption and application within the Australian grains industry. The insights and learnings about the application of digital technology for data and information access for the grains sector may be applicable to other agricultural sectors.

Vector species, pasture legume host range, and impact on grain legumes of an Australian soybean dwarf virus isolate.

Soybean dwarf virus (SbDV; family Tombusviridae, genus Luteovirus, species Soybean dwarf virus) can cause damaging disease epidemics in cultivated plants of the family Fabaceae. The biological characteristics of SbDV isolate WA-8, including its vector species, host range, and impact on Australian grain legume cultivars, were investigated in a series of glasshouse experiments. Isolate WA-8 was classified as the YP strain, as it was transmitted by Acyrthosiphon pisum (pea aphid) and Myzus persicae (green peach aphid) and infected known strain indicator species. Of the 18 pasture legume species inoculated with SbDV, 12 were SbDV hosts, including eight that had not been identified previously as hosts. When inoculated with SbDV, field pea (Pisum sativum), faba bean (Vicia faba), lentil (Lens culinaris), and narrow-leafed lupin cv. Jurien were the most susceptible (70 to 100% plant infection rates), and albus lupin (Lupinus albus), chickpea (Cicer arietinum), and narrow-leafed lupin cv. Mandelup were less susceptible (20 to 70%). Over the course of three experiments, chickpea was the most sensitive to infection, with a > 97% reduction in dry above-ground biomass (AGB) and a 100% reduction in seed yield. Field pea cv. Gunyah, faba bean, and lentil were also sensitive, with a 36 to 61% reduction in AGB. Field pea cv. Kaspa was relatively tolerant, with no significant reduction in AGB or seed yield. The information generated under glasshouse conditions in this study provides important clues for understanding SbDV epidemiology and suggests that it has the potential to cause damage to Australian grain legume crops in the field, especially if climate change facilitates its spread.

Profitable, low-emission nitrogen application strategies in Western Australian dryland cropping

Context Australian grain producers may need to report their farm greenhouse emissions. Accordingly, nitrogen fertiliser application strategies will need to include consideration of their environmental as well as economic impacts. Aims We aim to identify the nitrogen application strategies suited to dryland cropping in Western Australia that are highly profitable and that generate lower emissions. Methods Simulation modelling is used to examine the gross margins and emissions associated with four broadly different nitrogen strategies at 14 locations in the grainbelt of Western Australia for different frequencies of cropping. Key results Strategies that generate high gross margins and moderate emissions often focus on maximising the gross margin of crop production, and apply a decile 5 view of unfolding seasonal conditions. A similarly useful strategy applies nitrogen in a fixed ratio where a tonne of expected cereal receives 45 units of nitrogen from various sources, and a tonne of expected canola receives 70 units of nitrogen from various sources. Where a farmer prefers to apply a constant rate of nitrogen, then exceedingly high or low rates of application should mostly be avoided, either for economic or for environmental reasons, with the better option at many locations being to apply 50 or 75 kg N/crop ha. Conclusions A few preferred nitrogen application strategies are suggested to be applicable to dryland cropping in the study region. The strategies achieve high profits and generate moderate or low emissions. Implications Selection of highly profitable and lower emission nitrogen application strategies across the study region can deliver sizeable economic and environmental benefits.

Should crop sequences in Western Australia include more lupins?

Context Reducing greenhouse gas emissions is an increasing priority for Australian grain producers. Could substituting lupins for canola, as a rotational break crop, enable farmers to reduce their emissions by less use of nitrogenous fertilisers? Aim This study aims to identify if replacing canola with lupins in rotations at a range of locations in Western Australia’s grainbelt is environmentally and economically attractive. Methods Bio-economic simulation modelling is used to examine the gross margins and emissions associated with replacement of canola by lupins at 14 locations in the grainbelt of Western Australia in various land use sequences. Key results Replacing canola with lupins unambiguously leads to reduced emissions in crop sequences at all locations considered. However, the higher gross margins from canola production cause lupins to only be a preferred break crop option at 4 of the 14 locations. Even with various plausible incentives to favour lupins, they remain economically unattractive at most locations other than those where lupins are well adapted to the environment. Conclusions Lupins’ current lack of commercial attractiveness for farmers limits its role in emissions reduction in the region’s farming systems. Implications The profitability of lupins needs to increase if lupins are to be widely readopted. This requires developing higher yielding lupin varieties, grain quality improvements, and policy changes to reward lower emission cereals. However, this study shows these changes, apart from yield improvement, are unlikely in the short term. At locations with suitable soils alternative pulse crops may offer higher gross margins whilst delivering emission reductions.

Lethal impacts of insecticides and miticides on three agriculturally important aphid parasitoids

Globally, agricultural industries are contending with escalating insecticide resistance evolution among a number of arthropod pests. The Australian grains industry is no exception, with the indiscriminate use of broad-spectrum insecticides contributing to the rise of resistant aphid populations. As such, there is a growing appreciation for the need to harness the full potential of biological control offered by aphid parasitoid wasps, yet few studies have quantified the non-target effects of pesticide use on these taxa using Australian populations and rates relevant to the grains industry. With this in mind, we followed IOBC protocols and tested the acute toxicity of 20 insecticides and miticides against three important aphid parasitoids: Diaeretiella rapae (M’Intosh), Aphidius colemani Viereck, and Aphelinus abdominalis (Dalman). We found toxicities across the three species were generally consistent for many of the active ingredients tested, however notable differences for paraffinic oil, diafenthiuron, indoxacarb, and thiodicarb were observed. Overall, the aphelinid, A. abdominalis, showed greater tolerance to several active ingredients, with lower IOBC toxicity rating categories compared with the two braconid species, D. rapae and A. colemani. Of the eight active ingredients tested that are currently registered to control aphids in Australian grain crops, only two (flonicamid and afidopyropen) had low toxicity across all three parasitoid species, with four active ingredients resulting in very high toxicity for one or more species. We additionally found that the toxicity of synthetic pyrethroids differed between chemical types, with type I pyrethroids (bifenthrin) found to be more toxic than type II (gamma-cyhalothrin and lambda-cyhalothrin) pyrethroids. Taken together, these results highlight the risks of making generalised toxicity inferences across active ingredients and species. We recommend further toxicity testing be undertaken in the field, in addition to quantifying the sub-lethal effects of insecticides and miticides on aphid parasitoids.

Infrared Thermal Imaging and Morpho-Physiological Indices Used for Wheat Genotypes Screening under Drought and Heat Stress

Bread wheat, one of the largest broadacre crops, often experiences various environmental stresses during critical growth stages. Terminal drought and heat stress are the primary causes of wheat yield reduction worldwide. This study aimed to determine the drought and heat stress tolerance level of a group of 46 diverse wheat genotypes procured from the Australian Grains Gene Bank, Horsham, VIC Australia. Two separate drought stress (DS) and heat stress (HS) pot experiments were conducted in separate growth chambers. Ten days after complete anthesis, drought (40 ± 3% field capacity for 14 days) and heat stress (36/22 °C for three consecutive days) were induced. A significant genotype × environment interaction was observed and explained by various morpho-physiological traits, including rapid, non-destructive infrared thermal imaging for computational water stress indices. Except for a spike length in DS and harvest index in HS, the analysis of variance showed significant differences for all the recorded traits. Results showed grains per spike, grains weight per spike, spike fertility, delayed flag leaf senescence, and cooler canopy temperature were positively associated with grain yield under DS and HS. The flag leaf senescence and chlorophyll fluorescence were used to measure each genotype's stay-green phenotype and photosystem II activity after DS and HS. This study identified the top ten best and five lowest-performing genotypes from drought and heat stress experiments based on their overall performance. Results suggest that if heat or drought adaptive traits are brought together in a single genotype, grain yield can be improved further, particularly in a rainfed cropping environment.

Molecular characterization of Brassica genebank germplasm confirms taxonomic identity and reveals low levels and source of taxonomic errors

AbstractCrop germplasm conserved in genebanks, are a fundamental resource of genetic diversity for crop improvement activities, underpinning future food security and sustainable agricultural practices. However, taxonomic errors in genebank germplasm (due to misclassification, contamination and poor data collation) restrict the effective use of this material for correct purpose. Earlier studies investigating species genetic diversity using genebank germplasm, have shown varying levels of taxonomic error within the Brassica species. In response to this reported taxonomic error of global collections, together with the availability of a multiplex PCR (MPCR) marker, targeting the specific chromosomes (A, B and C) of the six Brassica species in U's triangle, this study was undertaken to confirm the taxonomic identity of accessions within the Australian Grains Genebank's (AGG) long-term Brassica collection. A total of 5161 accessions were analysed with MPCR for taxonomic identification, of which, 4842 (93.8%) were confirmed to be consistent (correct) with their labelled taxonomy, while the remaining 319 (6.2%) were identified as taxonomically inconsistent (in-error). Through the evaluation of earlier regeneration and original seed of the error accessions with MPCR, we determined that 80.9% of the taxonomic errors were traced back to the original seed, while 19.1% of errors were the result of genebank seed regeneration handling practices. Results from this study directly enhance information of the AGG Brassica collection and shape directions for distribution, acquisition and regeneration practices within the AGG and potentially other global genebanks, which will facilitate in a more effective use of these valuable genetic resources by researchers and breeders.

Herbicide residues in Australian grain cropping soils at sowing and their relevance to crop growth

Herbicides are used extensively in Australian grain cropping systems. Despite occasional observations of herbicide-induced phytotoxicity, there is little information on the persistence and carryover of multiple herbicide classes in cropping soils and the risk to subsequent crops. Two soil surveys were conducted, in 2015 (n = 40) and 2016 (n = 42), across different Australian grain cropping fields prior to sowing of winter crops, and soil samples analysed for herbicide residues (16 analytes in 2015 and 22 analytes in 2016). Samples in 2015 were taken at two depths (0–10 cm and 10-30 cm), whilst samples in 2016 were taken in topsoil (0–10 cm) only, but from two discrete locations in each field. Our research in both years found at least one herbicide (or herbicide metabolite) residue at all sites, with a median of 6 analytes detected in 2015 and 7 analytes detected in 2016. The most frequently detected residues were glyphosate and its primary breakdown product aminomethylphosphonic acid (AMPA), in 87 and 100%, respectively, of topsoil (0–10 cm) samples in 2015, and 67 and 93% of samples in 2016. The median concentration of glyphosate in 2015 was 0.12 mg kg−1, while AMPA was 0.41 mg kg−1. In 2016, median concentrations of glyphosate and AMPA were 0.22 mg kg−1 and 0.31 mg kg−1. Residues of 2,4-dichlorophenoxyacetic acid, trifluralin and diflufenican were also detected in >40% of topsoil samples in both seasons, but with median concentrations of <0.05 mg kg−1. A literature review found limited availability of phytotoxicity thresholds for major grain crops exposed to soilborne herbicide residues. A risk assessment using available thresholds suggested that although up to 29% of fields contained trifluralin residues that could constrain cereal crop growth, and 24% of fields contained residues of phenoxy or sulfonylureas that could affect dicotyledonous crops, the majority of these fields when planted with tolerant crops would be unlikely to be affected by herbicide residues. More work is required to ascertain the spatial distribution, bioavailability and phytotoxicity of residues and residue mixtures to enable a more accurate agronomic risk assessment.

Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors

Wheat dominates the Australian grain production market and accounts for 10–15% of the world’s 100 million tonnes annual global wheat trade. Accurate wheat yield prediction is critical to satisfying local consumption and increasing exports regionally and globally to meet human food security. This paper incorporates remote satellite-based information in a wheat-growing region in South Australia to estimate the yield by integrating the kernel ridge regression (KRR) method coupled with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the grey wolf optimisation (GWO). The hybrid model, ‘GWO-CEEMDAN-KRR,’ employing an initial pool of 23 different satellite-based predictors, is seen to outperform all the benchmark models and all the feature selection (ant colony, atom search, and particle swarm optimisation) methods that are implemented using a set of carefully screened satellite variables and a feature decomposition or CEEMDAN approach. A suite of statistical metrics and infographics comparing the predicted and measured yield shows a model prediction error that can be reduced by ~20% by employing the proposed GWO-CEEMDAN-KRR model. With the metrics verifying the accuracy of simulations, we also show that it is possible to optimise the wheat yield to achieve agricultural profits by quantifying and including the effects of satellite variables on potential yield. With further improvements in the proposed methodology, the GWO-CEEMDAN-KRR model can be adopted in agricultural yield simulation that requires remote sensing data to establish the relationships between crop health, yield, and other productivity features to support precision agriculture.

Environmental effect on temporal patterns in lentil seed quality development

AbstractTo maximize seed longevity, seeds should be harvested at optimal maturity, that is, when seeds have acquired maximum physiological quality before deterioration begins. The aim of this study was to map the variation in temporal patterns of lentil (Lens culinaris Medik.) seed quality development when grown across four regeneration environments, which differ in the level of temperature and humidity control throughout the growing season, at the Australian Grains Genebank. Seeds of two lentil accessions (76080 and 76072) were harvested at different stages throughout development, commencing at 21 d after 50% anthesis until a maximum of 130 d. At each harvest, physiological quality traits, including germinability (fresh and dried seeds) and seed longevity, were determined, as well as seed dry weight and moisture content. Seeds of both accessions, and in all environments, started to accumulate physiological quality early on in development but did not reach their maximum until 3–54 d after mass maturity. The temporal patterns of desiccation tolerance and storage longevity were highly influenced by the environmental conditions during the maturation drying phase, affecting both ‘when’ maximum quality was attained and for how long it was maintained, thereafter. Seeds did not show a typical developmental response, rather variation was observed in seed quality development both between and within accessions grown in the different environments. The poorest storage longevity was seen when seeds of both accessions were grown in the cooler, temperature-controlled glasshouse, and the maximum longevity was observed in the warmer, semi-protected environments of the green and the big igloo for accessions 76080 and 76072, respectively.