Kirsty J. Owen

Mung bean ( Vigna radiata and Vigna mungo ) is susceptible to the endoparasitic root-lesion nematode Pratylenchus thornei ( Pt ), which limits crop productivity. Mung bean roots host symbiotic arbuscular mycorrhizal fungi (AMF), which improve nutrient uptake and plant growth. The interaction of these organisms was previously reported in a single mung bean cultivar to increase P. thornei reproduction, suggesting potential consequences for phenotyping. Therefore, twelve diverse mung bean genotypes were evaluated to investigate the effect of AMF on P. thornei reproduction. A factorial design of genotypes, P. thornei and the AMF species Funneliformis mosseae ( Fm ) was evaluated in two glasshouse experiments. At 16 weeks after sowing, in mung bean inoculated with F. mosseae , there was a significant ( P < 0.05) decrease in P. thornei population densities in nine genotypes whereas no significant effect on P. thornei population densities was observed in the remaining three genotypes. Root colonisation by F. mosseae was not affected by the presence or absence of P. thornei , with consistent root colonisation of ~ 26% across all genotypes. The widest range of P. thornei reproduction between genotypes, and hence the best discrimination of responses, occurred without F. mosseae inoculation. Consequently, it is recommended that mung bean germplasm should be screened for P. thornei resistance in the glasshouse in the absence of AMF for maximal differentiation between genotypes.

A new method of selecting wheat genotypes for tolerance and resistance to Pratylenchus thornei could enhance early-generation selection in wheat-breeding programs. Currently, the tolerance of fixed genotypes is determined in field experiments at a P. thornei-infested site, and resistance indices are determined by inoculated glasshouse experiments. For early-generation selection from segregating populations, resistance screening is limited to assessing single plants for resistance only using glasshouse experiments. The objective of this study was to develop a novel method that evaluates a single plant for both tolerance and resistance by using low density (LD) sowing in the field. Four replicated LD (1, 4, 16 and 32 plants/m²) field experiments evaluated 14 or 15 fixed wheat genotypes over two growing seasons in a field with damaging population densities of P. thornei (>2500 P. thornei/kg soil). To check the validity of these experiments, a linear regression analysis was performed for each experiment between the single plant grain yield and the population density of P. thornei with the published tolerance and resistance indices derived from multiple field and glasshouse experiments, respectively. Tolerance was best determined by the grain yield of each single plant grown at a density of 16 plants/m² in 2021 (R² = 0.63, p < 0.001) and 4 plants/m² in 2022 (R² = 0.79, p < 0.001), when compared to published results of tolerance indices assessed by grain yield from plots grown at 100 plants/m². Resistance was best determined from the final population density of P. thornei in the soil and roots under each single plant when grown at a density of 4 plants/m² in 2021 (R² = 0.73, p < 0.001) and 1 plant/m² in 2022 (R² = 0.54, p = 0.001), when compared to published resistance indices derived from multiple glasshouse resistance experiments. This study demonstrated that LD can be used to effectively identify individual plants with both tolerance and resistance to P. thornei, with single-plant ultra-low densities (ULD) between 1 and 4 plants/m² being the most suitable. The advantage of using ULD sowing in the field for segregating populations of wheat over single plant glasshouse resistance screening experiments is the ability to simultaneously screen plants for tolerance to P. thornei.

Accurate identification and estimation of the population densities of microscopic, soil-dwelling plant-parasitic nematodes (PPNs) are essential, as PPNs cause significant economic losses in agricultural production systems worldwide. This study presents a comprehensive review of emerging techniques used for the identification of PPNs, including morphological identification, molecular diagnostics such as polymerase chain reaction (PCR), high-throughput sequencing, meta barcoding, remote sensing, hyperspectral analysis, and image processing. Classical morphological methods require a microscope and nematode taxonomist to identify species, which is laborious and time-consuming. Alternatively, quantitative polymerase chain reaction (qPCR) has emerged as a reliable and efficient approach for PPN identification and quantification; however, the cost associated with the reagents, instrumentation, and careful optimisation of reaction conditions can be prohibitive. High-throughput sequencing and meta-barcoding are used to study the biodiversity of all tropical groups of nematodes, not just PPNs, and are useful for describing changes in soil ecology. Convolutional neural network (CNN) methods are necessary to automate the detection and counting of PPNs from microscopic images, including complex cases like tangled nematodes. Remote sensing and hyperspectral methods offer non-invasive approaches to estimate nematode infestations and facilitate early diagnosis of plant stress caused by nematodes and rapid management of PPNs. This review provides a valuable resource for researchers, practitioners, and policymakers involved in nematology and plant protection. It highlights the importance of fast, efficient, and robust identification protocols and decision-support tools in mitigating the impact of PPNs on global agriculture and food security.

Root-knot nematodes ( Meloidogyne spp.; RKN) are major plant-parasitic nematodes that cause significant loss to agricultural production. An accurate assessment of the RKN population density at a field level is crucial for decisions about the application of control measures to minimise yield losses. Traditionally, RKN populations are identified and counted by nematologists using a microscope. This method is a specialised, time-consuming process and prone to errors. In our study, we investigated three semi-automated methods to detect and count RKN eggs using image analysis: contour arc (CA), skeleton structure (SS), and extreme point (EP). These methods were used to automate the length measurement of RKN eggs, and the results were compared with traditional methods of quantification. The EP method produced the highest correlation with the manual length measurement of RKN eggs. Further, these methods were used to detect and count RKN eggs to quantify low and highly cluttered images. We estimated the optimal range of the ratio of each method to detect and count RKN eggs. Overall, the EP method computed using mid-width of RKN eggs revealed better detection and counting of RKN eggs as compared to the SS and CA methods. A counting correlation up to R ² = 0.905 was obtained. This study found that the difference between mid-width and the average width of RKN eggs and soil particles could be used to discriminate 70-80 % of soil particles. Our research thus contributes a new feature that can be used to discriminate or classify objects in object detection techniques.

In the subtropical grain region of eastern Australia, two experiments were conducted, one initially with 2490 P. thornei/kg soil, the other with 8150 P. thornei/kg soil at 0–0.9 m soil depth. We determined the effect of P. thornei, residual from a weed-free fallow and pre-cropping with several cultivars each of barley (Hordeum vulgare), faba bean (Vicia faba), chickpea (Cicer arietinum), and wheat (Triticum aestivum) (Phase 1), on the growth of wheat cultivars with intolerance or tolerance to P. thornei (Phase 2). Pratylenchus thornei substantially increased after growing all cultivars of the Phase 1 faba bean, barley, and most cultivars of chickpea and wheat, and decreased after two moderately resistant wheat cultivars and the fallow treatment. The biomass of the Phase 2 tolerant cultivar ranged from 5070 to 6780 kg/ha and the intolerant cultivar 1020 to 4740 kg/ha. There was a negative linear relationship between P. thornei population densities and biomass of the Phase 2 intolerant cultivar but not of the tolerant cultivar. Growers are at risk of financial loss because they are restricted in their choice of crops to reduce damaging population densities of P. thornei. The development of resistant and tolerant crop genotypes can maximize production in P. thornei-affected farming systems.

To understand the yield response of cereal cultivars to Pratylenchus thornei , eight experiments were conducted within the subtropical northern, and temperate southern grain‐producing regions of Australia. Wheat cultivars ( Triticum aestivum ) ranging from susceptible to moderately resistant to P . thornei were grown in Year 1 to establish a range of population densities. In Year 2 before sowing, P . thornei was quantified in each plot and six cereal cultivars were each grown on a similar range of population densities (average minimum to maximum of 3.4–60.6 P . thornei /g soil); P . thornei was quantified again at harvest. In the four experiments in the northern region there was a significant, negative logarithmic response of yield of the three most intolerant/susceptible cultivars as P . thornei population densities increased (yield decreased 172–479 kg/ha per unit increase in log _e ‐transformed P . thornei /g soil). The responsiveness of yield to increasing P . thornei population densities diminished as the tolerance and resistance of the cultivars improved. In the southern region, there was no relationship between yield and P . thornei in three experiments and minor, positive increases in one experiment (1.6 kg/ha per unit increase in P . thornei /g soil). Across both regions, the change in P . thornei population densities from sowing to harvest was logarithmic and positive, and generally greatest in the northern region. The contrast of responses of cereal cultivars between the regions, despite similar population densities of P . thornei , is indicative of the influence of the environment particularly on tolerance, therefore management with a regional focus is essential.

The root lesion nematode (RLN) species Pratylenchus thornei and P. neglectus are widely distributed within cropping regions of Australia and have been shown to limit grain production. Field experiments conducted to compare the performance of cultivars in the presence of RLNs investigate management options for growers by identifying cultivars with resistance, by limiting nematode reproduction, and tolerance, by yielding well in the presence of nematodes. A novel experimental design approach for RLN experiments is proposed where the observed RLN density, measured prior to sowing, is used to condition the randomization of cultivars to field plots. This approach ensured that all cultivars were exposed to consistent ranges of RLN in order to derive valid assessments of relative cultivar tolerance and resistance. Using data from a field experiment designed using the conditioned randomization approach and conducted in Formartin, Australia, the analysis of tolerance and resistance was undertaken in a linear mixed model framework. Yield response curves were derived using a random regression approach and curves modeling change in RLN densities between sowing and harvest were derived using splines to account for nonlinearity. Groups of cultivars sharing similar resistance levels could be identified. A comparison of slopes of yield response curves of cultivars belonging to the same resistance class identified differing tolerance levels for cultivars with equivalent exposures to both presowing and postharvest RLN densities. As such, the proposed design and analysis approach allowed tolerance to be assessed independently of resistance.

The root-lesion nematode, Pratylenchus thornei, can reduce wheat yields by >50%. Although this nematode has a broad host range, crop rotation can be an effective tool for its management if the host status of crops and cultivars is known. The summer crops grown in the northern grain region of Australia are poorly characterised for their resistance to P. thornei and their role in crop sequencing to improve wheat yields. In a 4-year field experiment, we prepared plots with high or low populations of P. thornei by growing susceptible wheat or partially resistant canaryseed (Phalaris canariensis); after an 11-month, weed-free fallow, several cultivars of eight summer crops were grown. Following another 15-month, weed-free fallow, P. thornei-intolerant wheat cv. Strzelecki was grown. Populations of P. thornei were determined to 150 cm soil depth throughout the experiment. When two partially resistant crops were grown in succession, e.g. canaryseed followed by panicum (Setaria italica), P. thornei populations were <739/kg soil and subsequent wheat yields were 3245 kg/ha. In contrast, after two susceptible crops, e.g. wheat followed by soybean, P. thornei populations were 10 850/kg soil and subsequent wheat yields were just 1383 kg/ha. Regression analysis showed a linear, negative response of wheat biomass and grain yield with increasing P. thornei populations and a predicted loss of 77% for biomass and 62% for grain yield. The best predictor of wheat yield loss was P. thornei populations at 0–90 cm soil depth. Crop rotation can be used to reduce P. thornei populations and increase wheat yield, with greatest gains being made following two partially resistant crops grown sequentially.