The root-knot nematode, Meloidogyne javanica, is one of the most damaging plant-parasitic nematodes, affecting chickpea and causing substantial yield losses worldwide. The damage potential and population dynamics of this nematode in chickpea in Ethiopia have yet to be investigated. In this study, six chickpea cultivars were tested using 12 ranges of initial population densities (Pi) of M. javanica second-stage juveniles (J2): 0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64 and 128 J2 (g dry soil)-1 in a controlled glasshouse pot experiment. The Seinhorst yield loss and population dynamics models were fitted to describe population development and the effect on different measured growth variables. The tolerance limit (TTFW) for total fresh weight ranged from 0.05 to 1.22 J2 (g dry soil)-1, with corresponding yield losses ranging from 31 to 64%. The minimum yield for seed weight (mSW) ranged from 0.29 to 0.61, with estimated yield losses of 71 and 39%. The 'Haberu' and 'Geletu' cultivars were considered good hosts, with maximum population densities (M) of 16.27 and 5.64 J2 (g dry soil)-1 and maximum multiplication rate (a) values of 6.25 and 9.23, respectively. All other cultivars are moderate hosts for M. javanica; therefore, it is crucial to initiate chickpea-breeding strategies to manage the tropical root-knot nematode M. javanica in Ethiopia.

Plant-parasitic nematodes pose a silent yet devastating threat to global agriculture, causing significant yield losses and economic damage. Traditional detection methods such as soil sampling, microscopy, and molecular diagnostics are slow, labor-intensive, and often ineffective in early-stage infestations. Nano biosensors: cuttingedge analytical tools that leverage nanomaterials like carbon nanotubes, graphene, and quantum dots to detect nematode-specific biochemical markers such as volatile organic compounds (VOCs) and oesophageal gland secretions, with unprecedented speed and accuracy. The real breakthrough lies in the fusion of artificial intelligence (AI) and nano-biosensor technology, forging a new frontier in precision agriculture. By integrating AI's powerful data analysis, pattern recognition, and predictive capabilities with the extraordinary sensitivity and specificity of nano-biosensors, it becomes possible to detect biomolecular changes in real-time, even at the earliest stages of disease progression. AI-driven nano biosensors can analyze real-time data, enhance detection precision, and provide actionable insights for farmers, enabling proactive and targeted pest management. This synergy revolutionizes nematode monitoring, paving the way for smarter, more sustainable agricultural practices. This review explores the transformative potential of AI-powered nano-biosensors in advancing precision agriculture. By integrating these technologies with smart farming systems, we move closer to real-time, costeffective, and field-deployable solutions, ushering in a new era of high-tech, eco-friendly crop protection.

Root-lesion nematodes, particularly Pratylenchus neglectus and P. crenatus (PNC), are widely distributed in New Zealand and cause significant damage to maize roots, reducing crop productivity. Despite their economic importance, no comprehensive assessment of commercial maize hybrids' resistance to PNC has been conducted in the country. Significant variation was observed in the nematode reproduction factor (Rf) and final population (Pf) among hybrids. In Experiment 1 (initial population (Pi) = 1250 PNC kg(-)(1) soil), Rf ranged from 3.1 in hybrid P8500 to 7.1 in hybrid P9127, with Pf values ranging from 3863 to 8903 PNC kg(-)(1) soil + roots in 45 days. In Experiment 2 (Pi = 750 PNC kg(-)(1) soil), Rf ranged from 18.4 in hybrid P1613 to 37.5 in hybrid P8805, with Pf values from 13,784 to 28,426 PNC kg(-)(1) soil + roots in 60 days. These results indicate active nematode reproduction and substantial hybrid-dependent variation in host response. Experiment 3 examined the impact of varying initial inoculum densities (500, 1000 and 1500 PNC kg(-)(1) soil), showing a dose-dependent increase in Pf and corresponding root damage. Susceptible hybrid (P9127) exhibited up to 42% root dry weight and 22% shoot dry weight reductions. This study is the first systematic evaluation of PNC resistance in New Zealand maize hybrids. It identifies P9127 and P8805 as highly susceptible, and P0891, P8500, and P1613 as moderately resistant. These findings offer valuable benchmarks for future breeding and support nematode management in New Zealand.

Crops produced using the practice of continuous cropping can become seriously damaged by plant-parasitic nematodes, an important indicator of continuous cropping obstacles. As a typical and important perennial economic crop, dragon fruit is prone to serious plant-parasitic nematode infestation; however, whether it encounters continuous cropping obstacles remains unclear. Here, we studied plant-parasitic nematodes (Meloidogyne spp. and Tylenchorhynchus sp.) in the soil and roots, soil nematode communities, metabolic footprint, soil integrated fertility, and the yield of intensively planted dragon fruit under non-continuous cropping (Y1) and 3 years (Y3) and 5 years (Y5) of continuous cropping, to determine potential continuous-cropping obstacles and factors that affect the yield of this fruit. The largest numbers of plant-parasitic nematodes in the soil and roots were observed in Y5; the associated yield was reduced, and the dragon fruit was severely stressed. Further analysis of the composition, diversity, and ecological function indices of soil nematodes showed that the soil ecological environment deteriorated after 3 years of continuous cropping, with Y5 having the worst results. Similarly, the soil at Y5 had a significant inhibitory effect on the growth and reproduction of Caenorhabditis elegans. Mantel test analysis and a random forest model showed that soil available phosphorus, soil exchange calcium, and soil nematode abundance and diversity were related significantly to yield. Partial least squares path modeling revealed that soil fertility and soil nematode diversity directly impacts the yield of continuously cropped dragon fruit. In summary, continuous cropping obstacles occurred in Y5 of intensive dragon fruit cultivation, with soil nematode diversity and soil fertility determining the crop's yield.

Plant-parasitic nematodes (PPNs) are significant agricultural pests that cause substantial crop losses globally. This study investigated the abundance and distribution of PPNs concerning elevation in rice fields in Malang District, East Java, Indonesia. Nematodes were sampled across elevation gradients between 0 to over 1000 meters above sea level (masl). Pratylenchus, Aphelenchoides, and Longidorus, were found in the soil and rice roots in Malang District. Pratylenchus dominated the relative abundance of PPNs in the soil at 0-400 masl, whereas Longidorus dominated at 600 to > 1000 masl. In rice root samples, Pratylenchus sp. also dominated at 0-400 masl and Longidorus was dominated at 800-100 masl. The population density of Pratylenchus negatively correlated to elevation, pH, soil organic matter, and carbon organic. However, soil temperature positively correlated with the population density of Pratylenchus. Elevation and pH showed a negative influence on the population density of Aphelenchoides, whereas soil temperature showed a positive influence on the population density of Aphelenchoides. Soil temperature negatively correlated to the population density of Longidorus, whereas elevation and soil humidity positively influenced the population density of Longidorus. However, the population density of Longidorus increased with higher elevation and soil humidity. Understanding the specific relationships between PPN populations and environmental factors is essential for developing effective pest management strategies. Targeted approaches that consider these ecological dynamics can help mitigate crop damage and enhance rice production in varying environmental conditions, especially in the Java region.

The prevalence and abundance of plant-parasitic nematodes (PPNs) associated with corn ( Zea mays; Poaceae) in the Anuradhapura district of Sri Lanka are poorly understood. This study investigated the occurrence and population densities of major PPN genera associated with corn. Over 92% of the corn fields were positive for PPNs in all the sampled fields. Major PPN genera identified were Pratylenchus spp. (71.4%), Helicotylenchus spp. (28.6%), Meloidogyne spp. (21.4%), Criconemella spp. (21.4%), and Hoplolaimus spp. (35.7%). The mean population density of Pratylenchus spp. was 2020 nematodes kg-1 of soil, in the Anuradhapura corn fields. During the cropping season from November (2021) to February (2022), all PPN genera except Meloidogyne spp. were observed. Pratylenchus spp. were detected at levels below 1000 nematodes kg-1 of soil at the seedling stage, except in Kelenikawewa where the initial population was 1865 nematodes kg-1 . At the time of harvest, Pratylenchus spp. increased by 2 to 10 folds. These findings suggest a potential impact of Pratylenchus spp. on corn yield in Anuradhapura, highlighting the need for further research to assess damage levels and the overall effect of PPNs on corn production in Sri Lanka.

The present investigation aimed to analyze the community structure and its relationship with selected soil parameters in the Gangetic plains. In total, 60 soil samples were collected from the fields of vegetable crops at different pH. Thirty-nine soil-inhabited nematodes were isolated and identified to the species level where possible. The most prevalent nematodes encountered were Hoplolaimus indicus followed by Helicotylenchus californicus and Pratylenchus thornei with 66.67, 53.33, and 40.00% frequency, respectively. Prominence Value of H. indicus (271.62), H. californicus (115.87), and P. thornei (31.62) was higher as compared to other PPN species. The result indicated that there is a significant correlation between the plant-parasitic species and pH (e.g., Rotylenchus reniformis; r = 0.991). On the other hand, EC showed a significant negative correlation with R. reniformis (r = -0.965). However, organic carbon and sand percentage significantly correlated with PPN. Organic carbon was highly correlated (r = 1.00) with R. reniformis. In contrast, organic carbon showed a significant positive correlation with Rhabditis and no correlation with Mesodorylaimus. In conclusion, the high-producing regions suggested a considerable range of plant-parasitic and free-living nematodes, with the highest diversity in Baghpat (H' = 0.604 +/- 0.14). Therefore, further studies are required to evaluate the ecological and threshold level of damage by the PPN. Additionally, the current finding suggests that soil fertility in upper 'Gangetic plains' agricultural fields was reduced due to the high load of PPN infection. However, ecological indices could help assess the plant and soil health of all the regions in future investigations.

Nematodes are highly abundant soil organisms, and their presence can have profound effects on soil health and plant growth. Among them, Rotylenchus species are known for their economic importance as root ectoparasites or semi-endoparasites, inflicting damage on a wide variety of economically important plants. Their impact on agricultural crops, ornamentals, and fruit and forest trees makes them significant subjects for study. In this paper, we present an updated species list of Rotylenchus spp., a genus of spiral plant-parasitic nematodes belonging to the family Hoplolaimidae. As of the current research, 107 species within the Rotylenchus genus have been recognized. To facilitate the identification of Rotylenchus species, we introduce a novel browser-based interactive key for the identification of such huge number of species. This web-assisted tool utilizes a list of 48 diagnostic character-states belonging to 11 characters for identifying 107 Rotylenchus species, providing an easy and accurate method for the identification of these plant-parasitic nematodes. This paper contributes to the understanding of Rotylenchus species' diversity and their taxonomy while offering a valuable tool to aid researchers, agricultural professionals, and plant pathologists in accurate species identification and subsequent management strategies.