Multivariate morphometric analysis of Meloidogyne spp. in Tamil Nadu, India: A PCA-based approach to population differentiation in carrot ecosystems

Root-knot nematodes (Meloidogyne spp.) are major agricultural pests threatening carrot (Daucus carota L.) cultivation in Tamil Nadu, India, causing significant yield losses. This study employed Principal Component Analysis (PCA) to investigate the morphometric traits of second-stage juveniles (J2) and adult females from eight Meloidogyne spp. populations collected from carrot-growing regions across Tamil Nadu. Morphological characterization involved extracting J2 and adult females, preparing whole mounts in glycerin, dissecting female perineal patterns, and recording morphometric measurements using Camera Lucida, phase contrast, and scanning electron microscopy. It revealed variations in key traits, including body and stylet length, with significant differences between nematode populations from hill and plain regions. PCA reduced the high-dimensional data, explaining 93.80% and 93.45% of the total variance in females and juveniles, respectively. Strong positive correlations were observed between body length and median bulb length in juveniles, dorsal gland orifice (DOGO), and body width in females. Negative correlations were also noted for stylet width and DOGO in females. PCA clustering revealed three distinct groups, with juveniles from Shoolagiri and Hosur forming one group and females from the Nilgiris and Kodaikanal clustering together, indicating geographic and environmental influence on morphometric traits. Stylet length emerged as a key distinguishing factor for both juvenile and female populations. These findings clearly explain the morphometric diversity within Meloidogyne populations, offering new insights into nematode management strategies in Tamil Nadu’s carrot ecosystems. This study also underscores the utility of PCA in streamlining morphometric analysis, enhancing the precision and speed of nematode identification.

Integrating grafting and bio-inputs for sustainable management of root knot nematode, Meloidogyne incognita, in tomato cultivation

IntroductionRoot-knot disease in tomato, caused by Meloidogyne incognita, presents a major challenge to global tomato production. This study explored a sustainable management approach by evaluating host-plant resistance through grafting combined with bio-inputs in farmers’ fields with high natural infestations of M. incognita.MethodsThe commercial F1 hybrid Shivam® tomato was grafted onto bacterial wilt-resistant eggplant rootstocks, EG 203 and TS 03. Two field experiments were conducted with six treatment groups to compare the performance of 'EG 203-tomato' and 'TS 03-tomato' grafts against the non-grafted hybrid tomato, both with and without bio-input applications. The bio-input protocol included soil application of neem cake (250 kg/ha) and soil and seedling drenching at nursery and transplant stages using biocontrol agents (Bacillus subtilis, Trichoderma asperellum, and Purpureocillium lilacinum, each at 5 g/L).ResultsResults indicated that the 'EG 203-tomato' graft demonstrated strong resistance to M. incognita, while the 'TS 03-tomato' graft remained susceptible, akin to the non-grafted Shivam® hybrid. The EG 203-tomato graft treated with the bio-inputs achieved the highest suppression of M. incognita, with reductions of 76.8–77.7% juvenile populations in the soil, 62.0–66.1% in female populations within roots, 73.6–77.3% in egg masses per female, and 38.1–40.0% in eggs per egg mass. This treatment also resulted in the lowest root gall index, measured at 2.0–2.1.DiscussionIn both trial locations, 'EG 203-tomato' graft plants enriched with bio-inputs outperformed the non-grafted tomato in growth and yield metrics, achieving greater plant height (54.6–54.7 cm), leaf count (81.3–84.3 per plant), branch count (3.1–3.7) and fruit yield (10.8–11.5 kg/plant). These findings support the recommendation of EG 203-tomato grafts with bio-input management as an effective large-scale strategy for tomato growers combating M. incognita infestations