RESUMO
While conducting field trial of 82 genotypes of bottle gourd at Delhi during 2020-2021, a particular genotype, IC-0262269 was found to be affected by chlorotic curly stunt disease (CCSD). The affected plants were severely stunted and bearing very small chlorotic and crinkle leaves. The disease incidence in the said genotype was as high as 80% among different replicated trial blocks. The application of PCR using a generic primers specific to begomoviruses, as well as species-specific PCR diagnostics to six tomato-infecting begomoviruses: tomato leaf curl New Delhi virus (ToLCNDV), tomato leaf curl Palampur virus (ToLCPalV), tomato leaf curl Joydebpur virus (ToLCJoV), tomato leaf curl Gujrat virus (ToLCGuV), tomato leaf curl Bangalore virus (ToLCBV), and chilli leaf curl virus (ChiLCV) showed that, only ToLCPalV could be detected in the genotype IC-0262269. Following, rolling circle amplification, cloning and sequencing of full-length DNA-A and DNA-B genome of an isolate BoG1-ND from the genotype IC-0262269 revealed association of ToLCPalV with the disease. The successful agro-infection of the cloned genome of BoG1-ND (DNA-A and DNA-B) in the plants of Nicotiana benthamiana and bottle gourd demonstrated that ToLCPalV is the causal begomovirus of CCSD. The study provides the first evidence of the natural occurrence of ToLCPalV in bottle gourd crop and also showed that the bottle gourd genotype IC-0262269 is super-susceptible to ToLCPalV. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03838-y.
RESUMO
Tomato leaf curl New Delhi virus (TolCNDV) causes yellow mosaic disease, which poses a significant biotic constraint for sponge gourd cultivation, potentially resulting in crop loss of up to 100%. In the present investigation, 50 diverse genotypes were screened for 3 years under natural epiphytotic conditions. A subset of 20 genotypes was further evaluated across four different environments. The combined analysis of variance revealed a significant genotype × environment interaction. Eight genotypes consistently exhibited high and stable resistance in the preliminary screening and multi-environment testing. Furthermore, genotype plus genotype × environment interaction biplot analysis identified DSG-29 (G-3), DSG-7 (G-2), DSG-6 (G-1), and DSGVRL-18 (G-6) as the desirable genotypes, which have stable resistance and better yield potential even under diseased conditions. The genotype by yield × trait biplot analysis and multi-trait genotype-ideotype distance index analysis further validated the potential of these genotypes for combining higher yield and other desirable traits with higher resistance levels. Additionally, resistant genotypes exhibited higher activities of defense-related enzymes as compared to susceptible genotypes. Thus, genotypes identified in our study will serve as a valuable genetic resource for carrying out future resistance breeding programs in sponge gourd against ToLCNDV.
RESUMO
Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.