Browsing by Author "Dhirendra Kumar Singh"

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Biotic Stress Management of Makhana Crops
(CRC Press, 2025) Santosh Hari Krishna Kumar; Tribhuwan Kumar; S. B. Sah; Tamoghna Saha; Sailabala Devi; Kishan Lal; Dhirendra Kumar Singh
Makhana (Euryale ferox Salisb.), a member of the Nymphaeceae family and also called gorgon/fox nut, is a floating annual aquatic plant. This plant grows in 1.5–meter-deep and stagnant wetland ecosystems. The demand for makhana in other countries has surged owing to the expanding potential of makhana. However, more than 80% of the makhana production is restricted to the Bihar State of India. The productivity of this high-value crop is affected by various biotic factors particularly diseases and insect pests such as leaf blight, leaf spot, botrytis grey mold, tumor formation, aphids, case worms, Singhara beetle, gastropod, etc. This leads to yield losses in makhana of 20–25% of the total yields. Therefore, effective management of these diseases and insect pests is crucial to enhancing the production of makhana, which has nutritional, medicinal and ritualistic significance. Limited research is available on the disease management and pests related to makhana as the biology of biotic stresses of makhana and their management is not well understood. Management of diseases of makhana either in the pond or submerged field conditions is not easy, as makhana is generally cultivated along with fish culture. However, we have tried to incorporate available management strategies developed up to now in this book chapter. Application of bio-control agents should be preferred in the case of makhana considering the lives of aquatic fauna and flora in view. The detailed study of the interaction of insect pests and plant pathogens including their involvement in disease development and their role in crop loss is also required to formulate an effective management practice. Therefore, more research work on the control of insect pests like aphids and some prominent diseases must be accelerated to cope with the challenge faced in the case of makhana. © 2026 selection and editorial matter, Dinesh Singh, Rashid Pervez, and Anoop Kumar; individual chapters, the contributors.
Inheritance studies on fusarium wilt resistance in long duration pigeonpea [Cajanus cajan (L.) Millsp.]
(Agricultural Research Communication Centre, 2018) Anil Kumar Singh; Dhirendra Kumar Singh; Rajeev Kumar; Mahendra Narain Singh; Ved Prakash Rai
Fusarium wilt (FW) is a major fungal disease of pigeonpea causing huge economic losses annually and breeding of FW resistant cultivars is essential as other control measures such as fungicides are expensive and harmful to environment. To understand the inheritance of FW resistance, nine populations each of F 1 , F 2 and BCSF 1 (F 1 × susceptible parent) derived from crossing between three adopted but susceptible long duration pigeonpea cultivars (MA-6, MAL-13 and MAL-18) with three FW resistant lines (BSMR-846, BWR-23 and BDN-2029). All F 1 plants were resistant to FW indicating the dominance of resistance. The χ 2 test for goodness-of-fit showed F 2 segregation ratio of 13:3 (one dominant and one recessive), 15:1 (two dominant genes) and 3:1 (one dominant gene) in BSMR-846, BWR-23 and BDN-2029, respectively. The information generated on the genetics of FW resistance will be helpful in development of high yielding and stable wilt resistant, long duration pigeonpea varieties. © 2018, Agricultural Research Communication Centre. All rights reserved.
Isolation and characterization of a novel nitrogen fixer Beijerinckia fluminensis strain BAUMS11 from litchi (Litchi chinensis L.) rhizosphere
(Applied and Natural Science Foundation, 2024) Mahendra Singh; Santosh Kumar; Dhirendra Kumar Singh; Tushar Ranjan; Alok Kumar Pandey
Indiscriminate use of mineral fertilizers has a broad negative impact on soil health. Because of the above, there is an urgent need to search for natural organic alternatives, including using soil microbial resources to replenish soil nutrients for enhanced Agri productivity vis a vis sustainably maintaining soil health. The nitrogen-fixing rhizobacteria (NFR) are such type of bacteria which fix gaseous atmospheric nitrogen in the soil and in nodules of certain plant species in considerable amounts that are readily available for plants' uptake and may be considered as a viable alternative source of mineral nitrogen application. The present study was conducted to isolate the most potent nitrogen-fixing bacteria from the litchi rhizosphere. Hence, Five NFR (NFR1 to NFR5) were isolated from the rhizosphere of litchi orchard of Bihar Agricultural University, Sabour, Bhgalpur, India, based on their ability to fix atmospheric nitrogen in a nitrogen-free mineral salt medium. NFR2 was found to be the most potent in fixing atmospheric nitrogen (11.31 mg N per gram carbon source)among all the isolated rhizobacterial strains. Hence, on the basis of biological nitrogen fixation ability, the isolate NFR2 was subjected to 16S ribosomal RNA (16S rRNA) gene sequencing for molecular characterization. Based on 16S rDNA sequence analysis, NFR2 showed the closest sequence homology with Beijerinckia fluminensis and was identified and reported as Beijerinckia fluminensis strain BAUMS11, Accession number MN533953. The study noticeably indicated that the B. fluminensis strain BAUMS11 was found most efficient in fixing gaseous atmospheric nitrogen and may be used for the manufacturing of nitrogenous biofertilizer, which can fix atmospheric nitrogen to the tune-up to 30 kg N ha-1yr-1. © Author (s).
Morpho-molecular Diversity Analysis in Rice (Oryza sativa L.) Genotypes using Microsatellite Markers
(Agricultural Research Communication Centre, 2025) Simran K. Singh; Mounika Korada; Amrutlal R. Khaire; Dhirendra Kumar Singh; Sonali Vijay Habde; Prasanta Kumar Majhi; Bhawana Rai
Background: The insight concerning genetic diversity and relationship among the rice genotypes is a basic contribution to the crop improvement programs. The present field experiment was conducted to study the level of diversity present in 47 rice genotypes using both morphological and molecular analysis. Methods: The experiment was carried out at Agricultural Research Farm, Banaras Hindu University, Varanasi (U.P.), during Kharif-2019 with 47 rice genotypes. Mahalanobis’ D2 analysis was carried out to evaluate the morphological diversity present among the genotypes and 24 polymorphic SSR markers were used for molecular analysis using the NTSYSpc software. Result: Mahalanobis’ D2 grouped 47 rice genotypes into 6 clusters based on the inter-se genetic distance. The highest inter-cluster distance (1134.14) was observed between clusters II and IV indicating the genotypes present in these clusters to be highly divergent. Molecular diversity analysis grouped the 47 rice genotypes into 3 main clusters i.e., cluster I, cluster II and cluster III, which were further divided into sub-clusters. Polymorphic Information Content varied from 0.12 to 0.86, with an average of 0.465. The highest PIC value was observed for locus RM 507 (0.86). All the 24 primers showed polymorphism and the number of alleles was common for all i.e., 2. Together, the morphological and molecular diversity analysis revealed that Desi Dhan and IR 91143-AC 293-1, Desi Dhan and BD 105, IR 85850 and Lal Sundiya, Chauli and Swarna were the most diverse genotypes among the 47 rice genotypes included in the study. © (2025), (Agricultural Research Communication Centre). All rights reserved.
Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and Iron
(Nature Research, 2025) Akansha K. Singh; Dhirendra Kumar Singh; Shravan Kumar Singh; Vikas Kumar Singh; Arvind Kumar
The present study was conducted to evaluate 30 rice genotypes at three different locations in eastern Uttar Pradesh during the Wet- 2020–21 and determine the impact of GEI on grain yield (tha-1), days to 50% flowering, grain Fe content (PPM), and grain Zn content (PPM). The study also aimed to identify the genotypes that displayed the best performance according to the multi-trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), and factor analysis and ideotype-design (FAI-BLUP) index. AMMI analysis demonstrated significant variation for environment (E), genotype (G), and genotype-by-environment interaction (GEI) (P < 0.01) for all the studied traits. The AMMI1 biplot showed that PC1 explained the majority of the variation for GY (77.6%), DTF (90.5%), Fe (73.5%), and Zn (86.8%), helping to identify stable and high-performing genotypes. AMMI2 biplot further resolved complex GEI patterns, highlighting genotypes with specific adaptability to individual environments. The GGE biplot revealed clear “which-won-where” patterns for GY, DTF, Fe, and Zn, explaining 94.37%, 99.71%, 83.49%, and 96.93% of GEI variation, respectively. BLUP analysis using a linear mixed model revealed significant GEI effects for GY, DTF, Fe, and Zn across 30 rice genotypes in three environments. Low heritability was observed for Fe (28.2%) and moderate for GY (54.4%) and Zn (56.4%), while DTF showed high heritability with strong genotypic accuracy. Genotype G7 was identified as stable, early, high-yielding, and rich in Fe based on HMGV, RPGV, and HMRPGV indices. The MTSI, MGIDI and FAI-BLUP analysis revealed that BHU-SKS-1 (G15) and IR105696 -1–2-3–1-1–1 -B (G9) were the most stable and best mean performer for high grain yield and high grain Fe & Zn content, while IR 108,195–3-1–1-2 (G7) was the most stable and best mean performer for high grain yield and high grain Fe content with early flowering. © The Author(s) 2025.
QTL mapping reveals different set of candidate genes governing stable and location specific QTLs enhancing zinc and iron content in rice
(Springer Science and Business Media B.V., 2024) Sonali Vijay Habde; Shravan Kumar Singh; Dhirendra Kumar Singh; Arun Kumar Singh; Rameswar Prasad Sah; Mounika Korada; Amrutlal R. Khaire; Prasanta Kumar Majhi; Uma Maheshwar Singh; Vikas Kumar Singh; Arvind Kumar
Rice is a cornerstone of global food security. Addressing contemporary dual challenge of global food and nutritional security, this study focuses on identification of genomic regions/QTLs that control uptake and translocation of micronutrients (Zn and Fe) in rice. Using mapping population derived from a cross between URG 30 (Zn 32.2 ppm and Fe 15.3 ppm) and Rajendra Kasturi (Zn 19.2 ppm and Fe 9.5 ppm), evaluated at three locations, we identified 8 QTLs each for grain Zn and Fe content distributed across 8 chromosomes. Notably 3 major QTLs for grain Zn content (chromosomes 1, 5 and 6) and 1 major QTL for grain Fe content (chromosome 3) were identified with phenotypic variance (PV) ranging from 10.7 to 15.19% for Zn and 12.10% for Fe. Two stable QTLs for grain Zn content (PV 5.89–8.98% and 3.18–13.62%) and one for Fe content (PV 1.84–7.59%) were consistently identified at two locations. Seven transgressive segregants for yield and Zn content are identified at two locations. Correlation analysis uncovered significant positive associations between grain Zn and Fe content. We also interpreted the functional role of 24 candidate genes including key candidates OsZIP1, OsSPR1, OsZIP2, OsPEZ1, OsZIP6, OsNAS1, OsNAS2, OsYSL3 underlying stable and location specific QTLs in the context of mineral uptake strategies utilized by rice. The research supports marker assisted breeding efforts towards substantial nutritional enhancement in rice grain. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.
Yield attributing traits of high zinc rice (Oryza sativa L.) genotypes with special reference to principal component analysis
(Action for Sustainable Efficacious development and Awareness, 2022) Partha Pratim Behera; Shravan Kumar Singh; Kasireddy Sivasankarreddy; Prasanta Kumar Majhi; Bodeddula Jayasankar Reddy; Dhirendra Kumar Singh
Total 21 high zinc rice genotypes were evaluated under five different locations for 14 different yield attributing traits, including grain yield/plant (gm) to determine the pattern of variation, the relationship among the individuals and their characteristics through Principal Component Analysis (PCA) during the Kharif-2017. PCA was done for all the locations individually as well as pooled analysis for all locations using R software. Out of the 14 PCs, the initial four PCs contributed more to the total variability. The highest cumulative variability of the first four PCs found at Bhikaripur (81.11%) followed by BHU Agriculture research farm-II (79.23%) etc. and Pooled variability was 76.61%. Pooled data analysis indicates PCA biplot or loading plot of first two principal components revealed that days to maturity, days to 1st flowering date and days to 50% flowering loaded more on the first component and number of spikelets per panicles, number of grains/panicles, grain weight per panicle, grain yield/plant accounted more variation in the second component compared to the other parameters. Thus, the pooled analysis of principal component analysis revealed the characters contributing to the variation and genetic variability that exists in these rice genotypes. This is because the genotypes BRRIdhan 72, Sambamahsuri and Swarna were identified in different principle components related to grain yield and grain quality, and were also located farthest away from biplot origin in individual PCA based biplot. So they may be employed to improve yield attributing factors like total effective tiller number. PC1, PC2 and PC3 have days to first flowering and days to 50% flowering, hence their genotypes may be valuable in producing early maturing cultivars. Thus, the results revealed that wide range of variability was shown by different traits of the genotypes which can be utilized in rice improvement programmes. © ASEA.