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30 results on '"Manohar, Surendra S."'

6. Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut

Author

Sharma, Vinay, primary, Gangurde, Sunil S., additional, Nayak, Spurthi N., additional, Gowda, Anjan S., additional, Sukanth, B.S., additional, Mahadevaiah, Supriya S., additional, Manohar, Surendra S., additional, Choudhary, Rakeshkumar S., additional, Anitha, T., additional, Malavalli, Sachin S., additional, Srikanth, S.N., additional, Bajaj, Prasad, additional, Sharma, Shailendra, additional, Varshney, Rajeev K., additional, Latha, Putta, additional, Janila, Pasupuleti, additional, Bhat, Ramesh S., additional, and Pandey, Manish K., additional

Published
2023
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9. Discovery of Major Quantitative Trait Loci and Candidate Genes for Fresh Seed Dormancy in Groundnut

Author

Bomireddy, Deekshitha, primary, Gangurde, Sunil S., additional, Variath, Murali T., additional, Janila, Pasupuleti, additional, Manohar, Surendra S., additional, Sharma, Vinay, additional, Parmar, Sejal, additional, Deshmukh, Dnyaneshwar, additional, Reddisekhar, Mangala, additional, Reddy, Devarapalli Mohan, additional, Sudhakar, Palagiri, additional, Reddy, Bommu Veera Bhaskara, additional, Varshney, Rajeev K., additional, Guo, Baozhu, additional, and Pandey, Manish K., additional

Published
2022
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12. Single Seed-Based High-Throughput Genotyping and Rapid Generation Advancement for Accelerated Groundnut Genetics and Breeding Research

Author

Parmar, Sejal, primary, Deshmukh, Dnyaneshwar B., additional, Kumar, Rakesh, additional, Manohar, Surendra S., additional, Joshi, Pushpesh, additional, Sharma, Vinay, additional, Chaudhari, Sunil, additional, Variath, Murali T., additional, Gangurde, Sunil S., additional, Bohar, Rajaguru, additional, Singam, Prashant, additional, Varshney, Rajeev K., additional, Janila, Pasupuleti, additional, and Pandey, Manish K., additional

Published
2021
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15. G × E interactions in QTL introgression lines of Spanish-type groundnut (Arachis hypogaea L.)

Author

Rathnakumar, A. L., primary, Manohar, Surendra S., additional, Nadaf, Hajisaheb L., additional, Patil, Sudam C., additional, Deshmukh, Milind P., additional, Thirumalaisamy, P. P., additional, Kumar, Narendra, additional, Lalwani, H. B., additional, Nagaraju, P., additional, Yenagi, Basavaraj, additional, Patil, S. S., additional, Suryawanshi, J., additional, Khatod, J., additional, Kumbhar, C. T., additional, Kathmale, D. K., additional, Naik, K. S. S., additional, Rajesh, Prasanna, additional, Vemana, K., additional, Sundaravadana, S., additional, Premalatha, N., additional, Variath, Murali T., additional, Chaudhari, S., additional, Radhakrishnan, T., additional, Pandey, Manish K., additional, Varshney, Rajeev K., additional, and Janila, Pasupuleti, additional

Published
2020
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16. Improvement of three popular Indian groundnut varieties for foliar disease resistance and high oleic acid using SSR markers and SNP array in marker-assisted backcrossing

Author

Shasidhar, Yaduru, primary, Variath, Murali T., additional, Vishwakarma, Manish K., additional, Manohar, Surendra S., additional, Gangurde, Sunil S., additional, Sriswathi, Manda, additional, Sudini, Hari Kishan, additional, Dobariya, Keshavji L., additional, Bera, Sandip K., additional, Radhakrishnan, Thankappan, additional, Pandey, Manish K., additional, Janila, Pasupuleti, additional, and Varshney, Rajeev K., additional

Published
2020
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18. Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

Author

Kumar, Rakesh, primary, Janila, Pasupuleti, additional, Vishwakarma, Manish K., additional, Khan, Aamir W., additional, Manohar, Surendra S., additional, Gangurde, Sunil S., additional, Variath, Murali T., additional, Shasidhar, Yaduru, additional, Pandey, Manish K., additional, and Varshney, Rajeev K., additional

Published
2019
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20. Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut.

Author

Kumar, Rakesh, Janila, Pasupuleti, Vishwakarma, Manish K., Khan, Aamir W., Manohar, Surendra S., Gangurde, Sunil S., Variath, Murali T., Shasidhar, Yaduru, Pandey, Manish K., and Varshney, Rajeev K.

Subjects
SEED dormancy, GLYCINE (Plants), ABSCISIC acid, GENES, SEED development, GENETIC markers
Abstract

Summary: The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human‐made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut. [ABSTRACT FROM AUTHOR]

Published
2020
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21. Assessing variability for disease resistance and nutritional quality traits in an interspecific collection of groundnut (Arachis hypogaea)

Author

Bera, Sandip K., primary, Manohar, Surendra S., additional, Variath, Murali T., additional, Chaudhari, Sunil, additional, Yaduru, Shasidhar, additional, Thankappan, Radhakrishnan, additional, Narayana, Manivannan, additional, Kurapati, Sadaiah, additional, Pandey, Manish K., additional, Sudini, Hari K., additional, Shanmugavel, Saravanan, additional, Kulandaivelu, Ganesamurthy, additional, Varshney, Rajeev K., additional, and Pasupuleti, Janila, additional

Published
2018
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22. Assessment of the genetic diversity of groundnut (Arachis hypogaeaL.) genotypes for kernel yield, oil and fodder quantity and quality under drought conditions

Author

Abadya, Seltene, Shimelis, Hussein, Pasupuleti, Janila, Mashilo, Jacob, Chaudhari, Sunil, and Manohar, Surendra S.

Abstract

The objective of this study was to determine drought tolerance, kernel (KY) and fodder yield and quality amongst diverse groundnut genotypes for direct production or breeding. Hundred genotypes were evaluated at ICRISAT, India during 2018–2019 and 2019–2020 under drought‐stressed (DS) and nonstressed (NS) conditions. Data were collected on KY; oil content (OC); oil yield (OY); protein content; palmitic, stearic, oleic, and linoleic acid contents; haulm yield (HY); and fodder quality parameters such as the contents of dry matter, ash, nitrogen (NC), neutral detergent fiber (NDFDM), acid detergent fiber (ADFDM), acid detergent lignin (ADLDM), in vitro digestibility, and metabolizable energy. Data were subjected to parametric and nonparametric statistical analyses. Combined analysis of variance revealed significant (P< .05) genotype differences for all assessed traits. Genotype × water regime interaction effects were significant for KY, OC, ash, NC, NDFDM, and ADLDM. Kernel yield positively and significantly (P< .05) correlated with OY (r= .99), LAC (r= .13), ash (r= .32), and NDFDM (r= .54) under DS condition. Haulm yield was positively and significantly (P< .05) correlated with OC (r= .24), NDFDM (r= .19), ADFDM (r= .18), and ADLDM (r= .17) under DS condition. The study identified four genotypes with high kernel and haulm yields, and six genotypes with high oleic acid content. Further, 10 genotypes were selected with relatively better drought tolerance. The selected genotypes are recommended for further breeding and variety release adapted to drought conditions. Diverse groundnut germplasm collections are available and can be evaluated for drought.Strong correlations observed among haulm quality traits under drought‐stressed and optimum conditions.The study identified genotypes with high kernel and haulm yields and drought tolerance.

Published
2021
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27. Genomic Tools in Groundnut Breeding Program: Status and Perspectives

Author

Janila, P., primary, Variath, Murali T., additional, Pandey, Manish K., additional, Desmae, Haile, additional, Motagi, Babu N., additional, Okori, Patrick, additional, Manohar, Surendra S., additional, Rathnakumar, A. L., additional, Radhakrishnan, T., additional, Liao, Boshou, additional, and Varshney, Rajeev K., additional

Published
2016
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28. Molecular breeding for introgression of fatty acid desaturase mutant alleles ( ahFAD2A and ahFAD2B ) enhances oil quality in high and low oil containing peanut genotypes

Author

Janila, Pasupuleti, primary, Pandey, Manish K, additional, Shasidhar, Yaduru, additional, Variath, Murali T, additional, Sriswathi, Manda, additional, Khera, Pawan, additional, Manohar, Surendra S, additional, Nagesh, Patne, additional, Vishwakarma, Manish K, additional, Mishra, Gyan P, additional, Radhakrishnan, T, additional, Manivannan, N, additional, Dobariya, KL, additional, Vasanthi, RP, additional, and Varshney, Rajeev K, additional

Published
2016
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29. Genotype x Environment Interactions for Oil Content in Peanut and Stable High-Oil-Yielding Sources.

Author

Janila, P., Manohar, Surendra S., Patne, Nagesh, Variath, Murali T., and Nigam, S. N.

Subjects
*PEANUT breeding, *GENOTYPE-environment interaction, *FATS & oils, *FOOD, *BREEDING
Abstract

Peanut (Arachis hypogaea L.) genotypes with superior and stable agronomic performance and high oil content were identified from testing of 160 advanced breeding lines over six seasons. The study revealed significant genotype and genotype x environment (G x E) interaction determining oil and protein content; shelling outturn; and pod, kernel, and oil yield in peanut. The variability among genotypes was high across the environments for pod yield (546-7382 kg ha-1), oil yield (301-2742 kg ha-1), oil content (37-60%), 100-seed weight (21-127 g), and protein content (19-31%). The GGE biplot technique revealed that ICGV 05155 is a stable genotype for oil yield with an average oil yield of 1886 kg ha-1. ICGV 05155 recorded highest average pod yield of 4928 kg ha-1, kernel yield of 3420 kg ha-1, and oil content of 55.1%. ICGV 06049, ICGV 06041, ICGV 06420, and ICGV 03043 were other genotypes with stable oil yield. Simple regression showed significant contributions of oil content (18-54%), and kernel yield (92-99%) to oil yield across the environments. Simultaneous improvement of kernel yield and oil content is feasible in breeding programs, as kernel yield had no negative association with oil content. The high oil content genotypes, ICGV 05155, ICGV 06049, ICGV 06041, ICGV 06420, and ICGV 03043, with stable oil yield were promoted to multilocation adaptive trials required for their release for cultivation and used as parents in breeding programs and development of mapping population to identify quantitative trait loci (QTL) governing oil content. [ABSTRACT FROM AUTHOR]

Published
2016
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30. Foliar fungal disease-resistant introgression lines of groundnut ( Arachis hypogaea L.) record higher pod and haulm yield in multilocation testing.

Author

Pasupuleti, Janila, Pandey, Manish K., Manohar, Surendra S., Variath, Murali T., Nallathambi, Premalatha, Nadaf, Hajisaheb L., Sudini, Harikishan, Varshney, Rajeev K., and Singh, R.

Subjects
PEANUT disease & pest resistance, INTROGRESSION (Genetics), FUNGAL diseases of plants, LEAF spots, PEANUT breeding, GENOTYPE-environment interaction, PREVENTION
Abstract

Introgression lines ( ILs) of groundnut with enhanced resistance to rust and late leaf spot ( LLS) recorded increased pod and haulm yield in multilocation testing. Marker-assisted backcrossing ( MABC) approach was used to introgress a genomic region containing a major QTL that explains >80% of phenotypic variance ( PV) for rust resistance and 67.98% PV for LLS resistance. ILs in the genetic background of TAG 24, ICGV 91114 and JL 24 were evaluated for two seasons to select 20 best ILs based on resistance, productivity parameters and maturity duration. Multilocation evaluation of the selected ILs was conducted in three locations including disease hot spots. Background genotype, environment and genotype × environment interactions are important for expression of resistance governed by the QTL region. Six best ILs namely ICGV 13192, ICGV 13193, ICGV 13200, ICGV 13206, ICGV 13228 and ICGV 13229 were selected with 39-79% higher mean pod yield and 25-89% higher mean haulm yield over their respective recurrent parents. Pod yield increase was contributed by increase in seed mass and number of pods per plant. [ABSTRACT FROM AUTHOR]

Published
2016
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