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"Micronutrient"

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"Micronutrient"

Research Articles
Correlation and Path Analysis of Association among Yield, Micronutrients, and Protein Content in Rice Accessions Grown Under Aerobic Condition from Karnataka, India
Nguyen Phuong Thuy, Nguyen Ngoc Trai, Bui Dang Khoa, Nguyen Hoang Xuan Thao, Vuong Tuan Phong, Quach Van Cao Thi
Plant Breed. Biotech. 2023;11(2):117-129.   Published online June 1, 2023
DOI: https://doi.org/10.9787/PBB.2023.11.2.117

Genetic variability and correlation analysis are fundamental references for the innovative development of breeding programs to improve varieties and desirable traits. In the present study, the correlation and path analysis was conducted to understand the association among yield, micronutrients (iron and zinc), and protein content under aerobic conditions in local rice landraces from various agro ecological regions of Karnataka, India. The grain yield per plant showed a significant positive correlation with plant height, the tiller number, spikelet fertility, flag leaf length, and test weight. The zinc content was negatively correlated with grain yield per plant. The phenotypic path-coefficient analysis revealed that the total number of tillers, grain length, test weight, and harvest index exhibited a positive direct effect on grain yield per plant, while Grain protein content showed a low direct effect on this trait. This study also indicated that harvest index, flag leaf length, spikelet fertility, and test weight could be considered to make for a higher yield.

Citations

Citations to this article as recorded by  
  • Deciphering Genetic Variability, Correlation and Path Analysis for Yield and Yield Related Traits in Early Rice (Oryza sativa) Genotypes Under the Direct-Seeded Rice (DSR) System
    Shravan Kumar Singh, Vivekanand Sirohi, Ritik Digamber Bisane, Vemula Anjula Krishna, Amrit Prasad Poudel, Akansha Singh
    Agricultural Research.2026; 15(2): 706.     CrossRef
  • Characterization of Iranian rice genetic resources for key grain quality traits
    Mostafa Modarresi
    Genetic Resources.2026; 7(13): 153.     CrossRef
  • Genetic variability, heritability and genetic advance in Iranian local rice genotypes for yield, and some agronomic traits
    Mostafa Modarresi
    Reproduction and Breeding.2026; 6(1): 9.     CrossRef
  • A new approach for evaluating maize transgressive segregants and their three-way cross potential in the S4 convergent breeding population
    Nuniek Widiayani, Muhammad Fuad Anshori, Nasaruddin Nasaruddin, Muh Farid, Ifayanti Ridwan, Abd. Haris Bahrun, Muhammad Azrai, Amin Nur, Purnama Isti Khaerani, Willy Bayuardi Suwarno, Karlina Syahruddin, Naeem Khan, Majed A. Alotaibi, Mahmoud F. Seleiman
    BMC Plant Biology.2025;[Epub]     CrossRef
  • Agronomic performance of advanced double haploid elite rice ( Oryza sativa ) lines in Estuaire, Gabon
    Yonnelle Dea Moukoumbi, Esther Pegalepo, Mouritala Sikirou, Julia Edoxie Olong Obiang, Roland Bocco, Romaric Avou Tsoboua, Adote Herve Gildas Akueson, Yedomon Ange Bovys Zoclanclounon, Moussa Sie
    Cogent Food & Agriculture.2025;[Epub]     CrossRef
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QTL Analysis for Fe and Zn Concentrations in Rice Grains Using a Doubled Haploid Population Derived from a Cross Between Rice (Oryza sativa) Cultivar 93-11 and Milyang 352
So-Myeong Lee, Ju-Won Kang, Ji-Yoon Lee, Jeonghwan Seo, Dongjin Shin, Jun-Hyeon Cho, Sumin Jo, You-Chun Song, Dong-Soo Park, Jong-Min Ko, Hee-Jong Koh, Jong-Hee Lee
Plant Breed. Biotech. 2020;8(1):69-76.   Published online March 1, 2020
DOI: https://doi.org/10.9787/PBB.2020.8.1.69

Biofortification is a cost-effective method for increasing the availability of micronutrients. Rice breeding for high levels of micronutrients is one of the best approaches to solve the problem of malnutrition. In this study, we developed a doubled haploid (DH) population derived from a cross between the rice cultivars 93-11 and Milyang 352 and evaluated QTLs for grain micronutrients and grain shape. Two co-localized QTLs, qFe3-1 and qZn3-1, were identified in the interval between ah03002520 and cmb0336.5 on chromosome 3, which explained 17.6% and 10.5% of the phenotypic variation, respectively. Correlation analysis between agronomic and micronutrient traits showed positive correlations between grain Fe and Zn contents but a negative correlation between grain Fe content and length-to-width ratio. This indicated the possibility of simultaneously increasing both Fe and Zn content in rice grains for improving the micronutrient profile of rice. We selected some promising lines by recombinant selection using linked markers on chromosome 3. The co-localized QTLs qFe3-1 and qZn3-1 might be useful for the improvement of biofortified rice breeding by marker-assisted selection and gene pyramiding.

Citations

Citations to this article as recorded by  
  • Precision breeding strategy to enrich iron and zinc in rice
    Rajvir Kaur, Rupinder Kaur, Renu Khanna, Gurjeet Singh, Dinesh Kumar Saini, Amandeep, Kumari Neelam, Navjot Sidhu, Ranvir Singh Gill
    Cereal Research Communications.2026; 54(1): 657.     CrossRef
  • Genomic Insights into the Genetic Control of Iron and Zinc Content in Rice: A Meta-analysis of Key Hotspots
    Om Prakash Raigar, Gaurav Augustine, Rupinder Kaur, Nitika Sandhu
    Journal of Plant Growth Regulation.2025;[Epub]     CrossRef
  • Analysis of quantitative trait loci and candidate gene exploration associated with cold tolerance in rice (Oryza sativa L.) during the seedling stage
    Sumin Jo, Seong-Gyu Jang, Sais-Beul Lee, Ji-Yoon Lee, Jun-Hyeon Cho, Ju-Won Kang, Yeongho Kwon, So-Myeong Lee, Dong-Soo Park, Soon-Wook Kwon, Jong-Hee Lee
    Frontiers in Plant Science.2025;[Epub]     CrossRef
  • Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated GBS-based SNP linkage map
    Mark Ian C. Calayugan, Tapas Kumer Hore, Alvin D. Palanog, Amery Amparado, Mary Ann Inabangan-Asilo, Gaurav Joshi, Balachiranjeevi Chintavaram, B. P. Mallikarjuna Swamy
    Scientific Reports.2024;[Epub]     CrossRef
  • Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents
    P. Senguttuvel, Padmavathi G, Jasmine C, Sanjeeva Rao D, Neeraja CN, Jaldhani V, Beulah P, Gobinath R, Aravind Kumar J, Sai Prasad SV, Subba Rao LV, Hariprasad AS, Sruthi K, Shivani D, Sundaram RM, Mahalingam Govindaraj
    Frontiers in Plant Science.2023;[Epub]     CrossRef
  • Genome-wide association study (GWAS) with high-throughput SNP chip DNA markers identified novel genetic factors for mesocotyl elongation and seedling emergence in rice (Oryza sativa L.) using multiple GAPIT models
    Nkulu Rolly Kabange, Simon Alibu, Youngho Kwon, So-Myeong Lee, Ki-Won Oh, Jong-Hee Lee
    Frontiers in Genetics.2023;[Epub]     CrossRef
  • Genetic variability, G × E interaction and stability for iron and zinc content in sorghum grains in advanced breeding lines
    R. Madhusudhana, K. Hariprasanna, C. Aruna, Gowri M. Sajjanar, N.G. Hanamaratti, S. Sameera, Vilas A. Tonapi
    Journal of Cereal Science.2023; 110: 103653.     CrossRef
  • Improvement of Selection Efficiency of Haploid Maize Seeds Using Fluorescence Imaging
    Younguk Kim, Jeong Heon Han, Jaeyoung Kim, Yeongtae Kim, Nyunhee Kim, Chaewon Lee, Seoyeoun Lee, Song Lim Kim, Moon Jong Kim, Si Hwan Ryu, Hongro Lee, Hyeonso Ji, Kyung-Hwan Kim, Jeongho Baek
    Korean Journal of Breeding Science.2022; 54(4): 276.     CrossRef
  • QTL Analysis of Rice Grain Size Using Segregating Populations Derived from the Large Grain Line
    Ja-Hong Lee, Jeonghwan Seo, San Mar Lar, Seong-Gyu Jang, Hongjia Zhang, Ah-Rim Lee, Fang-Yuan Cao, Na-Eun Kim, Joohyun Lee, Soon-Wook Kwon
    Agriculture.2021; 11(6): 565.     CrossRef
  • Transcriptional Changes in the Developing Rice Seeds Under Salt Stress Suggest Targets for Manipulating Seed Quality
    Choonseok Lee, Chong-Tae Chung, Woo-Jong Hong, Yang-Seok Lee, Jong-Hee Lee, Hee-Jong Koh, Ki-Hong Jung
    Frontiers in Plant Science.2021;[Epub]     CrossRef
  • Iron Biofortification in Rice: An Update on Quantitative Trait Loci and Candidate Genes
    B. P. Mallikarjuna Swamy, Balram Marathi, Ana I. F. Ribeiro-Barros, Mark Ian C. Calayugan, Felipe Klein Ricachenevsky
    Frontiers in Plant Science.2021;[Epub]     CrossRef
  • Combined Linkage Mapping and Genome-Wide Association Study Identified QTLs Associated with Grain Shape and Weight in Rice (Oryza sativa L.)
    Ju-Won Kang, Nkulu Rolly Kabange, Zarchi Phyo, So-Yeon Park, So-Myeong Lee, Ji-Yun Lee, Dongjin Shin, Jun Hyeon Cho, Dong-Soo Park, Jong-Min Ko, Jong-Hee Lee
    Agronomy.2020; 10(10): 1532.     CrossRef
  • Identification of a Novel QTL for Chlorate Resistance in Rice (Oryza sativa L.)
    Nkulu Rolly Kabange, So-Yeon Park, Dongjin Shin, So-Myeong Lee, Su-Min Jo, Youngho Kwon, Jin-Kyung Cha, You-Chun Song, Jong-Min Ko, Jong-Hee Lee
    Agriculture.2020; 10(8): 360.     CrossRef
  • Genetic Manipulation for Improved Nutritional Quality in Rice
    Priyanka Das, Sanghamitra Adak, Arun Lahiri Majumder
    Frontiers in Genetics.2020;[Epub]     CrossRef
  • STUDY OF ALLELIC VARIATION AT GENOME WIDE SSR LOCI IN PARENTS OF MAPPING POPULATION FOR HIGH GRAIN ZINC IN RICE (Oryza sativa L.)
    Sonali Habde, S. K. Singh, Korada Mounika, Amrutlal Khaire, D. K. Singh, Prasanta Kumar Majhi
    Journal of Experimental Biology and Agricultural Sciences.2020; 8(5): 558.     CrossRef
  • QTL Analysis of Heading Date Using 93-11×Milyang352 Doubled Haploid Lines in Rice
    So-Myeong Lee, Ju-Won Kang, Jun-Hyeon Cho, Ji-Yoon Lee, Dongjin Shin, Young-Ho Kwon, Jin-Kyung Cha, Sais-Beul Lee, Jong-Min Ko, Jong-Hee Lee
    Korean Journal of Breeding Science.2020; 52(4): 332.     CrossRef
  • Genetic Analysis Reveals a Major Effect QTL Associated with High Grain Zinc Content in Rice (Oryza sativaL.)
    Shaikh J. Mohiuddin, Md. Ashraful Haque, Md. Manjurul Haque, Md. Tofazzal Islam, Partha S. Biswas
    Plant Breeding and Biotechnology.2020; 8(4): 327.     CrossRef
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