Genetic Analysis to Improve Rice (Oryza sativa L) Grain Yield Attributes and Quality Traits | ||||
| Journal of Plant Production | ||||
| Article 8, Volume 15, Issue 4, April 2024, Page 197-206 PDF (1.1 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/jpp.2024.275948.1319 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Randa S Nofal  1; Nessreen N. Bassuony2; M. M. Gaballah2
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| 1Rice Research and Training center, Agricultural Research Center | ||||
| 2Rice Research Department, Field Crops Research Institute, Agricultural Research Center, Egypt | ||||
| Abstract | ||||
| The investigation was carried out in rice growing seasons of 2020, 2021 and 2022, comprising P1, P2, F1 and F2 for thee crosses Giza 179 × Suweon 361, Giza 177 × Milyang 349, Giza 177 × Sakha super 300 were used to improve grain yield attributes and quality traits. Therefore, the highest grain yield plant-1 resulted with Sakha Super 300 (50.80 g). While F1 of the crosses Giza 177 × Sakha super 300 and Giza 179 × Suweon 361 provided the highest values 55.80 and 55.14 g, respectively, and F2 of the cross (Giza 177 × Sakha super 300) give 50.80 g. The parent Sakha super 300 reported highest milling percentage value 73.06%. While, F1 of Giza 177 × Sakha super 300 displayed the highest value 74.60%. However, F2 of cross (Giza 177 × Milyang349) was noted maximum value 62.83%. The degree of dominance was greater than unity (±1.0) for all the studied traits for the three crosses except panicle length, panicle weight, and fertility percentage for cross 1, panicle length, number of tillers, grain length and head rice for cross 2, and 1000-grain weight, grain length and grain width for cross 3, suggesting the important of over dominance in controlling traits. The first PCA (PC1) was 98.45% of the difference and directionally positive associated with Suweon 361, F1 of cross (Giza 179 × Suweon 361), F1 of cross (Giza 177 × Milyang 349), P2 of cross (Sakha super 300) and F1 of cross (Giza 177 × Sakha super 300). | ||||
| Keywords | ||||
| grain yield; quality; PCA analysis; phenotypic correlation; prediction selection; rice | ||||
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