IMPROVING EARLINESS AND PRODUCTIVITY FOR PEA BY SELECTION UNDER SOHAG CONDITIONS..

The present study was carried out at Shandaweel Research Station during the three winter seasons of 2019/20, 2020/21 and 2021/22 using two F2 populations of Master-Hindy x Super-2 (population I) and Progress x Sweet-2 (Population II) to improve earliness, yield traits using pedigree selection for two cycles. The genetic parameters were estimated in the F3 and F4 generations. The main genetic parameters studied were the phenotypic (PCV) and genotypic (GCV) coefficient of variance, response to selection, selection differential and broad sense heritability. The measurements recorded were (number of days to 50% flowering, number of branches/plant, pod length (cm), number of seeds/pod, number of pods/plant, pod felling%, fresh pods weight and fresh seeds weight (g). Results showed slight values repugnancy differences were observed between PCV and GCV in all generations, indicating the importance of the genetic effects in controlling the inheritance of the studies traits. Therefore, these traits might be more genotypically predomonant and it would be possible to achieve further improvement in them. Heritability were recorded from 88.42 to 90.81% for fresh pods weight. Increasing obtained for fresh pods weight/plant by 147.27% and 132.69% over Master (better check parent) in population I and population II, respectively, and also, for fresh seeds weight/plant by 87.79 and 85.11% in population I and population II, respectively.

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Publication Details

Journal
Journal of Sohag Agriscience (JSAS)/Journal of Sohag Agriscience (JSAS)
Published
2024-12-01
DOI
https://doi.org/10.21608/jsasj.2024.402769
Primary Topic
Agronomic Practices and Intercropping Systems
Type
article
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article

IMPROVING EARLINESS AND PRODUCTIVITY FOR PEA BY SELECTION UNDER SOHAG CONDITIONS..

Hussein M. Ali, Mohamed Hosny, M. A. Abdel-Hady, Fatma Mohamed
Journal of Sohag Agriscience (JSAS)/Journal of Sohag Agriscience (JSAS)
Agronomic Practices and Intercropping Systems
article

IMPROVING EARLINESS AND PRODUCTIVITY FOR PEA BY SELECTION UNDER SOHAG CONDITIONS..

Hussein M. Ali, Mohamed Hosny, M. A. Abdel-Hady, Fatma Mohamed
article en

Abstract

The present study was carried out at Shandaweel Research Station during the three winter seasons of 2019/20, 2020/21 and 2021/22 using two F2 populations of Master-Hindy x Super-2 (population I) and Progress x Sweet-2 (Population II) to improve earliness, yield traits using pedigree selection for two cycles. The genetic parameters were estimated in the F3 and F4 generations. The main genetic parameters studied were the phenotypic (PCV) and genotypic (GCV) coefficient of variance, response to selection, selection differential and broad sense heritability. The measurements recorded were (number of days to 50% flowering, number of branches/plant, pod length (cm), number of seeds/pod, number of pods/plant, pod felling%, fresh pods weight and fresh seeds weight (g). Results showed slight values repugnancy differences were observed between PCV and GCV in all generations, indicating the importance of the genetic effects in controlling the inheritance of the studies traits. Therefore, these traits might be more genotypically predomonant and it would be possible to achieve further improvement in them. Heritability were recorded from 88.42 to 90.81% for fresh pods weight. Increasing obtained for fresh pods weight/plant by 147.27% and 132.69% over Master (better check parent) in population I and population II, respectively, and also, for fresh seeds weight/plant by 87.79 and 85.11% in population I and population II, respectively.

Journal of Sohag Agriscience (JSAS)/Journal of Sohag Agriscience (JSAS) Vol. 9(2)
Agricultural Research Center (EG), Sohag University (EG)
Openalex Percentile: Top 63%
Agronomic Practices and Intercropping Systems
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IMPROVING EARLINESS AND PRODUCTIVITY FOR PEA BY SELECTION UNDER SOHAG CONDITIONS.. — Hussein M. Ali, Mohamed Hosny, et al. · Journal of Sohag Agriscience (JSAS)/Journal of Sohag Agriscience (JSAS) (2024) | TGRS Research Map | TGRS