Agricultural Sciences

Agricultural Sciences

ISSN Print: 2156-8553
ISSN Online: 2156-8561
www.scirp.org/journal/as
E-mail: as@scirp.org
"Performance Assessment of Some Flax (Linum usitatissimum L.) Varieties Using Cluster Analysis under Sandy Soil Conditions"
written by Bakry Ahmed Bakry, Omar Maghawry Ibrahim, Tarek Abd El-Fattah Elewa, Mohamed Farouk El-Karamany,
published by Agricultural Sciences, Vol.5 No.8, 2014
has been cited by the following article(s):
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[1] Genetic Variance In Flax Cultivars Using RAPD Technique, Cluster And Principal Component Analysis
NVEO-NATURAL VOLATILES & …, 2022
[2] Water stress intensified the relation of seed color with lignan content and seed yield components in flax (Linum usitatissimum L.)
Scientific Reports, 2021
[3] Linu ģenētisko resursu rezistence pret slimībām-rezistences izvērtējums un uzlabošanas metodes
2020
[4] Genetic diversity study for useful breeding traits in maize inbred lines using principle component and cluster analysis grown under rainfed condition
2020
[5] PERFORMANCE AND COMBINING ABILITY FOR STRAW YIELD AND RELATED CHARACTERS IN A DIALLEL CROSS OF FLAX (Linum usitatissmum, L.) UNDER …
2019
[6] The Evaluation of Yield and Agronomic Traits of Flax Genotypes Under Latvian Conditions
2019
[7] Influence of biofertilizers on growth and some biochemical aspects of flax cultivars grown under sandy soil conditions
2019
[8] Genetic Diversity and Relationship among Nine Cultivated Flax Genotypes (Linum usitatissimum L.) Based on SCoT Markers
2018
[9] OM Ibrahim, MM Tawfik Elham, A. Badr and Asal M. Wali
Journal of Applied Sciences, 2016
[10] Evaluating the Performance of 16 Egyptian Wheat Varieties Using Self-Organizing Map (SOM) and Cluster Analysis
Journal of Applied Sciences, 2016
[11] Yield and Quality Traits of Some Flax Cultivars as Influenced by Different Irrigation Intervals
Journal of Agricultural Science, 2016
[12] ESTIMATION OF YIELD STABILITY FOR FLAX GENETIC RESOURCE USING REGRESSION AND CLUSTER ANALYSIS
2016
[13] Assessing the performance and variability of some Sugar beet varieties using Self-organizing map artificial neural network and Cluster analysis
International Journal of ChemTech Research, 2015
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