The genotype × environment (G×E) interaction is considered a stumbling block to plant breeders, since the presence of significant GxE interaction component can complicate the identification of superior genotypes and reduce the usefulness of selection. Seed yields of 26 soybean genotypes were evaluated in three locations i.e. Sakha, Etay ElBaroud and Mallawy, through four successive summer seasons from 2012 to 2015. The used design was a randomized complete block design with three replications. This research is aimed to estimate the stability parameters of seed yield of 26 soybean genotypes over twelve environmental conditions and to examine the usefulness and validity of a new simple stability method comparing with four widely used methods. The four stability methods follow three main statistical models namely; regression, variance, and non-parametric approaches. Results showed highly significant mean squares for genotypes, environments and G×E interaction indicating that the tested genotypes exhibited different responses to environmental conditions giving the justification for running stability analysis. The terms of predictable (linear) and unpredictable (non-linear) interaction components were highly significant indicating that the tested soybean genotypes were different in their relative stability. The two soybean cultivars Giza 111 and Giza 21 in addition to their high mean yields, they met all the rules of stable genotypes. Therefore, both cultivars could be considered a good breeding material stock in any future breeding program. Also, when the simplified stability method was applied, the unstable eighteen genotypes were differentiated into three classes. These classes included three genotypes (L162, H29 L115, and H2 L12) were adapted to the unpredictable low yielding environments, while five others (H15 L273, L163, H3 L4, H4 L24 and DR 101) were adapted to high yielding environments. Whereas, the rest ten genotypes were unstable over the low, medium and high environmental groups. The results proved also that, the proposed stability method of Thillainathan and Fernandez (2002) is very simple and easy to apply, understand and interpret by agronomists and plant breeders than the other popular stability models. Also, it is possible to support the results of this stability method by a scatter plot diagram that enable the researchers to visually, directly and quickly compare the mean yield performance and stability of the tested genotypes.

This work conducted on the research farm of Mallawi Agricultural Research Station, El-Minia Province, Egypt, during two successive seasons of 2004 and 2005 to study the role of the late plantings on the productivity of soybean. Three out of four genotypes selected to achieve that goal were new released cultivars, Giza-22; Giza-35; and Giza-111, and the commercial one, Crawford, the common parent of the three genotypes, as control. Three planting dates started on June 1 st , June 15 th for the second date of sowing and ended on June 30 th for the third sowing date in both seasons. The package of the recommendations of soybean culture carefully applied to get the best results of each sowing date. The results showed that all of the morphological, yield and productivity traits highly significantly affected by genotype and three out of five morphological traits, number of days to both flowering and maturity and plant height, also highly significantly affected by late sowing date. The other two traits, number of branches and leaf area at 75 days just significantly affected by late sowing date. In terms of yield and its components traits, only seed index highly significantly affected by late sowing date and yield per plot significantly affected by sowing time. All productivity traits were significantly affected by late sowing date specially the content of both oil and protein. Although yield per plot was significantly affected by late sowing date, the yield per plant was not affected by late sowing date indicating that the factor of time of sowing may affect the rate of the germination and control the stand of the plots. Number of active nodules considered as productivity trait because of the residual nitrogen that remain in the soil after harvest for the next crop. This number was significantly affected by sowing time and reached the highest values in the second date of June 15 th that may due to the high temperature at this time which lead to increasing the interaction between soybean roots and the nodule bacteria.

The efficiency of the triple test cross (TTC) and the six-population biometrical analyses was compared in terms of assessing and quantifying the components of genetic variance for two faba bean crosses : Triple WhiteiGiza 843 and NA112iGiza 429. Several traits were studied including days to first flower, plant height, branches\plant, pods\plant, seeds\pod, 100-seed weight and seed yield\plant. The results supported the triple test cross biometrical approach as it uses first degree statistics and can be applied to any population irrespective of its genetic architecture. Absence of a scalar relationship between triple test cross families (orthogonality) ensures independence between means and variance with no restrictive assumptions. Both methods provided evidence for epistasis, and both additive and dominance genetic components in the genetic control of the studied traits.

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