In order to study the effect of genotype × environment interaction and stability of sugar beet genotypes for seven cultivars, viz Lilly, DS 9004, Gazella, Oscar Poly, Pather, Toro and Hercule. A field trail was sown in eight environments as major four locations (Sakha, Giza, El-Fayoum and Malawy) for two years (2011/12 and 2012/13) using a randomized complete block design, with three replications. Analysis of variance for root yield, sugar yield and sugar content showed that the environment and genotype and genotype × environment interaction (GEI) were significant. GEI were evaluated by two methods (phenotypic stability and AMMI model). According to phenotypic stability analysis results, genotype (Lilly) was the most stable for sugar content and root and sugar yield. This genotype recorded the highest root and sugar yield (30.34 and 5.22 ton/fed, respectively) across environments, and Sakha environment had the highest mean values of environments followed by El-Fayoum environment. AMMI model explained most of the genotype × environment interaction (85.97%, 83.34 % and 86.47 %) for root yield, sugar content and, sugar yield, respectively. Lilly was the best genotype based on the biplot, and showed specific adaptation to Sakha and El-Fayoum location. The varieties Pather, Hercule and Toro were the lowest variety among the evaluated varieties and it is better not to use it in the studied areas. The genotypes Gazella, Oscar poly and DS9004 had an average genetic potential for the studied traits, but its high general adaptability, then it could be introduced for all areas. Among the locations, Sakha was the best location, and was more similar to El-Fayoum. Meanwhile, Malawy was the poorest location. Therefore, two stability methods confirmed that Sakha and El-Fayoum are recommended as suitable regions for sowing sugar beet and Lilly variety could be suggested as the best genotype for these locations. Meanwhile, AMMI method showed new information.

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Two field experiments were conducted at Giza Research Station, ARC, Egypt, during 2013/14 and 2014/15 seasons. Twenty faba bean genotypes were evaluated in this study in an Alpha Lattice design with three replications for seven traits. The aim was to assess the efficiency of two experimental designs to minimizing experimental error and the coefficient of variation for yield variable, and to identify the more suitable design. Thus, data were analyzed according to alpha lattice design and randomized complete blocks design (RCBD). The results showed an improvement in the precision level thought decline in both the mean square error and the coefficient of variation. The relative efficiency (R.E.%) of trials showed that alpha lattice design was more efficient than RCBD. The estimated average of R.E.% indicated that the use of alpha lattice design instead of RCBD increased the experimental accuracy by 10. 46, 8.01, 22.47, 13.60, 17.56 and 55.00% for days to 50% maturity, plant height, number of branches/plant, 100-seed weight, seed yield/plant and seed yield ard/fed, respectively. Mean rank comparisons for both randomized complete block and alpha lattice design were performed. Data showed that the ranks for both designs were not constant across the experiments. Generally, the results showed that the traditional RCBD should be replaced by alpha lattice in the agricultural field trials when the number of treatments tested in an experiment is high, where a homogeneous block is quite difficult to find in field experiments. Results performed that the estimation of heritability according to alpha lattice was higher than the RCBD; therefore, the results indicated a greater efficiency for alpha design, enabling more precise estimates of genotypic variance, greater precision in the prediction of heritability in broad sense.

A field experiment was conducted during two winter seasons 2018/2019 and 2019/2020 at Sakha Agricultural Research Station, Kafr El-Sheikh Governorate, Egypt to study the effect of deficit irrigation and weed control treatments on grain yield and water productivity of three bread wheat genotypes. The experimental design was stripe split-plot, with three replicates. Irrigation treatments were in the vertical plots which include I1 irrigation at all stages (full irrigation), while I2, I3 and I4 were deficit irrigation through withholding one irrigation at elongation, booting, and anthesis stages, respectively. Four weed control treatments were allocated in horizontal plots that include, W1 (Gerostar + Action), W2 (Atlants), W3 (hand weeding twice), and W4 control (untreated), Sub-Subplots were three wheat genotypes G1 (Giza 171), G2 (Sakha 95) and G3 (promising Line). The results revealed that the highest values of plant height, number of spikes m -2 , number of kernels spikes -1 , 1000-kernel weight, biological yield, grain yield and straw yield were recorded under I1 compared to all the studied irrigation treatments, as well as under W1 compared to other weed control treatments and G2 compared to others genotypes in the two seasons. The highest values of water consumptive use (CU), and applied water (AW) were recorded under I1 to be 37.67, and 48.26 cm respectively, the values of AW under I2, I3 and I4 were reduced by 18.5%, 17.6%, and 22.3% respectively compared to I1 as mean of the two seasons. The values of productivity of irrigation water (PIW), and water productivity (WP) were taken the descending order W1> W2 > W3 > W4 and G2 > G1 > G3 for weed, and genotypes respectively. It could be recommended the I2 × W1 × G2 interaction which recorded the highest grain yield, PIW and WP, moreover saved a reasonable amount of irrigation water.

This work aimed to study the effect of FYM rates (0, 10 & 20 m 3 fed-1) and application in time of N fertilizer on maize grain yield and its attributes using single cross hybrid 130 at two field experiments. The technique of treatment-trait (TT) biplot graph was used to study the interrelationships among maize traits. The Results showed that application of 10 or 20 m 3 FYM and adding the recommended N fertilizer on these doses with first, second or third irrigations gave highest values for the grain yield and most agronomic traits. It is obvious that the highest correlation coefficients were obtained between grain yield and each of number of ears plot-1 (NE),ear length (EL), ear diameter (ED) and 100 kernel weight (KW),under Gemmeiza location, while the traits of days to 50%tassiling and silking, plant height (PH), ear height (EH), number of ears plot-1 (NE) and 100 kernel weight (KW) were the most associated traits with grain yield under Sids location. Using the TT biplot graph, results revealed that the best performance treatments for most studied across the two locations were the application (T11) before as well as application (T10). The results showed that TT biplot graph was an effective statistical tool to study the effects of treatments on yield and its attributes and also to discover the interrelationships among these traits. Accordingly, the maize breeder should give interest in the interrelationships among grain yield and its attributes when planning the breeding program.