1 Introduction

Obviously, the global warming and climate change have an opposite effect on the growth and productivity of the economic crops. Climate change scenario studies have shown that the average temperature will rise by 1.8 to 4 °C by year 2100 (IPCC 2007). An increase in the temperature by 1 °C of the growing season of crops can reduce their yields by up to 17% (Ozturk et al. 2015). It has been documented that climate change had a major impact on crop production (Mourtzinis et al. 2019). Thus, the consistency of factors limiting crop yields, involving climatic ones, is so crucial. The date of sowing is particularly significant in soybean cultivation since it influences the adequate formation of vegetative and reproductive organs (Nico et al. 2019) and final product (Divito et al. 2016). Since the unfavorable climate conditions during crop growth and development caused significant yield loss (Mandić et al. 2017; El-Bially et al. 2018; Abou El-Enin et al. 2023; Saudy and El-Metwally 2023), sowing dates of different genotypes adapted to the local and regional conditions should be chosen carefully (Vidić et al. 2010; Noureldin et al. 2013; Saudy et al. 2018). Owing to generating variations in different ecological factors (rainfall, temperature, humidity, and photoperiod) along the year, various sowing dates influence the plant phenological phases, hence affecting the growth, development, and production of soybean (Filho 1986; Saudy and El-Metwally 2009; El-Metwally et al. 2021). In Egypt, soybean crop is sown at the beginning of May and harvested in September. Thus, the flowering (R1–R2), pod formation and development (R3–R4), seed development (R5–R6), and maturity (R7–R8) stages of soybean synchronize most often have higher summer temperatures with no precipitation occurrence during July and August. Accordingly, delaying sowing date from April to August decreased the duration from emergence to flowering (E-FL) stage and flowering to physiological maturity (FL-PM) stage, correlating with the prevailing air temperature, actual sunshine hours, and solar radiation energy (Kandil et al. 2019). Such adverse conditions at the reproductive stage of soybean can reduce the seed yield by approximately 74.0% compared to adequate conditions (Jumrani and Bhatia 2018). Also, due to the association of drought periods with late sowing specifically at reproductive phase, reductions in yield attributes were obtained (Egli and Cornelius 2009; Purcell et al. 2013; Saudy and El-Metwally 2019; Kumagai and Takahashi 2020). Delaying the sowing date resulted in the shortening of the length of the vegetative development and the entire vegetation period contributing a significant decrease in yield (Serafin-Andrzejewska et al. 2021). Not only yield parameters affected by delaying the sowing, but also the seed chemical composition (Soliman et al. 2007; EL-Harty et al. 2010; Bellaloui et al. 2015; Ojo et al. 2002). However, seed sowing too early in unheated soil has a distinctive impact on prolonged and uneven seed emergence (Praczyk 2017).

For adapting to climate change and reducing the associated crop yield reductions, sowing dates should be adjusted in addition to cultivating heat-tolerant/drought-tolerant genotypes (Chen et al. 2012). Climate conditions, especially air temperature, precipitation, and solar radiation, are the most crucial factors affecting crop yields (Liu et al. 2021). The climatic conditions at each growth stage changed with variation in the cultivated genotype and sowing date, causing changes in growth and productivity (Yan et al. 2017, Gao et al. 2021).

Soybean (Glycine max, L. Merr) is one of the most prevalently used oilseed crops in the globe. Its uses range from human foods to animal feeds and industrial products. Among oil crops, soybeans are the first most cultivated annual crop with a productivity of 353 million tons, followed by rapeseed and cottonseed (FAOSTAT 2020). Soybean seed has high oil and protein, being 18–22% and 38–42%, respectively, and it is characterized by both high essential amino acids and unsaturated fatty acids (James and Yang 2016; Patil et al. 2018; Zhang et al. 2018). The suitable temperature for soybean is 15–22 °C at emergence, 20–25 °C at flowering, and 15–22 °C at maturity. Therefore, soybean growth, yield, and quality are greatly influenced by temperature (Liu et al. 2008). Kucharik and Serbin (2008) report that soybean yield decreased by 16–17% when the temperature rises 1 °C. Thus, with the continuation of global warming, it is expected that soybean yield will decrease in the year 2100 by 49% than the current situation (Schlenker and Roberts 2009).

Plants exposed to ecological stress suffer serious or fatal damage (El-Bially et al. 2022b; Saudy et al. 2020a; Saudy et al. 2023a; Shaaban et al. 2023a). Herein, complex mechanisms have been developed by plants to reduce the harmful effect of unfavorable conditions. For instance, plants respond to various stresses through modification of many basic vital processes such as photosynthesis, respiration, and water metabolism (Akter and Islam 2017; Liu et al. 2020). Due to inappropriate growth conditions, the efficiency of photosynthesis decreases which, in turn, results in shortening the plant life cycle with lowering productivity as well (Xalxo et al. 2020; Mubarak et al. 2021). In this regard, it is well documented that exposure plants to environmental stressful cause overproduction of reactive oxygen species (ROS), such as superoxide (O2•–), hydroxyl free radical (OH•), singlet oxygen (1O2) and hydrogen peroxide (H2O2) (Nosaka and Nosaka 2017). As a result, oxidative stress promotes lipid peroxide due to ROS damage to the cell membrane (Hasanuzzaman et al. 2013). Stress conditions enhanced the activities of peroxidase (POX), glutathione reductase (GR), and ascorbate peroxidase (APX), which prevented oxidative damage in soybean plants. In this respect, soybean plants exposed to 38/28 °C day/night temperature significantly increased oxidative damage and reduced the activities of antioxidant enzymes superoxide dismutase (SOD), peroxidase (POX), and catalase (CAT) (by 16.8, 30.1, and 103.1%, respectively), compared to the optimum temperature (D’Souza 2013). Proline is an amino acid and a natural molecule that stimulates several bioresponses in plants. Proline known to occur widely and normally accumulates in large quantities in response to different stresses in higher plants (Kavi-Kishore et al. 2005; Ramadan et al. 2023; Shaaban et al. 2023b). It has been documented that a stressful environment leads to increased proline production in plants which, in turn, impart stress tolerance by maintaining cell disruption or osmotic homeostasis. Stabilization of membranes that prevent electrolyte leakage and carry ROS concentrations within normal ranges was enhanced with proline application, thus preventing oxidative burst in plants (Murmu et al. 2017).

On the other hand, there are some crop genotypes that are sensitive, while others are tolerant to various stresses; these responses could be exhibited in genotype performance variations under stress conditions (Koti et al. 2005; Koti et al. 2007; Saudy et al. 2020b; El-Bially et al. 2023). The plant breeder, therefore, must screen the crop genotypes and select the most promising one(s) to counteract the future changes in climate (Saudy et al. 2021b; Abd El-Mageed et al. 2022).

We hypothesized that the nonoptimal sowing time will cause different yield decreases among soybean genotypes due to exposure to unfavorable weather conditions. Appropriate agronomic management, including the best choice of genotypes and an optimum sowing time, could substantially improve crop performance in regions with different climatic conditions. Therefore, the current research aimed to study the impact of unfavorable environmental changes (due to sowing in different dates) throughout life cycle on the performance (physiology, growth, yield, protein, and oil contents as well) of some soybean genotypes. If there is a difference between earlier sowing and later sowing, which has a more negative effect on the outcomes? Which genotype is the most tolerant to unfavorable conditions occurring due to nonoptimal sowing dates?

2 Materials and Methods

2.1 Site Description

The present study was undertaken during the two successive summer seasons of 2019 and 2020. In each season, a field experiment was carried out at a farm at EL-Mansourieh region, Giza Governorate, Egypt (latitude 30° 08′ 17.0″ N, longitude 30° 05′ 06.2″ E). The soil of the study site is loam and its properties are presented in Table 1. Location of the study belongs to arid regions with no rainfall and hot dry in summer (April–September). The average monthly climatic data of the site during both growing seasons are illustrated in Fig. 1 (obtained from Central Laboratory for Agricultural Climate, Agriculture Research Center, Ministry of Agriculture and Land Reclamation).

Table 1 Basal physical and chemical properties of the study site soil at EL-Mansourieh region, Giza Governorate, Egypt
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Fig. 1
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Mean values of air temperature (°C), relative humidity (%), wind speed (m sec–1) and solar radiation (MJ m–2day–1) of EL-Mansourieh region, Giza Governorate, Egypt in 2019 and 2020 growing seasons

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2.2 Plant Material and Experimentation

Four soybean genotypes, i.e., Giza 21, Giza 35, Giza 111, and Crawford, were cultivated at four sowing dates (15th April, 30th April, 15th May, and 30th May). It should be noted that temperature degrees are lower in 15th April and higher in 30th May than the appropriate date (30th April), in addition to progressive reduction in relative humidity and increase of sunshine hours; this means subjecting soybean plants to unfavorable conditions during different growth stages. Table 2 shows the common names, pedigree, origin, maturity group, and growth habit of the parental soybean tested genotypes. A split-plot design trial with three replications was used, and sowing dates were arranged in the main plots while soybean genotypes are allocated in the subplots. The experimental unit area was 10.5 m2, involving five ridges each of 3.5 m long and 0.6 m wide. Soybean seeds were obtained from Field Crops Research Institute, Agricultural Research Center, Egypt. Seeds were inoculated with Rhizobium japonicum and sown in two sides of the ridge with 4 seeds in hill spaced 20 cm. After emergence, plants were thinned to obtain two plants per hill after 21 days from sowing (DAP). Normal recommended cultural practices for growing soybean crop were used. The mineral fertilizers’ recommended rates were applied as follows: approximately 360.0 kg P2O5 ha−1 was subjoined during the soil preparation as calcium super phosphate 15.5% P2O5. Ammonium nitrate (33.5% N) at a rate of 54.0 kg N ha−1 in two equal portions at sowing and after thinned was applied. Also, 79.2 kg K2O ha−1 was added as potassium sulfate (48% K2O) in two equal portions at sowing and flowering stage. Wheat was the preceding cultivated crop in the both seasons of experimentation.

Table 2 Description of the tested soybean genotypes
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2.3 Data Estimation

2.3.1 Physiological and Growth Traits

From each subplot, ten plants were chosen randomly at 80 days after sowing (DAS) to estimate some physiological and growth traits. At this stage, soybean plants are reaching the maximum vegetative development, and plants are subjected to different conditions of sowing dates. Plant height and plant dry weight were recorded. Furthermore, leaves area plant−1 was measured using electronic planimeter (Cl 202 AREA METER, manufactured by CID, Inc., USA). Physiological traits, i.e., leaf proline content (Bates et al. 1973) and catalase (CAT) activity (Cakmak, et al. 1993), were measured.

2.3.2 Yield Attributes

At maturity (110 DAS), 10 plants from each plot were taken randomly from the three central rows to determine pods weight plant−1, and seed yield plot−1 was obtained, and then seed yield ha−1 was calculated.

2.3.3 Chemical Constituents

Representative samples of 50 g of mature seeds (12.0 moisture) were grinded and oven dried at 70 °C until constant weight. The dry pulverized were digested by acid to determine total nitrogen, phosphorus, and potassium. Nitrogen content (N) was determined using the micro-Kjeldahl apparatus of Parnos–Wagner as described by Van-Schouwenburg and Walinga (1978). Phosphorus content (P) was estimated colorimetrically by using chlorostannous reduced molybdophosphoric blue color method according to the method as described by Chapman and Parker (1961). Potassium content (K) was determined in the digested plant materials using a flame photometer according to page et al. (1982). Furthermore, seed protein and oil contents were determined according to procedures outlined in AOAC (2012).

2.4 Statistical Analysis

Since the combined analysis of variance (ANOVA) proved that there were significant differences between the two years, data for each growing season were subjected to two–way ANOVA according to Casella (2008), using Costat software program Version 6.303 (2004). Genotypes and sowing dates were considered as fixed effects while replications (blocks) were considered as random effects. For comparing among treatment means, Duncan’s multiple range test at 0.05 probability level was used.

3 Results

3.1 Physiology and Growth of Soybean

Significant differences were detected among soybean genotypes, sowing dates, and their interactions for proline content and catalase (Table 3) as well as plant height, fresh weight plant−1, and leaves area plant−1 (Table 4), during 2019 and 2020 seasons.

Table 3 Proline content and catalase activity of soybean genotypes as influenced by sowing dates in 2019 and 2020 season
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Table 4 Plant height, plant dry weight, and leaves area plant−1 of soybean genotypes as influenced by sowing dates in 2019 and 2020 season
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As shown in Table 3, significant changes in physiological parameters of soybean were observed among soybean genotypes sown under different sowing dates both seasons. In this concern, the maximum proline content was obtained with Crawford in both seasons, in addition to Giza-35 in the first season. Also, Crawford showed the highest catalase (CAT) enzyme content. Contrariwise, along the two seasons, Giza-111 gave the lowest values of proline and CAT.

Sowing soybean on 15th April resulted in higher contents for proline and catalase, while sowing on 30th April produced the lowest values in 2019 and 2020 seasons.

Sowing Crawford, Giza-111, or Giza-35 on 15th April in both seasons, in addition to sowing Crawford or Giza-35 on 30th May and Giza-21 on 15th April in the first season exhibited the maximum proline content in soybean leaves (Table 3). Sowings Crawford (in both seasons) and Giza-35 (in the first season) on 15th April were the distinctive combinations for producing the highest CAT values.

Concerning the growth parameters (Table 4), Giza-111 produced the tallest plants in the first season and the maximum values of plant dry weight and leaves area plant-1 in both seasons, significantly equaled Crawford for leaves area plant−1 in the first season. Giza-35 was the tallest genotype in the second season. Giza-35 (for leaves area plant−1 in the first season) as well as Crawford (for plant height and plant dry weight in both seasons and leaves area plant−1 in the second season) recorded the lowest values.

Results in Table 4 show that plant height, plant dry weight, and leaves area plant−1 had the highest values under 30th April sowing date, surpassing the other sowing dates in both seasons. While sowing date of 15th April recorded the lowest values of plant height and leaves area plant−1 in both seasons, sowing date of 30th May showed the lowest plant dry weight in both seasons statistically at par the sowing date of 15th April in the second season.

Sowing Giza-111 (in the first season) or Giza-35 (in both seasons) on 30th April possessed the tallest soybean plants (Table 4). Sowing Giza-111 on 30th April or 15th May as well as sowing Giza-21 on 30th April in both seasons produced the maximum plant dry weight. In plots sown on 30th April, Crawford and Giza-21 (in the first season) and Giza-111 (in both seasons) exhibited the highest leaf expand expressed in leaves area plant−1.

3.2 Agronomic Traits of Soybean

Genotypes and sowing dates and their interactions are markedly affected all traits of soybean yield and its attributes as shown in Table 5. Giza-111 achieved the highest seed yield in both seasons significantly leveled Giza-21 for seed yield in the first season. Both Crawford and Giza-35 recorded the highest pods weight plant−1 in 2019 and 2020 seasons.

Table 5 Pods weight plant−1 and seed yield of soybean genotypes as influenced by sowing dates in 2019 and 2020 season
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Sowing soybean on 30th April caused the highest increases in seed yield in both seasons, surpassing the other tested sowing dates. The difference was not significant between sowing on 30th April and 15th May for pods weight plant−1 in both seasons.

Plots sown by Giza-111 on 30th April was the potent interaction for enhancing seed yield in both seasons. Crawford × 30th April, Giza-111 × 15th May, and Giza-35 × any sowing date in the first season as well as Crawford × 30th April or 15th May, Giza-111× 30th April, and Giza-35 × 15th May in the second season were the efficient practices for improving pods weight plant-1.

3.3 Seed Nutrient Contents

Available data in Table 6 show the discrepancy among soybean genotypes for their seed nitrogen, phosphorus, and potassium content. Crawford along Giza-35 were the efficient genotypes for accumulating the maximum nitrogen in seed in 2019 and 2020 seasons. Unlike, the highest values of phosphorus and potassium were accumulated in the seeds of Giza-21 and Giza-111 in both seasons.

Table 6 Seed nitrogen, phosphorus and potassium content of soybean genotypes as influenced by sowing dates in 2019 and 2020 season
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Sowing soybean on 15th April achieved the maximum values of nitrogen, phosphorus, and potassium content which significantly equaled the sowing dates of 15th May and 30th May for nitrogen and potassium in both seasons.

The most remarkable interactions for increasing seed nitrogen content were Crawford × 15th April or 30th May and Giza-35 × 15th April in both seasons as well as Giza-21 × 15th April and Giza-35 × 15th May or 30th May in the first season. Sowing on 15th April, Crawford in the first season and each of Giza-21 and Giza-111 in both seasons possessed the highest seed phosphorus content. The same combinations in addition to Giza-21 × 30th May in both seasons and Giza-111 × 15th May or 30th May in the first season were also the efficient practices for improving seed potassium content.

3.4 Oil and Protein Contents

Data depicted in Fig. 2 indicate that oil and protein statistically influenced by soybean genotypes, sowing dates, and their interactions. The oil in Giza-111 seeds increased by 26.7 and 36.7% compared to the lowest oil of Giza-35 seeds in both seasons, respectively, while Crawford and Giza-35 recorded the highest values of protein during two seasons.

Fig. 2
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Seed oil and protein content of soybean genotypes as influenced by sowing dates in 2019 and 2020 season. Different letters between bars indicate that there are significant differences by Duncan’s multiple range test at p ≤ 0.05

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Sowing date of 30th April treatment increased oil surpassing the sowing dates of 15th April, 15th May, and 30th May by 28.4 and 34.7%, 11.2 and 13.8%, and 19.8 and 24.0% increases in 2019 and 2020 seasons, respectively (Fig. 2).

Under sowing date of 30th April in 2019 and 2020 seasons, Giza-111 and Giza-21 were the effective genotypes for recording the maximum seed oil content significantly leveled Giza-111 × 15th May or 30th May in 2020 season. Crawford × 15th April or 30th May and Giza-35 × 15th April in both seasons as well as Giza-21 × 15th April and Giza-35 × 15th May or 30th May in 2019 season were the most promising combinations for increasing seed protein content (Fig. 3).

Fig. 3
figure 3

Seed oil and protein content of soybean as influenced by the interaction between genotypes and sowing dates in 2019 and 2020 season. Different letters between bars indicate that there are significant differences by Duncan’s multiple range test at p ≤ 0.05

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4 Discussion

Crop storage organ development could be affected either by the supply of assimilates from leaves as a photosynthetic structure or by the sink potential to utilize photosynthesis (Aluko et al. 2021). It has been documented that various stresses disturb the homeostasis between source and sink in plants (Salem et al. 2021; El-Metwally et al. 2022; Salem et al. 2022; Saudy et al. 2023b). Findings of the present research proved that the inappropriate sowing dates caused abiotic pressure on soybean plants which negatively influenced the metabolic processes and thus the growth and yield. In this context, decreases in plant height, plant weight, leaves area, oil content, and seed yield as well as increase in proline and catalase content were observed under the unfavorable conditions of the nonoptimal sowing time. The current research proved that sowings on 30th April up to 15th May are the suitable dates for cultivating soybean in Egypt, since the most tested parameters recorded higher values than early (on 15th April) or late (30th May) sowings. Results showed significant reductions with nonoptimal sowings (15th April or 30th May) in plant height, plant dry weight, leaves area per plant (Table 4), pods weight per plant, and seed yield of soybean (Table 5). Accordingly, the early sowing on 15th April made soybean plants to grow in an unfavorable condition. Herein, early plantings may delay and decrease seedling emergence if the soil is cold and wet at planting (Egli and Cornelius 2009), resulting in plant populations that are below the threshold for maximum yield (Lee et al. 2008). The impact of the unfavorable conditions was more pronounced with sowing on late time (on 30th May). Generally, the later the planting date, the shorter the interval between soybean planting and harvest (Grichar et al. 2008). Delayed sowing by approximately 3 weeks significantly reduced soybean yield (Kumagai and Takahashi 2020). Sadeghi and Niyaki (2013) recorded a steady decrease in soybean seed yield when sowing was delayed due to lack of sufficient vegetative growth, lower number of pods per plant, and reduced seed weight. Owing to the distinctive late sowing-associated reductions in leaf are index, plant height, bottom pod height, number of pods and seeds per unit area, and seed index, soybean seed yield reduced substantially (Umburanas et al. 2019). The environmental stressors generate excess production of ROS in plant cell (Souri et al. 2019; Hatamian et al. 2020), causing demolishing in cell membrane, photosynthesis pigments, nucleic acids, and lipids while enhancing the content of antioxidants enzymes such as catalase and peroxidase (El-Metwally and Saudy 2021; Abd–Elrahman et al. 2022; Makhlouf et al. 2022; Saudy et al. 2023a) as well as proline content (Saudy et al. 2021a; El-Bially et al. 2022a). Due to photosynthetic pigment degradation caused by environmental oxidative stress, leaf senescence is accelerated. Genotypes having delayed senescence sustain greater photosynthetic potential and could have higher crop productivity compared to genotypes with earlier onset of senescence (Thomas and Ougham 2014). Genotypes with delayed senescence should therefore be considered a significant source of germplasm for improving the stress tolerance (Luche et al. 2015).

Chloroplast damage could be prevented since antioxidants equip the plants against the oxidative surge (Foyer 2018). The improvement in the antioxidant activity, specifically CAT increase, enables plants to cope with oxidative stress (Liang et al. 2018). Furthermore, plants accumulate proline as a defender to mitigate the negative effect of environmental stress on plant growth and development (Siddique et al. 2018). By reducing adverse effects on key enzymes in carbon and oxidative metabolism, proline could enhance stress tolerance (AlKahtani et al. 2021). Proline in plant cells plays an important role as a scavenger of free radicals by its high concentration may reflect a decrease in lipid peroxidation products (Sadeghipour 2020). Chen et al. (2014) reported that increasing leaves area as strong source can share in greatly to improve weight of pods which was positively reflected on the oil content and seed yield. Soybean plants exposed to stress conditions at flowering stage led to cause seed set reduction result pollen sterility (Onat et al. 2017). Furthermore, the ecological stresses stimulate the fall of flowers and buds reducing seed production (Firmansyah and Argosubekti 2020). Choi et al. (2016) found high positive correlation between the pod number per plant and seed yield. Concerning the nutrient contents of soybean seeds, it has been noted that nonoptimal sowing dates recorded higher values of N, P, and K comparing to sowing on 30th April (Table 6). Biochemical analysis of soybeans showed that with the delay of sowing in later terms, the content of the main components of the chemical composition slightly increases (Kim 2019). Thus, protein content in seeds was significantly higher after sowing the seeds at a delayed time compared to the early one (Jarecki and Bobrecka-Jamro 2021). An increase in protein content and decrease in fat content of seeds as a result of later soybean sowings were observed (Pierozan Junior et al. 2017; Umburanas et al. 2018). Bobrecka-Jamro et al. (2018) stated that the macronutrient content of soybeans depends on weather conditions.

The knowledge of genetic variability is the most important aspect of plant improvement program. It is of equal importance for a soybean breeder to evaluate soybean genotypes from different genetic backgrounds under different environments. The current findings indicate that soybean is among the most stress sensitive crops and production could fluctuate with a slight change in the environmental conditions which could be observed from the lower yields under later sowing dates compared with the best sowing date. The effects of sowing dates on soybean genotypes were evident as expressed agronomic traits measured in this study. Soybean genotypes varied in the average values of the tested agronomic traits, which indicate the existence of genetic diversity. Findings showed that sowing Giza-111 genotype on 30th April in two growing seasons recorded the highest values for yield and most attributes, i.e., plant height, plant dry weight, leaves area, and seed yield/ha (Tables 4 and 5) and oil content (Fig. 3), while Crawford gave the lowest value for most agronomic traits in both seasons. Giza-35 had the lowest oil content and highest protein content in both seasons, and Giza-21 gave the highest phosphorus and potassium content in late sowing date in both seasons. The variability among the soybean genotypes for yield and its attributes indicates differences in genetic background and heterotic pattern among the genotypes. The growth and development of soybean plant are affected by the environmental factors. The unfavorable environmental conditions have negative effects on soybean growth, development, and yield (Nakagawa et al. 2020). Early maturing varieties of soybean are more sensitive to temperature variations than late ones (Borowska and Prusiński 2021). Genotypes grown in conditions with longer days (photoperiod) compared to that they were adapted to will prolong their vegetation. Genotypes grown in conditions with shorter days (photoperiod) will have shortened vegetations. Further, information on cultivar-specific tolerance to a degree of temperatures can be exploited in breeding programs to develop tolerant genotypes that are highly suited for cold or hot environments. However, several confounding weather factors vary during the growing season that limits the results of such studies to validate cultivar’s tolerance to low or high-temperature tolerance (Alsajri et al. 2019). Various responses of soybean cultivars were obtained under different sowing dates (Jarecki and Bobrecka-Jamro 2021)

5 Conclusions

It could be concluded that sowing the tested soybean genotypes on 30th April to 15th May saves favorable conditions for growth and development, hence obtaining high yield and quality. Soybean genotypes interacted by different responses to sowing date since changing the date of sowing revealed different changes among genotypes mainly expressed in seed yield and quality. Owing to high stimulation of antioxidant defense and buildup of osmolytes, Giza-111 is the most adapted and stable genotype under various sowing dates. Thus, such genotype could be used as a genetic effective tool in breeding programs to improve soybean cultivars. However, more investigations along several years should be implemented to confirm the stability of Giza-111 cultivar.