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Article

Effects of Seed Quality and Hybrid Type on Maize Germination and Yield in Hungary

by
Suhana Omar
,
Rosnani Abd Ghani
,
Noriza Khalid
,
Márton Jolánkai
,
Ákos Tarnawa
,
Attila Percze
,
Péter Pál Mikó
and
Zoltán Kende
*
Institute of Agronomy, Hungarian University of Agriculture and Life Sciences, Páter Károly u.1, H-2100 Gödöllő, Hungary
*
Author to whom correspondence should be addressed.
Agriculture 2023, 13(9), 1836; https://doi.org/10.3390/agriculture13091836
Submission received: 20 August 2023 / Revised: 12 September 2023 / Accepted: 17 September 2023 / Published: 19 September 2023
(This article belongs to the Section Seed Science and Technology)
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Abstract

:
After wheat and rice, maize is one of the most significant cereal crops worldwide. However, high-quality seed materials are prerequisites for stable yields, and low-quality maize seeds significantly contribute to low yields and deteriorate over time. Therefore, the present investigation aims to investigate the effects of seed quality and hybrid types on maize germination by emphasizing seed viability and vigor and their impact on maize crops’ overall performance and productivity. The study was separately conducted in the laboratory and on a field experiment plot under the Department of Crop Production, Hungarian University of Agriculture and Life Sciences, in spring 2022. Nine parental lines, six hybrids, and a controlled hybrid were tested in this study. The studies were laid out using a complete randomization design (CRD) and a randomized complete block design (RCBD) in the laboratory and in the field. The results of the study showed that there was a statistically significant difference between genotypes and number of days and their interaction in seed vigor. The parental lines showed better performance in terms of germination percentage and radicle elongation, whereas single-cross hybrids (SC) produced better plumule length. The radicle and plumule length also expanded significantly as incubation days increased. In field evaluations, as expected, hybrid lines produced better performance than parental lines, and SC hybrids were more prevalent than the other hybrids. In addition, the number of rows per ear, number of kernels per ear, 1000-kernel weight, and ear weight directly affected the final grain yield. However, further research is needed on new approaches that can assist researchers in advancing their work by considering biotic and abiotic factors to address seed-quality issues and enhance yield production.

1. Introduction

Maize, or corn (Zea mays L.), is one of the most significant cereal crops cultivated in various regions of the world, after wheat and rice [1]. It is a staple food in many countries, especially in Africa, Latin America, and Asia [2]. Maize is consumed raw and used as food, as starch, as a sweetener, for oil beverages, for non-food products, as a coffee substitute, and as feed grain in livestock industries [3,4,5]. The wide adaptability of maize due to its versatility and diverse applications makes it the world’s largest crop in terms of production volume [6]. This led to intense cultivation, which favored its spread [7,8]. In Hungary, maize is one of the most important crops, accounting for almost 55% of cereal production in 2020 [9]. It has surpassed wheat, barley, and other crops as the main crop grown by farmers. In 2021, the total production was 6,462,205 metric tons, which decreased to 2,803,206 metric tons in 2022 [10] due to heat waves and droughts across the continent [11]. Global climate change is leading to abiotic consequences, including increases in CO2 concentrations, temperature, rainfall intensity, and the likelihood of extreme weather events [12]. Extreme heat, drought, and intense rainfall significantly reduce the yield of maize production [13]. Therefore, soil temperature affects maize germination and the growth of both the radicle and the shoot [14].
Hybrid maize, first grown commercially in America in the 1930s [15], is higher yielding and more disease resistant than parental lines. Hybrid maize varieties are now grown in over 95% of the world’s maize-growing regions [16]. Due to favorable environmental conditions and technical competence, global hybrid maize seed production has expanded rapidly, and China, India, the United States, Brazil, Mexico, and Argentina account for more than 60% of global hybrid maize seed production [17]. In Hungary, the first hybrid was MV 5, which was registered in 1953, and since 1964, 100% of the cultivated area has been planted with hybrid maize [18]. Single crosses (SC), double crosses (DC), and three-way crosses (TC), as well as certain modified forms of these three combinations, are also utilized in commercial production [19,20]. The heterosis effect of F1 generations is the reason for developing hybrids rather than open-pollinated varieties [21,22]. SC maize hybrids are the most productive, uniform, and expensive because both parents are inbred lines, whereas DC hybrids are more affordable due to both parents being single crosses [20]. SC hybrids are developed by crossing two unrelated parents, whereas TC hybrids involve crossing an inbred line as the male parent with a single cross as the female parent. DC hybrids involve crossing two single crosses in two stages [23].
In maize, low-quality seed has a significant impact on low yields [24]. Various circumstances may lead to a decrease in seed quality, a condition referred to as “seed deterioration.” [25]. Seed quality can be determined by evaluating physical and physiological characteristics [26]. Seed quality is an essential quality measure for seed breeders because of the variation among different seed types [27]. Physical quality is determined by seed size, weight, and shape, whereas physiological quality is determined by viability and vigor [28]. Seed germination is also a complex physiological process involving water uptake by dry seeds and the emergence of radicles. Dormancy, an adaptive characteristic, prevents germination under favorable environmental conditions [29]. Temperature, light, and water ability are crucial factors for seed germination, and these elements are closely related to environmental conditions, seed physiology, and the germination process [30]. In artificial conditions, the optimal temperature for gemination is between 20 °C and 25 °C [31]. Meanwhile, water is required to hydrate protoplasmic metabolism, stimulate germination, and minimize water stress in maize seeds [32].
The initial phase of the germination process is known as imbibition, where the seed coat swells and becomes soft due to rapid water absorption [33]. This process triggers internal physiological activity, promotes respiration, and allows for the development of radicles and plumules [33,34]. Germination is defined by several physiological and morphogenetic processes, including seed energy transfer, endosperm nutrient absorption, and metabolic changes [34]. Restoration of essential processes such as transcription, translation, and DNA repair, followed by cell elongation and division, are indicators of germination [35]. Vigorous seeds promote higher germination rates, seedling strength, and germination ability, as well as higher economic yields [36], as shown in hybrid seeds [19]. Furthermore, previous studies have found that seeds of different genotypes respond differently to seed yield and quality [37].
The quality of the seed and its impact on the generation of latent and field performance are mostly determined by the seed’s viability and vigor [38]. By assessing seed viability and vigor, an attempt is made to predict the number of seeds needed to avoid later declines in field performance due to a poor correlation with yield. This process is called field germination [39], and uniform and vigorous seedling germination ensures a good plant population and yield [40]. Therefore, seed evaluation and information are a source of great uncertainty for the seed industry [41]. Although many studies have characterized seed-quality parameters separately, a comprehensive study documenting the relationship between seed quality and the yield performance of different maize hybrid types has not yet been completed. This study focused on the intricacies of seed quality and hybrid types on maize germination assessment in the laboratory, with an emphasis on seed viability (germination percentage) and vigor (radicle and plumule length) and their impact on the overall performance and productivity of maize crops. The purpose of this study is to test the hypothesis that different hybrid types do not influence maize germination and yield. By exploring various parameters such as germination rate, radicle and plumule length, number of rows per ear, number of kernels per ear, 1000-kernel weight, and ear weight of different maize hybrid types, we aim to provide valuable insights and recommendations to enhance seed quality by assessing seed viability and vigor and their relationship to yield.

2. Materials and Methods

The experimental method in this research involves two parts, which are laboratory experiments and open-field experiments. Seeds of maize hybrids and lines were obtained from Szeged University, Hungary, and the Centre for Agricultural Research, Martonvásár, Hungary, and commercially available hybrids were used as the control. The seed types used in the study are listed in Table 1.

2.1. Laboratory Experiment

A laboratory experiment was carried out at the Laboratory of Agronomy, Hungarian University of Agriculture and Life Sciences (MATE), Gödöllő, Hungary. The selected hybrids, lines, and check variety were allowed to germinate in 13.5 cm Petri dishes lined with a single sheet of Whatman filter paper as part of a standard germination test [42]. Ten millimeters of distilled water were used to moisten the filter paper, and six seeds were placed in each Petri dish, which had four replicates for all genotypes and was laid out in a completely randomized design (CRD). The seeds were then incubated for nine days in a growth chamber at a temperature of 20 °C and a relative humidity (RH) of 70%. The observations and data collection of seed viability and vigor, germination rate (%), radicle length (cm), and plumule length (cm) were conducted on days 3, 5, 7, and 9. All seeds used in this study were treated with fungicide, i.e., 10% sodium hypochlorite.

2.2. Open Field Experiment

The open field experiment was conducted in the spring season of 2022 (May to November) at the Experimental Plot of the Department of Agronomy, Hungarian University of Agriculture and Life Sciences, Hungary (47.5948303′ N, 19.3698959′ E), which is in Gödöllő, to the northeast of Budapest, Hungary. July is the warmest month, with the maximum temperature reaching 32.0 °C (89.6 °F) and the minimum temperature reaching 20.0 °C (68.0 °F). Throughout the research period, the average maximum precipitation was approximately 104.0 mm (4.09 inches), and the minimum precipitation was 24.6 mm (0.97 inches), with the highest peak occurring in September. The soil at the experimental plot consisted of sandy loam and brown forest soil (Chromic Luvisol). The humus content was 1.32%, the pH (H2O) was 7.08, KA 40, sand content was 49%, silt content was 25%, and clay content was 26%. The maximum, minimum, and average temperature, precipitation amount, and number of rainy days during the maize growing season are displayed in Figure 1 and Figure 2 [43].

2.3. Experimental Design

The experiment was laid out in a randomized complete block design (RCBD) with three replications. Each replicate included 10 plants. The maize seeds were sown on 4 May 2022 using a Wintersteiger Plotman planter at a planting density of 75,000 plants per hectare. Standard agronomic practices, such as weeding and manual irrigation to supplement rainfall as needed, were especially important in July, August, and September, when the average afternoon temperatures ranged from 27 °C to 37 °C. In the meantime, the recommended fertilizer application for maize was used [44].

2.4. Data Collection

The maize yield measured in this study was influenced by four important components: number of rows per ear, number of kernels per ear, 1000-kernel weight (g), and ear weight (g). Typically, these components are selected in this order during the growing season.

2.5. Statistical Analysis

The data from the current study were analyzed based on multivariate analysis of variance (MANOVA) using a randomize complete design (CRD) for the laboratory study. On the other hand, the open-field study adopted one-way analysis of variance (ANOVA) with randomized complete block design (CRBD). In addition, Duncan’s multiple range test (DMRT) was used to compare the means with a probability of 0.05 using IBM SPSS 21 statistical analysis software and Microsoft Excel version 16.77 for descriptive statistics, including correlation analysis.

3. Results

3.1. Seed Viability and Vigor

The results of the MANOVA show that there were statistically significant differences between the two groups, the genotypes, the number of days, and their interaction on seed viability and vigor viz. germination rate (%), radicle length (cm), and plumule length (cm) for the confidence interval of 0.95 (Table 2).
The results displayed in Table 3 show the mean values of germination rate (%), radicle length (cm), and plumule length (cm) for various maize genotypes. For the total percentage of germination, most genotypes recorded a percentage rate above the grand mean (79.69%) except for V5 (SC hybrid), V7 (TC hybrid), V8 (parent), V12 (parent), V14 (SC hybrid), and V15 (SC hybrid), which recorded a percentage rate of 79.17%, 66.67%, 54.17%, 50.00%, 33.33%, and 75.00%, respectively. Meanwhile, the highest 100% germination rate was observed in V3 (parent) and V6 (DC hybrid), followed by V2 (parent) and V13 (SC hybrid), with 95.83%, whereas V14 (SC hybrid) showed the lowest germination rate (%), which was 33.33%.
The greatest radicle length was found in genotypes V2 (parent), V3 (parent), and V12 (parent), with 18.95 cm, 18.45 cm, and 18.09 cm, respectively. However, V9 (parent) produced the shortest radical length throughout the investigation period (11.41 cm). The study, which also focused on plumule length, found a substantial difference between the genotypes with the longest and shortest plumule lengths (V14 (parent), with 9.88 cm, and V7 (TC hybrid), with 5.79 cm), with a grand mean of 7.73 cm.
Based on observation, germination began on the second day after placing the seeds in the incubation chamber. The measurement and data collection started on the third day, once the radicle had reached more than 0.5 cm in length. Figure 3a illustrates a substantial relationship between the number of days and the percentage of germination. The results show that the percentage of germination was relatively slower and that there was no significant difference on days 3 and 5, at 36.61% and 39.62%, respectively. However, there was a significant increase in performance from day 5 to day 9 (76.04%).
The radicle length increased sharply, revealing highly significant differences, with values of 0.88 cm on day 3, 5.92 cm on day 5, 9.92 cm on day 7, and 15.97 cm on day 9 (Figure 3b). Additionally, Figure 3c shows that the length of the plumule expanded significantly as the number of incubation days increased. From 0.15 cm on day 3, the value increased to 1.64 cm on day 5, 4.08 cm on day 7, and 7.73 cm on day 9.

3.2. Yield Performance

3.2.1. Number of Rows Per Ear

A one-way ANOVA revealed that there was a statistical difference in means between groups (F (15, 224) = [40.48], p = [0.00] (Table 4). Table 5 shows the mean (12.35), minimum (7.00), maximum (18.00), and standard deviation (2.26) of the number of rows per ear for various maize genotypes. Nevertheless, Figure 4 displays the mean value for each genotype. V14 (SC hybrid) had the highest mean (15.07), which was followed by V8 (parent) and V13 (SC hybrid), with 14.53 and 14.27, respectively. V1 (parent) generated the lowest number of rows per ear (7.87), although V16 (check variety) generated a comparable number of rows per ear, which was 13.93.

3.2.2. Number of Kernels Per Ear

The results of the ANOVA in Table 6 reveal that there was a statistically significant mean between groups (F (15, 224) = [118.24], p = [0.00]. Although the mean number of kernels per ear was 214.80, the minimum value was 64.00, the maximum value was 538.00, and the standard deviation was 98.64 (Table 7). Nonetheless, Figure 5 displays the mean value for each genotype. The mean for V14 (SC hybrid) was the highest, at 436.27, and showed an astoundingly significant performance compared to other genotypes. V5 (SC hybrid) and V7 (TC hybrid) were next, with means of 329.13 and 325.67, respectively. V1 (parent) produced the lowest number of kernels per ear (74.00).

3.2.3. 1000-Kernel Weight (g)

According to the results of the ANOVA in Table 8, the mean difference in 1000-kernel weight between groups was highly significant (F (15, 32) = [9.56], p = [0.00]). The mean, minimum, maximum, and standard deviation values of the 1000-kernel weight for all genotypes were 318.23 g, 209.30 g, 472.20 g, and 60.59 g, respectively (Table 9). Meanwhile, Figure 6 reveals that V15 (SC hybrid) recorded the highest weight (438.87 g), whereas V3 (parent) recorded the lowest (220.33 g).

3.2.4. Ear Weight (g)

Ear weight is a crucial characteristic that greatly influences yield performance. According to the results, each genotype examined in this study demonstrated a significant difference, as shown in the results of the ANOVA in Table 10 (F (15, 224) = [41.815], p = [0.00]). On the other hand, Table 11 presents mean, minimum, maximum, and standard deviation values of 318.23 g, 22.20 g, 140.40 g, and 26.15 g, respectively. Overall, the ear weight was dominated by V14 (SC hybrid) at 105.89 g, followed by V7 (TC hybrid) at 100.05 g and V16 (control) at 98.45 g. Additionally, V3 (parent) delivered a less-than-satisfactory performance by only yielding an ear weight of 34.42 g (Figure 7).

3.3. Relationship between Seed Viability, Vigor, and Yield Traits

The correlation analysis between seed viability, vigor, and yield traits is shown in Table 12. The number of kernels per ear (NKPE) had a significant and positive correlation with the row number per ear (RPE) and 1000-kernel weight (1000 KWT), with values of 0.81, 0.41, and 0.77, respectively. In contrast, germination rate (%) (GR; 0.12) and radicle length (RL; 0.07) were not significant and were negatively correlated with plumule length (PL; −0.17). However, the proportion of ear weight (ER) was significantly and positively correlated with row number per ear (RPE; 0.65), the number of kernels per ear (NKPE; 0.77), and 1000- kernel weight (1000 KWT; 0.49) but not with radicle length (RL; 0.11) and was not significantly and was negatively correlated with germination rate (%) (GR; −0.06) and plumule length (PL; −0.08).

4. Discussion

Maize is a high-demand crop and is widely used in agriculture for food, animal feed, energy, and industrial materials. This is important to ensuring the survival of global food security. Understanding seed viability, vigor, and yield performance is a valuable method for improving seed quality, breeding high-yielding and disease-resistant maize varieties, and accelerating the development of modern and sustainable agriculture. Since the 1950s, Hungary has produced numerous hybrid varieties that have been widely used until now. Therefore, information on seed-quality testing and its relationship to hybrids and lines is an important indicator in maize production. the seed viability and vigor tests were carried out primarily according to ISTA’s international rules for seed testing [42]. Furthermore, field evaluation was carried out using hybrids and lines developed by local research institutes.

4.1. Seed Viability and Vigor

In this study, we found that seed viability and vigor performance were statistically significant between genotypes and the number of days. These significant differences in the characteristics studied appear to be highly dependent on genotypes and less responsive to other factors, as they typically appeared under ideal conditions [45,46]. Our findings revealed that the DC (100%) produced a better germination rate compared to the parent (81.47%), SC hybrid (70.83%), and TC hybrid (66.67%), which contradicted the previous findings [46], which found that single hybrids had the highest germination potential due to heterosis and genetic effects [35,47]. However, numerous factors affect the germination rate, which often varies by orders of magnitude between and within plant species [48,49]. Furthermore, previous studies also found significant paternal effects on seed germination characteristics [50]. In addition, seed size also affects the germination rate of maize, with small seeds being more water permeable, germinating faster, and being more uniform than larger seeds [51]. However, larger seeds retain their cotyledons for a longer amount of time, which is reflected in the strength and vigor of the seed, with a greater store of food, resulting in faster growth and emergence from the soil compared to seeds that store fewer nutrients [38,52]. On the other hand, larger seeds are associated with better performance in the field and more vigorous seedlings [53,54,55]. Although previous findings suggest that mature male or female plants would produce heavier seeds but are relatively slow to germinate [56], a reduction in seed vigor is a direct consequence of seed aging, which can affect crop performance [57].
The results obtained for radicle length and plumule length show that there were highly significant differences between genotypes. However, the overall results show that the parental lines dominated the development and elongation of the radicles and plumules. However, the radicle elongation rate was lowest in V9 (parent), whereas V7 (TC hybrid) showed the lowest performance in terms of plumule length. The DC hybrid exhibited better vigor potential based on the observed characteristics and possessed a better ability to develop and survive even under stressful conditions [46]. The findings from three separate studies indicated that some DC hybrid tomatoes displayed extreme rooting behavior compared to their parental lines [58], whereas TC hybrids outperformed the other hybrids and their parents because the ratio of chromosome structures increased with the number of parents involved in the crossing procedure [59]. In this laboratory study, it was also shown that V13 and V14 of SC hybrids were significantly different from several other genotypes in terms of plumule length, which is consistent with the results obtained from previous studies [19]. The differences in seed-quality characteristics discovered in hybrid types demonstrates that there were variances because of the genetic composition of the hybrids [46].

4.2. Yield Performance

Yield performance information is essential to ensuring consistency in maize cultivation and production sites. Many traits influence maize yield, including the number of rows per ear, kernels per ear, 1000-kernel weight, and ear weight. In all the genotypes examined in this study, we observed highly significant differences in the number of rows per ear among genotypes, and these results align with a study by [46], indicating that this characteristic contributes most to variation between different maize hybrid types. Our findings also revealed that SC hybrids were more prominent than the DC hybrid, the TC hybrid, and parental lines. This is mostly influenced by heterotic affect, which contributes greatly to hybrid performance in maize, especially for grain yield [60,61]. Additionally, it suggests that, in addition to environmental and nutritional factors, genetic factors also affect this trait [62,63,64] and that seed size directly affects the number of rows per ear [65].
Similar findings were observed for the number of kernels per ear, which is related to grain yield. Due to heterotic effects, the results show that SC hybrids dominated, followed by the TC hybrid, the DC hybrid, and parents, and, as expected, SC hybrids had the most uniform performance compared to others [66]. On the other hand, increasing the number of rows and kernels per ear directly increases grain yield [62,67]. In addition, environmental factors strongly influence kernel formation, particularly during the flowering stage, when moisture stress reduces the number of kernels by about 15% within two weeks of silking, with a reduction of up to 20% also having been observed [68]. In addition, pollination has a significant impact on grain yield, with 85% of yield being correlated with kernel production per acre and 15% being correlated with individual kernel weight at harvest for a specific hybrid [67]. At the same time, studies show that prolonged exposure to temperatures above 32 degrees Celsius could reduce pollen germination to almost zero for many genotypes [69]. Moreover, a statistically significant difference in the direct effect of temperature on the number of seeds per ear has been demonstrated [65].
The 1000-kernel weight is entirely determined by kernel size, and most of it is influenced by genetic, environmental, and nutrient factors [64,70]. It is also an important factor directly contributing to the final grain yield of the crop [62]. Findings from this trial showed that the performance trend of the 1000-kernel weight was correlated with the number of rows per ear and the number of kernels per ear. This demonstrates a significant difference for all genotypes studied, with hybrid lines predominating and producing heavier 1000-kernel weights than the parental lines. Furthermore, these findings suggest that kernel weight is influenced by size and source [65]. There was also a favorable association with ear weight.
In a way, ear weight is the ultimate objective for maize research, which directly contributes to the grain yield. In this study, we found that the ear weight was related to other traits, such as the number of rows per ear, the number of kernels per ear, and the 1000-kernel weight. These results are consistent with previous reports [62,71], which observed that considerable differences among maize lines, despite an increase or decrease in other traits, affect crop production yield.
In previous research, less emphasis was placed on the comparative benefits of TC hybrids and DC hybrids than SC hybrids. The present investigation supports the idea of previously established information that suggests that SC hybrids have advantages over TC hybrids or DC hybrids; however, this study demonstrates on a prominent level that the presence of TC confers advantages compared to SC and DC hybrids [72,73].

4.3. Relationship between Seed Viability, Vigor, and Yield Traits

The relationship between two variables can be measured quantitatively independent of other factors considered [74]. The relationship between these traits is also important in achieving the objectives of a breeding program. Among many techniques, correlation coefficient analysis is the most frequently utilized [75]. The relationship between seed viability, vigor, and yield traits also varies between hybrids and lines depending on production practices and crop market requirements [76]. This study found that kernel number per ear was significantly and positively correlated with the number of rows per ear and 1000-kernel weight.
However, there was no significant difference between germination rate and radicle length and a negative correlation with plumule length. Hence, an increase in kernel number, rows, kernel weight, and ear weight does not affect the viability and vigor of the seed. Furthermore, the results suggest that seed viability and vigor were most affected by genetic variables [19,47], which do not affect yield performance in the field. Seven key characteristics affect seed germination and vigor, including genetic content, the environment and nutrition of the maternal plant, harvest maturity stage, seed size or weight, mechanical integrity, seed aging, and pathogens [76]. Seed viability, vigor, and size can also directly and indirectly affect crop yield, in addition to seed emergence percentage and time from sowing to emergence [77]. According to earlier studies, seed vigor also influences vegetative growth. It affects yield if plants are harvested at the vegetative or early reproductive stages but not when they are harvested at full reproductive maturity [76,77].

5. Conclusions

Seed viability and vigor are complex traits that are determined at various maternal and seed development stages leading up to seed germination. In addition to genetic factors, environmental factors affect seed germination, emergence, and seedling performance in the field. Therefore, in the current study, we found that seed viability and vigor were statistically significant between genotype and number of days. The DC hybrid (100%) resulted in a better germination rate compared to parents (81.47%), SC hybrids (70.83%), and the TC hybrid (66.67%). These results emphasize that the parental lines showed better performance in terms of germination percentage and radicle elongation, whereas the SC hybrid produced better plumule length. Moreover, the length of the plumule expanded significantly as the number of incubation days increased. In the field evaluation, as expected, the hybrid lines performed better than the parental lines, and the SC hybrids were more dominant than the DC hybrid and the TC hybrid. The results indicate that the number of rows per ear, number of kernels per ear, 1000-kernel weight, and ear weight directly contributed to the final grain yield of the crop. Crop yield is affected whether the other traits increase or decrease. The study also revealed that 1000-kernel weight performance was influenced by the number of rows and kernel number per ear, with hybrid lines being the most dominant and ear weight showing a favorable association.
There are numerous opportunities to improve maize’s contribution to global crop production by addressing seed-quality issues and enhancing yield production by considering biotic and abiotic factors. Further research is needed to overcome this problem by increasing the utilization of genetic resources. Moreover, integrated and multidisciplinary approaches should also be implemented to strengthen improvement programs.
Furthermore, intensive research is required to expand the number of genotypes examined across diverse locations and growing seasons by adopting sustainable agriculture practices. That information will assist researchers in conducting research and producing superior varieties while ensuring the sufficiency of food supplies in the near future, thereby benefiting the agriculture and seed industries.

Author Contributions

Methodology, investigation, writing—original paper, S.O.; methodology, R.A.G.; methodology, N.K.; conceptualization, review, M.J.; supervision, Á.T.; supervision, review, Z.K.; funding acquisition, A.P. and P.P.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Hungarian University of Agriculture and Life Sciences.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data, tables, and figures in this manuscript are original.

Acknowledgments

We appreciate the funding provided by the Researchers Recruitment Programme of the National Agricultural Research and Innovation Centre (Gödöllo, Hungary).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Golob, P.; Kutukwa, N.; Devereau, A.; Bartosik, R.E.; Rodriguez, J.C. Chapter two: In Maize. In Crop Post-Harvest: Science and Technology; Hodges, R., Farrell, G., Eds.; Blackwell Publishing Ltd.: Ames, Iowa, 2004; Volume 2. [Google Scholar]
  2. Suleiman, R.; Rosentrater, K.A.; Bern, C. Effects of Deterioration Parameters on Storage of Maize: A Review. Wuhan Univ. J. Nat. Sci. 2003, 3, 147–165. [Google Scholar]
  3. Breadley, P.R. British Herbal Compendium; British Herbal Medicine Association: Bournemouth, UK, 1992; Volume 2. [Google Scholar]
  4. Ranum, P.; Peña-Rosas, J.P.; García-Casal, M.N. Global maize production, utilization, and consumption. Ann. N. Y. Acad. Sci. 2014, 1312, 105–112. [Google Scholar] [CrossRef] [PubMed]
  5. Kumar, D.; Jhariya, A.N. Nutritional, Medicinal and Economical Importance of Corn: A Mini Review. Res. J. Pharm. Sci. 2013, 2, 7–8. Available online: http://www.isca.in/IJPS/Archive/v2/i7/2.ISCA-RJPcS-2013-029.pdf (accessed on 23 June 2023).
  6. Pruitt, J.D. A Brief History of Corn: Looking Back to Move Forward. Doctoral Document. 2016, pp. 5–6. Available online: http://digitalcommons.unl.edu/planthealthdoc/7 (accessed on 23 June 2023).
  7. Hake, S.; Ross-Ibarra, J. Genetic, evolutionary and plant breeding insights from the domestication of maize. eLife 2015, 4, e05861. [Google Scholar] [CrossRef] [PubMed]
  8. States, T.U.; Maize, S.A.; Uses, O. Maize Cultivation: Advanced Maize Production Technologies Introduction: Importance: Land Preparation: Ecological Requirement. 2010. Available online: https://kvk.icar.gov.in/API/Content/PPupload/k0376_3.pdf (accessed on 23 June 2023).
  9. Hungarian Central Statistical Office Home Page. Harvest Results of Main Crops. 2020. Available online: https://www.ksh.hu/docs/eng/xftp/stattukor/fobbnoveny/2020/index.html#furtherdataandinformation (accessed on 30 June 2023).
  10. Hungarian Central Statistical Office Home Page. 19.1.2.5. Production of Maize by Country and Region. 2023. Available online: https://www.ksh.hu/stadat_files/mez/en/mez0072.html (accessed on 30 June 2023).
  11. Harvey, F. Falls in Europe’s Crop Yields Due to Heatwaves Could Worsen Price Rises. 2022. Available online: https://www.theguardian.com/environment/2022/jul/27/big-falls-in-crop-yields-across-europe-feared-due-to-heatwaves (accessed on 27 June 2023).
  12. Xiao, Y.; Wang, M.; Song, Y. Abiotic and biotic stress cascades in the era of climate change pose a challenge to genetic improvements in plants. Forests 2022, 13, 780. [Google Scholar] [CrossRef]
  13. Li, Y.; Guan, K.; Schnitkey, G.; DeLucia, E.H.; Peng, B. Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Glob. Change Biol. 2022, 25, 2325–2337. [Google Scholar] [CrossRef]
  14. Roger, E. Influence of Soil Temperature on Corn Germination and Growth. Integrated Crop Management 2012. Available online: https://crops.extension.iastate.edu/cropnews/2012/03/influence-soil-temperature-corn-germination-and-growth (accessed on 27 June 2023).
  15. Denis, T.; Gales, D.; Chiriac, G.; Răus, L.; Jităreanu, G. Impact of plowing on some soil physical properties under hybrid seed corn production. ProEnvironment/ProMediu 2013, 6, 183–186. [Google Scholar]
  16. Venkatesh, T.V.; Breeze, M.L.; Liu, K.; Harrigan, G.G.; Culler, A.H. Compositional analysis of grain and forage from MON 87427, an inducible male sterile and tissue selective glyphosate-tolerant maize product for hybrid seed production. J. Agric. Food Chem. 2014, 62, 1964–1973. [Google Scholar] [CrossRef]
  17. Arisnabarreta, S.; Solari, F. Hybrid maize seed production yield associations with inbred line performance in multi-environment trials. Crop Sci. 2017, 57, 3203–3216. [Google Scholar] [CrossRef]
  18. Marton, L.C. Hybrid maize in Hungary is 60 years old. In 60 Years of Hungarian Hybrid Maize; Pannonian Plant Biotechnology Association: Tolna County, Hungary, 2013; pp. 10–16. Available online: https://www.pannonbiotech.hu/_upload/editor/Hibridkukorica-beliv-angol-screen.pdf (accessed on 27 June 2023).
  19. Omar, S.; Tarnawa, Á.; Kende, Z.; Abd Ghani, R.; Kassai, M.K.; Jolánkai, M. Germination characteristics of different maize inbred hybrids and their parental lines. Cereal Res. Commun. 2022, 50, 1229–1236. [Google Scholar] [CrossRef]
  20. MacRobert, J.F.; Setimela, P.S.; Gethi, J.; Worku, M. Maize Hybrid Seed Production Manual. 2014. Mexico, D.F. CIMMYT. Available online: https//repositorycimmyt.org (accessed on 27 June 2023).
  21. Nagy, J. Maize Production: Food, Energy Biomass; Akadémiai Kiadó: Budapest, Hungary, 2008; ISBN 9789630586368. [Google Scholar]
  22. Berzy, T.; Záborszky, S.; Marton, L.C.; Spitkó, T.; Pintér, J.; Tóthné Zsubori, Z.; Szőke, C. Effect of seed deterioration, seed dressing agents and seed vigours parameters in maize (Zea mays L.) hybrids. Int. J. Agric. Environ. Biores. 2020, 5, 72–81. [Google Scholar] [CrossRef]
  23. Rajesh, S.; Ram, L.; Srivastava, R.P. A Journey of Hybrids in Maize: An Overview. India Res. J. Ext. Educ. 2012, 1, 340–344. [Google Scholar]
  24. El-Abady, M.I. Influence of maize seed size/shape, planted at different depths and temperature on seed emergence and seedling vigor. Res. J. Seed Sci. 2015, 8, 1–11. [Google Scholar] [CrossRef]
  25. Goggi, A.S.; Caragea, P.; Pollak, L.; McAndrews, G.; DeVries, M.; Montgomery, K. Seed quality assurance in maize breeding program: Test to explain variations in maize inbreds and populations. Agron. J. 2002, 100, 337–343. [Google Scholar] [CrossRef]
  26. Shibata, M.; Coelho, C.M.M.; Araldy, C.G.; Adan, N.; Peroni, N. Physiological and physical quality of local Araucaria angustifolia seed variety. Acta Sci. Agron. 2016, 38, 249–256. [Google Scholar] [CrossRef]
  27. Munamava, M.R.; Goggi, A.S.; Pollak, L. Seed quality of maize inbred lines with different composition and genetic backgrounds. Crop Sci. Soc. Am. 2004, 44, 542–548. [Google Scholar] [CrossRef]
  28. Illipronti, J.; Langerak, L.A.; Lommen, W.J.M. Variation in and relation between physical and physiological seed attributes within soyben seed lot. Seed Sci. Technol. 1997, 5, 215–231. [Google Scholar]
  29. Tuan, P.A.; Sun, M.; Nguyen, T.-N.; Park, S.; Ayele, B.T. Molecular mechanisms of seed germination. Sprouted Grains 2019, 1–24. [Google Scholar] [CrossRef]
  30. Rizzardi, M.A.; Luiz, A.R.; Roman, E.S.; Vargas, L. Temperatura cardeal e potencial hídrico na germinação de sementes de corda-de-viola (Ipomoea triloba). Planta Daninha 2009, 27, 13–21. [Google Scholar] [CrossRef]
  31. Aderounmu, A.F.; Nkemnkeng, F.J.; Anjah, G.M. Effects of seed provenance and growth media on the growth performance of Vitellaria paradoxa C.F. Gaertn. Int. J. Biol. Chem. Sci. 2020, 14, 2659–2669. [Google Scholar] [CrossRef]
  32. Prerna, D.I.; Govindaraju, K.; Tamilselvan, S.; Kannan, M.; Vasantharaja, R.; Chaturvedi, S.; Shkolnik, D. Influence of nanoscale micro-nutrient α-Fe2O3 on seed germination, seedling growth, translocation, physiological effects, and yield of rice (Oryza sativa) and maize (Zea mays). Plant Physiol. Biochem. 2021, 162, 564–580. [Google Scholar] [CrossRef] [PubMed]
  33. Masubelele, N.H.; Dewitte, W.; Menges, M.; Maughan, S.; Collins, C.; Huntley, R.; Nieuwland, J.; Scofield, S.; Murray, J.A.H. D-type cyclins activate division in the root apex to promote seed germination in Arabidopsis. Proc. Natl. Acad. Sci. USA 2005, 102, 15694–15699. [Google Scholar] [CrossRef]
  34. Ltroutwar, P.D.; Kasivelu, G.; Raguraman, V.; Malaichamy, K.; Sevathapandian, S.K. Effects of biogenic zinc oxide nanoparticles on seed germination and seedling vigor of maize (Zea mays). Biocatal. Agric. Biotechnol. 2020, 29, 101778. [Google Scholar]
  35. Vishal, B.; Kumar, P.P. Regulation of seed germination and abiotic stresses by gibberellins and abscisic acid. Front. Plant Sci. 2018, 9, 838. [Google Scholar] [CrossRef] [PubMed]
  36. Clor, M.A.; Al-Ani, T.A.; Charchafchy, F. Germinability and seedling vigor of Haloxylon salicornicumi as affected by storage and seed size. J. Range Manag. 1976, 29, 60–62. [Google Scholar] [CrossRef]
  37. Krishnan, P.; Rao, A.V.S. Effects of genotypes and environment on seed yield and quality of rice. J. Agric. Sci. 2005, 143, 283–292. [Google Scholar] [CrossRef]
  38. Lafta, A.K.; Chilab, Y.K. Evaluation of the vigor and viability of maize (Zea mays L.) seeds which resultant from planting date and plant density on yield character. Plant Arch. 2019, 19, 1663–1671. [Google Scholar] [CrossRef]
  39. Hamza, J.H. The Effect of Seed Size and Which Produced from Planting Dates on Seed Vigor and Grain Yield of (Sorghum bicolor L. Monech). Ph.D. Thesis, Field Crops Department, Agriculture College, Baghdad University, Baghdad, Iraq, 2006; p. 131. [Google Scholar]
  40. Shirin, M.; Enayatgholizadeh, M.R.; Siadat, E.; Fathi, G. Comparison of suitable seed vigour of hybrid Zea mays (CV. SC.704) in the field condition of Ahvaz. In Proceedings of the 10th Congress of Agronomy and Plant Breeding of Iran, Karaj, Iran, 18–20 August 2008; p. 330. [Google Scholar]
  41. Marcos, J. Seed vigor testing: An overview of the past, present, and future perspective. Sci. Agric. 2015, 72, 363–374. [Google Scholar] [CrossRef]
  42. ISTA. International Rules for Seed Testing; International Seed Testing Association: Bassersdorf, Switzerland, 2014. [Google Scholar]
  43. World Weather Online. Available online: https://www.worldweatheronline.com/ (accessed on 7 September 2023).
  44. Hoffmann, R. A Kukorica Trágyázása. In Agroforum.hu. 8 October 2018; Hungary. Available online: https://agroforum.hu/szakcikkek/tapanyag-utanpotlas/a-kukorica-tragyazasa/ (accessed on 7 September 2023).
  45. Soyelu, L.O.; Ajayi, S.A.; Aluko, O.B.; Fakorede, M.A.B. Varietal differences for development of maize (Zea mays L.) seedlings on compacted soils. J. Agron. Crop Sci. 2001, 186, 157–166. [Google Scholar] [CrossRef]
  46. Oluwaranti, A.; Badmus, O.T.; Awoniyi, S.O.; Akintola, A.M.; Bankole, O.O.; Awosanmi, F.E. Comparative analysis of physiological seed quality and field performance of single-, three-way and double-cross hybrids of tropical maize germplasm. Life J. Agric. 2018, 30, 83–98. [Google Scholar]
  47. Bewley, J.D.; Lack, M. Physiology and Biochemistry of Seeds in Relation to Germination, 2nd ed.; Springer Press: New York, NY, USA, 1982; p. 365. [Google Scholar] [CrossRef]
  48. Leishman, M.R.; Westoby, M.; Jurado, E. Correlates of seed size variation: A comparison among five temperate floras. J. Ecol. 1995, 83, 517–529. [Google Scholar] [CrossRef]
  49. Silvertown, J.; Bullock, J.M. Do Seedlings in Gaps Interact? A Field Test of Assumptions in ESS Seed Size Models. Oikos 2003, 101, 499–504. [Google Scholar] [CrossRef]
  50. Andersson, S.; Mansby, E.; Prentice, H.C. Paternal effects on seed germination: A barrier to the genetic assimilation of an endemic plant taxon? J. Evol. Biol. 2008, 21, 1408–1417. [Google Scholar] [CrossRef] [PubMed]
  51. Kadafi, M.; Anne, N.; Agus, W.; Anita Lestari, S. The Relationship Between Seed Size and Seed Quality in UNPAD New Seed Collection of Sweet Corn Lines After Storage. In Proceedings of the International Conference on Food, Agriculture and Natural Resources (FANRes 2018), Bantul, Indonesia, 12–14 September 2018. [Google Scholar] [CrossRef]
  52. Jallow, R.A.J.; Fissah, A.T.; Al-Beiruty, R.Z.; Shakir, S.H. Effect of seed maize and depth of planting on field germination percentage and it’s relation to maize grain yield and components of maize. Iraqi J. Agric. 2009, 14, 9–20. [Google Scholar]
  53. Ambika, S.; Manonmani, V.; Somasundaram, G. Review on effect of seed size on seedling vigour and seed yield. Res. J. Seed Sci. 2014, 7, 31–38. [Google Scholar] [CrossRef]
  54. Al-Karaki, G.N. Seed size and water potential effects on water uptake, germination, and growth of lentil. J. Agron. Crop Sci. 1998, 181, 237–242. [Google Scholar] [CrossRef]
  55. Shi, R.; Tong, L.; Du, T.; Shukla, M.K. Response and Modeling of Hybrid Maize Seed Vigor to Water Deficit at Different Growth Stages. Water 2020, 12, 3289. [Google Scholar] [CrossRef]
  56. Meena, R.K.; Pullaiahgari, D.; Gudipalli, P. Proteomic analysis of heterotic seed germination in maize using F1 hybrid DHM 117 and its parental inbreds. Turk. J. Biol. Turk Biyol. Derg. 2018, 42, 345–363. [Google Scholar] [CrossRef]
  57. Ghassemi-Golezani, K.; Dalil, B. Effects of seed vigor on growth and grain yield of maize. Plant Breed. Seed Sci. 2014, 70, 81–90. [Google Scholar] [CrossRef]
  58. Ashakina, A.; Hasanuzzaman, M.; Arifuzzaman, M.; Rahman, M.; Kabir, M. Performance of single, double, and three-way cross hybrids in tomato (Lycopersicon esculentum Mill.). J. Food Agric. Environ. 2016, 1414, 71–77. [Google Scholar]
  59. Yıldırım, M.; Cakmak, M. Evaluation of hybrid seeds of three-way and single cross for grain number and weight in bread and durum wheat. Turk. J. Agric. -Food Sci. Technol. 2018, 6, 22. [Google Scholar] [CrossRef]
  60. Li, D.; Zhou, Z.; Lu, X.; Jiang, Y.; Li, G.; Li, J.; Liu, W. Genetic dissection of hybrid performance and heterosis for yield-related traits in maize. Front. Plant Sci. 2021, 12, 774478. [Google Scholar] [CrossRef]
  61. Joshi, P.; Gautam, D. Genetic insights on single cross maize hybrid and its importance on maize self-sufficiency in Nepal. Arch. Agric. Environ. Sci. 2021, 6, 218–226. [Google Scholar] [CrossRef]
  62. Tahir, M.; Tanveer, A.; Ali, A.; Abbas, M.; Wasaya, A. Comparative Yield Performance of Different Maize (Zea mays L.) Hybrids under Local Conditions of Faisalabad-Pakistan. Pak. J. Life Soc. Sci. 2008, 6, 118–120. Available online: https://www.researchgate.net/publication/236330855 (accessed on 28 June 2023).
  63. Ladan, K.M.; Hassan, A.H. Yield performance of three maize (Zea mays L.) varieties as influenced by time of nitrogen fertilizer topdressing in savannah zone of Nigeria. J. Agric. Environ. 2020, 16, 43–52. [Google Scholar]
  64. Ali, Z. Studies on Comparative Economic Returns of Different Maize Genotypes. Master’s Thesis, Department Agronomy, University Agriculture, Faisalabad, Pakistan, 1994. [Google Scholar]
  65. EnayatGholizadeh, M.; Bakhshandeh, A.; Shoar, M.D.; Ghaineh, M.; Saeid, K.A.; Sharafizadeh, M. Effect of Source and Seed Size on Yield Component of Corn S.C704 in Khuzestan. Afr. J. Biotechnol. 2012, 11, 2938–2944. Available online: https://www.ajol.info/index.php/ajb/article/view/100681 (accessed on 28 June 2023). [CrossRef]
  66. Geletata, L. Comparative performance and heterosis in single, three-way, and double cross pepper hybrids. J. Agric. Sci. 2004, 142, 659–663. [Google Scholar] [CrossRef]
  67. Stephen, D.S. Corn Grain Yield in Relation to Stress during Ear Development. Crop Insights 2016, 26, 1–5. Available online: https://www.pioneer.com/CMRoot/Pioneer/US/Non_Searchable/programs_services/earn-the-right/Corn-Yield-Stress-Ear-Development.pdf (accessed on 28 June 2023).
  68. Harder, H.J.; Carlson, R.E.; Shaw, R.H. Yield, yield components, and nutrient content of corn grain as influenced by post-silking moisture stress1. Agron. J. 1982, 74, 275–278. [Google Scholar] [CrossRef]
  69. Herrero, M.P.; Johnson, R.R. High temperature stress and pollen viability of maize1. Crop Sci. 1980, 20, 796–800. [Google Scholar] [CrossRef]
  70. Jing, Q.; Bingwv, W.; Yong, M. A study on comprehensive evaluation of maize hybrids. J. Jilin-Agric. Univ. 2003, 25, 139–142. [Google Scholar]
  71. McCutcheon, J.; Siegrist, H.; Rzenwncki, P. Fair Field, Licking, and Perry Counties- Commercial Corn Hybrid Side by Side Performance Trials. Spec. Circ. Ohio Agric. Res. Dev. Cent. 2001, 179, 54–56. Available online: https://agcrops.osu.edu/research-report/1999/fairfield-licking-and-perry-counties-commercial-corn-hybrid-side-side (accessed on 1 July 2023).
  72. Zeng, L.; Wu, J.; Bechere, E. Comparative genetic analysis of lint yield and fibre quality among single, three-way, and double crosses in upland cotton. Crop Sci. 2017, 57, 192–201. [Google Scholar] [CrossRef]
  73. Zemach, S.; Wassu, M.; Dagne, W.; Amsal, T. Performances of three-way cross hybrids over their respective single crosses and related heterosis of maize (Zea mays L.) hybrids evaluated in Ethiopia. Heliyon 2023, 9, 1–12. [Google Scholar] [CrossRef]
  74. Owen, E.; Jones, F. Statistics 3rd; Renold Publishing Company: New York, NY, USA, 1977; 30p. [Google Scholar]
  75. Yagdi, K.O.K.S.A.L.; Sozen, E. Heritability, variance components and correlations of yield and quality traits in durum wheat (Triticum durum Desf.). Pak. J. Bot 2009, 41, 753–759. [Google Scholar]
  76. Finch-Savage, W.E.; Bassel, G.W. Seed vigour and crop establishment: Extending performance beyond adaptation. J. Exp. Bot. 2016, 67, 567–591. [Google Scholar] [CrossRef]
  77. TeKrony, D.M.; Egli, D.B. Relationship of seed vigor to crop yield: A review. Crop Sci. 1991, 31, 816–822. [Google Scholar] [CrossRef]
Agriculture 13 01836 g001
Figure 1. Max, min, and average weather temperature 2022 (Gödöllö, Hungary). https://www.worldweatheronline.com/ (accessed on 7 September 2023).
Figure 1. Max, min, and average weather temperature 2022 (Gödöllö, Hungary). https://www.worldweatheronline.com/ (accessed on 7 September 2023).
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Agriculture 13 01836 g002
Figure 2. Average precipitation amounts and rainy days in 2022 (Gödöllö, Hungary). https://www.worldweatheronline.com/ (accessed on 7 September 2023).
Figure 2. Average precipitation amounts and rainy days in 2022 (Gödöllö, Hungary). https://www.worldweatheronline.com/ (accessed on 7 September 2023).
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Agriculture 13 01836 g003
Figure 3. Seed viability and vigor in response to the incubation days. (a) Germination rate (%); (b) radicle length (cm); (c) plumule length (cm). Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
Figure 3. Seed viability and vigor in response to the incubation days. (a) Germination rate (%); (b) radicle length (cm); (c) plumule length (cm). Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
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Agriculture 13 01836 g004
Figure 4. Histograms represent mean values of the number of rows per ear for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
Figure 4. Histograms represent mean values of the number of rows per ear for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
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Agriculture 13 01836 g005
Figure 5. Histograms represent mean values of the number of kernels per ear for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
Figure 5. Histograms represent mean values of the number of kernels per ear for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
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Agriculture 13 01836 g006
Figure 6. Histograms represent mean values of 1000-kernel weight (g) for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
Figure 6. Histograms represent mean values of 1000-kernel weight (g) for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
Agriculture 13 01836 g006
Agriculture 13 01836 g007
Figure 7. Histograms represent mean values of the ear weight (g) for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
Figure 7. Histograms represent mean values of the ear weight (g) for various maize genotypes. Different lowercase letters represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) starting sequentially, with the letter (a) being the most significant.
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Table 1. Maize genotypes used in the sample and their descriptions.
Table 1. Maize genotypes used in the sample and their descriptions.
SourceEntryGenotypesDescription
MartonvásárV1B1026/17Parent
V2MCS901/19Parent
V3TK/15/DVParent
V4TK1083/18Parent
V5TK623/18SC Hybrid 1
V6TK256/17DC Hybrid 2
V7TK222/17TC Hybrid 3
Szeged UniversityV8GK131Parent
V9GK144Parent
V10GK150Parent
V11GK154Parent
V12GK155Parent
V13GK144X150SC Hybrid 1
V14GK154X155SC Hybrid 1
V15Szegedi 521SC Hybrid 1
CommercialV16MV277Control
1 TC Hybrid = triple-cross hybrid, 2 SC Hybrid = single-cross hybrid, 3 DC Hybrid = double-cross hybrid.
Table 2. Multivariate analysis of variance (MANOVA) for germination rate (%), radicle length (cm), and plumule length (cm) of various maize genotypes on different incubation days.
Table 2. Multivariate analysis of variance (MANOVA) for germination rate (%), radicle length (cm), and plumule length (cm) of various maize genotypes on different incubation days.
SourceDependent VariablesSum SquareDfMean SquareF
DaysGermination rate (%)388.9533129.651142.246 **
Radicle length (cm)7824.54532608.1821681.805 **
Plumule length (cm)2110.9863703.6621419.352 **
GenotypesGermination rate (%)158.1091510.54111.565 **
Radicle length (cm)182.8611512.1917.861 **
Plumule length (cm)51.976153.4656.989 **
Days × genotypesGermination rate (%)62.422451.3871.522 *
Radicle length (cm)247.334455.4963.544 **
Plumule length (cm)33.788450.7511.515 *
ErrorGermination rate (%)175.0001920.911
Radicle length (cm)297.7581921.551
Plumule length (cm)95.1861920.496
TotalGermination rate (%)3714.000256
Radicle length (cm)25,731.023256
Plumule length (cm)5249.053256
* = p < 0.005; ** = p < 0.001.
Table 3. Mean values of germination rate (%), radicle length (cm), and plumule length (cm) of various maize genotypes.
Table 3. Mean values of germination rate (%), radicle length (cm), and plumule length (cm) of various maize genotypes.
1 Genotypes2 Germination Rate (%)3 Radicle Length (cm)4 Plumule Length (cm)
V1 (parent)83.33 a–d13.42 fg8.23 b
V2 (parent)95.83 ab18.95 a7.41 b
V3 (parent)100 a18.45 ab7.54 b
V4 (parent)87.50 abc14.60 ef7.45 b
V5 (SC hybrid)79.17 bcd16.92 a–e7.76 b
V6 (DC hybrid)100 a16.37 b–e7.22 b
V7 (TC hybrid)66.67 de15.86 c–f5.79 c
V8 (parent)54.17 e16.78 a–e7.91 b
V9 (parent)83.33 a–d11.41 g7.42 b
V10 (parent)91.65 abc17.70 a–d8.30 b
V11 (parent)87.49 abc13.9 f7.65 b
V12 (parent)50.00 ef18.09 abc7.75 b
V13 (SC hybrid)95.83 ab16.91 a–e8.04 b
V14 (SC hybrid)33.33 f13.68 fg9.88 a
V15 (SC hybrid)75.00 cd15.17 def7.65 b
V16 (control)91.67 abc17.30 a–d7.78 b
Grand mean79.6915.977.73
SEM (±)2.710.310.14
Different lowercase letters (column) represent significant differences between the means (p < 0.05) based on Duncan’s multiple range test (DMRT) and starting sequentially, with the letter (a) being the most significant; 1 sixteen genotypes that were used in this study; 2 the percentage of germination of various genotypes (%); 3 the mean length of the radicles of various genotypes (cm); 4 the mean of the length of the of various genotypes (cm).
Table 4. Analysis of variance (ANOVA) for number of rows per ear of various maize genotypes.
Table 4. Analysis of variance (ANOVA) for number of rows per ear of various maize genotypes.
SourceSum of SquaredfMean SquareFSig.
Rows ear−1Between groups893.1331559.54240.4820.00
Within groups329.4672241.471
Total1222.600239
df: Degree of freedom; Sig.: significance; significance level = p < 0.01.
Table 5. Mean, minimum, maximum, and standard deviation for the number of rows per ear of various maize genotypes.
Table 5. Mean, minimum, maximum, and standard deviation for the number of rows per ear of various maize genotypes.
SourceNo.MeanMinimumMaximumStd. Deviation
Rows ear−124012.35007.0018.002.26174
Valid N (listwise)240
Table 6. Analysis of variance (ANOVA) for kernels per ear of various maize genotypes.
Table 6. Analysis of variance (ANOVA) for kernels per ear of various maize genotypes.
SourceSum of SquaredfMean SquareFSig.
No. of kernels per ear−1Between groups2,064,762.86315137,650.858118.2430.000
Within groups260,766.9932241164.138
Total2,325,529.796239
df: degree of freedom; Sig.: significance; significance level = p < 0.01.
Table 7. Mean, minimum, maximum, and standard deviation for kernels per ear of various maize genotypes.
Table 7. Mean, minimum, maximum, and standard deviation for kernels per ear of various maize genotypes.
SourceNo.MeanMinimumMaximumStd. Deviation
No. of kernels per ear−1240214.8064.00538.0098.64203
Valid N (listwise)240
Table 8. Analysis of variance (ANOVA) for the 1000-kernel weight (g) of various maize genotypes.
Table 8. Analysis of variance (ANOVA) for the 1000-kernel weight (g) of various maize genotypes.
SourceSum of SquaredfMean SquareFSig.
1000-kernel weight (g)Between groups141,061.910159404.1279.5610.000
Within groups31,476.45332983.639
Total172,538.36347
df: degree of freedom; Sig.: significance; significance level = p < 0.01.
Table 9. Mean, minimum, maximum, and standard deviation for the 1000-kernel weight (g) of various maize genotypes.
Table 9. Mean, minimum, maximum, and standard deviation for the 1000-kernel weight (g) of various maize genotypes.
SourceNo.MeanMinimumMaximumStd. Deviation
1000-kernel weight (g)48318.23209.30472.2060.58902
Valid N (listwise)48
Table 10. Analysis of variance (ANOVA) for the ear weight (g) of various maize genotypes.
Table 10. Analysis of variance (ANOVA) for the ear weight (g) of various maize genotypes.
SourceSum of SquaredfMean SquareFSig.
Ear weight (g)Between groups120,460.654158030.71041.8150.000
Within groups45,822.069224192.054
Total166,282.723239
df: Degree of freedom; Sig.: significance; significance level = p < 0.01.
Table 11. Mean, minimum, maximum, and standard deviation for the ear weight (g) of various maize genotypes.
Table 11. Mean, minimum, maximum, and standard deviation for the ear weight (g) of various maize genotypes.
SourceNo.MeanMinimumMaximumStd. Deviation
Ear weight240318.2322.20140.4026.15377
Valid N (listwise)240
Table 12. Relationship between the seed viability and vigor yield traits (N = 240).
Table 12. Relationship between the seed viability and vigor yield traits (N = 240).
1RPE2NKPE31000 KWT4EW5GR %6RL7PL
1RPE1
2NKPE0.81 **1
31000 KWT0.38 **0.41 **1
4EW0.65 **0.77 **0.49 **1
5GR %−0.04 ns0.12 ns−0.004 ns−0.06 ns1
6RL0.15 ns0.07 ns0.03 ns0.11 ns0.18 *1
7PL−0.19 ns−0.17 *−0.05 ns−0.08 ns−0.20 **0.09 ns1
* = p < 0.005; ** = p < 0.001; ns = not significant (2–tailed). 1RPE—rows per ear; 2NKPE—number of kernels per row; 31000 KWT—1000-kernel weight (g); 4EW—ear weight (g); 5GR %—germination rate (%); 6RL = radicle length (cm); 7PL = plumule length (cm).
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Omar, S.; Abd Ghani, R.; Khalid, N.; Jolánkai, M.; Tarnawa, Á.; Percze, A.; Mikó, P.P.; Kende, Z. Effects of Seed Quality and Hybrid Type on Maize Germination and Yield in Hungary. Agriculture 2023, 13, 1836. https://doi.org/10.3390/agriculture13091836

AMA Style

Omar S, Abd Ghani R, Khalid N, Jolánkai M, Tarnawa Á, Percze A, Mikó PP, Kende Z. Effects of Seed Quality and Hybrid Type on Maize Germination and Yield in Hungary. Agriculture. 2023; 13(9):1836. https://doi.org/10.3390/agriculture13091836

Chicago/Turabian Style

Omar, Suhana, Rosnani Abd Ghani, Noriza Khalid, Márton Jolánkai, Ákos Tarnawa, Attila Percze, Péter Pál Mikó, and Zoltán Kende. 2023. "Effects of Seed Quality and Hybrid Type on Maize Germination and Yield in Hungary" Agriculture 13, no. 9: 1836. https://doi.org/10.3390/agriculture13091836

APA Style

Omar, S., Abd Ghani, R., Khalid, N., Jolánkai, M., Tarnawa, Á., Percze, A., Mikó, P. P., & Kende, Z. (2023). Effects of Seed Quality and Hybrid Type on Maize Germination and Yield in Hungary. Agriculture, 13(9), 1836. https://doi.org/10.3390/agriculture13091836

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