Traits In Maize Research Articles

Investigation of Ustilago maydis Infection on Some Physiological Parameters and Phenotypic Traits of Maize

One of the most dangerous diseases of corn is Ustilago maydis DC. Corda, which damages the maize yield every year. It is difficult to protect against the corn smut infection because the efficiency of fungicide treatment is inadequate. The purpose of this research was to examine the effects of corn smut infection on some physiological and morphological parameters of maize (Zea mays L. cv. Armagnac). Furthermore, the aim of this research was to examine the possible compensation effects of gibberellin (GA3) and ethylene (as ethrel) separately, and in combination on the corn smut infection. The plants were grown in a greenhouse, they were infected and treated in the five leaf phenological phase with two ml of sporidium suspension (10,000 sporidium/ml), injected into the stem. At the same time, one ml of gibberellin, ethylene and the combination of the two hormones were injected. The relative chlorophyll content, stem diameter and plant height were measured in the fourth and fifth leaves of plants, 7, 11 and 14 days after the infection (DAI). The photosynthetic pigments were determined from the fourth leaf, and the rate of lipid peroxidation was measured from the fifth leaves, 14 DAI. The corn smut infection significantly reduced the relative-chlorophyll content 14 DAI compared to the control. The gibberellin reduced the harmful effects of the pathogen. No significant difference was recorded in case of stem diameter. The infected plants were shorter than the control plants when treated with ethylene. The effect of corn smut infection was more pronounced in the terms of photosynthetic pigments and the rate of lipid peroxidation. Ethylene treatment increased while gibberellin treatment reduced the impact of the infection. In this research, the corn smut infection and hormone treatments had larger impact on measured physiological parameters than on morphological parameters.

Natural Variation and Domestication Selection of ZmCKX5 with Root Morphological Traits at the Seedling Stage in Maize.

Root system architecture plays a crucial role in water and nutrient acquisition in maize. Cytokinins, which can be irreversibly degraded by the cytokinin oxidase/dehydrogenase (CKX), are important hormones that regulate root development in plants. In this study, ZmCKX5 was resequenced in 285 inbred lines, 68 landraces, and 32 teosintes to identify the significant variants associated with root traits in maize. Sequence polymorphisms and nucleotide diversity revealed that ZmCKX5 might be selected during domestication and improvement processes. Marker–trait association analysis in inbred lines identified 12 variants of ZmCKX5 that were significantly associated with six root traits, including seed root number (SRN), lateral root length (LRL), total root area (RA), root length in 0 to 0.5 mm diameter class (RL005), total root volume (RV), and total root length (TRL). SNP-1195 explained the most (6.01%) phenotypic variation of SRN, and the frequency of this allele G increased from 6.25% and 1.47% in teosintes and landraces, respectively, to 17.39% in inbred lines. Another significant variant, SNP-1406, with a pleiotropic effect, is strongly associated with five root traits, with the frequency of T allele increased from 25.00% and 23.73% in teosintes and landraces, respectively, to 35.00% in inbred lines. These results indicate that ZmCKX5 may be involved in the development of the maize root system and that the significant variants can be used to develop functional markers to accelerate the improvement in the maize root system.

GENETIC ASSOCIATION AMONG SEEDLING TRAITS OF ZEA MAYS UNDER MULTIPLE STRESSES OF SALTS, HEAVY METALS AND DROUGHT

Maize is highly sensitive for drought, heat, cold, salinity and heavy metals toxicity. The grain yield and quality of grains is highly affected due to abiotic environmental factors. For evaluating maize under drought as well as salts and heavy metals we have conducted an experiment in the greenhouse of IMBB (Institute of Molecular Biology and Biotechnology), University of the Lahore. Four maize genotypes were selected for our research work, viz., B-316, EV-1097Q, Raka-poshi and Sahiwal-2002. The seeds of selected maize genotypes were sown in 72 pots. Each of the pot was in triplicate for each of the maize genotype. The treatments of drought, salt and heavy metals were kept as following: Control, 50% irrigation water, 0.5m Molar NaCl, 0.5m Molar ZnSO4, 0.5m Molar AlCl3 and 0.5m Molar MgCl2. It has been revealed from results the performance of maize genotypes was variable under different treatments of heavy metals, drought and salt stress environments. The treatments of AlCl3 and NaCl were found as the higher toxic treatments for most of the study traits of maize which may decrease the photosynthetic rate and accumulations of organic compounds in maize seedlings and may cause the death of seedlings. Significant and positive correlation was reported between shoot length other studied traits while the higher contribution for shoot length was reported for root length, leaf area and fresh root/shoot weight ratio. It was found from results that the Sahiwal -2002 performed better under all stress treatments for seedling traits as compared with B-316, Raka-poshi and EV-1097Q maize genotypes.

Regulator Network Analysis of Rice and Maize Yield-Related Genes.

Rice and maize are the principal food crop species worldwide. The mechanism of gene regulation for the yield of rice and maize is still the research focus at present. Seed size, weight and shape are important traits of crop yield in rice and maize. Most members of three gene families, APETALA2/ethylene response factor, auxin response factors and MADS, were identified to be involved in yield traits in rice and maize. Analysis of molecular regulation mechanisms related to yield traits provides theoretical support for the improvement of crop yield. Genetic regulatory network analysis can provide new insights into gene families with the improvement of sequencing technology. Here, we analyzed the evolutionary relationships and the genetic regulatory network for the gene family members to predicted genes that may be involved in yield-related traits in rice and maize. The results may provide some theoretical and application guidelines for future investigations of molecular biology, which may be helpful for developing new rice and maize varieties with high yield traits.

QTL analysis across multiple environments reveals promising chromosome regions associated with yield-related traits in maize under drought conditions

Drought is one of the most critical abiotic stresses influencing maize yield. Improving maize cultivars with drought tolerance using marker-assisted selection requires a better understanding of its genetic basis. In this study, a doubled haploid (DH) population consisting of 217 lines was created by crossing the inbred lines Han 21 (drought-tolerant) and Ye 478 (drought-sensitive). The population was genotyped with a 6 K SNP assay and 756 SNP (single nucleotide polymorphism) markers were used to construct a linkage map with a length of 1344 cM. Grain yield (GY), ear setting percentage (ESP), and anthesis–silking interval (ASI) were recorded in seven environments under well-watered (WW) and water-stressed (WS) regimes. High phenotypic variation was observed for all traits under both water regimes. Using the LSMEAN (least-squares mean) values from all environments for each trait, 18 QTL were detected, with 9 associated with the WW and 9 with the WS regime. Four chromosome regions, Chr. 3: 219.8–223.7 Mb, Chr. 5: 191.5–194.7 Mb, Chr. 7: 132.2–135.6 Mb, and Chr. 10: 88.2–89.4 Mb, harbored at least 2 QTL in each region, and QTL co-located in a region inherited favorable alleles from the same parent. A set of 64 drought-tolerant BC3F6 lines showed preferential accumulation of the favorable alleles in these four regions, supporting an association between the four regions and maize drought tolerance. QTL-by-environment interaction analysis revealed 28 edQTL (environment-dependent QTL) associated with the WS regime and 22 associated with the WW regime for GY, ESP, and ASI. All WS QTL and 55.6% of WW QTL were located in the edQTL regions. The hotspot genomic regions identified in this work will support further fine mapping and marker-assisted breeding of drought-tolerant maize.

Genome-Wide Prediction of Complex Traits in Two Outcrossing Plant Species Through Deep Learning and Bayesian Regularized Neural Network.

Genomic selection models were investigated to predict several complex traits in breeding populations of Zea mays L. and Eucalyptus globulus Labill. For this, the following methods of Machine Learning (ML) were implemented: (i) Deep Learning (DL) and (ii) Bayesian Regularized Neural Network (BRNN) both in combination with different hyperparameters. These ML methods were also compared with Genomic Best Linear Unbiased Prediction (GBLUP) and different Bayesian regression models [Bayes A, Bayes B, Bayes Cπ, Bayesian Ridge Regression, Bayesian LASSO, and Reproducing Kernel Hilbert Space (RKHS)]. DL models, using Rectified Linear Units (as the activation function), had higher predictive ability values, which varied from 0.27 (pilodyn penetration of 6 years old eucalypt trees) to 0.78 (flowering-related traits of maize). Moreover, the larger mini-batch size (100%) had a significantly higher predictive ability for wood-related traits than the smaller mini-batch size (10%). On the other hand, in the BRNN method, the architectures of one and two layers that used only the pureline function showed better results of prediction, with values ranging from 0.21 (pilodyn penetration) to 0.71 (flowering traits). A significant increase in the prediction ability was observed for DL in comparison with other methods of genomic prediction (Bayesian alphabet models, GBLUP, RKHS, and BRNN). Another important finding was the usefulness of DL models (through an iterative algorithm) as an SNP detection strategy for genome-wide association studies. The results of this study confirm the importance of DL for genome-wide analyses and crop/tree improvement strategies, which holds promise for accelerating breeding progress.

Grain Yield of Maize Hybrids in Response to Inoculation with Azospirillum sp. under Nitrogen Limiting Conditions in Huaura, Peru

This experiment was conducted to evaluate the effect of Azospirillum sp. inoculated with different nitrogen levels (0, 60, 90, 180 kg ha-1) on grain yield, yield components and agronomic traits of hybrid maize at the arid conditions of the central coast of Peru. The experimental design used was randomized complete block design with four replications per treatment, under the arrangement of subdivided plots, in which three corn hybrids were assigned to complete plots and four inoculant-N fertilization treatments, to the subplots. The results showed that for dose fertilization of 180 kg ha-1 of nitrogen (control), the grain yield of hybrid corn was similar as compared to 60-120 kg ha-1 N fertilization inoculated at 15 and 45 days with a native strain of Azospirillum sp., suggesting that the response in grain yield for hybrid corn can be balanced with nitrogen fertilization and inoculation with Azospirillum sp. 1x108 CFU mL-1 in conditions of arid soils, with possible impact on the use of this microorganism in the maize production system

Genetic analysis of yield and its component traits in maize (Zea mays L.)

Maize (Zea mays L.) a member of grass family, poaceae (gramineae) having 2n = 2x = 20 chromosomes is one of the most important cereal crops of India. Mexico and Central America are the origin place of this crop. It has more than thirty-two thousand genes in its genome and the size of genome is about 2.3 gigabase. The objective of this study was to evaluate seventy-seven maize genotypes in relation to heritability and genetic advance for fourteen quantitative traits. The estimates of heritability provide information regarding to possibility and extent to which improvement is possible through selection. In this experiment it was found that the mean sum of squares due to genotypes were highly significant for all the characters under study. Indicated that significant amount of variability was available in the genotypes for all the traits. Majority of the traits were found to exhibit moderate to high estimates of genotypic coefficient of variance (GCV) and phenotypic coefficient of variance (PCV), however some traits such as days to 50% tasseling, days to 50% silking, days to 75% dry husk, cob diameter and shelling% had low estimates of GCV and PCV. Highest estimate of GCV was reported for grain yield per plant (36.706) followed by kernels per cob (32.136) cob weight (31.066) and kernels per row (27.087) while the lowest estimate of GCV was reported for days to 75% dry husk (3.162). High estimates of heritability in broad sense (>61%) were reported for all the fourteen characters under study but among them nine traits such as grain yield per plant (75.452), kernels per cob (66.191), cob weight (63.952), kernels per row (55.639), cobs per plant (37.46), 100-kernel weight (27.718), cob length (27.529), kernel rows per cob (23.856) and plant height (20.957) had high estimates of genetic advance in percent of mean (>20%). High estimates of heritability coupled with high estimates of genetic advance are the indicative of additive gene effects in the inheritance of above-mentioned traits. Therefore, selection will be rewarding for the improvement of these traits.

A new empirical equation to describe the vertical leaf distribution profile of maize

AbstractThe characteristic traits of maize (Zea mays L.) leaves affect light interception and photosynthesis. Measurement or estimation of individual leaf area has been described using discontinuous equations or bell-shaped functions. However, new maize hybrids show different canopy architecture, such as leaf angle in modern maize which is more upright and ear leaf and adjacent leaves which are longer than older hybrids. The original equations and their parameters, which have been used for older maize hybrids and grown at low plant densities, will not accurately represent modern hybrids. Therefore, the aim of this paper was to develop a new empirical equation that captures vertical leaf distribution. To characterize the vertical leaf profile, we conducted a field experiment in Jilin province, Northeast China from 2015 to 2018. Our new equation for the vertical distribution of leaf profile describes leaf length, width or leaf area as a function of leaf rank, using parameters for the maximum value for leaf length, width or area, the leaf rank at which the maximum value is obtained, and the width of the curve. It thus involves one parameter less than the previously used equations. By analysing the characteristics of this new equation, we identified four key leaf ranks (4, 8, 14 and 20) for which leaf parameter values need to be quantified in order to have a good estimation of leaf length, width and area. Together, the method of leaf area estimation proposed here adds versatility for use in modern maize hybrids and simplifies the field measurements by using the four key leaf ranks to estimate vertical leaf distribution in maize canopy instead of all leaf ranks.

Dealing with multiple traits in maize: A new approach for selecting progenies

AbstractMany maize (Zea mays L.) breeding programs select genotypes considering just grain yield. However, this strategy may not be efficient due to undesirable associations between grain yield and other traits. The breeder's challenge is to combine good characteristics in one genotype. The aim of this study was to propose a new approach to select maize progenies considering multiple traits. One hundred forty‐one half‐sib progenies were evaluated for 14 agronomic traits in a 12 by 12 triple lattice design in two environments. Four progeny selection strategies were performed to increase yield. Strategy 1, considering just yield; Strategy 2, considering all traits in a selection index; Strategy 3, considering only traits that have effect in yield, based on path analysis; and Strategy 4, similar to Strategy 3, but disregarding any trait showing undesirable correlation with other traits. Strategies 2, 3, and 4 considered Smith and Hazel index. The progenies selected by Strategy 4 showed more balanced predicted gains considering all traits. Its predicted gain in all traits related to yield was higher than the of Strategies 2 and 3, and it led to smaller gains in height and flowering time, which breeders want to decrease its means. Strategy 1 showed the best gains in yield, as expected, but obtained undesirable phenotypes for the other traits. The use of path analysis to delineate the Smith and Hazel index is a very appealing approach for selecting maize progenies and the Strategy 4 was the most efficient at accomplishing balanced gains for multiple traits.

Drought tolerance in high-generation transgenic maize inbred lines overexpressing the betaine aldehyde dehydrogenase gene

Abiotic stress such as drought seriously endangers maize growth and production. Glycine betaine (GB) accumulation in transgenic crops following heterologous overexpression of the BADH gene has been shown to dramatically improve the tolerance to salt, cold, and oxidative stresses, but it is unclear if GB accumulation leads to improved drought tolerance of maize. In this study, we analyzed the drought tolerance of high-generation BADH transgenic maize inbred lines at different growth stages using the hyperosmotic solution and water-withholding methods. Molecular detection revealed that exogenous BADH was successfully introduced into the maize plant genome and overexpressed in three transgenic maize inbred lines. Under osmotic stress, transgenic maize held better germination ability than the unmodified Dan988 (WT) line. In addition, transgenic maize contained higher levels of antioxidant enzymes and osmotic regulatory substances compared with WT, and thus accumulated less harmful substances and this alleviated the negative effects of drought. We used the membership function method to quantify the drought tolerance and found that Dan988-BADH-4 showed the best tolerance, followed by Dan988-BADH-2 and Dan988-BADH-1 while WT ranked lowest. This was consistent with the statistical analysis of the experiments. From the indoor and field survey, we observed that the agronomic traits of transgenic maize were not affected by the overexpression of BADH. In conclusion, BADH overexpression in maize is beneficial for drought tolerance and the three transgenic maize lines can be used for further breeding experiments.

A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize.

The effect of drought on maize yield is of particular concern in the context of climate change and human population growth. However, the complexity of drought-response mechanisms makes the design of new drought-tolerant varieties a difficult task that would greatly benefit from a better understanding of the genotype–phenotype relationship. To provide novel insight into this relationship, we applied a systems genetics approach integrating high-throughput phenotypic, proteomic, and genomic data acquired from 254 maize hybrids grown under two watering conditions. Using association genetics and protein coexpression analysis, we detected more than 22,000 pQTLs across the two conditions and confidently identified 15 loci with potential pleiotropic effects on the proteome. We showed that even mild water deficit induced a profound remodeling of the proteome, which affected the structure of the protein coexpression network, and a reprogramming of the genetic control of the abundance of many proteins, including those involved in stress response. Colocalizations between pQTLs and QTLs for ecophysiological traits, found mostly in the water deficit condition, indicated that this reprogramming may also affect the phenotypic level. Finally, we identified several candidate genes that are potentially responsible for both the coexpression of stress response proteins and the variations of ecophysiological traits under water deficit. Taken together, our findings provide novel insights into the molecular mechanisms of drought tolerance and suggest some pathways for further research and breeding.

Genome-wide association study (GWAS) reveals genetic basis of ear-related traits in maize

Maize ear-related traits are important components of grain yield that directly influence maize production. The genetic basis of ear-related traits is still not completely understood, which would be helpful in the improvement of grain yield. In this study, to dissect the genetic basis of ear diameter (ED), ear row number (ERN), and kernel number per row (KNR), a genome-wide association study of maize inbred lines was conducted using the phenotype of the three traits in two environments and the best linear unbiased prediction (BLUP) value. We detected 116 significant loci, i.e., 37, 42, and 37 related to ED, ERN, and KNR, respectively. Among these significant loci, 19 were co-localized when using the traits in two environments and BLUP value. The increase of superior allele number for the 19 co-localized loci was positively correlated with maize grain yield. Further, from the candidate regions of 116 significant loci, 558 genes expressed in maize cob and silk and participated in 71 biological pathways, such as RNA transport, protein export, biosynthesis of amino acids, and starch and sucrose metabolism. Of these candidate genes, some putative functional genes from the co-localized regions were predicted including ts6, pin4, Zm00001d038022, and Zm00001d041584, of which ts6 located in a known major QTL for ERN (named krn1). These results promote the understanding of the genetic basis for these three traits, which contributes to maize grain yield improvement by breeding.

Assessment of genetic variability, heritability and genetic advance for yield traits in maize (Zea mays L.) under high plant density

Assessment of genetic variability, heritability and genetic advance for yield traits in maize (Zea mays L.) under high plant density

Assessment of the Potential for Genomic Selection To Improve Husk Traits in Maize.

Husk has multiple functions such as protecting ears from diseases, infection, and dehydration during development. Additionally, husks comprised of fewer, shorter, thinner, and narrower layers allow faster moisture evaporation of kernels prior to harvest. Intensive studies have been conducted to identify appropriate husk architecture by understanding the genetic basis of related traits, including husk length, husk layer number, husk thickness, and husk width. However, marker-assisted selection is inefficient because the identified quantitative trait loci and associated genetic loci could only explain a small proportion of total phenotypic variation. Genomic selection (GS) has been used successfully on many species including maize on other traits. Thus, the potential of using GS for husk traits to directly identify superior inbred lines, without knowing the specific underlying genetic loci, is well worth exploring. In this study, we compared four GS models on a maize association population with 498 inbred lines belonging to four subpopulations, including 27 lines in stiff stalk, 67 lines in non-stiff stalk, 193 lines in tropical-subtropical, and 211 lines in mixture subpopulations. Genomic Best Linear Unbiased Prediction with principal components as cofactor, performed the best and was selected to examine the impact of interaction between sampling proportions and subpopulations. We found that predictions on inbred lines in a subpopulation were benefited from excluding individuals from other subpopulations for training if the training population within the subpopulation was large enough. Husk thickness exhibited the highest prediction accuracy among all husk traits. These results gave strategic insight to improve husk architecture.

Effects of biofertilizers and iron nano-oxide on maize yield and physiological properties under optimal irrigation and drought stress conditions.

In this research, effects iron nano‐oxide and biofertilizers and chemical was investigated on the yield and some traits of Maize under normal and drought stress conditions in two years (2018 and 2019). The experiment was performed in the form of split–spilt plot in a complete random block design with three replications. The studied irrigation treatment included three levels (normal, 85% and 65% optimum water requirement) in the main plots and iron nano‐oxide at four levels (0, 0.5, 1, and 1.5 g/L) in subplots, and biofertilizers at four levels (noninoculation, inoculation with mycorrhiza, inoculation with pseudomonas and combined inoculation of mycorrhiza and pseudomonas) in sub‐plots. The results showed that grain yield, 1000‐grain weight, and leaf chlorophyll contents decreased by drought stress. Use of pseudomonas and mycorrhiza increased these traits in normal and stress conditions, but iron nano‐oxide had no significant effect on the measured traits. Also, drought stress increased malondialdehyde, ion leakage, catalase, peroxidase, proline, and polyphenol oxidase in both light and severe stress regimes. The amount of antioxidant enzymes increased under drought stress conditions in corn. The results indicated that all the characteristics measured by double inoculation with Pseudomonas and Microoriza had the best performance in conditions of water shortage and the use of these biofertilizers increases yield, 1000‐seed weight, and chlorophyll content of maize. Also, the use of biofertilizers modulates the effect of drought stress and reduces its negative effects.

Evaluation of plant characteristics related to grain yield of FAO410 and FAO340 hybrids using regression models

In breeding programs, estimation of increase in yield based on changes in effective plant traits is of great importance, which can be identified using regression modeling. The regression model refers to the prediction of the value of a dependent variable from the values of one or more independent variables. This study evaluated morphological traits of maize (FAO410) on six treatments of fertilizer in 2 years in Debrecen University by the regression model. This experiment was RCBD with four replications in the Látókép zone. Treatments were included in different levels of fertilizer: nitrogen, phosphor, and potassium. The regression model was significant at one percent that showed morphological traits have a straight effect on the yield of maize in FAO410 and FAO340. Grain yield had a positive correlation with plant height, outer ear diameter, the weight of ear, weight of cob, number of leaves, weight of all seeds in each ear, the weight of one thousand seeds on FAO410, and grain yield had a positive correlation with plant height, stem diameter, outer ear diameter, the weight of ear, weight of cob, number of seeds in each column, weight of all seeds in each ear, weight of the fresh plant in a hectare, the weight of one thousand seeds on FAO340 too. Cluster analysis showed the traits classification on two groups on hybrids. Reach maximum grain yield require the evaluation of yield components and their effect.

Identification of QTLs for grain yield and other traits in tropical maize under Striga infestation.

Striga is an important biotic factor limiting maize production in sub-Saharan Africa and can cause yield losses as high as 100%. Marker-assisted selection (MAS) approaches hold a great potential for improving Striga resistance but requires identification and use of markers associated with Striga resistance for adequate genetic gains from selection. However, there is no report on the discovery of quantitative trait loci (QTL) for resistance to Striga in maize under artificial field infestation. In the present study, 198 BC1S1 families obtained from a cross involving TZEEI 29 (Striga resistant inbred line) and TZEEI 23 (Striga susceptible inbred line) plus the two parental lines were screened under artificial Striga-infested conditions at two Striga-endemic locations in Nigeria in 2018, to identify QTL associated with Striga resistance indicator traits, including grain yield, ears per plant, Striga damage and number of emerged Striga plants. Genetic map was constructed using 1,386 DArTseq markers distributed across the 10 maize chromosomes, covering 2076 cM of the total genome with a mean spacing of 0.11 cM between the markers. Using composite interval mapping (CIM), fourteen QTL were identified for key Striga resistance/tolerance indicator traits: 3 QTL for grain yield, 4 for ears per plant and 7 for Striga damage at 10 weeks after planting (WAP), across environments. Putative candidate genes which encode major transcription factor families WRKY, bHLH, AP2-EREBPs, MYB, and bZIP involved in plant defense signaling were detected for Striga resistance/tolerance indicator traits. The QTL detected in the present study would be useful for rapid transfer of Striga resistance/tolerance genes into Striga susceptible but high yielding maize genotypes using MAS approaches after validation. Further studies on validation of the QTL in different genetic backgrounds and in different environments would help verify their reproducibility and effective use in breeding for Striga resistance/tolerance.

Mapping quantitative trait loci associated with stem-related traits in maize (Zea mays L.).

Mapping QTL for stem-related traits using RIL population with ultra-high density bin map can better dissect pleiotropic QTL controlling stem architecture that can provide valuable information for maize genetic improvement. The maize stem is one of the most important parts of the plant and is also a component of many agronomic traits in maize. This study aimed to advance our understanding of the genetic mechanisms underlying maize stem traits. A recombinant inbred line (RIL) population derived from a cross between Ye478 and Qi319 was used to identify quantitative trait loci (QTL) controlling stem height (SH), ear height (EH), stem node number (SN), ear node (EN), and stem diameter (SD), and two derived traits (ear height coefficient (EHc) and ear node coefficient (ENc)). Using an available ultra-high density bin map, 46 putative QTL for these traits were detected on chromosomes 1, 3, 4, 5, 6, 7, 8, and 10. Individual QTL explained 3.5-17.7% of the phenotypic variance in different environments. Two QTL for SH, three for EH, two for EHc, one for SN, one for EN, and one for SD were detected in more than one environment. QTL with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1, 3, 4, 6, 8, and 10, which are potential target regions for fine-mapping and marker-assisted selection in maize breeding programs. Further, we discussed segregation of bin markers (mk1630 and mk4452) associated with EHc QTL in the RIL population. We had identified two putative WRKY DNA-binding domain proteins, AC209050.3_FG003 and GRMZM5G851490, and a putative auxin response factor, GRMZM2G437460, which might be involved in regulating plant growth and development, as candidate genes for the control of stem architecture.

Genetic Analysis of Some Traits in Maize

Bu çalışmanın amacı mısırda çiçeklenme süresi, bitki boyu, tane/koçan oranı, tane nemi ve bin tane ağırlığı gibi bazı özelliklerde genetik parametreleri incelemek, hatların ve melezlerin uyum yeteneklerini belirleyerek gelecek dönem çalışmaları için seleksiyonlar yapmaktır. 2016 ve 2017 yıllarında 8 mısır hattı Griffing Metod III’e göre melezlemelere alınmış, elde edilen 56 adet mısır melezi 2017 ve 2018 yıllarında Antalya ve Sakarya lokasyonlarında tesadüf blokları deneme desenine göre üç tekerrürlü olarak denenmiştir. Çalışmada genotipler, genel kombinasyon yeteneği ve özel kombinasyon yeteneği etkileri bakımından önemli bulunurken, resiprokal etkilerin bu özelliklerde önemsiz olduğu bulunmuştur. Araştırmada, bu özelliklerde eklemeli gen etkilerinin baskın olduğu tespit edilmiştir. En yüksek dar (0.82) ve geniş anlamda kalıtım dereceleri (0.90) çiçeklenme süresinden alınırken, en düşük değerler tane/koçan oranında sırasıyla 0.20 ve 0.27 olarak belirlenmiştir. Yüksek kalıtım dereceleri nedeniyle tane/koçan oranı hariç diğer özelliklerde doğrudan seleksiyonların yapılabileceği öngörülmüştür. Çalışma sonucunda, erkencilik ve düşük tane nemine sahip çeşit geliştirme çalışmaları için, M1, M2, M3 ve A1 hatları, bitki boyu için S1 ve S2 hatları, tane /koçan oranı için M3 ve A1 hatları ve bin tane ağırlığı için A1, S1 ve M3 hatları seçilerek ıslah programlarına aktarılmıştır.