
Maize (
Morphological differences in crop germplasm between regions of cultivation area have attracted considerable interest in genetic studies of landrace varieties in each region. Phenotypic variation has been utilized to characterize and manage the genetic diversity for various crop species because it is a strong determinant of agronomic value as well as revealing differences between cultivars or varieties (Cömertpay
For this study, we collected 31 maize landrace acces-sions from local farmers’ field in various climatic zones of South Sudan, aiming to investigate the phenotypic vari-ations among them. The results of current study will provide maize breeders with information on the morpho-logical differentiation among maize landrace accessions which will aid in the development of improved maize varieties.
The materials used for this study were 31 maize landrace accessions collected from the fields of different farmers across South Sudan (17 accessions from the southern region, 7 accessions from the central region, and 7 accessions from the northern region). These maize landrace accessions were divided into 3 populations based on their geographi-cal distribution, namely northern, central, and southern South Sudan. Information about the 31 maize landrace accessions collected from South Sudan is presented in Table 1 and Fig. 1.
Table 1 . Summary of 31 maize landrace accessions of South Sudan used for morphological analysis.
Regions | No. | Abbr. | State, County, Payam or Village | Country | Type |
---|---|---|---|---|---|
Southern accession | 1 | BO1 | Gonglei, Bor | South Sudan | Landrace |
2 | BO2 | Gonglei, Bor | South Sudan | Landrace | |
3 | BO3 | Gonglei, Bor | South Sudan | Landrace | |
4 | GO1 | Central Equatoria, Gondokoro | South Sudan | Landrace | |
5 | GO2 | Central Equatoria, Gondokoro | South Sudan | Landrace | |
6 | GO3 | Central Equatoria, Gondokoro | South Sudan | Landrace | |
7 | GO4 | Central Equatoria, Gondokoro | South Sudan | Landrace | |
8 | YA | Western Equatoria, Yambio | South Sudan | Landrace | |
9 | RJ1 | Central Equatoria, Rajaf county | South Sudan | Landrace | |
10 | RJ2 | Central Equatoria, Rajaf county | South Sudan | Landrace | |
11 | RJ3 | Central Equatoria, Rajaf county | South Sudan | Landrace | |
12 | RJ4 | Central Equatoria, Rajaf county | South Sudan | Landrace | |
13 | TO | Torit, Eastern Equatoria | South Sudan | Landrace | |
14 | MN1 | Eastern Equatoria, Mangala | South Sudan | Landrace | |
15 | MN2 | Eastern Equatoria, Mangala | South Sudan | Landrace | |
16 | MN3 | Eastern Equatoria, Mangala | South Sudan | Landrace | |
17 | MA | Eastern Equatoria, Magwi | South Sudan | Landrace | |
Central accession | 18 | MD1 | Lakes State, Madhok | South Sudan | Landrace |
19 | MD2 | Lakes State, Malok | South Sudan | Landrace | |
20 | AR | Lakes State, Karic | South Sudan | Landrace | |
21 | AD1 | Lakes State, Adull | South Sudan | Landrace | |
22 | AD2 | Lakes State, Kolniet | South Sudan | Landrace | |
23 | KO | Warrap State, Kuajok | South Sudan | Landrace | |
24 | TO | Warrap State, Tonj | South Sudan | Landrace | |
Northern accession | 25 | RE | Upper Nile, Renk | South Sudan | Landrace |
26 | BE | Unity State, Bentiu | South Sudan | Landrace | |
27 | AW | Northern bahr el-ghazal, Awil | South Sudan | Landrace | |
28 | YD1 | Ruweng Administrative Area, Yida | South Sudan | Landrace | |
29 | YD2 | Ruweng Admistrative Area, Yida | South Sudan | Landrace | |
30 | RA | Western bahr el-ghazal, Raja | South Sudan | Landrace | |
31 | WA | Western bahr el-ghazal, Wau | South Sudan | Landrace |
In our study, to evaluate the morphological variation of the 31 maize landrace accessions collected from South Sudan, 10 individuals of each accession were cultivated from the middle of May to the end of October in 2022 at the research field of Kangwon National University, Chuncheon, Gangwon-do. We examined 7 quantitative characteristics: days to tasseling (DT), days to silking (DS), plant height (PH), ear height (EH), stem width (SW), leaf width (LW), and leaf length (LL) for each maize accession (Table 2).
Table 2 . Morphological characteristics used in morphological variation analysis of maize landrace accessions.
Code | Morphological characters | Category | Time of detecting | Methods of detecting |
---|---|---|---|---|
QN1 | Days of tasseling (DT) | days | Flowering stage | Days from seedling to tasseling |
QN2 | Days of silking (DS) | days | Flowering stage | Days from seedling to silking |
QN3 | Plant height (PH) | cm | Flowering stage | Length from the ground surface to under corn tassel |
QN4 | Ear height (EH) | cm | Flowering stage | Length from the surface to the second kernel |
QN5 | Stem width (SW) | cm | Flowering stage | Stem width near the kernel |
QN6 | Leaf length (LL) | cm | Flowering stage | Length of the leave near the kernel |
QN7 | Leaf width (LW) | cm | Flowering stage | Leafe width near the kernel |
PCA was performed to detect any morphological dif-ferences between and within the maize accessions col-lected from the different regions of South Sudan. To analyze the morphological variation of the 31 maize land-race accessions of South Sudan, multivariate analysis was performed using the Microsoft Excel Statistical Analysis System Program and NTSYS-pc V2.1 Program (Rohlf 1998). SPSS software was used to perform correlation analysis for the 7 quantitative characteristics of the 31 maize landrace accessions of South Sudan.
All maize landrace accessions collected from South Sudan used in this study showed considerable morphological differences in accordance with their collection area (southern, central, and northern regions). The morphological characteristics of the 31 maize landrace accessions for the 7 agricultural characteristics are shown in Supplementary Table S1.
To understand the differences in morphological variation among the maize accessions of the 3 regions (southern region accessions, central regions accessions, and northern region accessions) of South Sudan, the mean, standard deviation, and minimum and maximum values for all characteristics were calculated for accessions of the 3 regions (Table 3). Based on the survey of the 7 quantitative characteristics for accessions of the 3 regions of South Sudan, the average of DT for the maize landrace accessions of southern, central, and northern regions was 83.0 ± 6.24 (76-97), 91.9 ± 9.06 (80-99), and 83.6 ± 4.22 (79-89), respectively. The average of DS was 86.1 ± 6.89 (78-101), 93.1 ± 10.3 (79-101), and 82.3 ± 4.26 (78-90) for the accessions of southern, central, and northern regions, respectively. The average values of PH were 253.7 ± 34.7 (210-350), 252.6 ± 19.8 (214-273), and 266.6 ± 12.8 (250-281) cm for the accessions of southern, central, and northern regions, respectively. The average values of EH for the maize landrace accessions of southern, central, and northern regions were 137.6 ± 30.9 (96-225), 141.3 ± 21.0 (103-170), and 156.5 ± 16.2 (134-176) cm, respectively. The average values of SW for the maize landrace acces-sions of southern, central, and northern regions were 3.0 ± 0.86 (2.1-5.4), 3.5 ± 0.73 (2.5-4.4), and 3.8 ± 0.85 (2.8-5.4) cm, respectively. The average values of LL were 98.6 ± 12.6 (66.5-120), 96.3 ± 4.85 (89.3-103), and 107.1 ± 12.9 (94.3-131) cm for the maize landrace accessions of southern, central, and northern regions, respectively. The average values of LW were 9.7 ± 1.08 (7.3-11.7), 10.2 ± 1.64 (7.2-11.8), and 10.5 ± 1.06 (8.5-12) cm for the accessions of southern, central, and northern regions, respectively (Table 3).
Table 3 . Morphological characteristics of 7 quantitative characteristics among 31 maize landrace accessions of 3 regions of South Sudan.
Code | Morphological Characters | Region | Category/Unit | Mean ± SD | Min | Max | |||
---|---|---|---|---|---|---|---|---|---|
Values | Genotype | Values | Genotype | ||||||
QN1 | Days of tasseling (DT) | SA | Days | 83.0 ± 6.24 | 76 | MN1 | 97 | GO1 | |
CA | - | 91.9 ± 9.06 | 80 | AD2 | 99 | AR | |||
NA | - | 83.6 ± 4.22 | 79 | AW | 89 | AW | |||
QN2 | Days of silking (DS) | SA | Days | 86.1 ± 6.89 | 78 | MN1 | 101 | GO1 | |
CA | - | 93.1 ± 10.3 | 79 | AD2 | 101 | AR | |||
NA | - | 82.3 ± 4.26 | 78 | WA | 90 | RE | |||
QN3 | Plant height (PH) | SA | cm | 253.7 ± 34.7 | 210 | GO3 | 350 | TR | |
CA | - | 252.6 ± 19.8 | 214 | MD1 | 273 | AR | |||
NA | - | 266.6 ± 12.8 | 250 | RE | 281 | BE | |||
QN4 | Ear height (EH) | SA | cm | 137.6 ± 30.9 | 96 | GO3 | 225 | TR | |
CA | - | 141.3 ± 21.0 | 103 | MD1 | 170 | KO | |||
NA | - | 156.5 ± 16.2 | 134 | WA | 176 | YD2 | |||
QN5 | Stem width (SW) | SA | cm | 3.0 ± 0.86 | 2.1 | GO4 | 5.4 | RJ2 | |
CA | - | 3.5 ± 0.73 | 2.5 | MD1 | 4.4 | AD1 | |||
NA | - | 3.8 ± 0.85 | 2.8 | RE | 5.4 | YD1 | |||
QN6 | Leaf length (LL) | SA | cm | 98.6 ± 12.6 | 66.5 | BO1 | 120 | TR | |
CA | - | 96.3 ± 4.85 | 89.3 | AD2 | 103 | TO | |||
NA | - | 107.1 ± 12.9 | 94.3 | YD1 | 131 | WA | |||
QN7 | Leaf width (LW) | SA | cm | 9.7 ± 1.08 | 7.3 | RJ3 | 11.7 | GO1 | |
CA | - | 10.2 ± 1.64 | 7.2 | AD2 | 11.8 | KO | |||
NA | - | 10.5 ± 1.06 | 8.5 | RE | 12 | AW |
SA: southern region accessions, CA: central region accessions, NA: northern region accessions.
Meanwhile, we performed a correlation analysis to detect the morphological relationships between the 7 agronomic characteristics in the 31 maize landrace acces-sions collected from the 3 regions of South Sudan (Table 4). In our study, the 7 agronomic characteristics showed statistically significant positive or negative correlation coefficients at significance levels of 0.05 and 0.01. Among all the morphological characteristics, the combinations between DT (QN1) and DS (QN2) (0.960**), between PH (QN3) and EH (QN4) (0.767**), between QN3 and SW (QN5) (0.518**), between QN4 and QN5 (0.564**), and between QN4 and LL (QN6) (0.496**) showed compara-tively higher positive correlation coefficients at signifi-cance levels of 0.01. Further, the combination between QN3 and QN6 (0.373*), between QN3 and LW (QN7) (0.440*), between QN4 and QN7 (0.401*), and between QN5 and QN6 (0.403*) showed comparatively higher positive correlation coefficients at the 0.05 significance level. The remaining characteristics showed low correla-tions in both positive and negative directions (Table 4).
Table 4 . Pearson correlation coefficient for 7 quantitative characteristics in 31 maize landrace accessions of South Sudan.
Morphological characters | QN1 | QN2 | QN3 | QN4 | QN5 | QN6 | QN7 |
---|---|---|---|---|---|---|---|
QN1 | 0.960** | 0.120 | 0.044 | ‒0.09 | 0.119 | 0.036 | |
QN2 | 0.127 | 0.015 | ‒0.166 | 0.091 | ‒0.003 | ||
QN3 | 0.767** | 0.518** | 0.373* | 0.440* | |||
QN4 | 0.564** | 0.496** | 0.401* | ||||
QN5 | 0.403* | 0.324 | |||||
QN6 | 0.238 |
**Significance at
PCA in this study was performed to evaluate the mor-phological differentiation among the 31 maize landrace accessions. The first principal component (PC1) and second principal component (PC2) accounted for 40.9% and 28.6%, respectively, of the total variance (Table 5). Among all morphological characteristics, 3 characteristics, PH (QN3), EH (QN4), and SW (QN5) made a significant contribution to the positive direction of PC1. Also DT (QN1) and DS (QN2) made a remarkable contribution in the positive direction on PC2 (Table 5). Along axis 1 of the PCA (Fig. 2), most maize landrace accessions of South Sudan were not clearly segregated based on their collection areas of the southern, central, and northern regions. In detail, except for several exceptional accessions, most maize landrace acces-sions of the southern region were formed in a group on the negative side on the first axis, and most maize landrace accessions of the central region were formed in a group on the positive and negative sides on the first axis. Also, most maize landrace accessions of the northern region, with a few exceptional accessions, were formed in a group on the positive side on the first axis.
Table 5 . Cumulative variances of first and second principal components and loadings of 7 quantitative cha-racteristics on each principal component.
Code | Morphological characteristics | Eigenvectors | |
---|---|---|---|
1 | 2 | ||
QN4 | Ear height (EH) | 0.88 | ‒0.077 |
QN3 | Plant height (PH) | 0.855 | 0.03 |
QN5 | Stem width (SW) | 0.732 | ‒0.278 |
QN6 | Leaf length (LL) | 0.654 | 0.051 |
QN7 | Leaf width (LW) | 0.603 | 0.051 |
QN1 | Days of tasseling (DT) | 0.149 | 0.971 |
QN2 | Days of silking (DS) | 0.108 | 0.984 |
Cumulative variance (%) | 40.9 | 28.6 |
Morphological characterization is a fundamental method for estimating the variation and genetic diversity in plant breeding programs (Park
Descriptive statistics used in our study were calculated to account for morphological variation in maize landrace accessions collected from South Sudan. The data obtained provides measurements and forms the basis for almost all quantitative analysis of data, including the mean, mini-mum, maximum, and standard deviation of each quanti-tative characteristic in the accessions of maize germplasm (Table 3). Previously there have been few reports on the results of cultivation tests in domestic cultivation fields for foreign maize germplasm accessions from areas such as Africa including South Sudan. Thus, in the present study, morphological characteristics were investigated to under-stand the morphological variation of 31 maize landrace accessions collected from farmers' fields in South Sudan. Even though the growth survey experiment was conducted in Korean fields, an examination of the morphological characteristics of the 31 maize landrace accessions col-lected in the southern, central, and northern regions of South Sudan showed that they had different growth characteristics depending on the collection region. In our study, although the maximum and minimum values for each accession collected from the 3 regions of South Sudan did not show any particular tendency based on the collection region, for the average value of the accessions of each of the 3 regions, the accessions of CA region showed the highest values for DT (QN1) and DS (QN2), while the accessions of SA region showed the highest values for PH (QN3), EH (QN4), SW (QN5), and LL (QN6). Despite the results being from an investigation in the climatic environment of South Korea, the maize landrace acces-sions collected in the central and southern regions of South Sudan showed comparatively good growth characteristics. In addition, relationships between morphological characte-ristics were examined using correlation coefficients, and the results of a simple correlation coefficient analysis revealed generally the existence of both significant positive and negative correlations between the 7 morphological characteristics. However, among the combinations, the combinations between QN1 and QN2 (0.960**), between QN3 and QN4 (0.767**), QN3 and QN5 (0.518**), and between QN4 and QN5 (0.564**), and QN4 and QN6 (0.496**) showed significant high positive correlation coefficient compared with the other characteristics at
PCA helps in determining the most relevant traits that can be employed as indicators by explaining much of the overall variation in the original set of variables, and the traits that contribute greatly to the divergence provide considerable affirmation for deciding on a cluster for the purpose of selection of parents for hybridization (Thakur
Scatter plot based on PC1 and PC2 showed the existence of 3 major groups (Fig. 2). Group 1 allocated in the first quadrant on the positive side on the first axis included 5 maize accessions that had higher values for DT (QN1), DS (QN2), and PH (QN3). Group 2 allocated in the second and third quadrants on the positive side on the first axis comprised 14 maize accessions that showed low values for PH (QN3) and EH (QN4). Group 3 allocated in the fourth quadrant on the negative side on the first axis included 10 maize accessions that showed high values for PH (QN3) and EH (QN4). PH (QN3), EH (QN4), and DS (QN2) are important characteristics associated with flowering time, which is a crucial characteristic that contributes to crop yield (Zhang
In conclusion, despite the morphological characterization studies being conducted in the Korean climate, our study sheds light on and provides details about morphological variation among maize landrace accessions collected from South Sudan. The characteristics that show high variability among the accessions are the most discriminating cha-racteristics and were the best for describing the morpho-logical variation for our explored genotypes. The grouping results based on PCA offer information for selecting suitable genetic materials for breeding. This study together with our previous report provides a comprehensive under-standing of genetic diversity present in South Sudan maize, which had been little investigated. These findings will be crucial in future for advancing molecular breeding studies such as marker-assisted selection (MAS), genome wide association study (GWAS), and genome selection.
This study was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2021R1A6A1 A03044242) and the Golden Seed Project (No. 213009- 05-1-WT821, PJ012650012017), Ministry of Agriculture, Food, and Rural Affairs (MAFRA), Ministry of Oceans and Fisheries (MOF), Korea Forest Service (KFS), Republic of Korea.
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