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Communication

What Traits Should Be Measured for Biomass in Kenaf?

1
Department of Plant Resources and Environment, Jeju National University, Jeju 63243, Korea
2
ICAR-National Research Centre for Banana, Tiruchirappalli 620102, India
3
Institute of Mathematics and Statistics, Federal University of Goias, Goiania 74001, Brazil
4
National Agrobiodiversity Center, National Institute of Agricultural Sciences (NAS), RDA, Jeonju 54875, Korea
5
Seeds Research, Syngenta Crop Protection LLC, Research Triangle Park, NC 27709, USA
6
Department of Plant Life and Environmental Science, Hankyong National University, Anseong-si 17579, Korea
*
Authors to whom correspondence should be addressed.
These authors also contributed equally to this work.
Plants 2021, 10(7), 1394; https://doi.org/10.3390/plants10071394
Submission received: 8 June 2021 / Revised: 1 July 2021 / Accepted: 3 July 2021 / Published: 7 July 2021

Abstract

:
Kenaf (Hibiscus cannabinus L.) is widely used as an important industrial crop. It has the potential to act as a sustainable energy provider in the future, and contains beneficial compounds for medical and therapeutic use. However, there are no clear breeding strategies to increase its biomass or leaf volume. Thus, to attain an increase in these parameters, we examined potential key traits such as stem diameter, plant height, and number of nodes to determine the relationship among them. We hypothesized that it would be easier to reduce the amount of time and labor required for breeding if correlations among these parameters are identified. In this study, we found a strong positive correlation between height and number of nodes (Spearman’s Rho = 0.67, p < 0.001) and number of nodes and stem diameter (Spearman’s Rho = 0.65, p < 0.001), but a relatively low correlation (Spearman’s Rho = 0.34, p < 0.01) between height and stem diameter in the later stages of kenaf growth. We suggest that an efficient breeding strategy could be devised according to the breeding purpose, considering the correlations between various individual traits of kenaf.

1. Introduction

Kenaf (Hibiscus cannabinus L.) is an important industrial crop worldwide [1]. It is cultivated in more than 20 countries because of its importance and various roles in industrial and agricultural applications; it is a constituent of paper and pulp, fabrics, textiles, biocomposites, insulation mats, absorption materials, animal bedding, medicinal formulations, musical instruments, and value-added plant-based foods [2,3,4,5,6]. These numerous applications are due to kenaf’s fibrous stems and functional compounds. It is characterized by rapid growth, with an average increase of 10 cm in a single day, and a large biomass, reaching 4–6 m in height [7,8]. These plants also have a wide adaptability in various climates and soils [9]. Consequently, its cultivars have spread to Asia through Southern and Western Africa, although its origin might have been Zambia or the surrounding areas [10].
Importantly, owing to its large volume of biomass, kenaf could be a potential material for sustainable energy supply in the future, and its useful phytocompounds and phytol from leaves could be extracted for medical purposes [11]. Kenaf leaf extract contains many plant compounds, including phytol and linolenic acid, which are known to have various health benefits [12,13,14]. Its leaves have been used to treat dysentery, blood and throat disorders, and in the management of atherosclerosis [15,16]. A recent study showed that the fortification of bread using kenaf leaves improved the total dietary fiber content of the former [17]. Furthermore, leaves contribute to an increase in total biomass. After drying, kenaf leaf biomass is approximately 40% of its total biomass [18,19].
Despite the importance of kenaf leaves for total biomass increment and other uses, kenaf fibers have been relatively more useful for industrial applications. Therefore, increasing the fiber production of kenaf is a primary breeding goal [18,19]. Most kenaf breeding programs in the United States are aimed at developing varieties suitable for the production of fibers, while in Cuba, Guatemala, and a few states such as Florida, they are aimed at producing high-yielding and disease-resistant varieties [20,21,22]. Fiber yield, which is related to biomass in kenaf, is strongly associated with bark thickness, stem diameter, and plant height [20,21]. However, research on the correlations of traits that affect biomass or traits related to biomass is insufficient. Information on the correlation of key traits, such as stem diameter, leaves by number of nodes, and height for kenaf breeding, is lacking, making its breeding inefficient. In other plants, these key traits have been reported to be related to biomass. For instance, in rice, the height of a plant is used to estimate the biomass [23]. In sorghum, a thicker stem diameter is preferred as this indicates a greater biomass yield [24]. In addition, Mauro-Herrera and Doust [25] have suggested that biomass is highly correlated with the height of the plant and the number of nodes on the main stem. Furthermore, in the giant reed, a higher number of nodes on the stem means a higher amount of meristem tissue, and thereby, a larger amount of biomass [26].
In this study, the growth patterns of the potential key traits mentioned above were examined over time in 23 kenaf cultivars, and the correlation between each trait was determined. By elucidating the correlation among the traits studied, biomass increment-related breeding in kenaf could be established. Furthermore, we measured the traits mentioned above at different growth stages to determine whether early selection for each trait is possible.

2. Materials and Methods

2.1. Experiment Site and Plant Materials

The experiment was conducted from 2 May 2019 to 5 September 2019 in the Jeju National University Test Field, Korea (33°27′35.7″ N 126°33′50.3″ E DMS). The average temperature ranged from 16.6 °C to 30.6 °C, and the total precipitation was measured to be 1056.7 mm during the experiment (Table 1). Kenaf cultivars were provided by the Rural Development Administration (RDA, Korea) and SJ Global Co., Ltd. (https://koreakenaf.modoo.at/, accessed on 6 June 2021, Bucheon, Korea) (Table 2).
On 2 May 2019, 15 individuals of each of the 24 cultivars were planted in a row at a distance of 25 cm between each other in one planting section. A total of 24 plots of each cultivar were replicated three times and randomly arranged. The distance between each section was 50 cm, and the distance between each row was approximately 100 cm. All individuals were well irrigated from 14 days after planting, once a day, until the end of the experiment. Additionally, only data from 23 cultivars were used in the experiment because of the lack of germination in EF-2 and lodged individuals due to the influence of typhoons during their growth, meaning that they had to be supported with stakes.

2.2. Measurements

The number of nodes, stem diameter, and height of three randomly selected kenaf individuals from each section were measured in four sets on days 75 (15 June 2019), 86 (26 July 2019), 103 (12 October 2019), and 127 (5 September 2019) after planting. The number of nodes was measured by counting the nodes of the main stem as these were visible to the naked eye. The stem diameter was estimated at the middle of the first and second nodes of the main stem using a Vernier caliper, and the height was measured from the ground to the tip of the individuals using a measuring tape.

2.3. Statistical Analysis

Data analysis was performed using R software (Ver. 1.3.1056., RStudio Team, R Foundation for Statistical Computing, Boston, MA, USA). Non-parametric tests (Kruskal–Wallis test, post hoc Dunn’s test with Benjamini–Hochberg FDR correction) were applied to compare the stem diameter, number of nodes, and height of the 23 kenaf cultivars. Spearman’s rank correlations were used to determine the degree of agreement of the ranking of each parameter.

3. Results and Discussion

Significant differences in the germplasms in terms of the stem, nodes, and shoot tip were found, except in the stem and nodes of plants in Set 2 (Table 3). The lack of differences in all replications implies that the data were consistent and reproducible. However, the rank of each trait did not remain the same (Figure 1, Table 4, Table 5 and Table 6). Although the rank of each trait was similar in the majority of germplasms, some of them decreased or increased dramatically. This strongly indicates that the selection must be performed at the end of the growth stage. In addition, differences in the germplasms of different tissues at different time points suggest that the growth rate of each germplasm is different in different environments, which could be worth examining.
We found that correlations among traits varied at different growth stages (Table 7). This could be due to the rank changes mentioned above, meaning that the growth rates for each trait in each germplasm are diverse. Assuming selection would be made at the end of the growth stage, the correlation between the number of nodes and stem diameter, as well as that between the number of nodes and height, were relatively high at 0.65 and 0.67, respectively. This could be because the number of nodes increases both horizontally and vertically as plant diameter and plant height, respectively, increase. Hence, an increase in the number of leaves is a direct function of stem diameter and plant height, which are much easier to measure for efficient plant selection for breeding purposes. With the same assumption, height and stem diameter had a low correlation (0.34). This indicates that they need to be measured separately to increase biomass because biomass is highly associated not only with height but also with stem diameter.
The high correlation can be attributed to two possibilities—co-selection and genetic linkage—while the reasons are the opposite for a low correlation. Plant height is the result of primary growth, and its diameter is that of secondary growth [27]. The question to be considered is how the two are related. In rice, there was no overlap between quantitative trait loci (QTLs) for increased stem diameter and QTLs for plant height [28]. In addition, in soybean, many QTLs for height and the number of nodes are not linked to each other [29]. Likewise, in Eucalyptus, woody plants, Chinese silver grass, and herbal plants, height and circumference have a strong phenotypic correlation, although many QTLs for height and circumference have not been linked to each other [30]. In addition, the chance of co-selection is low, considering that the plant materials used in the current study are mostly germplasm.
In summary, both stem diameter and height should be measured for a more effective biomass-based breeding strategy. In addition, to breed a kenaf cultivar with many leaves (for obtaining the functional compounds or for other purposes), height or stem diameter could be measured because they have a high correlation with the number of nodes. Additionally, height or stem diameter are more accessible and measurable traits, especially height, and could be estimated using an unmanned aerial vehicle for easier selection [31]. Moreover, selection should be made at the end of the growth stage because the rank of each trait varies significantly in this phase of growth.

4. Conclusions

In this study, correlations and growth patterns of major traits, such as stem diameter, number of nodes, and height over time, were confirmed in various germplasms. Since different germplasms have different traits, it is necessary to screen them according to the breeding purposes. In addition, this study showed a strong correlation between the number of nodes and height over time and a weak correlation between stem diameter and height. We showed that the correlation of each trait in kenaf implies that the breeding strategy could be made more efficient if this information is utilized.

Author Contributions

Conceptualization, Y.S.C., S.-C.Y. and J.-K.Y.; methodology, Y.S.C.; validation, S.-C.Y. and Y.S.C.; formal analysis, G.D.H. and R.R.; investigation, G.D.H. and G.M.; data curation, D.Y.H., S.-H.K. and J.P.; writing—original draft preparation, J.K. and G.D.H.; writing—review and editing, Y.S.C.; funding acquisition, Y.S.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by a grant from the Standardization and integration of resources information for seed-cluster in Hub-Spoke material bank program (Project No. PJ01587004), Rural Development Administration, Republic Korea.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This research was supported by a grant from the Standardization and integration of resources information for seed-cluster in Hub-Spoke material bank program (Project No. PJ01587004), Rural Development Administration, Republic Korea. We are also grateful to the Sustainable Agricultural Research Institute (SARI) in Jeju National University for providing the experimental facilities. Lastly, this research was supported by National University Development Project funded by the Ministry of Education (Korea) and National Research Foundation of Korea 2021).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) Stem diameter (mm); (b) Number of nodes; and (c) Height (cm) of 23 cultivars at four different growth stages.
Figure 1. (a) Stem diameter (mm); (b) Number of nodes; and (c) Height (cm) of 23 cultivars at four different growth stages.
Plants 10 01394 g001aPlants 10 01394 g001b
Table 1. Climate variables of experiment site, from May to September 2019.
Table 1. Climate variables of experiment site, from May to September 2019.
MayJuneJulyOctoberSeptember 1
Average min Temperature (°C)16.619.023.225.522.4
Average max Temperature (°C)23.825.127.930.627.6
Total monthly precipitation (mm)42.8145.8510.1242.3115.7
1 From 1–5 September.
Table 2. Twenty-four kenaf (Hibiscus cannabinus L.) cultivars were tested in the experiment.
Table 2. Twenty-four kenaf (Hibiscus cannabinus L.) cultivars were tested in the experiment.
EntryOrigins
CubanoCuba
Everglades 41US
Everglades 41US
KenafMyanmar
LocalAfrica
PI365441Taiwan
PI468075US
PI468077US
WIR119India
WIR214Iran
WIR274Iran
WIR275Iran
WIR276Iran
WIR333France
WIR360Italy
WIR452China
WIR453Iran
EF-1-
EF-2-
EF-3-
ET-1-
ET-2-
G-1-
Table 3. Kruskal–Wallis rank sum test at four growth stages.
Table 3. Kruskal–Wallis rank sum test at four growth stages.
Stem DiameterNumber of NodesHeight
SourceDfSet 1 1Set 2Set 3Set 4Set 1Set 2Set 3Set 4Set 1Set 2Set 3Set 4
Replication2NS 2NSNSNSNSNSNSNSNSNSNSNS
Entries22* 3NS******NS***********
1 Set 1, Set 2, Set 3, and Set 4 measured on 15 July, 26 July, 12 August, and 5 September. 2 NS, nonsignificant at p > 0.05. 3 * Significant at the 0.05, ** Significant at the 0.01, and *** Significant at the 0.001 probability level.
Table 4. Variation among Kenaf (Hibiscus cannabinus L.) cultivar in stem diameter at four growth stages.
Table 4. Variation among Kenaf (Hibiscus cannabinus L.) cultivar in stem diameter at four growth stages.
Set 1 1Set 2Set 3Set 4
CultivarDiameter 2CultivarDiameterCultivarDiameterCultivarDiameter
EF-326.74 ± 0.92 a 3Cubano35.70 ± 7.22 aPI36544136.84 ± 3.24 aPI36544153.77 ± 2.46 a
Cubano25.29 ± 2.73 abPI36544131.84 ± 1.70 aEverglades 7135.32 ± 1.65 aEF-148.83 ± 3.77 ab
EF-124.98 ± 2.36 abR31.26 ± 1.57 aR35.18 ± 2.88 aG-145.94 ± 3.10 ab
ET-224.35 ± 0.06 abET-131.09 ± 3.05 aEF-134.73 ± 3.73 abEverglades 7145.86 ± 0.69 ab
PI36544123.99 ± 0.95 abET-230.80 ± 1.12 aET-133.31 ± 3.52 abR45.75 ± 3.04 ab
Everglades 4123.75 ± 0.82 abEF-330.74 ± 2.88 aEverglades 4133.15 ± 2.05 abET-144.26 ± 2.14 abc
ET-123.43 ± 2.47 abEF-130.51 ± 3.40 aET-232.89 ± 2.94 abET-243.6 ± 1.30 abc
WIR27523.39 ± 1.88 abG-130.16 ± 3.59 aCubano32.72 ± 7.61 abcdPI46807742.93 ± 1.75 ab
R23.24 ± 1.56 abWIR33329.35 ± 1.06 aG-132.42 ± 2.16 abcEverglades 4142.61 ± 10.11 abcd
G-122.70 ± 2.93 abEverglades 4129.32 ± 0.50 aPI46807532.15 ± 4.21 abcdPI46807542.16 ± 6.59 abcd
WIR21422.60 ± 0.28 abPI46807528.43 ± 2.92 aWIR36031.84 ± 3.02 abcdEF-340.95 ± 2.01 abcde
WIR45322.26 ± 3.01 abWIR45328.36 ± 1.69 aWIR27530.42 ± 2.06 abcdWIR36039.77 ± 4.29 abcde
Everglades 7122.18 ± 1.21 abWIR27528.31 ± 2.79 aPI46807728.90 ± 2.70 abcdCubano38.74 ± 2.44 bcdef
WIR45221.98 ± 0.86 abWIR36028.19 ± 2.52 aWIR21428.65 ± 1.59 abcdWIR27538.07 ± 2.57 bcdef
WIR33321.50 ± 0.83 abEverglades 7127.95 ± 0.23 aWIR45328.49 ± 0.46 abcdKenaf37.98 ± 2.38 bcdef
WIR36021.18 ± 0.87 abPI46807726.90 ± 2.85 aWIR33328.15 ± 1.21 abcdWIR45334.91 ± 3.59 bcdef
PI46807720.89 ± 1.82 abWIR45226.15 ± 0.89 aEF-327.41 ± 0.99 abcdWIR33332.05 ± 3.63 cdef
WIR27620.12 ± 0.43 abKenaf24.93 ± 2.03 aKenaf25.94 ± 1.35 bcdLocal30.45 ± 6.09 cdef
WIR27419.72 ± 0.74 abWIR21424.66 ± 0.49 aWIR27625.29 ± 1.74 bcdWIR21429.95 ± 1.65 def
Local19.66 ± 1.38 abWIR27623.00 ± 0.82 aWIR45225.27 ± 0.48 bcdWIR45228.84 ± 2.60 def
WIR11919.49 ± 1.40 abWIR27422.66 ± 3.41 aWIR27424.05 ± 1.18 cdWIR27427.87 ± 1.79 ef
PI46807518.59 ± 2.73 abWIR11921.78 ± 0.77 aWIR11923.66 ± 0.24 dWIR27627.72 ± 1.58 ef
Kenaf13.31 ± 0.15 bLocal21.30 ± 2.42 aLocal22.97 ± 1.89 dWIR11924.76 ± 0.56 f
1 Set 1, Set 2, Set 3, and Set 4 measured on 15 July, 26 July, 12 August, and 5 September. 2 Unit = mm. 3 Means of ± standard errors followed by different letters within columns are significantly different by Dunn’s test with Benjamini–Hochberg. Non-parametric rank data were used for statistical analysis; however, untransformed data are presented.
Table 5. Variation among Kenaf (Hibiscus cannabinus L.) cultivar in the number of nodes at four growth stages.
Table 5. Variation among Kenaf (Hibiscus cannabinus L.) cultivar in the number of nodes at four growth stages.
Set 1 1Set 2Set 3Set 4
CultivarNumber of NodesCultivarNumber of NodesCultivarNumber of NodesCultivarNumber of Nodes
WIR21435.11 ± 1.44 a 2WIR11944.33 ± 2.33 aEF-151.89 ± 8.22 abWIR45369.56 ± 8.66 ab
WIR27534.56 ± 2.56 abWIR27542.33 ± 2.91 abWIR27548.44 ± 2.38 aEF-169.44 ± 2.44 a
Local33.89 ± 1.64 aR40.22 ± 2.90 abWIR27648.44 ± 3.26 abWIR36066.22 ± 10.39 abcd
WIR45233.11 ± 0.87 abcWIR33340.11 ± 1.72 abWIR11946.89 ± 2.44 abWIR27561.22 ± 3.58 abc
WIR27632.78 ± 0.80 abcdWIR21440.00 ± 2.46 abWIR36046.56 ± 2.89 abG-160.11 ± 0.48 abcd
WIR33332.78 ± 0.68 abcdEverglades 4139.56 ± 1.68 abWIR45345.11 ± 1.87 abET-260.00 ± 5.35 abcde
Everglades 4132.56 ± 2.00 abcdeWIR27639.33 ± 1.02 abET-143.78 ± 3.32 abcR59.56 ± 4.12 abcdef
EF-332.00 ± 1.17 abcdefWIR36038.89 ± 1.47 abWIR33342.78 ± 1.06 abcET-158.00 ± 3.47 abcdef
WIR36032.00 ± 2.04 abcdefEF-138.44 ± 2.45 abR42.56 ± 7.67 abcPI36544156.56 ± 2.51 abcdefg
WIR11931.33 ± 0.69 abcdefgLocal38.22 ± 1.87 abEverglades 4142.22 ± 3.76 abcEverglades 7156.33 ± 2.04 abcdefg
WIR27431.33 ± 1.02 abcdefgEF-337.89 ± 2.79 abPI36544141.94 ± 3.58 abcEverglades 4155.67 ± 7.37 abcdefgh
EF-130.89 ± 0.91 abcdefgWIR27437.67 ± 0.38 abEverglades 7141.78 ± 1.47 abcPI46807555.11 ± 4.41 abcdefghi
ET-230.22 ± 0.56 abcdefghWIR45337.11 ± 3.95 abWIR27441.22 ± 1.64 abcWIR33351.83 ± 3.59 bcdefghij
WIR45330.22 ± 1.82 abcdefgPI36544135.94 ± 1.00 abET-240.22 ± 1.28 abcLocal49.89 ± 9.92 cdefghijk
R28.67 ± 1.84 bcdefghET-135.89 ± 1.60 abEF-339.67 ± 0.19 abcPI46807749.67 ± 0.84 cdefghijk
Everglades 7128.22 ± 1.28 defghWIR45235.00 ± 1.84 abWIR21438.89 ± 4.08 abcWIR27647.78 ± 2.70 defghijk
G-128.00 ± 2.14 cdefghCubano34.89 ± 4.83 abWIR45237.67 ± 1.20 abcEF-347.42 ± 1.11 fghijk
ET-127.89 ± 0.78 efghEverglades 7134.56 ± 0.91 abCubano37.50 ± 6.06 abcWIR11947.33 ± 2.22 efghijk
PI46807726.89 ± 1.68 fghET-234.22 ± 1.75 abG-137.33 ± 3.48 abcCubano44.72 ± 3.82 ghijk
Cubano26.78 ± 1.89 fghG-134.22 ± 2.06 abLocal36.56 ± 2.22 abcWIR27442.33 ± 4.58 hijk
PI36544126.61 ± 1.11 ghPI46807732.11 ± 4.89 abPI46807534.22 ± 3.27 abcWIR21440.78 ± 2.31 jk
PI46807524.56 ± 3.09 ghPI46807530.89 ± 3.04 abPI46807733.83 ± 2.35 bcWIR45240.44 ± 4.58 ijk
Kenaf20.44 ± 0.59 hKenaf22.11 ± 1.06 bKenaf23.00 ± 1.20 cKenaf28.00 ± 2.52 k
1 Set 1, Set 2, Set 3, and Set 4 measured on 15 July, 26 July, 12 August, and 5 September. 2 Means of ± standard errors followed by different letters within columns are significantly different by Dunn’s test with Benjamini–Hochberg. Non-parametric rank data were used for statistical analysis; however, untransformed data are presented.
Table 6. Variation among Kenaf (Hibiscus cannabinus L.) cultivar in height at four growth stages.
Table 6. Variation among Kenaf (Hibiscus cannabinus L.) cultivar in height at four growth stages.
Set 1 1Set 2Set 3Set 4
CultivarHeight 2CultivarHeightCultivarHeightCultivarHeight
WIR214153.33 ± 7.75 a 3WIR119193.89 ± 4.72 aWIR333245.44 ± 4.07 aR285.33 ± 24.27 ab
EF-3151.78 ± 4.29 aR191.00 ± 12.10 abcWIR275225.78 ± 12.26 abWIR275274.89 ± 8.57 a
WIR275142.00 ± 8.34 abWIR275190.56 ± 10.20 abET-1223.33 ± 25.29 abcET-1261.22 ± 22.02 abc
Local141.67 ± 5.06 abWIR274185.33 ± 1.84 abcWIR276221.44 ± 10.23 abEverglades 71256.44 ± 16.25 abcd
Everglades 71136.33 ± 6.94 abcWIR452185 ± 4.10 abcWIR119202.89 ± 10.79 abcdG-1256.44 ± 2.95 abc
WIR276135.44 ± 2.98 abcWIR333184.39 ± 8.05 abcG-1200.33 ± 3.51 abcdWIR333253.50 ± 17.15 abcd
R133.44 ± 16.48 abcWIR214176.78 ± 14.35 abcdeEF-1198.44 ± 17.12 abcdEF-1253.00 ± 18.38 abcd
WIR274133.22 ± 13.64 abcEF-3176.44 ± 8.73 abcdWIR274198.00 ± 8.14 abcdWIR453242.11 ± 13.57 abcde
WIR119132.22 ± 3.35 abcWIR276170.78 ± 8.83 abcdeR197.22 ± 33.21 abcdET-2237.00 ± 1.54 abcde
ET-2132.00 ± 0.51 abcLocal167.22 ± 7.95 abcdeEF-3197.17 ± 7.41 abcdWIR274236.92 ± 12.43 abcde
WIR333130.22 ± 7.75 abcG-1165.22 ± 2.63 abcdeWIR452197.11 ± 9.56 abcdWIR360230.89 ± 10.37 abcdef
PI365441128.94 ± 8.04 abcEverglades 71164.11 ± 7.53 abcdeWIR360193.11 ± 10.29 abcdeEF-3227.92 ± 2.55 bcdefg
ET-1128.11 ± 6.27 abcET-1163.44 ± 9.34 abcdeWIR214192.33 ± 8.21 abcdePI365441226.56 ± 9.72 cdefg
G-1127.67 ± 6.89 abcWIR453156.22 ± 6.88 cdefPI365441191.06 ± 12.35 abcdePI468075225.00 ± 20.34 cdefg
WIR452127.44 ± 18.93 abcEF-1154.89 ± 16.23 bcdefEverglades 71189.67 ± 11.18 abcdeEverglades 41223.00 ± 5.59 cdefgh
Everglades 41127.44 ± 6.79 abcET-2154.44 ± 4.90 defET-2185.67 ± 5.03 abcdeWIR452219.89 ± 13.46 cdefgh
WIR453121.00 ± 6.26 abcEverglades 41149.56 ± 8.79 defWIR453178.67 ± 12.39 bcdeWIR276215.67 ± 7.45 defghi
WIR360117.00 ± 7.24 abcWIR360149.44 ± 5.67 defEverglades 41174.44 ± 6.44 cdeWIR119210.44 ± 5.06 efghi
PI468075116.00 ± 18.56 abcPI365441143.50 ± 8.46 defLocal171.33 ± 10.15 cdeWIR214197.89 ± 8.12 fghi
EF-1112.33 ± 4.26 bcPI468075140.22 ± 22.48 defPI468075166.11 ± 16.43 cdePI468077193.67 ± 3.89 ghi
PI468077110.00 ± 10.02 bcPI468077137.00 ± 17.46 defPI468077150.83 ± 13.42 deLocal192.00 ± 17.03 fghi
Cubano103.33 ± 10.59 bcCubano125.67 ± 22.53 efCubano148.25 ± 20.64 deCubano148.61 ± 13.92 hi
Kenaf50.11 ± 4.33 cKenaf66.00 ± 3.98 fKenaf68.22 ± 5.61 eKenaf120.89 ± 9.43 i
1 Set 1, Set 2, Set 3, and Set 4 measured on 15 July, 26 July, 12 August, and 5 September. 2 Unit = cm. 3 Means of ± standard errors followed by different letters within columns are significantly different by Dunn’s test with Benjamini–Hochberg. Non-parametric rank data were used for statistical analysis; however, untransformed data are presented.
Table 7. Spearman’s rank correlation among diameter, number of nodes, and height in 23 kenaf germplasms at four growth stages.
Table 7. Spearman’s rank correlation among diameter, number of nodes, and height in 23 kenaf germplasms at four growth stages.
SetsNumber of NodesHeight
Stem DiameterSet 10.34 **0.40 ***
Set 20.15 NS−0.03 NS
Set 30.28 *0.20 NS
Set 40.65 ***0.34 **
Number of NodesSet 110.57 ***
Set 210.62 ***
Set 310.69 ***
Set 410.67 ***
Set 1, Set 2, Set 3, and Set 4 measured on 15 July, 26 July, 12 August, and 5 September. * Significant at the 0.05, ** Significant at the 0.01, and *** Significant at the 0.001 probability level. NS, nonsignificant at p < 0.05.
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Kim, J.; Han, G.D.; Muthukathan, G.; Rodrogues, R.; Hyun, D.Y.; Kim, S.-H.; Yu, J.-K.; Park, J.; Yoo, S.-C.; Chung, Y.S. What Traits Should Be Measured for Biomass in Kenaf? Plants 2021, 10, 1394. https://doi.org/10.3390/plants10071394

AMA Style

Kim J, Han GD, Muthukathan G, Rodrogues R, Hyun DY, Kim S-H, Yu J-K, Park J, Yoo S-C, Chung YS. What Traits Should Be Measured for Biomass in Kenaf? Plants. 2021; 10(7):1394. https://doi.org/10.3390/plants10071394

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Kim, Jaeyoung, Gyung Deok Han, Gopi Muthukathan, Renato Rodrogues, Do Yoon Hyun, Seong-Hoon Kim, Ju-Kyung Yu, Jieun Park, Soo-Cheul Yoo, and Yong Suk Chung. 2021. "What Traits Should Be Measured for Biomass in Kenaf?" Plants 10, no. 7: 1394. https://doi.org/10.3390/plants10071394

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