Legume Research

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Legume Research, volume 46 issue 3 (march 2023) : 386-391

Determining the Relationship between SPAD Values and Common Bean Seed (Phaseolus vulgaris L.) Yield by Correlation and Path Coefficient Analysis Method by using Different Organic Fertilizer

Umit Girgel1, Zekeriya Kara2, Alihan Cokkizgin3,*
1Kahramanmaras Sutcu Imam University, Goksun Vocational School, Goksun, Kahramanmaras, 46600, Turkey.
2Kahramanmaras Sutcu Imam University, Centre for University and Industry Collaboration (USKIM) Department, Kahramanmaras, 46050, Turkey.
3Gaziantep University, Nurdagi Vocational School, Nurdagi, Gaziantep, 27840, Turkey.

  • Submitted06-07-2022|

  • Accepted14-10-2022|

  • First Online 02-11-2022|

  • doi 10.18805/LRF-711

Cite article:- Girgel Umit, Kara Zekeriya, Cokkizgin Alihan (2023). Determining the Relationship between SPAD Values and Common Bean Seed (Phaseolus vulgaris L.) Yield by Correlation and Path Coefficient Analysis Method by using Different Organic Fertilizer . Legume Research. 46(3): 386-391. doi: 10.18805/LRF-711.

ABSTRACT

Path coefficient analysis provides a much better understanding of the correlation coefficient values. Spad values give information about the state of the leaf. In the study, path coefficient analysis was performed, especially SPAD values in beans. The study was carried out Kahramanmaraş Sutcu Imam University, treatment area in 2021 year. Mispir cultivar and Aydintepe local common bean genotype were used, leonardite and chicken litter and their mixture were used, various doses (3,6,9 t ha-1 and conventional fertilizer (25 kg ha-1 N/64 kg ha-1 P2O5) and control application) were added to the soil. Leaf chlorophyll content was measured in three periods: early leaf (1st SPAD), flowering stage (2nd SPAD), post-flowering (3rd SPAD). In addition, seed yield and biomass yield values were determined. Chicken Manure 3 t ha-1 organic fertilizer application showed the best performance among all applications in terms of seed yield. And the Aydintepe local genotype showed higher performance than the Mispir cultivar for the most of the properties examined.

INTRODUCTION

Organic, ecological and biological farming identified as a natural farming system (Lammerts et al., 2002). The rule in organic agriculture is that no synthetic substance is used during production (such as chemical fertilizers, chemical pesticides). These synthetic substances have negative effects on human health and food safety (Anonymous, 2021).

Common bean (Phaseolus vulgaris L.) also known as field bean, dry bean, french bean, kidney bean and green bean which is an important legume around the world (Camara et al., 2013; Swegarden et al., 2016; Jannat et al., 2019).

Relations of the common bean spad values and biomass yield are important for high yield. But yield parameters are changes due to the different interactions of various factors (Khan and Dar, 2010).

Correlation coefficient analysis examines the relationship between variables and path coefficient analysis enables the correlation coefficient values to be separated according to the variables and analyzed in more detail. Path coefficient analysis gives information on the common bean yield criteria relations (Ekinci et al., 2010).

Correlation and path coefficient analyzes of seed yield and bean components have been studied by many researchers (Agsakalli and Olgun, 2001; Peksen and Gulumser, 2005; Ghobary and Abdallah, 2010; Karasu and Oz, 2010; Salehi et al., 2010; Sadeghi et al., 2011; Cokkizgin et al., 2013; Prakash et al., 2014; Akhshi et al., 2015; Ejara et al., 2017; Panchbhaiya et al., 2017; Kalauni and Dhakal, 2020). However, little study has been done on the effect of spad values on yield. In addition, researching the subject with organic fertilizers is rarely studied.

This bean study investigated the SPAD-seed yield relationship that was not addressed in other studies. In the study, it was tried to determine the relationship of the spad values measured at three different times to seed yield and biomass yield to seed yield via correlation and path coefficient analysis.

This study was conducted to Kahramanmaraş Sutcu Imam University, Faculty of Agriculture, Department of Field Crops treatment area (37°35'38.3"N 36°48'46.2"E) in 2021 year from 04 April to 28 July.

Two bean genotypes, one local genotype (Aydintepe) and the other registered variety (Mispir), were used in the study. In the field treatment, leonardite and chicken litter and their mixture were used and their various doses (3,6,9 t ha-1) were added to the soil. The common bean conventional production method (25 kg ha-1 N and 64 kg ha-1 P2O5) and the application with no fertilizer were used for control.

The plots were 10 square meters, with 4 rows and the row length was 5 meters. On the other hand, the experiment was established with three replications. Sowing was done on 4th of April and harvesting on 28th of July 2021. During the growing period, irrigation and weed control were carried out at regular intervals. Organic farming principles were followed during these processes.

Leaf chlorophyll content (SPAD) values, biomass yield and seed yield were measured in the study (Estrada and Rodriguez-Gonzalez, 2017; Cokkizgin et al., 2018; Girgel and Cokkizgin, 2019; Girgel et al., 2019; Ahmadi and Arain, 2021; Amarapalli, 2022). Leaf chlorophyll content was measured in three periods: early leaf stage (SPAD I, 10.May.2021), flowering stage (SPAD II, 31.May.2021), post-flowering stage (SPAD III, 29. June. 2021).

Collected data were subjected to analysis of variance (ANOVA), using SAS 9.1 statistical analysis system (SAS, 2004). Duncan’s multiple range test (DMRT) was used to compare the means (Duncan, 1955). Correlation coefficients between all possible combinations of variables were worked out according to Snedecor (1957). Path coefficient technique (in other words multiple regression analysis) was performed according to the method of Wright (1934). On the other hand, correlation and path coefficients were determined using Totemstat, the Windows compatible version of the Tarist statistical analysis program (Acikgoz et al. 1993).
 
1st SPAD measurement (Early leaf stage)
 
According to the results obtained, the difference between the cultivars was found to be statistically significant (Table 1).

Table 1: Analysis of variance summary of 1st SPAD, 2nd SPAD and 3rd SPAD features.



Aydıntepe genotype has a higher spad value (40.337) than the Mispir variety (38.957). On the other hand, the Fertilizer X Genotype interaction and the differences in organic fertilizer applications were statistically insignificant. It was found to be statistically insignificant, but leonardite/chicken manure mix. 9 t ha-1 application had the highest spad value (40.927) among organic fertilizers (Table 2-3).

Table 2: The obtained values of 1st SPAD, 2nd SPAD and 3rd SPAD and their Duncan statistical groups in terms of fertilizer applications.



Table 3: According to the genotypes, the obtained values of 1st SPAD, 2nd SPAD and 3rd SPAD and their Duncan statistical groups.


                                          
2nd SPAD measurement (Flowering stage)
 
The statistical difference between cultivars was also found significant in the second spad measurement. It was determined that the spad value (43.883) of the application without fertilizer was higher than all other applications.

In the first spad measurement, FerXGen. interaction was statistically insignificant. Also, Aydintepe genotype also had a high value (39.677) in the second spad measurement; Mispir variety had lower value (35.144)..
 
3rd SPAD measurement (Post-flowering stage)
 
In the third spad measurement, all factors were found to be statistically insignificant. However, Mispir cultivar (32.640) had high value between genotypes and among the fertilizers, control (no fertilizer) got the highest spad value (33.927).
 
Biomass yield (kg da-1)
 
All sources of variation in biomass yield were found to be insignificant (Table 4).

Table 4: Analysis of variance summary of biomass yield and seed yield features.



However, Aydintepe genotype produced more biomass (491.00 kg da-1) than Mispir cultivar (439.88 kg da-1). Leonardite 3t ha-1 application (520.78 kg da-1) was also the fertilizer application in which the most biomass was obtained (Table 5-6).

Table 5: The obtained values of Biomass Yield and Seed Yield their duncan statistical groups in terms of fertilizer applications.



Properties such as biomass yield and yield are highly affected by the environment, climate and soil conditions. Similar views were also reported by Karavidas et al., (2022). On the other hand, it was reported that there was a strong influence of environmental influences on yield (Swegarden et al., 2016).

Table 6: According to the genotypes, the obtained values of biomass yield and seed yield and their duncan statistical groups.


 
Seed yield (kg da-1)
 
In terms of seed yield, both the difference between genotypes and the difference between fertilizer applications were found to be statistically significant (Table 4). Between the genotypes, Aydintepe genotype (106.59 kg da-1) had higher yield compared to Mispir cultivar (68.23 kg da-1). Considering the fertilizer issue; Chicken Manure 3 t ha-1 organic fertilizer application (118.79 kg da-1) was the application with the highest seed yield. However, the following were also included in the same statistical group: Leonardite/Chicken Manure Mix. 9 t ha-1 (102.83 kg da-1), Control (Chemical fertilizer) (100.94 kg da-1), Chicken Manure 6 t ha-1 (99.70 kg da-1) and Leonardite/Chicken Manure Mix. 6 t ha-1 (97.33 kg da-1) respectively (Table 5-6). The formation of the phenotype; It occurs as a result of genetic factors, environmental factors and the interaction of genetic and environmental factors (Falconer and Mackay 1996). For this reason, the amount of product we obtained varied according to the region and organic fertilizer. It was reported that the yield of bean varies according to the bean genotypes, fertilizer and fertilization (Karavidas et al., 2022). It has been reported that environmental factors have a great effect on yield (Swegarden et al. 2016).
 
Correlation and path coefficient analysis
 
Path coefficient analysis is used to examine the correlation coefficient in more detail. And the aim of the path coefficient analysis is the direct and indirect effects of the independent variables on the dependent variable (Wright, 1918; Wright, 1920; Wright, 1921; Wright, 1934).

When the relationships between the examined features are considered; A positive and significant correlation coefficient was determined between 1st SPAD and 2nd SPAD measurement (r=0.523). All correlation coefficients that could be calculated among other features were found to be insignificant. In this study the results obtained were different from other studies due to both genetic and environmental effects (Table 7).

Table 7: Matrix of correlation coefficients for all measurement parameters.



3rd SPAD had a direct and great negative effect on seed yield and the percentage of effect was 74.4852% (-0.6297). The 1st SPAD value had the greatest positive direct effect on seed yield and the effect percentage was 63.7681% (p=0.4612). Other direct effects were found positive and the biomass yield was 47.1668% (p=0.2522) and 2nd SPAD 20.6367% (p=0.0944), respectively (Table 8-9).

Table 8: Path coefficients for direct and indirect effects of variables.



Table 9: Path ratios for direct and indirect effects of variables.



Falconer and Mackay (1996) reported that genetic and environmental variations inluences physiological mechanisms. Therefore, the the relationships between these studied parameters have changed. For this reason, it is considered as the relationships between the features we examine to change.

CONCLUSION

As a result of spad measurements, it was determined that the Aydintepe genotype produced more chlorophyll. Spad values were found to be statistically insignificant among fertilizer applications, as they were generally similar.

In most of the traits examined, the Aydintepe local genotype showed higher performance than the Mispir cultivar.

Chicken Manure 3 t ha-1 organic fertilizer application showed the best performance among all applications in terms of seed yield. However, positive effects of Leonardite/Chicken Manure Mix. 9 t ha-1, Control (Chemical fertilizer), Chicken Manure 6 t ha-1 and Leonardite/Chicken Manure Mix. 6 t ha-1 applications were determined in terms of seed yield.

Considering the correlation and path coefficients, the effect of spad values on seed yield should also be considered.
 

ACKNOWLEDGEMENT

We thanks to Kahramanmaras Sutcu Imam University, Scientific Research Projects Coordination Unit for supporting this work with project number 2021/2-36 M.

Authors’ contribution

The authors declared that they contributed equally at all stages of the study/writing of the manuscript.

Conflict of interest

None

REFERENCES


  1. Acikgoz, N., Akkas, M.E., Moghaddam, A., Ozcan, K. (1993). TARIST:  A package program of statistics and quantitative genetics for PC, Computer Applications Symp., Konya-Turkey, 133p.

  2. Agsakalli, A. and Olgun, M. (2001). Use of Weighted Scaling Method in Dry Bean Breeding Programmes. Anadolu, J. of AARI, 11(2): 33-42.

  3. Ahmadi, A.Y. and Arai, M.J. (2021). The response of common bean (Phaseolus vulgaris L.) to different levels of organic and inorganic fertilizers. International Journal of Life Sciences and Biotechnology. 4(3): 439-450. DOI:10.38001/ijlsb. 981373.

  4. Akhshi, N., Firouzabadi, F.N., Cheghamirza, K. Dorri, H.R. (2015). Coefficient analysis and association between morpho- agronomical characters in common bean (Phaseolus vulgaris L.). Agronomic Research in Moldova. 48(4): 29-37.

  5. Amarapalli, G. (2022). Studies on the effect of water stress on root traits in green gram cultivars. Legume Research. (45): 422-428, DOI: 10.18805/LR-4630.

  6. Anonymous. (2021). The use of pesticides in developing countries and their impact on health and the right to food. Policy Department for External Relations Directorate General for External Policies of the Union. 45p. doi: 10.2861/28995.

  7. Camara, C.R.S., Urrea, C.A., Schlegel, V. (2013). Pinto beans (Phaseolus vulgaris L.) as a functional food: Implications on human health. Agriculture. 3(1): 90-111. http://doi. org/ 10.3390/agriculture3010090. 

  8. Cokkizgin, A., Colkesen, M., Idikut, L., Ozsisli, B., Girgel, U. (2013). Determination of relationships between yield components in bean by using path coefficient. Greener Journal of Agricultural Sciences. 3(2): 085-089, DOI: 10.15580/ GJAS.2013.2.010313357.

  9. Cokkizgin, A., Girgel, U., Colkesen, M. (2018). A Research on The Determination of Yield and Yield Characteristics of Different Legume Crops Under the Kahramanmaras Conditions. 3rd International Congress on Multidisciplinary Studies. 5th-6th October, Kiev-Ukraine. 405-415p.

  10. Duncan, D.B. (1955). Multiple Range and Multiple F Tests. Biometrics. 11(1): 1-42. https://doi.org/10.2307/3001478.

  11. Ejara, E., Mohammed, W., Amsalu B. (2017). Correlations and path coefficient analyses of yield and yield related traits in common bean accessions (Phaseolus vulgaris L.) at Abaya and Yabello, Southern Ethiopia. International Journal of Plant Breeding and Crop Science. 4(2): 215-224.

  12. Ekinci, R. Basbag, S., Gencer, O. (2010). Path Coefficient Analysis between seed cotton yield and some characters in cotton (Gossypium hirsutum L.). Journal of Environmental Biology. 31(5): 861-864.

  13. Estrada, J.A.S.E. Rodriguez-Gonzalez, M.T. (2017). Biomass and yield of common bean (Phaseolus vulgaris L.) as a function of the nitrogen source. Annual Report of the Bean Improvement Cooperative. 60: 77-78.

  14. Falconer, D.S., Mackay, T.F.C. (1996). Introduction to Quantitative Genetics. 4.ed. Longman, England. 464p.

  15. Ghobary, H.M.M. and Abdallah, S.A.M. (2010). Correlatýon and Path- Coeffýcýent Studýes in Common Bean (Phaseolus vulgaris L.). J. Plant Production, Mansoura University. 1(9): 1233-1239.

  16. Girgel, U. and Cokkizgin, A. (2019). A Research Conducted on Yield and Yield Characteristics of Chickpea Genotypes (Cicer arietinum L.) Under Bayburt Conditions. 1st International Congress on Sustainable Agriculture and Technology. Oral Presentation. p520.

  17. Girgel, U., Cokkizgin, A., Gul, V., Gidik, B., Cetin, G. (2019). New Horizons in Agriculture, Forestry and Aquaculture Sciences,  Chapter 6: Determination of Pods Properties and Yield Quantity of Pea Varieties and Lines (Pisum sativum L.). 99-111. ISBN 978-605-80229-7-3.

  18. Jannat, S., Shah, A.H., Shah, K.N., Kabir, S., Ghafoor, A. (2019). Genetic and nutritional profiling of common bean (Phaseolus vulgaris L.) germplasm from azad Jammu and Kashmir and exotic accessions. The Journal of Animal and Plant Sciences. 29(1): 205-214.

  19. Kalauni, S. and Dhakal, D. (2020). Correlation and path coefficient analysis of seed yield and yield components of french bean (Phaseolus vulgaris L.) genotypes in sub-tropical region. Turkish Journal of Agriculture - Food Science and Technology. 8(9): 1928-1934, DOI: https://doi.org/ 10.24925/turjaf.v8i9.1928-1934.3528.

  20. Khan, M.H. and Dar, A.N. (2010). Correlation and path coefficient analysis of some quantitative traits in wheat. African Crop Science Journal. 18(1): 9-14.

  21. Karasu, A. and Oz, M. (2010). A study on coefficient analysis and association between agronomical characters in dry bean (Phaseolus vulgaris L.). Bulgarian Journal of Agricultural Science. 16(2): 203-211.

  22. Karavidas, L, Ntatsi, G., Vougeleka, V., Karkanis, A., Ntanasi, T., Saitanis, C., Agathokleous, E. etal. (2022). Agronomic Practices to Increase the Yield and Quality of Common Bean (Phaseolus vulgaris L.): A Systematic Review. Agronomy. 12(271): 1-39, https://doi.org/10.3390/agronomy.  12020271.

  23. Lammerts, V.B.E.T., Struik, P.C., Jacobsen, E. (2002). Ecological concepts in organic farming and their consequences for an organic crop ideotype. Netherlands Journal of Agricultural Science. 50(1): 1-26, https://doi.org/10.1016/S1573- 5214(02)80001-X.

  24. Panchbhaiya, A., Singh, D.K., Jain, S.K. (2017). Inter-characters association studies for morphological, yield and yield attributes in the germplasm of French bean (Phaseolus vulgaris L.) in Tarai region of Uttarakhand, India. Legume Research-An International Journal. 40(1): 196-199.

  25. Peksen, E. and Gulumser, A. (2005). Relationships between seed yield and yield components and path analysis in some common bean (Phaseolus vulgaris L.) genotypes. J. of Fac. of Agric. OMU, 20(3): 82-87.

  26. Prakash, J. and Ram, R.B. (2014). Genetic variability, correlation and path analysis for seed yield and yield related traits in french bean (Phaseolus vulgaris L.) under Lucknow conditions. International Journal of Innovative Science. Engineering and Technology. 1(6): 41-50.

  27. Sadeghi, A., Cheghamirza, K., Dorri, H.R. (2011). The study of morphoagronomic traits relationship in common bean (Phaseolus vulgaris L.). Biharean Biologist. 5(2): 102-108.

  28. Salehi, M., Faramarzi, A., Mohebalipour, N. (2010). Evaluation of different effective traits on seed yield of common bean (Phaseolus vulgaris L.) with path analysis. American- Eurasian J. Agric. and Environ. Sci. 9(1): 52-54.

  29. SAS. (2004). SAS/STAT 9.1. User’s guide: Statistics. SAS institute Inc., Carry, NC, USA, pp 5121. 

  30. Snedecor, G.W. (1957). Statistical Methods (5th Ed.). Iowa State Univ. Press, Ames, USA, pp. 534.

  31. Swegarden, H.R., Sheaffer, C.C., Michaels, T.E. (2016). Yield stability of heirloom dry bean (Phaseolus vulgaris L.) cultivars in Midwest organic production. Hort Science. 51(1): 8-14. https://doi.org/10.21273/HORTSCI.51.1.8.

  32. Wright, S. (1918). On the nature of size factors. Genetics 3: 367-374.

  33. Wright, S. (1920). The relative importance of heredity and environment  in determining the piebald pattern of guinea pigs. Proc. Nat. Acad. Sci. 6: 320-332.

  34. Wright, S. (1921). Correlation and Causation. Jour. Ag. Res. 20: 557-585.

  35. Wright, S. (1934). The Method of Path Coefficients. The Annals of Mathematical Statistics. 5(3): 161-215.
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