DETERMINATION OF SUPERIOR BEAN GENOTYPES IN COOKING AND PHYSICAL BY MULTI-CRITERIA DECISION-MAKING METHOD

Abstract

It is aimed to examine and predict the effects of bean genotypes using cooking and physicochemical properties on seed quality index and yield in this study. The seed quality index was calculated by combining the analytical hierarchical process and standard scoring functions, which is one of the multi-criteria decision-making methods, using the linear combination technique. To determine the seed quality index, a data set was created with 11 indicators. analytical hierarchical process was used to weight importance levels of examined traits depending on the genotypes. Seed quality index of registered cultivars according to investigated characteristics of cultivars and genotypes IV. Class, 6 genotype (Bombay genotype) was found to be in class V. Obtained seed quality and physical properties by determining with seed quality index obtained in this study, estimation of seed quality in beans with analytical hierarchical process was evaluated successfully. As a result, according to seed quality index of bean cultivars and genotypes, it was determined that genotype 6 had superior characteristics in terms of productivity, in addition genotypes 8 with 9 and registered cultivars could also show superior characteristics. Keywords: Analytical hierarchical process, Cooking characteristics, Legumes, Physical properties, Yield

Keywords

• Analytical hierarchical process
• Cook characteristics
• Legumes
• Physical properties
• Yield

References

1. Agarwal, K.D., S.D. Billore, A.N. Sharma, B.U. Dupare and S.K. Srivastava. 2013. Soybean: introduction, improvement, and utilization in india-problems and prospects. Agric. Sci. 2(4): 293-300. https://doi.org/ 10.1007/s40003-013-0088-0
2. Anderson, J.A., M. Gipmans, S. Hurst, R. Layton, N. Nehra and J. Pickett. 2016. Emerging agricultural biotechnologies for sustainable agriculture and food security. J. Agric. Food Chem., 64: 383-393. https://doi.org/10.1021/acs.jafc.5b04543
3. Aydogan, S., M. Sahin, A.G. Akcacık, S. Hamzaoglu, B. Demir, C.M. Gucbilmez, and R. Keles. 2020. Determination of quality properties of some dry bean genotypes in Konya conditions. Academic J Agric., 9(2): 259-270. http://dx.doi.org/10.29278/azd.674716
4. Bakure, S., T. Yoseph and D. Ejigu. 2023. Effect of interrow spacings on growth, yield, and yield component of common bean (Phaseolus vulgaris L.) varieties in the cenral rift valley of Ethiopia. Adv Agric. 7434012. https://doi.org/10.1155/2023/7434012
5. Blair, M.W. 2013. Mineral biofortification strategies for food staples: the example of common bean. J. Agric. Food Chem. 61(35): 8287-8294. https://doi.org/10.1021/jf400774y
6. Coffey, L. and D. Laudio. 2021. In defense of group fuzzy AHP: A comparison of group fuzzy AHP and group AHP with confidence intervals. Expert Syst. Appl. 178, 114970. https://doi.org/10.1016/j.eswa.2021.114970
7. Cirka, M. and V. Ciftci. 2018. Determination of flower and seed characteristics of bean (Phaseolus vulgaris L.) gene resources collected from the south of Eastern Anatolia. Journal of the Institute of Science and Technology, 8(3): 53- 62.
8. Çukurcalıoğlu, K., E. Takıl, and N. Kayan. 2023. Influence of bacteria and chicken manure on yield and yield components of bean (Phaseolus vulgaris L.). TJFC, 28(2):138-146. doi:10.17557/tjfc.1265059

9. Darko, A., A.P.C. Chan, E.E. Ameway, E.K. Owusu, E. Parn and D.J. Edwards. 2018. Review of application of analytic hierarchy process (AHP) in construction. Int. J. Constr. Manag. 1-17. https://doi.org/10.1080/15623599.2018.1452098 Dhahri, M., M. Mezghani and I. Rekik. 2020. A weighted goal programming model for storage space allocation problem in a container terminal. JSDTL, 5(2): 6-21. https://doi.org/10.14254/jsdtl.2020.5-2.1
10. Diaz, H. and C.G. Soares. 2022. A multi-criteria approach to evaluate floating offshore wind farms siting in the Canary Islands. Energies, 14, 865. https://doi.org/10.3390/en14040865
11. Didani, B.S. and R. Dumlupınar. 2022. Common bean seedlings show increased tolerance to cool temperatures when treated with progesterone, β-oestradiol, abscisic acid, and salicylic acid. Zemdirbyste. 109(1): 43–48. https://doi.org/10.13080/z-a.2022.109.006
12. FAO, 2019. Plant production statistics. http://www.fao.org/faostat/en/#data/QC Garcia, G.G. 2022. Using multi-criteria decision making to aptimise solid waste management. Curr. Opin. Green Sustain. 37, 100650. https://doi.org/10.1016/j.cogsc.2022.100650
13. Garcia, D.J. and V.E. Guiart. 2022. Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain). Ecol. Inform. 70, 101739. https://doi.org/10.1016/j.ecoinf.2022.101739
14. Gebru, H., B. Abdissa, B. Addis, S. Alebachew and A. Ayele. 2023. Selection of conventional preservation technologies using analytical hierarchy process. Opsearch, 60: 217-233. https//doi.org/10.1007/s12597-023-00622-7
15. Gozukara, G., M. Acar, E. Ozlu, O. Dengiz, A.E. Hartemink and Y. Zhang. 2021. A soil quality index using Vis-NIR and pXRF spectra of soil profile. Catena, 211, 105954. https://doi.org/10.1016/j.catena.2021.105954
16. Karaman, R. 2019. Characterization in terms of phenological, morphological, agronomic, and some technological properties of mung bean (Vigna radiata Wilczek) genotypes/local populations in Isparta conditions. Ph.D. Thesis, Suleyman Demirel University, Institute of Science, 226 p.
17. Keshavarzi, A., M.P. Fernández, Zeraatpisheh, M. Tuffour, H.O. Bhunia, G.S. Shit, and J. Rodrigo-Comino. 2022. Soil Quality Assessment: Integrated Study on Standard Scoring Functions and Geospatial Approach. In Soil Health and Environmental Sustainability: Application of Geospatial Technology (pp. 261-281). Cham: Springer International Publishing.
18. Khan, M.H., M.Y. Rafi, S.I. Ramlee, M. Jusoh and A. Mamun. 2022. Path-coefcient and correlation analysis in Bambara groundnut (Vigna subterranea [L.] Verdc.) accessions over environments. Nature, 12, 245.
19. https://doi.org/10.1038/s41598-021-03692-z Koivunen, E., P. Tuunainen, E. Valkonen and J. Valaja. 2015. Use of semi-leafless peas (Pisum sativum L.) in laying hen diets. Agric. Food Sci. 24(2): 84–91. https://doi.org/10.23986/afsci.48421
20. Luo, M., J. Gao, R. Liu, S. Wang and G. Wang, 2023. Morphological and anatomical changes during dormancy break of the seeds of Fritillaria taipaiensis. Plant Signal. Behav., 18(1): 2194748. https://doi.org/10.1080/15592324.2023.2194748
21. MacCallum, R.C., S. Zhang, K.J. Preacher and D.D. Rucker. 2002. On the practise of dichotomization of quantitative variables. Psychol. Methods, 7(1): 19-40. https://doi.org/10.1037//1082-989X.7.1.19
22. Meltzer, H.M., A.L. Brantsater, E. Trolle, H. Eneroth, M. Fogelholm, T.A. Ydersbond and B.E. Birgisdottir. 2019. Environmental sustainability perspectives of the Nordic diet. Nutrients, 11(9): 2248. https://doi.org/10.3390/nu11092248
23. Oner, E.K., M. Yesil and M.S. Odabas, 2023. Prediction of matabolites content of laurel (Laurus nobilis L.) with artificial neural networks based on different temperature and storage times. Journal of Chemistry, 3942303. https://doi.org/10.1155/2023/3942303
24. Ozaktan, H. 2021. Technological characteristics of chickpea (Cicer arietinum L.) cultivars grown under natural conditions. Turkish J. Field Crop. 26(2): 235-243
25. Pushkarnath, K.M., A.J. Reddy, G.M. Lai and G.R. Lavanya. 2022. Direct and indirect effects of yield contributing characters on grain yield in rice. Int. J. Plant Soil Sci 34(21): 769-778. https://doi.org/10.9734/UPSS/2022/v34i2131331
26. Rouyendegh, B.D. and S. Savalan. 2022. An integrated fuzzy MCDM hybrid methodology to analyse agricultural production. Sustainability, 14, 4835. https://doi.org/10.3390/su14084835
27. Saaty, T.L. 1980. The analytic hierarchy process (AHP) for decision making. Kobe, Japan, p.1-69 Shimelis, E.A. and S.K. Rakshit. 2005. Proximate composition and physico chemical properties of improved dry bean (Phaseolus vulgaris L.) varieties grown in Ethiopia. LWT - Food Sci. Technol. 38(4): 331-338. https://doi.org/10.1016/j.lwt.2004.07.002
28. Sengupta, S., S. Mohinuddin, M. Arif, B. Sengupta and W. Zhang. 2022. Assessment of agricultural land suitability using GIS and fuzzy analytical hierarchy process approach in Ranchi District, India. Geocarto Int. 37(26): 13337-13368. https://doi.org/10.1080/10106049.2022.2076925
29. Sozen, O. and U. Karadavut. 2020. A study on determination of some quality traits of dry bean genotypes (Phaseolus vulgaris L.) grown in different locations. TURKJANS, 7(4): 1205-1217. https://doi.org/10.30910/turkjans.776613
30. Taner, A., Y.B. Oztekin, A. Tekguler, H. Sauk and H. Duran. 2018. Classification of varieties of grain species by artificial neural networks. Agron. 8(7): 123-128.
31. Unal, H., E. Isık, N. Izli and Y. Tekin. 2008. Geometric and mechanical properties of mung bean (Vigna radiata L.) grain: Effect of moisture. Int. J. Food Prop. 11(3): 585-599.
32. Ziemba, P. 2022. Application framework of multi-criteria methods in sustainability assessment. Energies, 15(23): 9201. https://doi.org/10.3390/en15239201