Yield and Quality Stabilities of Waxy Maize Genotypes using Biplot Analysis

Abstract

This study was carried out to determine the stability of the promising waxy maize (10 candidates, 2 standard varieties) genotypes in terms of yield, yield components and quality characteristics in different environments for two years (2018-2019) under Samsun conditions. The GGE and AMMI biplot analysis were used to determine the stability of genotypes. The experimental lay out was randomized blocks with 3 replications. Mean grain yields of genotypes ranged from 8560.6 to 17290.6 kg ha-1, number of days to flowering from 71.3 to 77.5 days, plant height from 251.7 to 295.0 cm, the height of first ear from 85.3 to 98.3 cm, grain cob ratio from 81.3 to 85.5%, grain moisture content from 20.5 to 25.0%, single cob weight from 145 to 286.3 g, the number of cobs per plant from 0.9 to 1.0 cob plant-1, 1000 grain weight from 317.7 to 402.2 g, hectoliter from 76.9 to 79.3%, crude protein ratio from 9.4 to 10.4%, crude oil content from 3.3 to 5.0%, total starch ratio from 57.5 to 60.0%, carbohydrate ratio from 69.6 to 71.6%, and energy value from 383.8 to 393.7 kcal. The result of variance analysis indicated that yield, yield components and chemical composition of maize varieties significantly (p>0.01) different between genotypes (G), environments (E) and genotype x environment (GE) interactions. The effect of environment on experimental variance was 95.15%, the genotype effect was 0.49%, and the GE interaction was 4.15%. The biplot (AMMI and GGE) multivariate analysis indicated a large variation in grain yield, yield components and quality characteristics of waxy maize genotypes. The yield and stability of ADAX11 and ADAX18 genotypes were higher compared to the other genotypes tested. In addition, AMMI model and GGE biplot analyzes provide great ease to the corn breeders in the scientific and accurate assessment of the high yield, stability and adaptations of the waxy corn hybrids.

Keywords

• Waxy maize
• GGE Biplot
• AMMI Biplot
• Stability
• Waxy quality

Supporting Institution

General Directorate of Agricultural Research and Policies

Project Number

TAGEM/TA/14/A12/P03/010

Thanks

I would like to thank the General Directorate of Agricultural Research and Policies (TAGEM) for the funding of this project and to the staff of the Corn Research Institute Directorate (MAEM) for the convenience in providing the materials used in the study.

References

1. [1] Collins, G. N., A new type of Indian corn from China. Bureau of Plant Industry (Bulletin) 1909,161: 1-30.
2. [2] Harakotr, B., Suriharn, B., Tangwongchai, R., Scott, M.P., Lertrat, K., Anthocyanins and antioxidant activity in coloured waxy corn at different maturation stages. Journal of Functional Foods. 2014, 9: 109-118.
3. [3] Fergason, V., Specialty Corn, High Amylose and Waxy Corns, Second Edition Ed: Halluer A.R. 2001, pp: 71-92.
4. [4] Hung P, V., Maeda, T., and Morita, N., Study on physicochemical characteristics of waxy and high-amylose wheat starches in comparison with normal wheat starch. Starch/Staerke 2007, 59(3-4), 125-131. http://dx.doi.org/10.1002/star.200600577.
5. [5] Alcázar-Alay S, C., and Meireles M, A, A., Physicochemical properties, modifications and applications of starches from different botanical sources. Food Sci. Technol, Campinas 2015, 35(2): 215-236.
6. [6] Cengiz, R., Cengiz, B., Esmeray, M., Sezer, C., Akarken, N., Özbey, E., Development of Waxy Corn (Zea mays ceratina) Varieties, 11th Field Crops Congress Proceedings Book-1 2015, 259-261.
7. [7] Fergason, V., Specialty Corn, High Amylose and Waxy Corns, Second Edition Ed: Halluer A.R. 2001, pp: 71-92.
8. [8] Zheng H, Wang H, Yang H, Wu J, Shi B, Cai R, Xu Y, Wu A and Luo L., Genetic diversity and molecular evolution of Chinese waxy maize germplasm. Plosone 2013, 8(6): e66606. Doi: 10.1371/journal.pone.0066606.

9. [9] Mostafavi, K., R. Choukan, M. Taeb, E.M. Heravan and M.R. Bihamta, Heterotic grouping of Iranian maize inbred lines based on yield-specific combining ability in diallel crosses and GGE biplot. J. Res. Agric. Sci., 2012, 8: 113-125.
10. [10] Badu-apraku, B., K., M.oyekunle, A., Obeng-antwi, S.G., Osuman, N., Ado, Coulibaly, C., Yallou, M.S., Abdulai, G.A., Boakyewaa, Didjeira A., Performance of extra-early maize cultivars based on GGE biplot and AMMI analysis. J. Agric. Sci., 2011, 150:1–11.
11. [11] Badu-apraku, B., M., Oyekunele, M.A.B., Fakorede, I., Vroh, R.O., Akinwale, Aderounmu M., Combining ability, heterotic patterns and genetic diversity of extra-early yellow inbreds under contrasting environments. Euphytica, 2013,192: 413-433.
12. [12] Ruswandi, D, J., Supriatna, A, T., Makkulawu, B., Waluyo, H., Marta, E., Suryadi and Ruswandi, S., Determination of combining ability and heterosis of grain yield components for maize mutants based on line x tester analysis. Asian J. Crop Sci., 2015, 7: 19-33.
13. [13] Stojaković, M, B., Mitrović, M., Zorić, M., Ivanović, D., Stanisavljević, A., Nastasić, D., Dodig Grouping pattern of maize test locations and its impact on hybrid zoning. Euphytica, 2015; 204, 2: 419-431.
14. [14] Oyekunle, M., Menkir, H., Mani, G., Olaoye, I.S., Usman, S, G., Ado, U, S., Abdullahi, H, O., Ahmed, L, B., Hassan, R, O., Abdulmalik, H., Abubakar A., Stability Analysis of Maize Cultivars Adapted to Tropical Environments Using AMMI Analysis. Cereal Res. Comm., 2017, 45, 2: 336–345.
15. [15] Boţovıć, D., Ţıvanovıć, T., Popovıć, V., Tatıć, M., Gospavıć, Zagorka, Mıloradovıć, Z., Stankovıć, G., Đokıć. M., Assessment Stability Of Maize Lines Yield By GGE-Biplot Analysis Genetıka, 2018, Vol. 50, No3, 755 -770, 2018. doi.org/10.2298/gensr1803755b
16. [16] Anonymous, 2018. Technical instruction for testing agricultural data. P.1-17, Ankara.
17. [17] Lambert,H., High oil corn hybrids. Second Edition Halluer 2001, A.R. pp: 148-150.
18. [18] Anonymous, 2013. Testing methodology and interpretation of results, Chapter 5, U.S. Grains Council, and U.S. America.
19. [19] Sayaslan, A., Mercan, R.V., Duman, A., Sakin, M, A., Wet-Milling Qualities of Dent Corn (Zea mays indentata L.) Hybrids Grown as Main Crop in Adana and Sakarya. Journal of Agricultural Faculty of Gaziosmanpasa University (2016) 33 (3), 167-180. E-ISSN: 2147-8848. Doi: 10.13002/jafag1144
20. [20] FAO, 2003, Food energy – methods of analysis and conversion factors. FAO food and nutrition paper. ISSN 0254-4725 p.23
21. [21] Yan, W., and Tinker, N, A., Biplot analysis of multi-environment trial data: principles and applications. Canadian journal of plant science, 2006, 86, 623-645. https://doi.org/10.4141/P05-169
22. [22] Yan, W., L.A. Hunt, Q. Sheng, and Z. Szlavnics, Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 2000, 40:597-605.
23. [23] Yan, W., Kang, M, S., Ma, B., Woods, S. and Cornelius, P, L., GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop science, 2007, 47, 643-653. https://doi.org/10.2135/cropsci2006.06.0374
24. [24] Yan, W., and Holland, J, B., A heritability-adjusted GGE biplot for test environment evaluation. Euphytica, 2010, 171, 355-369. https://doi.org/10.1007/s10681-009-0030-5
25. [25] Yan, W., GGE biplot: a Windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agron. J., 2001, 93: 1111–1118.
26. [26] Yan, W., and N. A. Tinker. An integrated biplot analysis system for displaying, interpreting, and exploring genotype X environment interaction. Crop Science 2005, 45:1004-1016.
27. [27] Oliviera, T, R, A., Carvalho, H, W, L., Oliviera, G, H, F., Costa, E, F, N., Gravina, G, A., Santos, R, D., and Filho, J, L, S, C., Hybrid maize selection through GGE biplot analysis. Bragantia vol.78 no.2 Campinas Apr./June 2019 Epub Mar 14, 2019. https://doi.org/10.1590/1678-4499.20170438.
28. [28] Fritsche-Neto, R., Vieira, R. A., Scapim, C. A., Miranda, G. V., and Rezende, L. M., Updating the ranking of the coefficients of variation from maize experiments. Acta Scientarium, 2012, 34, 99-101. https://doi.org/10.4025/actasciagron.v34i1.13115
29. [29] Solaimalai, A., Anantharaju, P., Irulandi, S., Maize Crop: Improvement, Production, Protection and Post-Harvest Technology. Fırst Edition. 2020
30. [30] Özata E., Öz A., and Kapar H Determination of yield and quality characteristics of silage hybrid corn variety candidates. Agricultural Sciences Research Journal 2012, 5 (1): 37-41,
31. [31] Özata, E., and Kapar, H., Determination of the quality and performance of some dent corn hybrid (Zea mays indentata Sturt) under Samsun conditions. Agricultural Sciences Research Journal 2014, 7 (2): 01-07, 2014 ISSN: 1308-3945, E-ISSN: 1308-027X,
32. [32] Özata, E., Geçit, H, H., Öz, A., and Ünver İkincikarakaya, S., Determination of the Performances of Candidate Dent Corn Hybrids under the Main Product Conditions. Iğdır Univ. Journal of Science Institute, 2013, 3(1): 91-98
33. [33] Özata, E., İkincikarakaya, Ünver, S., and Özturk, A., The Determination of Silage Yield and Quality Traits of Candidate Maize Hybrids Ekin Journal of Crop Breeding and Genetics. 2018, 4(1):31-40, 2018.
34. [34] Öz, A., Tezel, M., Kapar, H. and Üstün, A., A study on the development of corn varieties suitable for Samsun and Konya conditions. National Cereal Symposium, June 2-5 2008.
35. [35] Acıbuca, A., 2015, Researches on Silage and Grain Yield and Yield Characteristics of Some Corn Varieties Grown as the Second Crop in Mardin Ecological Conditions. Ege University Institute of Science and Technology, Master Thesis (Unpublished), Izmir.
36. [36] Sabancı, S., 2016, Determination of the yield, quality and antioxidant activities of some corn (Zea Mays L.) cultivars grown in the Aegean region. Ege University Institute of Science and Technology, Master Thesis (Unpublished), Izmir.
37. [37] Creech, R.G., Genetic control of carbohydrate Synthesis in maize endosperm. Genetics 1965, 52: 1175-1186 December 1965.
38. [38] Ma, Dongli Li, Juntao Huang Chengfei, Yang Fengjuan, WuYi, Liu Ling, Jiang, Wei Jia, Zhicheng Zhang, Peijun Liu, Xuezhen and Zhang Shuai, Determination of the energy contents and nutrient digestibility of corn, waxy corn and steam-flaked corn fed to growing pigs. Asian-Australasian Journal Animal Science Vol. 32, No. 10:1573-1579 October 2019 https://doi.org/10.5713/ajas.18.0713 pISSN 1011-2367 eISSN 1976-5517.
39. [39] Saygı, M., Toklu, F., Evaluation of some grain maize (Zea mays indentata sturt.) cultivars grown under the first crop conditions in Çukurova Region in terms of grain yield, some vegetative characteristics and inter-character relations. KSU Journal of Natural Sciences, 2017, 20 (Special Issue), 308-312, Kahramanmaraş.
40. [40] Souvandouane, S., Esguerra, M., Heo, K, H., Cyren M, R., and Sang-Chu L., Effects of Planting Dates and Mulch Types on the Growth, Yield and Chemical Properties of Waxy Corn Crosses Sonjajang×KNU-7 and Asan×KNU-7 KOREAN J. CROP SCI.), 55(2), 2010.
41. [41] Thakur, S., Singh, N., and Kaur, A., Characteristics of normal and waxy corn: physicochemical, protein secondary structure, dough rheology and chapatti making properties. J Food Sci Technol (September 2017) 54(10):3285–3296 DOI 10.1007/s13197-017-2775-5
42. [42] Storck, L., Lopes, S, J., Cargnelutti-Filho, A., Martini L, F, D., Carvalh, and M.P., Sample size for single, double and triple hybrid corn ear traits. Scientia Agricola 2007, 64: 30-35
43. [43] Akan, S., 2017, Determination of suitable maize varieties for the ecological conditions of Muş province. Bingöl University, Institute of Science and Technology, Master's Thesis (Unpublished).
44. [44] Sinay, H., Arumingtyas, E, L., Harijati, N., Indriyani, S., Proline content and yield components of local corn cultivars from Kisar Island, Maluku, Indonesia. International Journal of Plant Biology 2015; 6:6071.
45. [45] Khan, A.K., Minhas, N.M., Asad, M.J., Iqbal, A., Ilyas, M., Mahmood T.M., Estimation of Protein, Carbohydrate, Starch and Oil Contents of Indigenous Maize (Zea mays L.)Germplasm European Academic Research Vol. II, Issue 4/ July 2014.
46. [46] Edy, S, N., and Baktiar I., Increased Potential of Protein Content of Waxy Corn. International Journal of Environment, Agriculture and Biotechnology (IJEAB) Vol-2, Issue-4, July-Aug- 2017. http://dx.doi.org/10.22161/ijeab/2.4.55 ISSN: 2456-1878
47. [47] Klimek-Kopyra A, Szmigiel, A., Zając, T., Kidacka, A., Some aspects of cultıvatıon and utılızatıon of waxy maıze (Zea mays L. Ssp. Ceratina) ACTA AGROBOTANICA Vol. 65 (3): 3-12 2012.
48. [48] Faria, S. V., Luz, L. S., Rodrigues, M. C., Carneiro, J. E. D. S., Carneiro, P. C. S. and De Lima, R. O. Adaptability and stability in commercial maize hybrids in the southeast of the State of Minas Gerais, Brazil. Revista Ciência Agronômica, 2017, 48, 347-357. https:// doi.org/10.5935/1806-6690.20170040.
49. [49] Oliveira, T, R, A., Carvalho, H, W, L., Costa, E F, N., and Carvalho- Filho, J, L, S., Correlation among adaptability and stability assessment models in maize cultivars. Australian Journal of Crop Science, 2017, 11, 516-521. http://dx.doi.org/10.21475/ajcs.17.11.05.p304
50. [50] Kendal, E. and Dogan, Y., Stability of a Cveidate and Cultivars (Hordeum vulgare L) by GGE Biplot analysis of Multi-environment Yield Trials in Spring Barley. Agriculture and Forestry. 2015; 61(4), 307-318.
51. [51] Oral, E,, Kendal, E., ve Doğan, Y., Evaluation of Yield Stability in Some Bread Wheat Varieties using Biplot and AMMI Analysis Methods Journal of Agriculture, ADÜ, 2018;15(1):55-64 — doi: 10.25308/aduziraat.373685.
52. [52] Mitrović B, Stanisavljević D, Treskić S, Stojaković M, Ivanović M, Bekavac G & Rajković M. Evaluation of experimental maize hybrids tested in multi-location trials using AMMI and GGE biplot analyses. Turkish Journal of Field Crops 2012:17(1): 35-40.
53. [53] Yue, H, W., Wang, Y, B., Wei, J. W., Meng, Q. M., Yang, B. L., Chen, S. P.1 – Xie, J. L., Peng, H. C.1 – Jiang, X. W., Effects of genotype-by-environment interaction on the main agronomic traits of maize hybrids. Applied Ecology and Environmental Research, 2020
54. [54] Gauch, H, G., and Zobel R, W., “Predictive and postdictive success of statistical analysis of yield trials”. Theoretical and Applied Genetics 1997, 76.1 1988: 1-10.
55. [55] Gauch, H, G., Statistical analysis of yield trials by AMMI and GCE. Crop science 2006, 46: 1488- 1500.
56. [56] Oliveira, R.L., R.G., Von Pinho, M., Balestre, D.V., Ferreira Evaluation of maize hybrids and environmental Evaluation of maize hybrids and environmental stratification by the methods AMMI and GGE biplot stratification by the methods AMMI and GGE biplot. Crop Breeding App. Biotech., 2010, 10: 247-253.