ارزیابی عملکرد و پایداری ژنوتیپ‌های عدس با استفاده از شاخص WAASBو مدل اثرهای مخلوط خطی(LMM)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی،

2 استادیار پژوهشی، بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش

3 کارشناس، موسسه تحقیقات کشاورزی دیم کشور، معاونت سرارود ، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرمانشاه، ایران.

چکیده

اهداف: هدف از این تحقیق ارزیابی کارایی مدل های تجزیه پایداری با استفاده از مدل‎های امی (AMMI) و بلاپ (BLUP) بود .
مواد و روش‌ها: در این تحقیق 19 ژنوتیپ پیشرفته عدس به همراه سه رقم شاهد کیمیا، بیله سوار و توده محلی در ایستگاه‎های تحقیقات کشاورزی خرم آباد (لرستان)،زنجیره (ایلام) و سرارود (کرمانشاه) به مدت دو سال زراعی
(1397-99) در قالب طرح بلوک های کامل تصادفی با سه تکرار مورد ارزیابی قرار گرفتند. برای تعیین کمیت پایداری ژنوتیپی، از تجزیه مقادیر منفرد (SVD) با یک مدل اثرمخلوط خطی (LMM) استفاده شد.
یافته ها: نتایج آزمون نسبت درست نمایی (Likelihood ratio test, LRT) نشان داد که برهم‌کنش ژنوتیپ × محیط بر عملکرد دانه معنی دار بودند. بنابراین، تجزیه BLUPs برای این داده‎ها مناسب تشخیص داده شد. نمودار موزاییکی نشان داد که سهم مجموع مربعات ژنوتیپ و برهمکنش ژنوتیپ × محیط در مجموع مربعات کل به ترتیب 75/6 و 36/34 درصد بود. بای پلات اولین مؤلفه اصلی محیط در برابر عملکرد اسمی نشان داد که ژنوتیپ‎های 13، 6، 16، 9 و 10 از پایداری بیشتری برخوردار بودند.
نتیجه گیری: بای پلات عملکرد دانه در برابر میانگین وزنی نمرات مطلق (WAASB نشان داد که ژنوتیپ های 10، 16، 1، 20، ۱5 ، 4 ،13 و 7 به دلیل بزرگی متغیر پاسخ (داشتن عملکرد بالا) و پایداری بالا (مقادیر پایین WAASB)، بسیار پر محصول و پایدار بودند. شناسایی ژنوتیپ‎ها با معیار WAASBY نشان داد که ژنوتیپ های 16 و 1 پر محصول و پایدار بودند و می تواند نامزد معرفی ارقام جدید باشند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluation of Mean yield and stability of lentil genotypes using WAASB index and linear mixed effects model (LMM)

نویسندگان [English]

  • Payam Pezeshkpour 1
  • Amir Mirzaei 2
  • Iraj Karami 3
1 Crop and Horticultural Science Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, AREEO, Khorramabad, Iran
2 Assistant Professor, Crop and Horticultural Science Research Department, Ilam Agricultural and Natural Resources Research and Education Center, AREEO, Ilam, Iran
3 MSc., Dryland Agricultural Research Institute, Sararood Branch, Agricultural Research, Education and Extension Organization (AREEO), Kermanshah, Iran.
چکیده [English]

Abstract
Background and Objectives: The aim of study was to evaluate the efficiency of yield stability analysis models by BLUP and AMMI models.
Materials and methods: In this research, nineteen advanced lentil genotypes along with three cultivars of check Kimia, Bileh Sawar and local mass in agricultural research stations of Khorramabad, Ilam and Sararoud in the form of complete blocks design. Randomly with three repetitions and for two crop years (2018-2020), were evaluated. To quantify the genotypic stability, singular value decomposition (SVD) was used with a linear mixed effect model (LMM).
Results: The likelihood ratio test (LRT) indicated that the effect of GEI was significant on seed yield. Therfore, the best linear unbiased predictors (BLUPs) analysis was considered appropriate for these data. Mosaic plot showed that the portion of sum squares of genotype (G) and sum squares of genotype by environment interaction (GEI) in total sum of squares (TSS) were 6.75% and 34.36%, respectively. The bilot of first principle component (PC1) of the environment versus nominal yield showed that genotypes 13, 6, 16, 9 and 10, were more stable.
Conclusion: Biplot of seed yield versus WAASB Showed that the genotypes 10, 16, 1, 20, 15,4,13 and 7 were very productive and stabile due to the large value of response variable (high seed yield) and high stability (low values of WAASB). Identification of genotypes with WAASBY showed genotypes 16 and 1 high yielding and stable, and therefore can be candidate for cultivar inteoduction.

کلیدواژه‌ها [English]

  • Single Value Decomposition (SVD)
  • Simultaneous Selection
  • Weighted average of absolute scores
  • Lentil
  • Mosaic plot

مراجع

Abbas G, Asghar  MJ, Shahid M, Hussain J, Akram M and Ahmad F. 2019. Yield performance of some lentil genotypes over different environments. Agrosystems, Geosciences & Environment, 2(1): 1-3. DOI:10.2134/age2018.10.0051
Ahmadi K, Ebadzadeh H, Hatami F, Abdshah H and Kazemian H. 2021. Statistics of Agricultural Products (Crops, 2018 -2019). Ministry of Ariculture Jihad.97 P. (In Persian).
Azam MG, Iqba MS, Hossain MA, Hossain MF.2020. Stability investigation and genotype× environment association in chickpea genotypes utilizing AMMI and GGE biplot model. Genetics and Molecular Research, 19(3):1-5.
Baggar, A., Safi, A., Gaboun, F., Taghouti, M. and Benbrahim, N., 2023. Identification of stable lentil genotypes through genotype by environment interactions on yield potential in Morocco. Plant Science Today, 10(1), pp.57-66.doi.org/10.14719/pst.1814
Branković-Radojčić D, Babić V, Girek Z, Živanović T, Radojĉić A, Filipović M, Srdić J.2018. Evaluation of maize grain yield and yield stability by AMMI analysis. Genetika, 50(3):1067-80. doi.org/10.2298/GENSR1803067
Bermejo C, Cazzola F, Maglia F, Cointry E. 2020. Selection of parents and estimation of genetic parameters using BLUP and molecular methods for lentil (Lens culinaris Medik.) breeding program in Argentina. Experimental Agriculture, 56(1):12-25. doi.org/10.1017/S0014479719000061
Chen C, Etemadi F, Franck W, Franck S, Abdelhamid MT, Ahmadi J, Mohammed YA, Lamb P, Miller J, Carr PM, McPhee K. 2022. Evaluation of environment and cultivar impact on lentil protein, starch, mineral nutrients, and yield. Crop Science, 62(2):893-905.  https://doi.org/10.1002/csc2.20675.
Erskine, W., Muehlbauer, F.J., Sarker, A. and Sharma, B. 2009. Introduction: The lentil Botany, Production and Uses. In The lentil Botany, Production and Uses (pp. 1-3). CABI International.
Gauch HG and Zobel RW. 1997. Identifying mega‐environments and targeting genotypes. Crop Science, 37(2): 311-326. doi:10.2135/cropsci1997.0011183X003700020002x
Jeberson MS, Shashidhar KS, Wani SH, Singh AK and Dar SA. 2019. Identification of stable lentil (Lens culinaris Medik) genotypes through GGE biplotand AMMI analysis for North Hill Zone of India. Environment, 2(22.7432):11-3716. doi: 10.18805/LR-3901
Karimizadeh R, Safikhani M, Mohammadi M, Seyyedi F, Mahmoodi A and Rostami B. 2008. Determining rank and stability of lentil in rainfed condition by nonparametric statistics. Journal of Science and Technology in Agriculture and Natural Resources, 43(1): 93 -103 (In Persian).
Karimizadeh R and Mohammadi M. 2010. AMMI adjustment for rainfed lentil yield trials in Iran. Bulgarian Journal of Agricultural Science, 16(1):66-73.
Karimizadeh  R, Mohammadi M, Sabaghni N,  Mahmoodi AA, Roustami B, Seyyedi F, Akbari F. 2013. GGE biplot analysis of yield stability in multi-environment trials of lentil genotypes under rainfed condition. Notulae Scientia Biologicae, 5 (2): 256. doi: https://doi.org/10.15835/nsb529067
Karimizadeh R, Pezeshkpour P, Barzali M, Mehraban A and Sharifi P.  2020. Evaluation the mean performance and stability of lentil genotypes by combining features of AMMI and BLUP techniques. Journal of Crop Breeding, 12(36):160-170 .(In Persian).
Karimizadeh R, Pezeshkpour P, Mehraban A, Sharifi P and Barzali M. 2021. Grain yield stability analysis of lentil genotypes by AMMI method indices. Iranian Journal of Field Crop Science, 52(4):197-209.(In Persian). doi:10.22059/ijfcs.2020.310524.654752
Lin CS and Binns MR. 1988. A method of analyzing cultivar x location x year experiments: a new stability parameter. Theoretical and Applied Genetics, 76(3):425-430. doi: 10.1007/BF00265344
Migliozzi M, Thavarajah D, Thavarajah P.and Smith P. 2015. Lentil and kale: Complementary nutrient-rich whole food sources to combat micronutrient and calorie malnutrition. Nutrients, 7(11):9285-9298. doi: 10.3390/nu7115471
Nataraj  V, Bhartiya  A, Singh CP, Devi  HN, Deshmukh  MP, Verghese  P, Singh  K, Mehtre  SP, Kumari  V, Maranna  S and Kumawat  G. 2021. WAASB‐based stability analysis and simultaneous selection for grain yield and early maturity in soybean. Agronomy Journal, 113(4):3089-3099. doi:10.1002/agj2.20750.
Olivoto T.2019. Metan: multi environment trials analysis. R package version 1.1.0. https://github.com/TiagoOlivoto/metan (accessed 24 June 2019).
Olivoto  T, Lucio ADC, da Silva JAG , Sari BG   and Diel MI. 2019 a. Mean performance and stability in multi -environment trials II: selection based on multiple traits. Agronomy Journal, 111(6): 2961 -2969. doi:10.2134/agronj2019.03.0220
 Olivoto  T, Lucio ADC, da Silva JAG , Marchioro VS, de Souza VQ  and Jost E. 2019 b. Mean performance and stability in multi -environment trials I: combining features of AMMI and BLUP techniques. Agronomy Journal, 111(6): 2949 -2960. doi:10.2134/agronj2019.03.0220.
Olivoto T and Lúcio ADC. 2020. metan: An R package for multi‐environment trial analysis. Methods in Ecology and Evolution, 11(6):783-789.
Pezeshkpour P, Karimizadeh R, Mirzaei A, Barzali M. 2021.Analysis of Yield Stability of lentil Genotypes using AMMI Method. Journal of Crop Breeding.10; 13(37):132-45.(In Persian)
Sarker A, Erskine W, Singh M. 2003. Regression models for lentil seed and straw yields in Near East. Agricultural and forest meteorology, 116(1-2):61-72. doi:10.1016/S0168-1923(02)00247-2
Sellami MH, Pulvento C, Lavini A. 2021. Selection of suitable genotypes of lentil (Lens culinaris Medik.) under rainfed conditions in south Italy using multi-trait stability index (MTSI). Agronomy, 11(9):1807. doi.org/10.3390/agronomy11091807
    Smith AB, Cullis BR, Thompson R. 2005.  The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches. The Journal of Agricultural Science, 143(6):449-62.
Sharifi  P. 2020. Application of Multivariate Analysis Methods in Agriculural Sciences. Rasht branch, Islamic Azad University Press. 288 P. (In Persian).
Sellami MH, Pulvento C, Lavini A. 2021. Selection of suitable genotypes of lentil (Lens culinaris Medik.) under rainfed conditions in south Italy using multi-trait stability index (MTSI). Agronomy, 11(9):1807. doi.org/10.3390/agronomy11091807.
Smith AB, Cullis BR, Thompson R. 2005. The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches. The Journal of Agricultural Science, 143(6):449-62.
Shobeiri S, Sadeghzadeh Ahari D, Pezeshkpour P, Azimi M. Stability analysis of Lentil genotypes by GGE biplot. Journal of Crop Breeding,13(40):1-10.(In persian).
Subedi M, Khazaei H, Arganosa G, Etukudo E, Vandenberg A. 2021.  Genetic stability and genotype× environment interaction analysis for seed protein content and protein yield of lentil. Crop Science, 61(1):342-56.
Tadesse T, Tekalign A, Asmare B.2021.  Identification of Stable Lentil Genotypes Using AMMI Analysis for the Highlands of Bale, Southeastern Ethiopia. Chemical and Biomolecular Engineering, 19;6(4):74. doi: 10.11648/j.cbe.20210604.12.
Tekalign A, Sibiya J, Derera J, Fikre A.2017. Analysis of genotype× environment interaction and stability for grain yield and chocolate spot ('Botrytis fabae') disease resistance in faba bean ('Vicia faba'). Australian journal of crop science,11(10): 1228 -1235. doi: 10.21475/ajcs.17.11.10.pne413.
    Tinker NA, Yan W.2006. Information systems for crop performance data. Canadian journal of plant science,86(3):647-62. doi:10.4141/P05-171
Vineeth TV, Prasad I, Chinchmalatpure AR, Lokeshkumar BM, Kumar S, Ravikiran KT, Sharma PC.2022.  Weighted average absolute scores of BLUPs (WAASB) based selection of stable Asiatic cotton genotypes for the salt affected Vertisols of India. Indian Journal of Genetics and Plant Breeding, 82(01):104-8. doi: 10.31742/IJGPB.82.1.15
Wright, K. and J.L. Laffont. 2018. Package ‘gge’. https://github.com/kwstat/gge/issues
Yan W, Hunt LA, Sheng Q, Szlavnics Z.2000. Cultivar evaluation and mega‐environment investigation based on the GGE biplot. Crop Science 40(3):597-605. doi.org/10.2135/cropsci2000.403597x.
Yan W, Tinker NA.2006. Biplot analysis of multi-environment trial data: Principles and applications. Canadian journal of Plant Science, 86(3):623-45. doi.org/10.4141/P05-169.
Yue H, Gauch HG, Wei J, Xie J, Chen S, Peng H, Bu J, Jiang X.2022. Genotype by Environment Interaction Analysis for Grain Yield and Yield Components of Summer Maize Hybrids across the Huanghuaihai Region in China. Agriculture, 12(5):602. doi.org/10.3390/agriculture12050602.
Zaccardelli, M.; Sonnante, G.; Lupo, F.; Branca, F.; de Falco, E. 2010.  Leguminose minori (cece, lenticchia, cicerchia, fava); Consiglio per Ricerca Sperimentazione Agricoltura: Rome, Italy, 73 P.
دانش کشاورزی وتولید پایدار
دوره 34، شماره 1
فروردین 1403
صفحه 95-112

فایل ها

هم رسانی

ارجاع به این مقاله

آمار