Evaluation of Genotype × Environment Interaction and Yield Stability Analysis in Peanut Under Phosphorus Stress Condition Using Stability Parameters of AMMI Model

Ajay, B. C.; Bera, SK; Singh, A. L.; Kumar, Narendra; Gangadhar, K.; Kona, Praveen

doi:10.1007/s40003-020-00458-3

Cited by 56 publications

(50 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…1). Similar findings on genotypic stability based on IPCA and ASV were made in chickpea (Zali et al 2011), sorghum (Rakshit et al 2014), soybean (Kumar et al 2014), maize (Bo•oviae et al 2018, pigeonpea (Gaur et al 2020) and groundnut (Ajay et al 2020).…”

Section: Ammi Analysissupporting

confidence: 57%

“…The AMMI and GGE biplot analyses have been used extensively to identify stable cultivars with high yield and yield attributing characters in a wide variety of crops. In the last couple of years, their application was reported in evaluation of genotypes of rice (Dwivedi et al 2020), wheat (Bavandpori et al 2018;Lozada and Carter 2020;Manu et al 2020), maize (Choudhary et al 2019), barley (Kumar et al 2018;Yadav et al 2020), rapeseed (Sara et al 2019), groundnut (Kumar et al 2019;Ajay et al 2020), pigeonpea (Pagi et al 2017;Singh et al 2018;Gaur et al 2020), chickpea (Kanouni 2018), urdbean (Kumar et al 2020a;Kumar et al 2020b), and ashwagandha .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of pigeonpea genotypes with wider adaptability to rainfed environments through AMMI and GGE biplot analyses

Kumar¹,

Ramya²,

Kumar³

et al. 2021

Indian J. Genet

View full text Add to dashboard Cite

Pigeonpea [Cajanus cajan (L.) Millspaugh] is an important pulse crop grown under Indian rainfed agriculture. Twenty eight pigeonpea genotypes were tested for stability and adaptability across ten rainfed locations in the States of Telangana and Karnataka, India using AMMI (additive main effects and multiplicative interaction) model and GGE (genotype and genotype by environment) biplot method. The grain yields were significantly affected by environment (56.8%) followed by genotype × environment interaction (27.6%) and genotype (18.6%) variances. Two mega environments were identified with several winning genotypes viz., ICPH 2740 (G15), TS 3R (G10), PRG 176 (G8) and ICPL 96058 (G22). E2 (Gulbarga, Karnataka), E3 (Bidar, Karnataka) and E6 (Vikarabad, Telangana) were the most discriminating environments. Genotypes, ICPH 2740, PRG 176 and TS 3R were the best cultivars in all the environments whereas PRG 158 (G9), ICPL 87119 (G12), ICPL 20098 (G19) and ICPL 96058 (G22) were suitable across a wide range of environments. Genotypes, ICPH 2740 and PRG 176 can be recommended on a large scale to the farmers with small holdings to enhance pigeonpea productivity and improve the food security

show abstract

Section: Ammi Analysissupporting

confidence: 57%

Section: Introductionmentioning

confidence: 99%

Identification of pigeonpea genotypes with wider adaptability to rainfed environments through AMMI and GGE biplot analyses

Kumar¹,

Ramya²,

Kumar³

et al. 2021

Indian J. Genet

View full text Add to dashboard Cite

show abstract

“…Saat ini telah banyak penelitian yang menggunakan kombinasi model stabilitas parametrik dan non-parametrik dalam menyeleksi genotipe stabil dan berdaya hasil tinggi, diantaranya pada tanaman buncis (Cicer arietinum L.) (Farshadfar et al, 2012), pada tanaman kacang rumput (Lathyrus sativus L.) (Ahmadi et al, 2015), pada tanaman gandum (Abate et al, 2015), pada tanaman jelai (Khalili dan Pour-aboughadareh, 2016;Vaezi et al, 2019), pada tanaman jagung manis (Ruswandi et al, 2020), dan pada tanaman ubi jalar (Maulana et al, 2020). Pada penelitian lainnya, Ajay et al (2020) berhasil menyeleksi tanaman kacang pada kondisi cekaman pospor di India dan Sabaghnia et al (2013) pada tanaman gandum di Iran dengan penggabungan berbagai parameter AMMI. Penggunaan gabungan model stabilitas dikarenakan analisis dengan satu pengukuran stabilitas pada genotipe-genotipe yang diuji dianggap kurang informatif (Khalili dan Pouraboughadareh, 2016).…”

Section: Pendahuluanunclassified

Identifikasi Stabilitas Hasil Genotipe Ubi Jalar (Ipomoea batatas L. (Lam)) Harapan Baru di Tiga Lingkungan

Karuniawan¹,

Maulana

2020

J. Agron. Indonesia

View full text Add to dashboard Cite

Produktivitas merupakan salah satu karakter penting dalam perakitan varietas baru. Pengujian multilokasi diperlukan untuk mengestimasi stabilitas hasil dari tanaman yang diuji. Penelitian ini bertujuan untuk mengestimasi interaksi genotipe dengan lingkungan (GxE), mengidentifikasi stabilitas hasil genotipe-genotipe baru ubi jalar, serta mengidentifikasi pengukuran stabilitas yang statis dan dinamis terhadap hasil ubi jalar. Penelitian dilakukan di tiga lingkungan di Jawa Barat, diantaranya pada dataran medium yaitu Kabupaten Sumedang (729 mdpl), Kabupaten Bandung (857 mdpl), serta pada dataran rendah yaitu Kabupaten Karawang (24 mdpl) dari bulan Januari 2017-Juli 2018. Percobaan menggunakan rancangan lapangan Augmented design di setiap lokasi. Analisis ragam (ANOVA) gabungan digunakan untuk mengestimasi GxE, sedangkan stabilitas hasil diestimasi dengan pengukuran model stabilitas parametrik (Regresi linier Eberhart dan Russell (bi dan S2di), komponen rata-rata varians (θi), varians genotipe terhadap lingkungan (GE) (θ(i)), Wricke ecovalence (Wi2), varians stabilitas Shukla (σ²i), koefisien variasi (CVi), AMMI stability value (ASV)), non-parametrik (model Huehn (S(i)), model Thennarasu (NP(i)), Peringkat Kang (KR)), dan GGE biplot. Hasil penelitian menunjukkan bahwa GxE menunjukkan pengaruh yang signifikan terhadap hasil panen dengan kontribusi sebesar 14.17%. Dua genotipe ubi jalar teridentifikasi stabil dan memiliki hasil tinggi di tiga lingkungan yaitu PR79 dan PR126. Genotipe-genotipe tersebut dapat direkomendasikan sebagai genotipe unggul baru dan sebagai bahan untuk program pemuliaan tanaman ubi jalar selanjutnya. Pengukuran stabilitas NP(2) dan θᵢ merupakan model stabilitas statis yang dapat merekomendasikan genotipe stabil pada lingkungan yang kurang menguntungkan (unfavorable), sedangkan pengukuran S(1), S(2), S(3), S(6), NP(1), NP(3), NP(4), KR, CVi, bi, S2di, Wi2, ASV, dan σ²ᵢ merupakan model stabilitas dinamis yang dapat merekomendasikan genotipe stabil pada lingkungan yang menguntungkan (favorable). Kata kunci: GGE biplot, multilokasi, non-parametrik, parametrik, stabilitas hasil

show abstract

“…Large number of stability analysis measures have been developed to model GxE interactions efficiently (Mohammadi et al, 2015;Bocianowski et al, 2019;Agahi et al, 2020). AMMI based stability measures evaluate the stability of genotypes after reduction of the noise from the GxE interaction effects (Gauch 2013;Oyekunle et al, 2017;Ajay et al, 2020). Researchers have introduced various selection criteria for the simultaneous utilization of yield and stability of evaluated genotypes as stable varieties are generally not highly productive ( (Kang, 1993;Rao and Prabhakaran 2005;Farshadfar, 2008;Farshadfar et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Wheat genotypes as assessed by Additive main & multiplicative interactions (AMMI) and Best linear unbiased prediction (BLUP) for stability analysis under rainfed timely sown trials in Northern Hills Zone of India

Verma

Singh

2021

JANS

View full text Add to dashboard Cite

Stability analysis of wheat genotypes under rainfed timely sown trials in Northern Hills Zone of India by Additive main & multiplicative interactions (AMMI) analysis observed highly significant effects of the environment, GxE interaction and genotypes during 2018-19 and 2019-20. The ranking of genotypes had altered with utilization of more number of IPCA’s in AMMI and WAASB measures. Environments contributed about 53%, GxE interaction accounted for 30.5% and Genotypes explained only 5.4% of the total sum of squares due to treatments in the first year. Wheat genotypes HS668, VL2035, VL2036 , HS562 had been selected by Analytic measures of adaptability and Superiority indexes. Different quadrants comprised of a cluster of arithmetic, geometric, harmonic means along with corresponding adaptability measures. Superiority Indexes considering averages grouped separately. This group maintained the right angles with a group of MASV & MASV1 measures. Clustering of Adaptability measures as per arithmetic, geometric and harmonic means placed in a quadrant. Second-year reflected VL2041, HS675, HS676 & HS562, HPW471 genotypes selected by adaptability and superiority indexes. About 68% of the total variation with 38.4% and 30.2% contributions by PC1 & PC2. Adaptability measures maintained the right angle with other stability measures, with the exception of Superiority indexes. There is an additional advantage with these measures to assign variable weights to the yield and stability as per the goal of breeding trials. These indexes have the potential to provide reliable estimates of genotypes in future studies as they are considered more number of significant IPCA’s in biplots.

show abstract

Evaluation of Genotype × Environment Interaction and Yield Stability Analysis in Peanut Under Phosphorus Stress Condition Using Stability Parameters of AMMI Model

Cited by 56 publications

References 29 publications

Identification of pigeonpea genotypes with wider adaptability to rainfed environments through AMMI and GGE biplot analyses

Identification of pigeonpea genotypes with wider adaptability to rainfed environments through AMMI and GGE biplot analyses

Identifikasi Stabilitas Hasil Genotipe Ubi Jalar (Ipomoea batatas L. (Lam)) Harapan Baru di Tiga Lingkungan

Wheat genotypes as assessed by Additive main & multiplicative interactions (AMMI) and Best linear unbiased prediction (BLUP) for stability analysis under rainfed timely sown trials in Northern Hills Zone of India

Contact Info

Product

Resources

About