An overview of genotype x environment interaction and yield stability analysis in applied plant breeding: great emphasis given to coffee (Coffea arabica L.)

The inconsistence of genotypes across location during plant breeding is the major challenges to the breeder. That is the differential response of genotypes to different environment. Meanwhile stability is the ability of a genotype to withstand stressful conditions and yet be able to produce yield. Thus, stability is an absolute and relative measure. Arabica coffee has location specific adaptation nature and that leads to highly significant instability in its breeding program. In the study of coffee bean yield stability cultivars tested at multi- locations within the domain of coffee growing ecologies of Ethiopia, showed a significant genotype x environment interaction. The review of previous research also indicated inconsistent effects of genotype x environment interaction on cup quality. Yield-stability analysis is very important in measuring cultivar stability and suitability for growing crops across seasons and agro-ecological region to identify stable genotype. The yield stability have been challenge to the plant breeders and biometricians, it complicates the selection of superior genotypes. It is important to minimize the usefulness of the genotype across environments for selecting. Since approach of plant breeding is to develop genotypes that are, optimum for the condition under which they will be grown breeders have to manage yield instability throughout formalized procedures of plant breeding. During stability measurement if the variance is found to be significant, various methods of measuring the stability of genotypes can be used to identify the stable genotype(s). Most of stability analysis parameters are briefly discussed in this review. Int. J. Agril. Res. Innov. Tech. 11(2): 117-123, Dec 2021

Genotype X Environment Interaction and Yield Stability in Early-Maturing Cowpea (Vigna unguiculata (L.) Walp.) Landraces in Ethiopia

The study was conducted to estimate the effects of genotype, environment, and genotype × environment interaction on grain yield and yield-related traits and to identify stability genotype. At six environments, twenty-four cowpea landraces and one check were evaluated in a 5 × 5 triple lattice during the 2019 cropping season. Data were collected on yield and yield-related traits. The analysis of variance for each environment and across environments showed significant differences among genotypes, environments, and GEI for most traits including yield. Environment, genotype, and GEI showed 27.45%, 20.9%, and 49.55% contribution to the total sum of squares, respectively, for grain yield. This indicated that the environments were diverse and most of the variation in grain yield was caused due to interaction and environmental means. G24 (2632 kg ha−1) and G16 (2290 kg ha−1) were the highest yielder and stable genotypes with mean grain yields above the grand mean (2049.28 kg ha−1) and standard check (2273 kg ha−1). G24 and G16 were the most stable genotypes according to cultivar superiority, Wricke’s ecovalence, regression coefficient, and devotion from regression stability models.

Stability Analysis for Yield and it’s Related Characters in Linseed (Linum usitatissimum L.)

Thirty-six genotypes including eight parents and their 28 crosses developed in diallel fashion excluding reciprocals were used to studied their stability performance over six contrasting environments viz., early, normal and late sown under rainfed and irrigated conditions for seed yield and its contributing characters. Genotype x Environment interaction and Linear component of G x E interaction were showed significant for all the characters except plant height, secondary branches per plant and biological yield per plant under study. The parents Meera and PA2 showed stable performance for two characters and rest of the genotypes showed stable performance for one character over a range of environments under study. The cross Meera x RL13161 and RL15583 x KBA3 showed stable performance for seed yield and two crosses RL13161 x KBA3 and RL15583 x KBA3 showed stable performance for oil content and rest of four crosses showed stable performance for other characters.

GGE Biplot Analysis of Genotype X Environment Interaction and Yield Stability in Bambara Groundnut

In plant breeding and agricultural research, biplot analysis has become an important statistical technique. The goal of this study was to find the winning genotype(s) for the test settings in a part of the Southwest region of Nigeria, as well as to investigate the nature and extent of genotype X environment interaction (GEI) effects on Bambara groundnut (BGN) production. The experiment was carried out in four environments (two separate sites, Ibadan and Ikenne, for two consecutive years, 2018 and 2019) with ninety-five BGN accessions. According to the combined analysis of variance over environments, genotypes and GEI both had a substantial (p < 0.001) impact on BGN yield. The results revealed that BGN accessions performed differently in different test conditions, indicating that the interaction was crossover in nature. The results revealed that BGN accessions performed differently in different test conditions, indicating that the interaction was crossover in nature. To examine and show the pattern of the interaction components, biplots with the genotype main effect and genotype X environment interaction (GEI) were used. The first two PCs explained 80% of the total variation of the GGE model (i.e., G + GE) (PC1 = 48.59%, PC2 = 31.41%). The accessions that performed best in each environment based on the “which-won-where” polygon were TVSu-2031, TVSu-1724, TVSu-1742, TVSu-2022, TVSu-1943, TVSu-1892, TVSu-1557, TVSu-2060, and TVSu-2017. Among these accessions, TVSu-2017, TVSu-1557, TVSu-2060, TVSu-1892, and TVSu-1943 were among the highest-yielding accessions on the field. The adaptable accessions were TVSu-1763, TVSu-1899, TVSu-2019, TVSu-1898, TVSu-1957, TVSu-2021, and TVSu-1850, and the stable accessions were TVSu-1589, TVSu-1905, and TVSu-2048. In terms of discriminating and representativeness for the environments, Ibadan 2019 is deemed to be a superior environment. The selected accessions are recommended as parental lines in breeding programs for grain yield improvement in Ibadan or Ikenne or similar agro-ecological zones.

Evaluasi kegenjahan dan daya hasil jagung manis hibrida Indonesia menggunakan analisis GGE biplot pada lingkungan yang berbeda

AbstrakUji multilokasi merupakan fase yang penting dalam menyeleksi hibrida jagung yang stabil pada lingkungan yang luas dan menyeleksi hibrida superior untuk lokasi spesifik. Tujuan penelitian ini yaitu untuk mengetahui kegenjahan dan daya hasil hibrida Padjadjaran, serta menentukan interaksi genotip dengan lingkungan (G x E), stabilitas, dan adaptabilitas karakter kegenjahan hibrida Padjadjaran di tiga lokasi selama dua musim yang berbeda di Jawa Barat. Rancangan percobaan yang digunakan adalah Rancangan Acak Kelompok dengan delapan belas perlakuan yang terdiri dari enam belas hibrida Padjadjaran dan dua kultivar cek. Percobaan dilaksanakan selama dua tahun berturut- turut yaitu tahun ke-1 (Maret sampai Juli, 2014) dan tahun ke-2 (Maret sampai Juli, 2015) di tiga lokasi di Jawa Barat, yaitu: Jatinangor - Sumedang, Lembang - Kabupaten Bandung Barat, dan Wanayasa - Kabupaten Purwakarta. Uji lanjut yang digunakan untuk mengetahui perbedaan nilai rerata kegenjahan dan daya hasil digunakan analisis Duncan Multiple Range Test (DMRT), sedangkan untuk menentukan interaksi G x E, stabilitas, dan adaptabilitas menggunakan Genotype plus Genotype x Environment (GGE) biplot. Hasil memperlihatkan bahwa analisis GGE dapat menentukan interaksi G x E, stabilitas, dan adaptabilitas jagung manis hibrida Indonesia di Jawa Barat secara akurat. Model GGE disarankan untuk dapat digunakan sebagai aplikasi analisis untuk perilisan hibrida unggul di Indonesia oleh Kementerian Pertanian.Kata Kunci: Adaptabilitas, Interaksi G x E, kegenjahan, Stabilitas Abstract. Multi-environment testing is an important stage to select stable hybrid for broad environment and to select superior hybrid for a specific environment. To determined G x E (Genotype x Environment) interaction, stability and adaptability of Padjadjaran sweet corn in Indonesia, sixteen new Padjadjaran sweetcorn hybrids and two commercial hybrids were tested in three locations for two different seasons in West Java, Indonesia. Duncan multiple range was used to elaborate the difference between sweetcorn hybrids for short duration and yield, while Genotype plus Genotype x Environment (GGE) biplot analysis was used to determine G x E interaction, stability, and adaptability. Results showed that GGE analysis was accurately determined G x E interaction, stability, and adaptability of Indonesian sweet corn in West Java. The GGE model is suggested to implement as a tool for Ministry of Agriculture to release superior hybrid in Indonesia.Keywords: Adaptability, G x E interaction, Short duration, Stability