Yield Stability Analysis Research Articles

Adaptation and Grain Yield Stability Analysis of Winter Wheat Cultivars with and Without Fungicides Treatment from National Variety Trials in Sweden

Adaptation and Grain Yield Stability Analysis of Winter Wheat Cultivars with and Without Fungicides Treatment from National Variety Trials in Sweden

Deciphering Rice Genotypes Under Submergence Stress and Optimum Condition for Yield Stability Analysis

Deciphering Rice Genotypes Under Submergence Stress and Optimum Condition for Yield Stability Analysis

Genotype-Environment Interaction and Phenotypic Stability Analysis for Grain Yield of Durum Wheat in the Misurata Region

تهدف هذه الدراسة إلى تقييم التداخل بين التركيب الوراثي (GE)، والبيئة، وتحديد سلالات القمح الصلب (Triticum turgidum var. durum) المناسبة لإنتاج الحبوب في منطقة مصراتة - ليبيا. تم تقييم خمس عشرة سلالة، وصنف من القمح الصلب تحت الري التكميلي باستخدام تصميم القطاعات الكاملة العشوائية بثلاث مكررات. نفذت الدراسة لمدة 5 سنوات. وتم تحليل التداخل GE باستخدام تقنيات الانحدار الخطي. أوضحت النتائج وجود فروق معنوية عالية في صفة إنتاج الحبوب بين التراكيب الوراثية. أجري تقدير الثباتية وفقًا لتحليل الثبات باستخدام طريقة Eberhart، و Russell، كان التركيب الوراثي G9 هو الأكثر استقرارًا في صفة إنتاج محصول الحبوب. معامل الانحدار للسلالة G9 كان وحدة تقريبًا (bi = 1) وسجل أدنى انحراف عن معامل الانحدار (S2di) . في المقابل، أظهرت السلالات G10، و G3 معامل انحدار أكبر من 1.0، مما يشير إلى تأثرهما الكبير بالتغيرات البيئية لصفة محصول الحبوب. سجل أعلى محصول للسلالات G10، وG9بـ 3.65، و 3.19 طن/هكتار على التوالي متوسطا لكل البيئات. أظهرت السلالة G10 أعلى محصول للحبوب، ومعامل انحدار أكبر من الواحد، مما يشير إلى أنها حساسة للتغير البيئي، ويمكن التوصية بها تحت ظروف الزراعة المروية.

Genotypic × Environment Interaction and Stability Analysis for Bulb Yield and Yield Attributes in Onion (Allium cepa L.)

Genotypic × Environment Interaction and Stability Analysis for Bulb Yield and Yield Attributes in Onion (Allium cepa L.)

Stability analysis of yield and yield contributing traits in post rainy sorghum (Sorghum bicolor (l.) moench) mutant lines

Stability analysis of yield and yield contributing traits in post rainy sorghum (Sorghum bicolor (l.) moench) mutant lines

Stability Analysis of Yield and Its Components in Snap Melon (Cucumis melo var momordica)

Snap melon, scientifically known as Cucumis melo L. var. momordica (Roxb.), is a crop native to India and belonging to Cucurbitaceae family. This study was carried out to assess the nature and magnitude of genotype-environment interaction and stability among some parameters in snap melon genotypes. Twenty five local cultivars along with three standard checks were evaluated in randomized block design with three replications at three environments during summer 2023 at Navsari. The Eberhart and Russell model of stability analysis was employed which has been proved to be a reliable model. The study revealed that the mean sum of squares due to genotypes when tested against pooled deviation were highly significant for all the traits studied. Environment ´ Genotype (linear) showed significant differences for all characteristics except fruit weight and yield per vine, indicating that prediction could be possible by considering individual genotypes for these traits. A significant non-linear component (pooled deviation) was observed for fruit weight and fruit yield per vine, suggesting that genotypes varied considerably in terms of stable performance for these traits. The G ´ E interaction was only significant for flesh thickness and yield per vine, with all other traits being non-significant. The genotypes T 14 (HUB 18) and T 17 (HUB 21) were relatively stable and can be further used as parents to develop a more robust stable genotype. We identified genotypes which could pave way introducing high performing snap melon varieties.

Performance and yield stability of cayenne peppers (Capsicum frutescens) in multilocation trials in the Indonesian lowlands

Abstract. Sayekti TWDA, Syukur M, Hidayat SH, Maharijaya A, Sobir, Agustina K, Mareza E, Wahyudi A, Supriyanta B. 2024. Performance and yield stability of cayenne peppers (Capsicum frutescens) in multilocation trials in the Indonesian lowlands. Biodiversitas 25: 3008-3017. Cayenne pepper (Capsicum frutescens L.) plant breeding is becoming an increasingly interesting topic due to various usages. The diversity of uses of chilies needs to be balanced with high production and good product quality so that it can meet market needs. This experiment aimed to evaluate the performance and plant diversity of eight elite lines and six commercial varieties of cayenne pepper (C. frutescens) in three different environments. The development of location-specific superior genotypes can be guided to create varieties suited to the targeted environment. This study was conducted in three locations (environments) namely “Lampung”, “Yogyakarta” and “Palembang”. The experiment was conducted using a Randomized Complete Block Design (RCBD) with three replications for each location. Analysis of yield stability was conducted using three methods, namely “Francis-Kanneberg”, “Finlay-Wilkinson” and “AMMI” methods. Among the three locations, the Lampung location experienced a very significant yield loss. This is thought to be due to disease attacks on the plantations. Some genotypes are more suitable for planting at one of the test locations compared to the other two locations. However, there are two genotypes that are stable at three locations based on the three analysis methods used. Genotypes "F1.323340" and "F1.285290” were observed to be stable and produced well at all test locations. Both genotypes can be recommended for planting in lowland environment.

Application of AMMI and GGE biplot for genotype by environment interaction and yield stability analysis in potato genotypes grown in Dawuro zone, Ethiopia

The performance of most crop genotypes is greatly influenced by the interactions between genotype and environment. Providing information on well-adapted and high-yielding potato genotypes in a given environment is paramount for small-holder farmers to enhance their productivity. The study aimed to understand GEI effect on tuber yield, and identify and select widely or specifically adapted high-yielding potato genotypes for production. Eleven genotypes were evaluated using a randomized complete block design with three replications. The results of the AMMI analysis of variance showed that tuber yield significantly (p ≤ 0.05) influenced genotype-environment interaction. This reveals that genotypes exhibit varying mean performance in tuber yield across different environments. The sum squared results showed that genotype (62.40 %) and environment (26.73 %) were the main contributors to tuber yield variation, while the genotype-environment interaction effect (10.87 %) contributed least to then tuber yield total variation. The AMMI, GGE biplot, and GSI analysis revealed Gudanie and Gorebella as superior genotypes in tuber yield, demonstrating high mean performance across tested environments. Thus, Gudanie and Gorebella have been chosen as the most broadly adaptable genotypes for production in all potato-growing agroecologies in the Dawuro zone. The GGE and AMMI biplot provided the genotype-by-environment interaction association among environments and genotypes.

Genotype × environment interactions and stability analysis for grain yield in pearl millet [Pennisetum glaucum (L.) R. BR.]

Genotype × environment interactions and stability analysis for grain yield in pearl millet [Pennisetum glaucum (L.) R. BR.]

Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses

Bread wheat is a vital staple crop worldwide; including in Ethiopia, but its production is prone to various environmental constraints and yield reduction associated with adaptation. To identify adaptable genotypes, a total of 12 bread wheat genotypes (G1 to G12) were evaluated for their genotype-environment interaction (GEI) and stability across three different environments for two years using Additive Main Effect and Multiplicative Interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplots analysis. GEI is a common phenomenon in crop improvement and is of significant importance in genotype assessment and recommendation. According to combined analysis of variance, grain yield was considerably impacted by environments, genotypes, and GEI. AMMI and GGE biplots analysis also provided insights into the performance and stability of the genotypes across diverse environmental conditions. Among the 12 genotypes, G6 was selected by AMMI biplot analysis as adaptive and high-yielding genotype; G5 and G7 demonstrated high stability and minimal interaction with the environment, as evidenced by their IPCA1 values. G7 was identified as the most stable and high-yielding genotype. The GGE biplot's polygon view revealed that the highest grain yield was obtained from G6 in environment three (E3). E3 was selected as the ideal environment by the GGE biplot. The top three stable genotypes identified by AMMI stability value (ASV) were G5, G7, and G10, while the most stable genotype determined by Genotype Selection Index (GSI) was G7. Even though G6 was a high yielder, it was found to be unstable according to ASV and ranked third in stability according to GSI. Based on the study's findings, the GGE biplot genotype view for grain yield identified Tay genotype (G6) to be the most ideal genotype due to its high grain yield and stability in diverse environments. G7 showed similar characteristics and was also stable. These findings provide valuable insights to breeders and researchers for selecting high-yielding and stable, as well as high-yielding specifically adapted genotypes.

Characterization of High and Stable Yield Genotype for Maize based on Multivariate stability Analysis and Prediction of Crop Yield using Ensemble Learning Techniques

The production of maize globally surpassed the wheat and rice, because it is a staple crop in many regions of the world. Also, in addition to being directly consumed by people, maize is also used to make corn ethanol, animal food and several other products of maize, therefore the stability and high yield of maize is an extremely crucial part to promote long-term growth and food protection. This study looked at the effects of G ? E interaction on yield stability in 23 hybrids of maize in 53 distinct Indian environments. On the basis of analyses of variance, stability tests for multivariate stability parameters were carried out. In terms of all characteristics, the genotype and environment (G ? E interaction) differences were highly significant (p < 0.01), according to the pooled analysis of variance. A GGE biplot was created with the two principal components, which accounted for 66.02% and 8.51% variation in GEI for the corresponding yield per hectare. The GGE biplot and AMMI model exposed genotypes SYN916801, Bio 9682, DKC 9215, NMH 4313 as good with an indication of high mean yield and stability within the environment that were tested. By the results, we suggest breeding might boost output yield, and also the identified genotypes may be suggested for commercial farming. Also, for the creation of successful agricultural and food policy, reliable crop production estimates are essential. So, examinations were made on the machine learning techniques such as random forest and Gradient Boosting algorithm to predict crop yield responses in maize. While assessing statistical performance, GBM was found highly capable of predicting yield as compared to RF. Result showed that GBM is a good and adaptable machine learning technique for yield predictions.. KEYWORDS :Additive main effect and Multiplicative interaction, G ? E interaction, Machine learning techniques, Gradient boosting machine, Random forest.

Dissection of genotype x environment interaction and yield stability analysis in greengram (Vigna radiata L.) using AMMI and GGE biplot

Nineteen green gram [Vigna radiata (L.) Wilczek] genotypes were evaluated for yield stability under field conditions over three seasons. The AMMI analysis revealed that genotype TM 11007 (G3) had wider adaptation for grain yield, performing well across a wide range of environments. The genotypes TM 11038 (G14) in E1 and G3 in E2 and E3 were found to be highly stable and gave the highest yield in their respective mega-environments, while TM 11034 (G11) and TM 11042 (G17) located in the vertex performed better in all the three environments. E2 was the most discriminating test environment for selecting widely adapted genotypes for yield per se, while E3 was the most representative testing environment to provide unbiased information about the performance of genotypes. Based on the average versus stability graph, the genotype TM 11042 stands out because of simultaneous high yields and high stability.

Genotype × environment interactions and stability analysis for grain yield in pearl millet [Pennisetum glaucum (L.) R. BR.

Genotype × environment interactions and stability analysis for grain yield in pearl millet [Pennisetum glaucum (L.) R. BR.

Genotype by Environment Interaction and Stability Analysis for Yield of Chili Pepper (Capsicum annuum L.) in East Hararghe, Ethiopia

Genotype by Environment Interaction and Stability Analysis for Yield of Chili Pepper (Capsicum annuum L.) in East Hararghe, Ethiopia

Genotype x Environment Interaction and Grain Yield Stability Analysis of Soybean (Glycine max (L.) Merrill) Genotypes in Western Ethiopia

Genotype x Environment Interaction and Grain Yield Stability Analysis of Soybean (Glycine max (L.) Merrill) Genotypes in Western Ethiopia

Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters

Rice (Oryza sativa L.) is an important member of the family Poaceae and more than half of world population depend for their dietary nutrition on rice. Rice cultivars with higher yield, resilience to stress and wider adaptability are essential to ensure production stability and food security. The fundamental objective of this study was to identify higher-yielding rice genotypes with stable performance and wider adaptability in a rice growing areas of Pakistan. A triplicate RCBD design experiment with 20 Green Super Rice (GSR) advanced lines was conducted at 12 rice growing ecologies in four Provinces of Pakistan. Grain yield stability performance was assessed by using different univariate and multivariate statistics. Analysis of variance revealed significant differences among genotypes, locations, and G x E interaction for mean squares (p < 0.05) of major yield contributing traits. All the studied traits except for number of tillers per plant revealed higher genotypic variance than environmental variance. Broad sense heritability was estimated in the range of 44.36% to 98.60%. Based on ASV, ASI, bi, Wi2, σ2i and WAAS statistics, the genotypes G1, G4, G5, G8, G11 and G12 revealed lowest values for parametric statistics and considered more stable genotypes based on paddy yield. The additive main effects and multiplicative interaction (AMMI) model revealed significant variation (p < 0.05) for genotypes, non-signification for environment and highly significant for G × E interaction. The variation proportion of PC1 and PC2 from interaction revealed 67.2% variability for paddy yield. Based on ‘mean verses stability analysis of GGE biplot’, ‘Which-won-where’ GGE Biplot, ‘discriminativeness vs. representativeness’ pattern of stability, ‘IPCA and WAASB/GY’ ratio-based stability Heat-map, and ranking of genotypes, the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 were observed ideal genotypes with yield potential more than 8 tons ha−1. Discriminativeness vs. representativeness’ pattern of stability identifies two environments, E5 (D.I Khan, KPK) and E6 (Usta Muhammad, Baluchistan) were best suited for evaluating genotypic yield performance. Based on these findings we have concluded that the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 could be included in the commercial varietal development process and future breeding program.

Genotype x Environment Interaction and Grain Yield Stability Analysis of Soybean (Glycine max (L.) Merrill) Genotypes in Western Ethiopia

Genotype x Environment Interaction and Grain Yield Stability Analysis of Soybean (Glycine max (L.) Merrill) Genotypes in Western Ethiopia

Stability analysis for yield attributing traits and total alkaloid content in ashwagandha (Withania somnifera L.)

Stability analysis for yield attributing traits and total alkaloid content in ashwagandha (Withania somnifera L.)

Stability analysis of yield and its component traits in bread wheat (Triticum aestivum L.)

Stability analysis of yield and its component traits in bread wheat (Triticum aestivum L.)

Analysis of Yield Stability in Diverse Rice Genotypes

Aims/ objectives: This study aims to improve stable and sustainable rice varieties adaptable to changing climatic conditions. It involves assessing genetic variability and Genotype X Environment interaction (G x E) among 186 diverse rice genotypes. The goal is to select genotypes with high breeding value, contributing to the development of rice varieties well-suited to varying climatic conditions. Study Design: The study employed an augmented design in a Randomized Complete Block Design (RCBD). Swarna, Madhuraj-55, Safri-17, Improved Samba Mahsuri, Thavalkannan, and IR64 checks were replicated across environments. Place and Duration of Study: The study took place in College of Agriculture, Raipur, IGKV over two years (wet season-2020 and 2021). Methodology: Analysis of genetic variability and G X E interaction among 186 rice genotypes. Execution of the experiment in an augmented design with a randomized complete block design. Replication of standard rice checks across different environments. Assessment of yield-attributing traits such as plant height, number of effective tillers, panicle length, number of grains per panicle, biological yield per plot, and grain yield. Evaluation of stability was done using univariate (Shukla stability variance, Wricke’s ecovalence, Kang stability statistic) and multivariate (AMMI yield stability index and GGE biplot) stability parameters. Selection of stable genotypes with high yield based on stability analyses. Results: Significant phenotypic variation was observed in yield-attributing traits across seasons. Genetic variability and G x E interaction effect demonstrated by variable genotype performance across environments. Univariate and multivariate stability parameters (S2i, W2i, KSi, AMMI stability value, GGE biplot) were used for stability analyses. Identification of stable genotypes with high yield across environments, including IR13f167, ARC13156, IR93354, F50, Ngalongyi, Giza 178, Arc 10159, Sadajira 19-317, Arith, IR 57920-Ac 25-2-B, Pesagro 102, Mekenzie small, Nasaenge, Kula Karuppan, Vary Gony, MR 69, Kanu Dam, IRRI 123, Sativa IRGC17083-1, Kalia, and Swarna. Conclusion: The study concludes that stability in genotype performance across diverse environments is crucial for the development of sustainable rice varieties. Genotypes with high stability and yield, as identified through stability analyses, hold potential breeding value for developing rice varieties adaptive to climate change. The stable genotypes listed, including IR13f167, ARC13156, IR93354, and others, are recommended for further breeding and development efforts to enhance rice productivity and adaptability.