Parametric and nonparametric measures of phenotypic stability in linseed (Linum usitatissimum L.)

A combined analysis with three parametricand two nonparametric measures to assess G × E interactions and stability analyses toidentify stable genotypes of linseed across18 environments in Ethiopia wereundertaken. The combined analysis ofvariance for environments (E), genotypes(G) and G × E interaction was highlysignificant (p<0.01), suggestingdifferential responses of the genotypes andthe need for stability analysis. Theparametric stability measures ofcoefficient of variability and thestability variance showed that R12-N10D wasthe most stable genotype, whereascultivars' superiority measure indicatedChilalo to be the most stable cultivar.Like most of the parametric methods, thenon-parametric measures revealed thatR12-N10D had the smallest changes in ranksand thus was the most stable genotype incontrast to R12-D24C, which was unstableand the lowest yielder. A comparison of thefive stability measures showed that thecoefficient of variability, stabilityvariance and variance of ranks were similarin assessing the relative stability of thegenotypes, whereas cultivars' superioritymeasure deviated from the others. Thestability variance and variance of rankswere significantly rank correlated, andwere the best in determining thecomparative stability of linseed genotypes.The coefficient of variability was alsorelatively better than the cultivar'ssuperiority measure. Further studies ofrepeatability tests are, however, needed todetermine the best methods. The stabilitystatistics generally identified R12-N10D,followed by Chilalo, as the most stablevarieties, whereas R12-D24C and R11-M20Gwere the least stable varieties.     

Durum wheat varieties in N‐deficient environments and organic farming: a comparison of yield,quality and stability performances

Stability and reliability of yield and quality for 15 durum wheat genotypes (old and modern) were evaluated in a 5‐year experiment (southern Italy) in organic farming. Genotypes were grown at two N levels (0 and 80 kg/ha), with the aim of evaluating ‘genotype × environment’ (GE) interactions and their role on genotype selection in N‐limited environments. Several approaches to stability were used, within the frame of mixed models and additive main effects and multiplicative interaction analysis, and their validity in stressful conditions and organic farming was discussed. Especially for protein and gluten content, results indicate high environmental variability and the presence of crossover ‘N × environment’ interactions, which supports the need for specific breeding programmes in N‐deficient environments. The average response was strongly affected by N availability (on average, yield was 2.95 and 3.42 t/ha, protein content was 11.6% and 12.85%, gluten content was 8.55% and 9.92%, respectively, at 0 and 80 kg N/ha), and few genotypes gave high yield and quality at both fertilization levels. Only ‘Gargano’ and ‘Fortore’ showed a good inter‐year stability at both N levels. The old cultivars gave minimal responsiveness to increased N input, but gave good results in limiting conditions, indicating that they may play a role in organic farming.     

Nonparametric phenotypic stability analysis in advanced barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) genotypes

The development of genotypes with adaptation to a wide range of environments is one of the most important goals of plant breeding programs. In order to compare nonparametric stability measures and to identify promising high-yield and stable barley (Hordeum vulgare L.), 20 barley genotypes selected from the Iran/ICARDA joint project and grown in nine environments during 2009-11 in Iran. Four nonparametric statistical tests of significance for genotype × environment (GE) interaction and 10 nonparametric measures of stability were used to identify stable genotypes in nine environments. Results of nonparametric tests of G×E interaction (Kubinger, Hildebrand, and Kroon/ Laan) and a combined ANOVA across environments, indicated the presence of both crossover and non-crossover interactions. Also, only TOP and rank-sum values were positively associated with high yield. Thus, in the simultaneous selection for high yield and stability, only the rank-sum and TOP methods were useful in terms of the principal component analysis results, and correlation analysis of nonparametric stability statistics and yield. According to these stability parameters (TOP and rank-sum), three genotypes (G13, G12, and G17) were the most stable for grain yield. The results also revealed that based on nonparametric test results, stability could be classified into three groups, according to agronomic and biological concepts of stability.     

The Physiology and Stability of Leaf Carbon Isotope Discrimination as a Measure of Water‐Use Efficiency in Barley on the Canadian Prairies

Temporal and seasonal water deficit is one of the major factors limiting crop yield on the Canadian prairie. Selection for low carbon isotope discrimination (Δ¹³C) or high water‐use efficiency (WUE) can lead to improved yield in some environments. To understand better the physiology and WUE of barley under drought conditions on the Canadian prairie, 12 barley (Hordeum vulgare L.) genotypes with contrasting levels of leaf Δ¹³C were investigated for performance stability across locations and years in Alberta, Canada. Four of those genotypes (‘CDC Cowboy’, ‘Niobe’, ‘170011’ and ‘Kasota’) were also grown in the greenhouse under well‐watered and water‐deficit conditions to examine genotypic variations in leaf Δ¹³C, WUE, gas exchange parameters and specific leaf area (SLA). The water‐deficit treatment was imposed at the jointing stage for 10 days followed by re‐watering to pre‐deficit level. Genotypic ranking in leaf Δ¹³C was highly consistent, with ‘170011’, ‘CDC Cowboy’ and ‘W89001002003’ being the lowest and ‘Kasota’‘160049’ and ‘H93174006’ being the highest leaf Δ¹³C. Under field and greenhouse (well‐watered) conditions, leaf Δ¹³C was significantly correlated with stomatal conductance (g_s). Water deficit significantly increased WUE, with ‘CDC Cowboy’– a low leaf Δ¹³C genotype with significantly higher WUE and lower percentage decline in assimilation rate (A) and g_s than the other three genotypes (‘Niobe’, ‘170011’ and ‘Kasota’). We conclude that leaf Δ¹³C is a stable trait in the genotypes evaluated. Low leaf Δ¹³C of ‘CDC Cowboy’ was achieved by maintaining a high A and a low g_s, with comparable biomass and grain yield to genotypes showing a high g_s under field conditions; hence, selection for a low leaf Δ¹³C genotype such as ‘CDC Cowboy’ maybe important for maintaining productivity and yield stability under water‐limited conditions on the Canadian prairie.     

Genotype-Environment Interactions and Stability Analysis for Herbage and Seed Yields of Forage Peas Under Rainfed Conditions

Twenty-five genotypes of forage peas (Pisum sativum L.) were evaluated under rainfed conditions for two years at four locations in Syria and one in Lebanon. Since local climatic variation is significant, each location in each year was treated as a separate environment, to give ten environments. Genotype-environment interactions (GXE) were analysed using linear regression techniques. There was considerable variation in herbage and seed yields within both genotypes and environments. Genotype-environment interactions were present for both herbage and seed yields; a large proportion of these interactions was accounted for by the linear regression. Although the non-linear component was also significant, its magnitude was smaller than that of the linear component. The highest and most stable herbage yields were obtained from accessions 46/61, 135/175, 3211/323, 99/103 and 88/335. The highest and most stable seed yields were produced by accessions 4/166, 2428/240, 424/242 and 88/335. Accession 88/335 from Germany, F.R. was the only genotype to combine high herbage and seed yields with wide adaptation and stability and could thus be considered the most widely adapted genotype. Other stable genotypes were identified as suitable for poor environments. Yield of the locally collected genotype, though often high, was found to be unstable. The importance of genotype-environment interactions in future breeding strategies is discussed.     

Interpreting genotype × environment interactions for durum wheat grain yields using nonparametric methods

The objective of this study was to compare nonparametric stability procedures and apply different nonparametric tests for genotype × environment (G × E) interactions on grain yields of 15 durum wheat genotypes selected from Iran/ICARDA joint project grown in 12 environments during 2004–2006 in Iran. Results of nonparametric tests of G × E interaction and a combined ANOVA across environments indicated the presence of both crossover and noncrossover interactions, and genotypes varied significantly for grain yield. In this study, high values of TOP (proportion of environments in which a genotype ranked in the top third) and low values of sum of ranks of mean grain yield and Shukla’s stability variance (rank-sum) were associated with high mean yield. The other nonparametric stability methods were not positively correlated with mean yield but they characterized a static concept of stability. The results of correlation analysis indicated that only TOP and rank-sum methods would be useful for simultaneous selection for high yield and stability. These two methods identified lines Mrb3/Mna-1, Syrian-4 and Mna-1/Rfm-7 as genotypes with dynamic stability and wide adaptation. According to static stability parameters, the genotypes 12A-Mar8081 and 19A-Mar8081 with lowest grain yield were selected as genotypes with the highest stability.     

Environmental and genetic determination of protein content and grain yield in durum wheat under Mediterranean conditions

The unpredictability of the Mediterranean climate causes fluctuations in wheat yield and quality, but offers the opportunity for obtaining high‐quality durum wheat in terms of grain protein content. Twenty‐five durum wheat genotypes were grown under irrigated and rainfed conditions at each of two latitudes in Spain during 1998 and 1999. Differences between latitudes in grain protein content and chlorophyll content in the flag leaf were attributable to nitrogen fertilization management. Cycle length until anthesis was less affected by the environment than grain‐filling duration, and was longer under irrigated conditions than in the rainfed sites. A negative asymptotic curve was the best equation to fit the relationship between yield and protein content, suggesting that yield improvements in fertile environments may be attained with negligible reductions in protein content. ‘Jabato’, ‘Waha’, ‘Lagost‐3’, ‘Massara‐1’ and ‘Vit?on’ showed medium to high yield, yield stability and high protein content. Chlorophyll content in the flag leaf, measured at anthesis with the soil‐plant analysis development (SPAD) portable field unit, may be useful for the fast and cheap detection of durum wheat genotypes with high grain protein content in drought‐stressed Mediterranean environments.     

Stability and Adaptability of Cultivars in Non-balanced Yield Trials. Comparison of Methods for Selecting 'High Oleic' Sunflower hybrids for Grain Yield and Quality

The best‐yielding and most stable cultivars are identified by growing cultivars in different environments. The stability of grain‐quality traits has been less thoroughly investigated than the stability of grain yield. High‐oleic hybrids of sunflower have been available on the Argentinian seed market for several years. Research on the stability of these genotypes is scarce. The objectives of this work were (i) to compare, using three different methods, the stability and adaptability of high‐oleic hybrids for grain yield and oil and oleic acid contents, and (ii) to explore the advantages and disadvantages of each method in selecting stable or adapted genotypes with high grain yield and high quality. Stability and adaptability analyses were performed on results for grain yields and oil and oleic acid contents of 35 high‐oleic sunflower hybrids from 17 comparative yield trials conducted over 2 years in Argentina. Stability was estimated using two methods: Fisher's protected least significant difference (LSD) test, which compared hybrids with the best‐yielding hybrid in each environment, and the test of relative yield (RY), which uses standard deviation as the measure of stability. Adaptability was estimated using Piepho's method of ‘multiple comparisons with the best’. These three methods can be applied to unbalanced data. Piepho's method made little discrimination amongst the hybrids. The LSD and RY tests coincided in classifying the hybrids as stable and unstable in 85 % of cases for grain yield and 76 % for oil content. It is concluded that the most convenient method depends on characteristics of the experimental design and of variability of the evaluated trait. Results from the LSD test depend on the number of environments in which the cultivar is tested. The RY method is valuable for classifying some cultivars as high‐yielding and stable, avoiding the problem of high‐yielding environments biasing the general average. Use of both methods together could be effective for classifying hybrids when the number of environments is adequate.     

Response of Sericea Lespedeza Genotypes Low in Tannins to Different Environments

Transfer of the low-tannin trait to otherwise desirable sericea lespedeza high-tannin lines produced genotypes with considerably lowered forage yield. It is not known if low-tannin sericeas are proportionally less productive than high-tannin sericeas in high-yielding environments. If so, low-tannin sericeas would be less desirable to grow in more productive environments. Regression analysis was used to partition GE interactions between regressions and the residuals after regression, and to measure the response to changing environments, Shukla 's stability-variance parameters were used to measure genotype stability. Variance and coefficient of variation were calculated across environments for each genotype and rank correlated to the aforementioned parameters of stability to determine their usefulness in the early stages of cultivar testing. Stability analysis was carried out on the dry forage yield of 10 genotypes grown in 10 environments in Alabama. The only low-tannin genotype that consistently responded to environmental fluctuations like ‘Serala’ was 74-100-5. Low-tannin sericeas were found to be proportionally less productive than high-tannin sericeas in high-yielding environments. However, it is possible to select low-tannin lines with an environmental response similar to high-tannin sericeas. Rank correlations among stability parameters indicated that EV is a stability parameter which is easy to calculate and could be used in the early stages of cultivar testing.     

Nitrogen and phosphorus uptake and utilization efficiency in D(R) substitution lines of hexaploid triticale

Two sets of disomic substitution lines, derived from the cultivars ‘Presto’ and ‘Rhino’ of triticale, with rye chromosome pairs replaced by their wheat D‐genome homoeologues, were tested in hydroponic culture for nitrogen and phosphorus uptake and utilization efficiency. The effect of a substitution on the amount of absorbed nutrients was predominantly negative and proportional to the effect on plant dry matter. Significant decreases were found for the substitutions 5D(5R), 6D(6R) of both cultivars, 2D(2R), 4D(4R) of ‘Presto’ and 3D(3R) of ‘Rhino’. On the other hand, the nitrogen utilization efficiency was significantly increased in all substitution lines, with the exception of the 1D(1R) ones. The differences in phosphorus utilization were generally positive, but less pronounced, and significant only in the lines 2D(2R) and 6D(6R). The data suggest that presence of both rye and D‐genome chromosomes is conducive for the best effect of the applied N and P fertilizers.     

Dissection of genetic variance of fibre quality in advanced generations from an interspecific cross of Gossypium hirsutum and G. barbadense

The interspecific genetic introgression approach has been shown to facilitate the detection and dissection of quantitative trait loci (QTL). A population consisting of 121 F₆ recombinant inbred lines was developed by crossing Gossypium hirsutum cv. ‘Handan 208’ and G. barbadense cv. ‘Pima 90’ via single‐seed descent. Genotyping indicated that the mean ‘Pima 90’ allele frequency at each locus was 21%. Phenotyping and phenotypic distribution indicated a trend of return of individual lines’ characters to ‘Handan 208’ coupled with a wide variance for each trait. Significant loci influencing fibre quality were detected by one‐way analysis of variance (anova; P < 0.005) and association analysis [?log₁₀(P) ≥ 3]: five and three markers for fibre length, four and one marker(s) for uniformity, two and one marker(s) for micronaire, 13 and 15 markers for strength, six and 10 markers for elongation, respectively. Two‐way anova based on genotypes of all marker loci combination showed that 807 two‐locus combinations were significant, and two‐way anova based on marker genotypes of QTL markers combination showed five significant digenic interactions (P < 0.01).     

Classification of Global Environments and Cultivars of Spring Barley Based on Heading Time Interactions

Global heading time data collected by the International Center for Maize and Wheat Improvement (CIMMYT) during the International Barley Yield Trials were used to assess similarity of environments, variation among cultivars, and genotype × environment interactions. Data for 29 spring barley cultivars grown in 89 environments over three years were analyzed by cluster analysis. The deviation m days to heading of the mean of 28 photoperiod sensitive cultivars from the cultivar ‘Mona’ and the mean of ‘Mona’, homozygous recessive for the ea_k gene conferring photoperiod insensitivity and thermal stability, were used as environmental coordinates. In addition, diversity of heading time responses among genotypes was illustrated by differences among overall means and patterns of deviation for days to heading from ‘Mona’ in selected environments. Three main clusters were identified. Mexican environments were similar to warmer Mediterranean, eastern and southern African, West Asian, and Latin American environments. Heading time responses in Syria were similar to those observed m other cool Mediterranean environments. Early heading cultivars exhibited greater variation for heading response, especially in extremely warm-and equaiorial- short daylength environments, com-pared to late heading cultivars, presumably because of larger photothermal × genotype interactions. Photoperiod flux about the winter solstice appeared to be a major environmental cue for heading time in photoperiod sensitive spring barleys.     

Hexaploid triticales from hybrids of 'Langdon' durum D-genome substitutions with 'Gazelle' rye

The formation of unreduced gametes in some hybrids between disomic D‐genome substitutions (DS) of durum wheat cv.‘Langdon’ and rye provides a convenient approach for the rapid introduction of D‐genome chromosomes into hexaploid triticale. Meiotic pairing at metaphase I and seed fertility in spontaneous and colchicine‐induced amphidiploids derived from F₁ hybrids between a set of ‘Langdon’ DS and ‘Gazelle’ rye were analysed. The purpose was to determine the effects of the substitution of D‐genome chromosomes for their A‐ and B‐genome homoeologues on hexaploid triticale and to select stable disomic D‐genome substitutions of hexaploid triticale. The results showed that the disomic substitutions with D‐genome slightly increased the frequency of univalents (1.0‐3.13) compared with the ‘Langdon’ control primary hexaploid triticale (0.76). Substitutions 2D(2A) and 3D(3B) were partly desynaptic. The substitutions 1D(1A), 1D(1B) and 7D(7B) exhibited high seed fertility but the others had decreased fertility. Except for 2D(2A), 5D(5A), 3D(3B) and 5D(5B), 10 of the 14 possible hexaploid triticale D‐genome disomic substitutions have been obtained. The results suggest that the poor compensation ability of some D‐genome chromosomes for their homoeologous A‐ and B‐genome chromosomes is a major factor affecting meiotic stability and fertility in the hexaploid triticale D‐genome substitutions.     

Dissection of genetic architecture for oil content in soybean seed using two backcross populations

Soybean seed oil was valued in foods, animal feed and some industrial applications. Molecular marker‐assisted selection (MAS) for high‐oil‐content cultivars was an important method for soybean breeders. The objective of this study was to identify quantitative trait loci (QTL) and epistatic QTL underlying the seed oil content of soybeans across two backcross (BC) populations (with one common male parent ‘Dongnong47’) and two different environments. Two molecular genetic maps were constructed. They encompassed 1046.8 cM [with an average distance of 6.75 cM in the ‘Dongnong47’  ×  ‘Jiyu89’ (DJ) population] and 846.10 cM [with an average distance of 5.76 cM in the ‘Dongnong47’  ×  ‘Zaoshu18’ (DZ) population]. Nine and seven QTL were identified to be associated with oil content in the DJ and DZ populations, respectively. The phenotypic variation explained by most of the QTL was usually less than 10%. Among the identified QTL, those stable ones across multiple environments and populations often had stronger additive effects. In addition, three stable QTL in the DZ populations were identified in the similar genomic region of the three QTL in the DJ population [qDJE and qDZE‐1 were located near Satt151 of Chromosome 15 (Chr15), qDJA1 and qDZA1 were located near Satt200 of Chr15 (LG A1), and qDJD2‐1 and qDZD2‐1 were located near Sat365 of Chr17]. In conclusion, MAS will be able more effectively to combine beneficial alleles of the different donors to design new genotypes with higher soybean seed oil content using the BC populations.     

Genotype × environment interactions for seed yield in rainfed winter safflower (Carthamus tinctorius L.) multi-environment trials in Iran

Evaluation of genotype × environment interaction (GEI) is an important component of the variety selection process in multi-environment trials. The objectives of this study were first to analyze GEI on seed yield of 18 spine safflower genotypes grown for three consecutive seasons (2008–2011) at three locations, representative of rainfed winter safflower growing areas of Iran, by the additive main effects and multiplicative interaction (AMMI) model, and second to compare AMMI-derived stability statistics with several stability different methods, and two stability analysis approaches the yield-stability (Ysi) and the GGE (genotype + genotype × environment) biplot that are widely used to identify high-yielding and stable genotypes. The results of the AMMI analysis showed that main effects due to genotype, environment, and GEI as well as first six interaction principle component axes (IPCA1 to 6) were significant (P < 0.01). According to most stability statistics of AMMI analyses, genotypes G5 and G14 were the most stable genotypes across environments. According to the adjusted stability variance (s²), the high-yielding genotype, G2, was unstable due to the heterogeneity caused by environmental index. Based on the definition of stable genotypes by regression method (b = 1, S _d ²  = 0), genotypes G11, G9, G14, G3, G12 and G13 had average stability for seed yield. Stability parameters of Tai indicated that genotype G5 had specific adaptability to unfavorable environments. The GGE biplot and the Ysi statistic gave similar results in identifying genotype G2 (PI-209295) as the best one to release for rainfed conditions of Iran. The factor analysis was used for grouping all stability parameters. The first factor separated static and dynamic concepts of stability, in which the Ysi and GGED (i.e., the distance from the markers of individual genotypes to the ideal genotype) parameters had a dynamic concept of stability, and the other remaining parameters had static concept of stability.     

Genotype by environment interactions (GEIs) for barley grain yield under salt stress condition

Changes in the relative genetic performance of genotypes across environments are referred to as genotype × environment interactions (GEIs). GEIs can affect barley breeding improvement for salt tolerance because it often complicates the evaluation and selection of superior genotypes. The present study evaluated the GEIs over 60 barley genotypes for yield components and grain yield in six salinity environments in North Delta, Egypt. Data were analyzed using the additive main effects and multiplicative interaction (AMMI) and Tai’s stability parameters. GEIs effects on yield explained 20.3, 20.1, 14.6, and 33.0% of the total variation besides, the first two principal components account for 67.3, 56.3, 64.3, and 83.7% of the explained variance in the four sets, respectively. Six genotypes namely G-4, G-7, G-20, G-34, G-36, and G-39 were found to be most stable and high yielding across environments (GY >2.00 t ha^-1), and located close to zero projection onto the AEC ordinate. Tai’s stability parameters demonstrated that these genotypes were more responsive to the environmental changes. The genotypes G-50 and G-53 showed perfect/static stability (α = -0.95, -0.91, respectively). In contrast, the genotype; G-36 had α = 0 and λ = 1.10, indicating parallel with the environmental effects followed by G-44. Overall, we found that GEIs for grain yield are highly significant in all sets, suggesting that responded differently across environments. This interaction may be a result of changes in genotypes’ relative performance across environments, due to their differential responses to various abiotic factors.     

Yield stability studies of soybean (Glycine max (L.) Merrill) under rhizobia inoculation in the savanna region of Nigeria

Soybean (Glycine max (L.) Merrill) production is expanding into temperate and tropical environments. Yield stability studies under rhizobia inoculation were investigated in 24 soybean genotypes over two successive growing seasons at three agro‐ecological zone of Nigeria, during the 2015–2016 rainy seasons. Treatments were arranged in a split‐plot design and replicated three times. Treatments were 24 soybean genotypes and three levels of rhizobia inoculation. Results indicated that the variation of genotypes and inoculation on percentage emergence, height, number of leaves, number of branches per plant, total biomass yield, above‐ground biomass and seed yield was significant (p = .05). The effects of genotypes (G), environment (E) and G × E interactions on seed yield were also significant. Two soybean genotypes (TGx 1989‐45F and TGx 1990‐110FN) were identified as the most promising in relation to yield stability. Of the three locations, Abuja produced the least interaction effects followed by Igabi and may be most appropriate environments for large‐scale soybean production. Appropriate inoculation of soybean with inoculants (LegumeFix and or NoduMax) should be encouraged in farmer's field.     

Mapping QTL involved in adult plant resistance to powdery mildew in the winter wheat line RE714 in two susceptible genetic backgrounds

The objective was to study the genetic basis of adult plant resistance to powdery mildew of the winter wheat line RE714 by quantitative trait loci (QTL) analysis and to investigate the stability of the QTL detected in two different genetic backgrounds. Two DH populations from the crosses between RE714 and the susceptible parents ‘Festin’ and ‘Hardi’ were used. Reaction of the DH lines to powdery mildew was assessed in different environments in Belgium under natural disease infection. Considering both populations and according to the environment tested, one to seven QTL were detected. Among them, residual effects of the race‐specific resistance genes Pm4b and MIRE were found. Two major QTL were very stable (on chromosome 5D and at the MIRE locus), since they were detected in both populations and over all environments tested. The QTL detected varied according to the susceptible parent used, and a residual effect at the Pm4b gene was not observed with the genetic background of ‘Hardi’.     

Analysis of genotype-by-environment interaction for grain yield of rainfed durum wheat genotypes in warm winter areas of Iran

This study was performed for pattern analysis of genotype-by-environment (GE) interaction on 20 durum wheat genotypes grown in 15 testing environments during 2004–06 in Iran. Combined analysis of variance showed significant genotypes (G), environments (E), and GE interactions (P < 0.01), with environmental main effects being the predominant source of variation, followed by GE interaction. The results showed various patterns of genotype responses to different environment groups and assisted in structuring the durum wheat testing locations with identification of two major-environment groups with high genotype discrimination ability. The locations (Gachsaran and Ilam) corresponding to warm and semi-arid aresa were similar in genotype discrimination and showed no association with the other testing locations (Gonbad, Moghan, and Khoramabad) representing the Mediterranean area, indicating they differ in rankings of genotypes. The top-yielding genotypes, G13, G14 and G9, were highly adapted to warm and semi-arid environments, but those corresponding to the Mediterranean area had a high ability to discriminate the genotypes G16, G11, and Saimareh. The stability and adaptability of specific genotypes were assessed by plotting their nominal grain yields at specific environments in an ordination biplot, which aided in the identification of environment groups. Appropriate check genotypes for all environments or for specific environments were also identified. Pattern analysis allowed a sensible and useful summarization of GE interaction data set and helped to facilitate selecting superior genotypes for target-growing sites.     

Assessment of genotype × environment interactions for yield and fiber quality in cotton performance trials

Plant breeding programs involving a wide range of crop plants routinely practice selection (directly or indirectly) for genotypes that display stability for a given trait or set of traits across testing environments through the genotype evaluation process. Genotype stability for trait performance is a direct measure of the presence and effect of genotype × environment interactions, which result from the differential performance of a genotype or cultivar across environments. The genotype evaluation process also requires selection of the proper field trial locations that best represent the target environments the breeding program is directed toward. In this study, we assessed the extent to which genotype × environment interactions affected agronomic performance (lint yield, gin turnout) and fiber quality (fiber length, fiber strength, uniformity index, micronaire, fiber elongation) in a series of cotton (Gossypium hirsutum) performance trials in 12 location–year environments in South Carolina. Genotype × environment interactions affecting lint yield were larger in higher yielding environments, while interactions for fiber strength were greater for genotypes with lower mean fiber strength values. Two regions within the South Carolina cotton production areas were identified as proper testing locations for lint yield performance, while testing for fiber strength can be accomplished in any location within the statewide cotton production areas. The U.S. Government's right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.