multivariate ANOVA option of PROC GLM. Broad-sense heritability ( H ) of the trait was estimated by the entry mean basis ( Nyquist, 1991 ) as follows: where H represents the heritability, is genetic variance, is genotype-by-environment variance, is
Dilip R. Panthee, Chunxue Cao, Spencer J. Debenport, Gustavo R. Rodríguez, Joanne A. Labate, Larry D. Robertson, Andrew P. Breksa III, Esther van der Knaap, and Brian B. McSpadden Gardener
Shuyin Liang, Xuan Wu, and David Byrne
transformed data ( Razali and Wah, 2011 ). Correlation coefficients of all six components were generated from Pearson product-moment correlation analysis. Two-way factorial ANOVA was conducted to compare among the population and seasonal means as well as to
Richard P. Marini
Experiments with perennial crops often span several years, and a response variable may be measured on the same plant at several points in time. Such data are often analyzed as a split-plot design, taking time as the split-plot factor. In other cases, separate analyses are performed for each time. The mathematical conditions required for validity of these types of analyses might not hold because measurements repeated on the same plant are not independent. Annual trunk cross-sectional-area (TCSA) measurements from a peach tree training experiment will be used to compare two methods of analyses. The 6-year experiment was a factorial of two heading heights at planting (low vs. high) and two tree forms (central leader vs. open vase). Univariate analysis of variance (ANOVA) and a multivariate repeated measures analysis (MANOVA) was performed. Main effects and interactions were more often significant with ANOVA than with MANOVA. ANOVA performed each year inflated the probability of falsely rejecting a true null hypothesis (Type I error), and was not appropriate for this data set.
Khalid E. Ibrahim, Kanta Kobira, and John A. Juvik
Genotype-by-environment interaction (G×E) is a fundamental concern in plant breeding since it hinders developing genotypes with wide geographical usefulness. Analysis of variance (ANOVA) has been widely used to interpret G×E, but it does not elucidate the nature and causes of the interaction. Stability analysis provides a summary of the response patterns of genotypes to different growing environments. Two classes of phytochemicals with putative health promoting activity are carotenoids and tocopherols that are relatively abundant in broccoli. Growing clinical and epidemiological evidence suggests that vegetables with enhanced levels of these phytochemicals can reduce the risk of cancer, cardiovascular, and eye diseases. The objective of this study is to have better understanding of the genetic, environmental and G×E interaction effects of these phytochemicals in broccoli to determine the feasibility of the genetic enhancement. The ANOVA and Shukla's stability test were applied to a set of data generated by the HPLC analysis of different carotenoid and tocopherol forms for six broccoli accessions grown over three environments. The ANOVA results show a significant G×E for both phytochemicals that ranged from 22.6% of the total phenotypic variation for beta-carotene to 54.0% for delta-tocopherol while the environmental effects were nonsignificant. The genotypic effects ranged from as low as 1% for alpha-tocopherol to 31.5% and 36.0% for beta-carotene and gamma-tocopherol, respectively. Stability analysis illustrated that the most stable genotype for all phytochemicals is Brigadier. The results suggest that feasibility of the genetic enhancement for major carotenoids and tocopherols. A second experiment that includes a larger set of genotypes and environments was conducted to confirm the results of this study.
Felix C. Serquen, J. Bacher, and J. Staub
Linkage maps in cucumber have been constructed in broad and narrow genetic base populations, using mostly RFLPs. RAPD markers are believed to be more advantageous than RFLPs for mapping in narrow crosses. An F3 population derived from F2 intercrossing cucumber inbred lines (G421 and H19) was used to construct a linkage map and to perform QTL analysis for horticultural traits recorded in two locations. One hundred three F3 families were used for mapping purpose. The parents were screened using ≈1500 primers yielding 80 RAPD markers that exhibited expected 3:1 Mendelian segregation. Additionally, female sex expression (F), little leaf (l), and determinate (de) loci also were evaluated in the segregating population. The linkage analysis and mapping was performed with MAPMAKER software, using a LOD score of 3.0 and recombination frequency of 0.40. QTL analysis was performed using one-way analysis of variance (ANOVA) and MAPMAKER/QTL. The linkage map integrates 83 map-points assembled into nine linkage groups. F and de loci mapped to linkage group `B', and the l locus was placed on linkage group `D'. The total map length is 628 cM, with an average distance between loci of 8.4 cM. Results from using one-way ANOVA and MAPMAKER/QTL had a good agreement for most QTL detected. Some QTL were location specific. Across locations four, one and three QTL were detected for sex expression, mainstem length, and number of laterals, respectively.
A. Plotto, A. N. Azarenko, M. R. McDaniel, and J.P. Mattheis
`Gala' apples were harvested at weekly intervals for 6 weeks, refrigerated at 0C, and evaluated by a consumer panel monthly over a 6 month period for overall liking, firmness, sweetness, tartness and flavor intensities. Firmness, titratable acidity and soluble solids concentration were also measured. Initial analysis of sensory data revealed multicollinearity for overall liking, sweetness, and flavor. The five descriptors explained 75 % of the dataset variation in the first two factors. An orthogonal rotation separated overall liking, flavor and sweetness, and firmness and tartness into two independent factors. The distribution of mean scores along these independent factors showed that panelists could perceive changes due to ripening and maturation. The multivariate factor analysis was better than univariate ANOVA at illustrating how apple maturity stages were apparent to untrained panelists. Firmness was the only instrumental variable correlated to firmness ratings in the sensory tests. None of the analytical measurements could explain overall liking.
George C.J. Fernandez
Tire interpretation of variety trials conducted with many genotypes (G) grown in many environments (E) is usually complicated by the presence of the significant G × E interaction. The common statistical analysis using ANOVA and linear regression techniques are often inadequate to study the complex two-way data structure. The biplot, a multivariate technique provides, a graphical representation of the interaction, which allows the response of each G in each E to be displayed in a two dimensional plot. It displays not only the configuration of G and E, but it also relates the two. The importance of biplot display is illustrated by using the tall fescue variety trial data on mean quality ratings published by the National Turfgrass Evacuation Program. The biplot displays about 60% of the information in the 24 (G) × 23 (E) data matrix. Environments TX3 and GA1 responded differently from other environments. Based on the biplot display genotypes are grouped and their significance will be discussed.
Walter W. Stroup, Stacy A. Adams, and Ellen T. Paparozzi
An experiment was performed to investigate the effect of various nitrogen sulfer combinations on the quality of poinsettias. After various physiological measurements were taken, commercial growers, retailers, and consumers were asked to evaluate the salability of the plants. In order to avoid evaluator fatigue, only a limited number of plants could be evaluated. This presented both experimental design and data analysis problems. In view of these constraints, and in order to obtain meaningful results, an unreplicated 7 x 8 factorial design was used. Data were analyzed using the method of half-normal plots in conjunction with a modification of the analysis of variance procedure. Rationale and alternative designs will be presented, as well as the step-by-step procedure for using this method as contrasted with the standard ANOVA technique.
Kristin Schneider and James D. Kelly
Common beans, considered sensitive to moisture stress, are an important commodity in developing countries such as the Mexican Highlands where intermittent drought conditions are prevalent during the growing season. The selection and development of high performing cultivars under drought stress is confounded by the quantitative nature of drought tolerance. To employ indirect selection in earlier generations, RAPD markers were identified that associated with QTLs controlling performance under drought stress. RAPD markers are preferred for use in Phaseolus vulgaris, over RFLPs, because they generate polymorphisms between genetically related germplasm. 48% of 620 arbitrary primers screened against three parents of two F6 derived recombinant inbred pinto populations were polymorphic for one or more bands. These polymorphisms were screened against RILs in each population and associations were determined using one-way ANOVAs and Mapmaker. Yield data used for determination of associations was collected over five years in MI and Mexico where both stress and non stress treatments were applied.
Keith Woeste, Douglas Shaw, Gale McGranahan, and Robert Bernatzky
We characterized a population of hybrids between English walnut and Northern California black walnut (Juglans regia X J. hindsii) and their backcrosses (BC) using both genomic markers and morphological traits. ANOVA and regression methods were used on three years' data to identify a subset of five variables that describe the morphological variability among backcross populations and their parents (R2 = 0.89). Genomic markers were identified using randomly amplified polymorphic DNA (RAPD). A subset of 60 markers specific to the donor species (J. hindsii) were scored in 50 backcrosses to estimate the percent recipient genome in each evaluated BC. The backcrosses were ranked using each method of evaluation; correlation between the ranks was 0.423 and highly significant. Each evaluation method has advantages but neither was able to reliably identify elite progeny.