broad uses for landscaping. Whether it is park or green space, road greening, residential area, courtyard greening or indoor display, almost all have the figure of Sasanqua. ( Li et al. 2014 ). Phenotypic traits are the result of the combined effects
variation in TPC (milligrams GAE per gram FW) in a diverse collection of snap bean cultivars, 2) determine if TPC is associated with phenotypic traits such as growth habit and flower color, and 3) estimate genotype by environment effects for a subset of pole
genotypes for all traits. Path coefficient analysis was used to analyze the standardized phenotypic means of measurements as outlined by Akintunde (2012) . Path analysis has been used for other crops to understand the complex interactions that underlie
: First, it is necessary to establish whether the 3D phenotypic platform can differentiate capsule maturity through quantitative evaluation of traits, such as capsule color, shape, density, water content, and temperature sensitivity. Second, if difference
level for each of the four traits, and estimate the proportion of individuals selected above or below the critical phenotypic values in the offspring population (population size after primary selection), which indicates selection efficiency
Strawberry seedlings (Fragaria ×ananassa Duch.) from the Univ. of California strawberry improvement program were assigned randomly to soils prepared either with or without preplant fumigation with a mixture of 2 methyl bromide: 1 chloropicrin (by mass; 392 kg·ha-1) in order to evaluate sampling methods for root characters. After 5 months in annual hill culture, individual plant root systems were sampled with a single 1.9-cm-diameter × 24-cm-long soil core probe to determine root mass (RM), secondary rootlet mass (SRM), and a subjective root appearance score (RAS) based on root color and morphology. Whole plants were subsequently extracted and used to measure these root characters and total above-ground (shoot) mass. Soil core samples captured <1 % of total RM on average but explained 45% to 74% of the variability for whole-plant RM and SRM in both soil environments. Plants grown in fumigated soils had greater shoot mass, plant diameter, RM, SRM, and RAS than those grown in nonfumigated soils, regardless of sampling method. Phenotypic correlations between traits were fairly consistent across fumigation treatments, differing by more than ±0.20 only for associations involving RAS as a variable. Highly significant (P < 0.01) phenotypic correlations were detected among shoot mass, plant size, and root core and whole-plant RM and SRM in both fumigation environments; correlations between whole-plant RM and shoot mass were r =0.84 and 0.96 in fumigated and nonfumigated soils, respectively. Conversely, nearly all correlations between pairs of traits involving either soil core or whole-plant RAS were nonsignificant. Together, these results indicate that a strong correspondence exists between above- and below-ground vegetative growth and that most correlations between traits are consistent across fumigation treatments. Further, the strong relationship between soil core RM and whole-plant RM indicates that soil cores provide an accurate description of root growth relationships at the whole-plant level and can be substituted effectively for whole-plant (destructive) samples. Chemical name used: trichloronitromethane (chloropicrin).
cultivars Genet. Resources Crop Evol. 60 427 440 Lin, Y. Yi, X. Tang, S. Chen, W. Wu, F. Yang, X. Jiang, X. Shi, H. Ma, J. Chen, G. Chen, G. Zheng, Y. Wei, Y. Liu, Y. 2019 Dissection of phenotypic and genetic variation of drought-related traits in diverse
conferring complex traits for which phenotypic differentiation can be difficult to assess ( Farnham and Björkman, 2011a ; Heather et al., 1992 ). The need to develop a consistent, stringent, and robust means of identifying suitable or nonsuitable hybrids for
Thirteen peach [Prunus persica (L.) Batsch] fruit characteristics were investigated for 3 years, 1993, 1994, and 1995, in College Station, Texas, to determine heritability, genetic and phenotypic correlations, and predicted response to selection. Seedlings of 108 families resulting from crosses among 42 peach cultivars and selections were used in the evaluations. A mixed linear model, with years treated as fixed and additive genotypes as random factors, was employed to analyze the data. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances between traits. Genetic and phenotypic correlations ≥0.65 and <0.30 were considered strong or very strong and weak, respectively. Date of ripening, fruit development period (FDP) and date of full bloom had the highest heritability (h2) estimates, 0.94, 0.91, and 0.78, respectively. Fruit cheek diameter and titratable acidity (h2 = 0.31) were the traits with the lowest estimates. Fruit development period, fruit blush, and date of ripening had the highest predicted selection responses, whereas fruit suture, fruit cheek, L/W12 (ratio fruit length to average fruit diameters), and fruit tip had the lowest values. Most genetic correlations were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. All four measures of fruit size were genetically and phenotypically very strongly correlated. Important genetic correlation estimates were also observed for date of ripening with FDP (ra = 0.93), date of ripening and FDP with fruit blush (ra = -0.77, ra = -0.72), SS (percent soluble solids) (ra = 0.63, ra = 0.62) and TA (ra = 0.55, ra = 0.64), and SS with TA (ra = -0.56). Direct selection practiced solely for early ripening and short FDP is expected to have a greater effect on correlated traits than direct selection for early bloom and large fruit mass.
Seedlings of 108 families from crosses among 42 peach [Prunus persica (L.) Batsch] cultivars and selections were evaluated for six plant characteristics in 1993, 1994, and 1995. The data were analyzed by using a mixed linear model, with years treated as fixed and additive genotypes as random factors. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances among traits. The narrow-sense heritability estimates were 0.41, 0.29, 0.48, 0.47, 0.43, and 0.23 for flower density, flowers per node, node density, fruit density, fruit set, and blind node propensity, respectively. Most genetic correlations among pairs of traits were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. Flower density and flowers per node (ra = 0.95), fruit density and fruit set (ra = 0.84) and flower density and fruit density (ra = 0.71) were the combinations of traits that had the highest genetic correlation estimates. Direct selection practiced solely for flower density (either direction) is expected to have a greater effect on fruit density than direct selection for fruit density.