Stability Analysis of Fruit Weight in Paprika Pepper
Total Page：16
File Type：pdf, Size：1020Kb
Bulletin UASVM Agriculture, 67(1)/2010 Print ISSN 1843-5246; Electronic ISSN 1843-5386 Stability Analysis of Fruit Weight in Paprika Pepper Sorin CIULCA, Emilian MADOSA, Adriana CIULCA, Sabin CHIS Horticulture and Sylviculture Faculty, Banat’s University of Agricultural Sciences and Veterinary Medicine Timisoara, 119 Calea Aradului Street, 300645, Timisoara, Romania; [email protected] Abstract. In assessing the performance of different varieties both the production potential and its stability should be taken into account. High yield stability usually refers to a genotype ability to perform consistently, whether at high or low yield levels across a wide range of environments. An ideal variety should have a high mean yield combined with a low degree of fluctuation under different environments. The objectives of this study were to evaluate the stability of fruit weight for different cultivars and landraces of paprika pepper through different statistical models to analyze and partitioning the genotype-environment interaction. Landraces Cenad, Mocirla, Cermei, Belint achieved values of fruit weight superior to experimental mean with a high stability. In the same time for genotypes Seleu ş, Cutina, Csardas, Arad 6 high stability was associated with levels of this trait inferior to the experimental mean. Based on vector length, we observed that cultivars Szeged and Karmina achieve a fruit weight inferior to the experimental mean highly influenced by genotype x environment interaction, while the superior value of cultivars Carmen and Kalacsai was due to the influence of genotype x environment interaction. According to all results a high stability associated with low influence of the genotype x environment interaction over the phenotypic expression of fruit weight was observed in landraces: Buzad, Pocola, Craiva, Cutina. Keywords : paprika pepper, fruit weight, stability INTRODUCTION The paprika refers to a medium light green pepper grown exclusively for the production of high quality spice powder, after drying and milling. Paprika is classified according to its pigment contents, fineness of milling and pungency (Prohens and Nuez, 2008). Regarding the growth habit, they are continuous, semi-determinate and determinate, with erect and pendulous orientation of the fruits. To have a good quality product the aim is to harvest as much fruit as possible at the first picking, ideally 75-80 %. The paprika yield and quality of this is also strongly influenced by the climatic and technology conditions (Krishna De, 2003). In western counties (Timis, Arad and Bihor) different cultivars and especially landraces are cultivated by traditional paprika producers. In assessing the performance of different varieties both the production potential and its stability should be taken into account. High yield stability usually refers to a genotype ability to perform consistently, whether at high or low yield levels across a wide range of environments. An ideal variety should have a high mean yield combined with a low degree of fluctuation under different environments (Annicchiarico, 2002). The objectives of this study were to evaluate the stability of fruit weight for different cultivars and landraces of paprika pepper cultivated in West part Romania, through different statistical models to analyze and partitioning of the genotype-by-environment interaction. 235 MATERIALS AND METHODS The biological material was represented by a collection of 23 cultivars and landraces of paprika pepper. Experimentation with these genotypes was conducted in a comparative culture in three repetitions, by randomized block design, during 2006-2008. Biometric measurements of fruit weight (after drying) were made for 20 plants, from every plot-repetition. For estimating and interpreting the interaction genotype x environment and stability of studied traits, different statistical models were used. Fruit weight stability of the studied cultivars has been established using the regression coefficient following Finlay and Wilkinson (1963) method. The second method referring to the genotype-environment interaction, for the studied cultivars, was partitioned into two types of interaction: due to heterogeneous variances in scaling of genetics effects, and due to imperfect correlations, deviations from a perfect positive correlation respectively, according to the first method of Muir et al. (1992). Also, the Additive Main Effects and Multiplicative Interaction (AMMI) model was used to estimate the stability of grain number/spike and thousand grain weight for different cultivars (Chahal and Gosal, 2002). In this analysis, the information about GE interaction after taking out the main effects of environments and genotypes is used for PCA to extract patterns of GE or residual variation, to understand the underlying causes of such interactions (Gauch and Zabel, 1988). RESULTS AND DISCUSSION According to fruit weight (Tab.1), low regression coefficient values showing a high static stability (Anichiarico) were observed for Bocsig, Seleu ş, Karmina, Csardas, Tab. 1 Fruits weight stability through (Finlay-Wilkinson) linear regression for paprika pepper cultivars and landraces studied during 2006-2008 No Cultivars Mean Regr. Tip I(range) Tip II(range) Regr. Rezidual Tip III(range) Landraces (g) coefficient Stability Stability constant variance Stability 1 Aleva WK 13.90 1.021 12 2 -0.11 13.11 20 2 Arad 6 11.74 1.150 15 6 -4.03 8.30 18 3 Carmen 14.74 1.551 20 17 -6.53 1.45 10 4 Csardas 11.14 0.639 4 14 2.37 12.60 19 5 Kalacsai 15.68 1.399 18 15 -3.50 26.29 21 6 Karmina 11.18 0.393 3 18 5.78 1.15 6 7 NS 6 12.91 1.079 14 5 -1.89 2.89 13 8 Szeged 8.89 0.706 6 12 -0.79 1.30 8 9 Aldesti 18.09 0.818 8 8 6.86 44.06 23 10 Apateu 15.96 1.661 21 19 -6.83 6.82 15 11 Belint 11.69 1.226 16 9 -5.13 1.77 11 12 Bocsig 12.54 -0.083 1 23 13.68 2.42 12 13 Buzad 13.30 0.993 11 1 -0.32 0.10 2 14 Cenad 16.93 1.859 22 21 -8.56 1.19 7 15 Cermei 18.80 1.038 13 4 4.57 8.28 17 16 Craiva 11.88 0.820 9 7 0.63 0.26 3 17 Cutina 10.15 0.700 5 13 0.54 0.01 1 18 Mocirla 19.44 1.907 23 22 -6.71 7.96 16 19 Pocola 12.52 0.965 10 3 -0.72 0.40 4 20 Rachita 15.14 1.252 17 11 -2.03 0.46 5 21 Seleu ş 8.84 0.307 2 20 4.63 1.43 9 22 Zărand 17.37 1.469 19 16 -2.78 30.15 22 23 Zimand 12.61 0.756 7 10 2.25 6.79 14 236 Cutina genotypes, carrying constant values of this trait regardless of environmental conditions were tested. Different values of fruit weight from year to year, showing a low static stability were registered for Mocirla, Cenad, Apateu, landraces and Carmen cultivar. The lowest values of genotype x environment interaction, associated with a regression coefficient values close to the unit were presented by Buzad, Alewa WK, Pocola, Cermei genotypes, which highlights a high dynamic stability that enabled them to achieve a value of fruit weight parallel to the average of other landraces and cultivars of this experience. For landraces Bocsig, Mocirla, Cenad, Seleu ş, Apateu, fruit weight showed a pronounced dynamic instability and these landraces performances were not correlated with climatic favorability of the experimental years. Regarding to the higher type III stability, minimal values of fruit weight deviation from the regression line were observed for Cutina, Buzad, Craiva, Pocola, R ăchita, landraces. Also, Alde şti, Z ărand, Kalacsai, Alewa WK, genotypes fruit weight values during experimental period indicated high deviations from the regression line. The genotype-environment interaction analysis (Tab. 2) indicated that the highest stability of this trait and low genotype-environment interaction, respectively (below 2.3 % from the total value) was registered by Buzad, Pocola, Craiva landraces. High genotype- environment interaction associated with high instability of fruit weight was observed for Bocsig, Mocirla, Cenad, Alde şti, Z ărand. These landraces achieved mostly superior values of this trait. Tab. 2 Fruits weight stability through (Muir) heterogeneous variances (HV) and imperfect correlations (IC) for paprika pepper cultivars and landraces studied during 2006-2008 No. Cultivars Mean SS SS SS Landraces (g) (HV) (%) (IC) (%) (GE) (%) 1 Aleva WK 13.90 7.37 1.28 12.92 2.24 20.29 3.52 2 Arad 6 11.74 8.11 1.41 9.92 1.72 18.03 3.13 3 Carmen 14.74 17.12 2.97 7.50 1.30 24.62 4.27 4 Csardas 11.14 10.08 1.75 14.98 2.60 25.05 4.35 5 Kalacsai 13.25 9.18 1.59 7.81 1.36 16.99 2.95 6 Karmina 11.18 23.27 4.04 3.68 0.64 26.95 4.68 7 NS 6 12.91 7.28 1.26 6.60 1.15 13.87 2.41 8 Szeged 8.89 11.62 2.02 4.38 0.76 16.00 2.78 9 Alde şti 18.09 7.83 1.36 33.87 5.88 41.69 7.24 10 Apateu 15.96 23.22 4.03 10.14 1.76 33.37 5.79 11 Belin ţ 11.69 8.50 1.48 6.41 1.11 14.91 2.59 12 Bocsig 12.54 34.91 6.06 24.48 4.25 59.38 10.31 13 Buzad 13.30 7.36 1.28 4.46 0.77 11.82 2.05 14 Cenad 16.93 32.81 5.70 8.66 1.50 41.48 7.20 15 Cermei 18.80 7.28 1.26 9.91 1.72 17.19 2.98 16 Craiva 11.88 9.33 1.62 3.85 0.67 13.18 2.29 17 Cutina 10.15 12.18 2.11 3.11 0.54 15.29 2.65 18 Mocirla 19.44 37.97 6.59 11.28 1.96 49.26 8.55 19 Pocola 12.52 7.50 1.30 4.55 0.79 12.05 2.09 20 Răchita 15.14 8.75 1.52 5.79 1.00 14.55 2.52 21 Seleu ş 8.84 27.16 4.71 4.38 0.76 31.54 5.48 22 Zărand 17.37 20.14 3.50 19.86 3.45 40.00 6.94 23 Zimand 12.61 9.27 1.61 9.24 1.60 18.51 3.21 TOTAL 348.23 60.45 227.77 39.54 576.03 100.00 237 Concerning the fruit weight during experimental period 60.45 % of the genotype x environment interactions was due to the variances heterogeneous, therefore different genotype stability assessment based on variances related to fruit weight for different landraces and cultivars might be efficiently used.