scholarly journals Repeatability coefficients and number of measurements for evaluating traits in strawberry

2020 ◽  
Vol 42 ◽  
pp. e43357 ◽  
Author(s):  
Maria Inês Diel ◽  
Alessandro Dal'Col Lúcio ◽  
Tiago Olivoto ◽  
Marcos Vinícius Marques Pinheiro ◽  
Dionatan Ketzer Krysczun ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Block Design ◽  
Principal Component ◽  
Titratable Acidity ◽  
Component Analysis ◽  
Soluble Solids ◽  
Repeatability Coefficient ◽  
Randomized Block Design ◽  
Crop Cycle ◽  
Substrate Mixtures

The objective of this study was to estimate the coefficient of repeatability and the number of measurements required for production and quality variables in a strawberry crop. An experiment was conducted with two strawberry cultivars from two origins grown in four substrate mixtures, totaling 16 treatments, evaluated in a randomized block design with four replications. Mass (MF) and number (NF) of fruits per plant were evaluated as measures of production, and total soluble solids (SST), titratable acidity (AT) and firmness (FIR) of fruits during the crop cycle were evaluated as measures of quality. Subsequently, the repeatability coefficient was estimated by the following methods: analysis of variance (ANOVA), principal component analysis using a correlation matrix (PCcor), principal component analysis using a variance-covariance matrix (PCcov) and structural analysis (SA). The number of measurements was adjusted for each studied variable based on determination coefficients of 0.80, 0.85, 0.90, and 0.95. The repeatability coefficients ranged from low to medium. The ANOVA method gave the lowest r values, while the PCcov method presented the highest values of r. When using the PCcov method, 3.6, 2.9, 6.2, 3.2, and 3.8 measurements were needed to reach 80% confidence for the variables MF, NF, SST, AT, and FIR, respectively, and this increased to 7.3, 14.0, 29.6, 15.4, and 18.1 for 95% confidence in the results for MF, NF, SST, AT, and FIR, respectively.

Principal Component Analysis and Stability of Genotypes in French Bean (Phaseolus vulgaris L.)

2021 ◽  
Author(s):  
B. Rajasekhar Reddy ◽  
Maneesh Pandey ◽  
J. Singh ◽  
P.M. Singh ◽  
N. Rai
Keyword(s):  
Principal Component Analysis ◽  
Stability Analysis ◽  
Principal Components ◽  
Block Design ◽  
Principal Component ◽  
Component Analysis ◽  
French Bean ◽  
Pod Yield ◽  
Randomized Block Design ◽  
Stable Yield

Background: Principal component analysis and Finlay-Wilkinson stability analysis were carried out at research farm of ICAR-Indian Institute of Vegetable Research, Varanasi to identify diverse french bean genotypes for green pod yield and suitable genotypes for stable yield and yield related parameters.Methods: All the 24 genotypes were laid out in randomized block design with two replications during winter, 2017 and 2018. Principal component analysis and stability analysis was done to identify the diverse and stable genotypes.Result: Eight principal components were observed and the maximum variability was concentrated in the first three principal components PC1, PC2 and PC3 which contributed to 68.61% variance. Cluster analysis from principal component scores formed three clusters with a maximum of seventeen genotypes in cluster I followed by six genotypes in cluster II and one genotype in cluster III. High heritability was observed for 10 pod weight, number of pods per cluster and number of seeds per pod and moderate heritability was observed for yield per plant. Finlay-Wilkinson stability analysis identified the stable genotypes viz., FMGCV 1378, FMGCV 0958, Arka Suvidha, Valentino, Banoa and VRFBB-14-2 for green pod yield per plant, Cartagenta for pod length (cm) and Paulista, Slender Pack, Arka Suvidha, Valentino, FMGCV 0958, Banoa, FORC 6V 1136, VRFBB-14-1, VRFBB-14-2 for number of pods per plant.

scholarly journals Potassium and Nitrogen Fertigation Frequency on Pineapple Yield and Fruit Quality

2019 ◽  
Vol 11 (6) ◽  
pp. 416
Author(s):  
Ana Maria Alves de Souza Ribeiro ◽  
Robson Bonomo ◽  
Moises Zucoloto ◽  
Fábio Oseias dos Reis da Silva ◽  
Mariana Vasconcelos Barroca ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Block Design ◽  
Titratable Acidity ◽  
Additional Treatment ◽  
Soluble Solids ◽  
Fruit Characteristics ◽  
Physical Chemical ◽  
Randomized Block Design ◽  
Crop Cycle ◽  
Fruit Mass

Pineapple is a nutritionally demanding crop, with emphasis on potassium and nitrogen nutrients. In this context, the aim of this paper was to study the effect of nitrogen (N) and potassium (K) fertigation frequencies on the physical-chemical fruit characteristics of ‘Pérola’ pineapple crop. The experiment was conducted in a randomized block design, with 18 treatments and 4 replications. It was used a factorial scheme (4 × 4) + 1 + 1, which represents: four N fertigation frequencies applied by surface drip irrigation (4, 7, 27 and 54 times throughout the crop cycle); four K fertigation frequencies (4, 9, 35 and 70 times); one additional treatment (irrigated, but without fertigation); and one control (non irrigated and non fertigated). The fruit characteristics analyzed were: fruit mass with crown, yield, soluble solids, pH, titratable acidity and SS/TA ratio. The N fertigation frequencies had no effect on variables evaluated, however, the K frequencies had a significant influence on fruit mass with crown, yield and pH. The results showed that the effect of K frequencies applied through fertigation on pineapple yield and fruit physical-chemical quality was more pronounced in comparison to the effect of N applications. Monthly potassium fertigations, followed by four applications throughout the crop cycle, provided the greatest increase in fruit quality, allowing higher values of fruit mass, yield and pH.

scholarly journals Principal Component Analysis for Identification of Superior Castor Bean Hybrids

2019 ◽  
Vol 11 (9) ◽  
pp. 179
Author(s):  
Gabriela N. da Piedade ◽  
Lucas V. Vieira ◽  
Amanda R. P. dos Santos ◽  
Deoclecio J. Amorim ◽  
Maurício D. Zanotto ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Plant Breeding ◽  
Castor Bean ◽  
Block Design ◽  
Principal Component ◽  
Component Analysis ◽  
Plant Size ◽  
Simple Task ◽  
Randomized Block Design ◽  
Crop Performance

The identification of superior genotypes in plant breeding programs is not a quick and simple task and requires breeders to become aware of more suitable and efficient tools for evaluating crop performance. Univariate analyses are often too narrow for the scope of plant breeding because it lacks consideration of relations between variables. Therefore, the objective of this study was to select castor bean hybrids based on principal component analysis (PCA). Trials were conducted in 2017 with 31 hybrids in a randomized block design with 4 replications. The following variables were used to evaluate crop performance: plant height (PH), insertion height of the primary raceme (HPR), number of stem nodes (NN), number of racemes (NR), number of seeds (NS), stem diameter (SD), number of fruits (NF), 100-seed weight (S100) and seed oil content (SOC). The first three principal components (PCs) explained approximately 75.01 % of all the variability in the dataset. PC 1, 2 and 3 were particularly related to productivity (NS, NR, S100 and NF), plant size (SD, HPR and PH) and oil production (SOC), respectively. Hybrids 14 and 23 were the most suitable for grain production in commercial scale due to short-height, which favors mechanical harvesting. Commercial hybrid 26 showed high SOC, medium grain yield and medium-height.

scholarly journals Differences between strawberry cultivars based on principal component analysis

2020 ◽  
Vol 8 (6) ◽  
pp. 136-145
Author(s):  
Darlei Michalski Lambrecht ◽  
Alessandro Dal'Col Lúcio ◽  
Maria Inês Diel ◽  
Denise Schmidt ◽  
Francieli De Lima Tartaglia ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Latent Variables ◽  
Covariance Structure ◽  
Principal Component ◽  
Titratable Acidity ◽  
Component Analysis ◽  
Soluble Solids ◽  
Family Farms ◽  
Multivariate Technique ◽  
Strawberry Cultivars

Strawberry culture is of extreme economic importance, especially for small producers, as it has the capacity to add value to small family farms, in addition to absorbing family labor. Principal component analysis (PCA) is a multivariate technique for modeling covariance structure, where a basic idea is to find latent variables that represent linear combinations of a group of variables under study, which in turn are related between itself. In this way, the objective of the work was estimated, through the analysis of main components (PCA), as relationships between development variables, products and fruit quality in different strawberry cultivars. The design used was a randomized block with 11 treatments, consisting of strawberry cultivars of Italian and American origins, with four replications. During the culture cycle, the following variables were evaluated: phyllochron, number of commercial (FC) and non-commercial (FNC) fruits, mass of commercial (MFC) and non-commercial (MFNC) fruits, total titratable acidity (AT), total soluble quantities (SST) and total soluble ratio, titratable acidity (SST / AT). The relationships between the variables were evaluated by the PCA analysis and the results were plotted on the Biplot graph. From the analysis, it was possible to identify the relationships between the variables that show how to cultivate the same photoperiod and the same characteristic origin. Growing short photoperiods are more productive, for example, as the neutral photoperiod has less phyllochron and less acidity. The increase in soluble solids can cause a reduction in acidity, which is one of the characteristics that add flavor to the fruit.

scholarly journals Can Sustained Deficit Irrigation Save Water and Meet the Quality Characteristics of Mango?

Agriculture ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 448
Author(s):  
Leontina Lipan ◽  
Aarón A. Carbonell-Pedro ◽  
Belén Cárceles Rodríguez ◽  
Víctor Hugo Durán-Zuazo ◽  
Dionisio Franco Tarifa ◽  
...  
Keyword(s):  
Irrigation Water ◽  
Deficit Irrigation ◽  
Block Design ◽  
Water Productivity ◽  
Titratable Acidity ◽  
Soluble Solids ◽  
Total Phenolic ◽  
Drought Tolerant ◽  
Randomized Block Design ◽  
Peel Color

Mango is one of the most cultivated tropical fruits worldwide and one of few drought-tolerant plants. Thus, in this study the effect of a sustained deficit irrigation (SDI) strategy on mango yield and quality was assessed with the aim of reducing irrigation water in mango crop. A randomized block design with four treatments was developed: (i) full irrigation (FI), assuring the crop’s water needs, and three levels of SDI receiving 75%, 50%, and 33% of irrigation water (SDI75, SDI50, and SDI33). Yield, morphology, color, titratable acidity (TA), total soluble solids (TSS), organic acids (OA), sugars, minerals, fiber, antioxidant activity (AA), and total phenolic content (TPC) were analyzed. The yield was reduced in SDI conditions (8%, 11%, and 20% for SDI75, SDI50, and SDI33, respectively), but the irrigation water productivity was higher in all SDI regimes. SDI significantly reduced the mango size, with SDI33 generating the smallest mangoes. Peel color significantly changed after 13 days of ripening, with SDI75 being the least ripe. The TA, AA, and citric acid were higher in SDI75, while the TPC and fiber increased in all SDI levels. Consequently, SDI reduced the mango size but increased the functionality of samples, without a severe detrimental effect on the yield.

scholarly journals Rootstock-scion interaction:5. Effect on the evolution of Cabernet Sauvignon grape ripening

2019 ◽  
Vol 41 (3) ◽  
Author(s):  
Alberto Miele ◽  
Luiz Antenor Rizzon
Keyword(s):  
Principal Component Analysis ◽  
Regression Analysis ◽  
Yield Components ◽  
Polynomial Regression ◽  
Principal Component ◽  
Titratable Acidity ◽  
Soluble Solids ◽  
Cabernet Sauvignon ◽  
Total Soluble Solids ◽  
Wine Composition

Abstract The rootstock effect on grapevine yield components, grape must and wine composition and wine sensory characteristics were evaluated in previous studies. This experiment carried out over five years had the objective to determine the effect of the rootstock on the evolution of variables related to sugar and acidity contents of the juice during grape ripening. The treatments consisted of Cabernet Sauvignon grapevine grafted on rootstocks such as Rupestris du Lot, 101- 14 Mgt, 3309 C, 420A Mgt, 5BB K, 161-49 C, SO4, Solferino, 1103 P, 99 R, 110 R, Gravesac, Fercal, Dogridge and Isabel. The berries were sampled during the grape ripening period, on nine dates during the summer of each year. Taken to the laboratory, they were hand crushed and the juice was centrifuged to separate the solid and liquid phase, where the supernatant was then used for physicochemical analyses. The data were submitted to Principal Component Analysis (PCA) and polynomial regression analysis. The main results show that, at grape maturity, the PCA discriminated mainly the juices of CS/101-14 Mgt, CS/SO4 and CS/Gravesac, which had high density, total soluble solids, total soluble solids/titratable acidity ratio and pH, and CS/Dogridge and CS/Fercal, which had high titratable acidity. The density, total soluble solids, titratable acidity, total soluble solids/titratable acidity ratio increased as grape ripened, but the titratable acidity decreased. However, the increase or decrease rates were lower at the end of the grape ripening cycle according to the variable, and the total soluble solids having the highest increase (116.3%) and the titratable acidity the highest decrease (68.3%).

scholarly journals Production and quality of okra produced with mineral and organic fertilization

2019 ◽  
Vol 23 (2) ◽  
pp. 97-102
Author(s):  
Hemmannuella C. Santos ◽  
Emmanuel M. Pereira ◽  
Rafael L. S. de Medeiros ◽  
Paulo M. de A. Costa ◽  
Walter E. Pereira
Keyword(s):  
Vitamin C ◽  
Block Design ◽  
Titratable Acidity ◽  
Soluble Solids ◽  
Organic Fertilization ◽  
Randomized Block Design ◽  
Number Of Leaves ◽  
The Mean ◽  
Organic Compost

ABSTRACT Okra, Abelmoschus esculentus (L.) Moench, is a vegetable with annual fruit native to hot regions of Africa, well adapted to the conditions of the Northeast and Southeast regions of Brazil, where it is widely used by small farmers. This study aimed to evaluate the effect of mineral and organic fertilization on the production and quality of okra fruits. The experiment was conducted in randomized block design, with three replicates and eleven treatments defined according to a Baconian matrix. Treatments consisted of doses of N (0, 100, 200 and 300 kg ha-1), P (0, 100, 200 and 300 kg ha-1) and K (0, 80, 160 and 240 kg ha-1), as well as absence and presence of organic compost (30 t ha-1). The following parameters were evaluated: plant height, stem diameter, number of leaves, production of fruits plant-1, number of fruits plant-1, fruit length and diameter and fruit quality (pH, soluble solids, titratable acidity, vitamin C and electrical conductivity). The crop is demanding in terms of K and N fertilizations, with increments of 15.8 and 36% in the mean number and diameter of fruits, respectively. Organic fertilization did not influence the vegetative growth of okra, but was beneficial to the production of fruits with higher vitamin C content, 52% higher than the contents found in fruits produced without such input.

scholarly journals Effect of Integrated Nutrient Management on Fruit Yield and Quality of Peach (Prunus persica L. Batsch) cv. July Elberta

2020 ◽  
pp. 152-160
Author(s):  
S. P. S. Solanki ◽  
Naveen C. Sharma ◽  
J. S. Chandel ◽  
Debashish Hota
Keyword(s):  
Prunus Persica ◽  
Nutrient Management ◽  
Block Design ◽  
Titratable Acidity ◽  
Fruit Weight ◽  
Soluble Solids ◽  
Uniform Size ◽  
Randomized Block Design ◽  
Experimental Block ◽  
Old Trees

The present studies were carried out in Experimental Block, Department of Fruit Science, Dr. YS Parmar University of Horticulture and Forestry, Nauni, Solan (HP) during the year 2015-16. Nine years old trees of uniform size and vigour planted at 4.0 x 2.0 m spacing were selected for the studies. The experiment was laid out in a randomized block design with 11 treatments. The maximum increased in fruit set (87.70%) and yield (20.16 kg/tree) were observed significantly higher under 75% RDF + vermicompost 15 kg/tree. Maximum fruit length (64.06 mm), breadth (61.89 mm), fruit weight (129.51 g), total soluble solids (13.33 ºB) and total sugars (7.51%) were recorded under 75% RDF + vermicompost 15 kg/tree, however, highest fruit firmness (6.56 kg/cm2) and lowest titratable acidity (0.50%) were found with 4 applications of jeevamrut.

scholarly journals Performance of mini-tomato hybrids in different training systems with different number of stems

2017 ◽  
Vol 35 (3) ◽  
pp. 428-433
Author(s):  
Pablo F Vargas ◽  
Leonardo S Duarte ◽  
Edgard HC Silva ◽  
Amanda C Zecchini ◽  
Renato S Soares ◽  
...  
Keyword(s):  
Block Design ◽  
Fruit Weight ◽  
Soluble Solids ◽  
Production Cycle ◽  
Training Systems ◽  
Randomized Block Design ◽  
Crop Cycle ◽  
Chlorophyll Index ◽  
Number Of Stems ◽  
Fruit Diameter

ABSTRACT At present, Brazil is among the world's largest tomato producers. This production is directed both for the industry and for fresh consumption. Among the different tomato groups, production of mini-tomatoes has grown in recent years because of their high commercial value and mainly greater price stability. However, there are few studies investigating the proper management of this group, as it is recent in the country. The aim of the present study was to evaluate the viability of mini-tomato hybrids in different training systems, in greenhouse conditions. The experiment was set as a randomized block design in a 2×2×4 factorial arrangement with two numbers of stems (one and two stems per plant), two training systems [conventional (vertical) and horizontal], and four hybrids [AF 18196 (Sakata Seed); AF 13106 (Sakata Seed); Nina (Takii Seed) and Cocktail Mascot (Agristar/Top Seed Premium)], with three replicates and four plants per plot in the usable area. The evaluated variables were production per plant, fruit weight, transverse and longitudinal fruit diameter, number of fruits per plant, number of clusters per plant, number of fruits per cluster, precocity, production cycle, chlorophyll index, soluble solids, and crop cycle. The most promising hybrids are AF 13106 (2.71 kg/plant), AF 18196 (2.63 kg/plant) and Mascot (2.38 kg/plant), managed with two stems (2.63 kg/plant), in the vertical system (2.94 kg/plant).

scholarly journals Inheritance and Heritability of Resistance to Citrus Leprosis

2006 ◽  
Vol 96 (10) ◽  
pp. 1092-1096 ◽  
Author(s):  
Marinês Bastianel ◽  
Antonio Carlos de Oliveira ◽  
Mariângela Cristofani ◽  
Oliveiro Guerreiro Filho ◽  
Juliana Freitas-Astúa ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Growth Parameters ◽  
Block Design ◽  
Principal Component ◽  
Component Analysis ◽  
Factorial Analysis ◽  
Inheritance Of Resistance ◽  
Measured Variable ◽  
Citrus Leprosis ◽  
Discriminant Factorial Analysis

The genetic inheritance of resistance to leprosis, the most important viral disease of citrus in Brazil, was characterized through the phenotypic assessment of 143 hybrids resulting from crosses between tangor ‘Murcott’ (Citrus sinensis × C. reticulata) and sweet orange ‘Pêra’ (C. sinensis), considered to be resistant and susceptible to the disease, respectively. All plants were grafted onto Rangpur lime (C. limonia) and inoculated with Citrus leprosis virus, cytoplasmic type through the infestation with viruliferous mites, Brevipalpus phoenicis. The experiments were arranged in a completely randomized block design with 10 replicates. Incidence and severity of the disease in leaves and stems as well as plant growth parameters (plant height and stem diameter) were recorded for 3 years after the infestation with the viruliferous mites. The average values of all variables were analyzed using principal component analysis, discriminant factorial analysis, estimation of the clonal repeatability coefficients, and frequency of the distributions of the average values for each measured variable. The principal component analysis resulted in the identification of at least two groups with resistance and susceptibility to leprosis, respectively. About 99% of all hybrids were correctly classified according to the discriminant factorial analysis. The broad-sense heritability coefficients for characteristics associated with incidence and severity of leprosis ranged from 0.88 to 0.96. The data suggest that the inheritance of resistance to leprosis may be controlled by only a few genes.

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