Chili (Capsicum annuum L.) is one of the horticultural commodities that have high economic value which is used as vegetables or cooking spices, industrial raw materials, and has export opportunities. The development of superior chili varieties requires a large variety of germplasm that can be used as parents to be crossed with each other to obtain new superior traits. One of the efforts to determine the diversity of plants is to characterize the morphology and production. The purpose of this study was to obtain distinguishing characters among ten genotypes of large chilies, to determine the value of genetic parameter estimators for several genotypes of large chilies and to identify important characters that influence the yield of large chili genotypes. The study was a single factor field experiment in the form of 10 large chili genotypes arranged in a Completely Randomized Block Design (RCBD) with 3 blocks as replication. Genotypes of large chili are: Arimbi, Baja, Beautiful, Dewa Rengku, Gada, Jayadi, Jenio, Simpatik, Panex, and Thunder. Observation variables included morphological characters (plant habit, leaf color, leaf position, leaf shape, flower position, anther color, pistil color, leaf edge, fruit color), growth variables (plant height, stem diameter, number of leaves), and yield variable (weight per fruit, fruit length, fruit weight per plant). The results showed that all morphological characters for all varieties were the same, namely having an upright habitus, pointed leaf shape, green leaf color, leaf position falling, flower position lowering, purple anther warrant and green pistil stalk warrant, and red fruit skin color.
The focus of this research was to determine the growth and yield of several melon lines in generation S3, as well as to estimate the genetic variants, morphologies, and yield heritability. A randomized design was used, which consisted of a single factor with four replications. Six melon lines from generation S3 were used, namely DS-1-1-4, DS-1-1-10, DS-1-1-11, DS-1-2-10, DS-1-2-17, and DS-1-3-3, for a total of 24 experimental units. There were ten plants in each experimental unit. The smart farming hydroponic system was used. Plant height, stem diameter, male and female flowering, horizontal and vertical fruit girth, pulp thickness, fruit weight, and total soluble solids were the parameters measured. The data were analyzed using analysis of variance and the genetic parameter was estimated by analyzing the genetic coefficient of variation and broad sense heritability. Except for plant height, the results showed that all of the characteristics had a low genetic coefficient of variation. Plant height two weeks after planting showed high broad sense heritability (84.56%), as did pulp thickness (77.89%), female flowering (75.83%), male flowering (74.65%), plant height three weeks after planting (66.25%), and plant weight (50.81%). Plant height, male and female flowering, vertical fruit girth, and fruit weight were best represented by the DS-1-2-10 lines. Keywords: Melon lines, genetic parameters, smart farming, heritability.
Neutrophil Lymphocyte Ratio (NLR) is a laboratory available as a marker used for the evaluation of systemic inflammation, NLR is a significant predictor and is a critical prognosis for COVID-19 infection and can serve as a useful factor to reflect the intensity of the imbalance of inflammation and immune response in COVID-19 patients. This study aims to determine the difference in NLR values in negative and confirmed COVID-19 patients and description for comorbid for both. This study is an analytic observational study with a cross-sectional design. The study sample was 423 suspected COVID-19 patients at hospitals in Cilacap district for the period in March – October 2020. The data obtained were analyzed descriptively and using the fisher-exact test. In these results from suspected patients with negative COVID-19, lung illness were present 31.8%, viral infections 22.9%, other respiratory disorders 6.1%, diabetes mellitus 4.7%, and anemia 4.7%. Whereas suspected patients with confirmed COVID-19 were, without comorbid diseases (40.2%), lung disease (12.4%), diabetes mellitus (7.7%), hypertension (6.2%), and other respiratory illnesses (5.2%). The mean of NLR in confirmed patients is 3.57 but not any difference between negative and confirmed patients COVID-19, but there’s any a relationship between NLR and ARDS conditions.
Simulation study was done to evaluate QTL mapping and selection efficiency of molecular markers utilisation in the F2 population. The simulation study started with formulating genetic configuration which consists of chromosome maps and genetic models. Genetic model for diploid individuals is a model which consists two alleles for each locus. Genetic model that used is a mathematical model consists additive, dominance, and interactions with different effects at each locus, with maximum interaction occurs between two loci (digenic). QTL mapping was constructed by using single locus model, two loci model and multiple loci model. the effect of sample size, heritability, and marker density was observed. Three model was used to analyse QTL position, i.e. marker regression, interval mapping (IM) and composite interval mapping (CIM). Several parameters were specified in this study: genetic variability coefficient (GVC=15%), population mean (μ=10), epistasis and genetic variance ratio (f=0.1), dominance and additive variance ratio (r=0.25), the ratio of AA:AD:DD is 3:2:1 with additive and dominance gene action, and its interaction. The first and last marker were located at each edge of 150 cM chromosome for each chromosome. The interval distance between markers were equal. Haldane’s map function was used in this simulation. The simulation was performed by using the QTL Package on “R” software. With a heritability 0.2, the required sample size to indicate the interval markers associated with QTL were 50 for single locus model. The level of selection efficiency using molecular markers was higher than the phenotypic screening on. Efficiency level of selection based on molecular markers (Em) is a function of the distance between the markers to QTL (d) which follows “reciprocal quadratic” function. Efficiency level of selection based on phenotype (Ef) is a function of heritability favourable traits which follows “reciprocal quadratic” function.Keywords: efficiency, markers, QTL, simulation
One of the important stages of plants propagated by tissue culture before being moved to the field is acclimatization. Small plants must adapt to the outside environment in the acclimatization room. This research was aimed to figure out the composition of growing medium with the best concentration of auxin for the growth of chrysanthemum plant in the acclimatization room. This research was conducted from February until April 2017 in Hargobinangun Village, Pakem District, Sleman Regency, Special Region of Yogyakarta Province. The research was a field experiment with factorial Completely Randomized Design and was repeated five times. The growing medium tested was vermin compost (kascing fertilizer), manure and compost. Meanwhile, the concentrations of auxin being tested were 1.2 and 3 ppm. The results of the research show that the growing medium of compost made from bamboo leaves could increase the number of leaves, the height of the plant, the number of roots and the fresh weight of the plant. Meanwhile, the concentration of auxin of 2 ppm was able to increase the height of the plant, the number of roots, the length of roots, and the fresh weight of the plant.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.