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Oct 2018 DOI 10.14302/issn.2641-9467.jgrc-18-2339
Sarmah PrabaleeCorresponding author
Jr. Scientist-S2 (PBG), AICRP on Vegetable Crops, Department of Horticulture, AAU, Jorhat, Assam, India.
We evaluated a set of 37 chilli genotypes collected and maintained at Assam Agricultural University, Jorhat for 27 different traits related to plant habit (5), leaf (6), flower (2), fruit (13) and biotic stress (1). The variation in fruit yield among the genotypes could be attributed to high coefficients of variability for component traits viz., number of fruits per plant (91.7%), plant height (80.8%), leaf breadth (55.9 %), fruit weight (49.7%), leaf length (45.4%) fruit length (35.8%), fruit breadth (35.5%) and number of branches per plant (22.2%). Maximum phenotypic variants were observed for fruit traits followed by leaf characteristics. Phylogenetic analysis revealed Euclidean distances varying from a minimum of 2.065 and a maximum of 13.311 indicating the diverse nature of the genotypes. UPGMA clustering grouped the genotypes into 5 distinct clusters. The largest one, cluster I, had 26 genotypes belonging to Capsicum annuum var. acuminatum. Cluster II consisted of Capsicum annuum var. conoides with cone-shaped fruits. Cluster III included Moni Jolokia, a perennial shrub with cone-shaped globose erect fruits which clustered in between the other local C. annuum sp. Bireek and Mem Jolokia. The fourth cluster (IV) included the local chilli genotypes - Mem Jolokia, Bhekuri Jolokia and Haitha Jolokia which were perennial, with green stem and leaves. Cluster V included the C. chinense genotypes consisting of Manipuri Bhut, Bor Bhut and Lota Bhut. The first principal component explained 34.93% of the total variation contributed by mostly leaf and fruit characteristics. The fruit characters in this component showed significant positive correlation with leaf length, breadth and plant height indicating their importance in the morphological characterization of the chilli genotypes.
Jun 2019 DOI 10.14302/issn.2639-3166.jar-19-2785
A. Mari NicolásCorresponding author
Instituto Nacional de Tecnología Agropecuaria – Agencia de Extensión Rural Cruz del Eje
In Córdoba, Argentina, the peri-urban horticulture is in conflict with industrial agriculture and urban development. This problem is partly due to urban expansion to rural areas occurred in the last years and to monoculture farming, which has replaced traditional fruit and vegetable cropping in the region. This transformation process has raised concern about the current and future availability of productive sectors that can sustain food supply within the city boundaries and its immediate surroundings as well as about the loss of ecosystem services associated with peri-urban natural environments. Although these dynamic processes are well known, they have not been described or quantified in Córdoba. Baseline information about land use and its dynamics in productive areas or about number of producers is insufficient and/or out of date. At O-AUPA (Spanish acronym for Observatory of Urban and Peri-urban Agriculture and Agroecology) different mapping strategies are developed to contribute to the understanding of the land dynamics in the Green Belt of Córdoba (GBC) and the rural environments surrounding the city. In this work, we present a method based on the use of remote sensing and geographical information systems to characterize urban, peri-urban and rural areas of Córdoba city with the aim of evaluating the temporal dynamics of urban growth and the current state of land use and cover. We mapped and quantified the urban growth between 1974 and 2014, and evaluated land use in peri-urban and rural areas in 2015. We used satellite information from Landsat TM 5 to map the urban growth via a principal component analysis (PCA) and SPOT 5 imagery to characterize the current land use and land cover with the support vector machine classification algorithm. The results show an urban area growth of 46.5% over almost 40 years within the boundaries of the Capital department. Farm plot size increased, showing a concentration of land ownership, implying a reduced number of producers. Evidence indicates the importance of defining land planning guidelines that limit the advance of the urban frontier to valuable agricultural systems, ensure diversification of productive activities and protect and develop the fresh food production systems at the local level.
Sep 2017 DOI 10.14302/issn.2474-7785.jarh-17-1727
Akazawa ManabuCorresponding author
Public Health and Epidemiology, Meiji Pharmaceutical University
Background: Healthcare services provided to patients should vary depending on disease severity. However, disease severity bias, a type of selection bias, is a commonly encountered problem in administrative database studies. Herein, we selected chronic obstructive pulmonary disease (COPD), which commonly affects elderly Japanese citizens, for the development and validation of a severity classification system based on a health insurance claims database. Methods: Patients who received COPD-related diagnostic codes in 2011 were selected from a commercially based health insurance claims database. COPD patients were randomly divided into two groups to develop and validate severity scores. A principal component analysis was used to estimate factor loadings used to weight calculations of COPD severity scores. Score validity was evaluated using a linear trend test to predict COPD treatment costs and acute exacerbation events. Results: Using records from 880 patients, ten variables were created: acute exacerbation events, emphysema diagnoses, laboratory test and oxygen therapy procedures, prescribed anticholinergic, inhaled corticosteroid (ICS), short acting beta-agonist, and long acting bronchodilator (LABA) agents, asthma diagnosis and patient birth years. Factor loadings from LABA and ICS prescriptions had the strongest impacts on estimated severity scores (0.50 and 0.49, respectively). Among 300 validation group patients, scores were found to associate with increasing trends of median costs and exacerbation risks (p for trend < 0.05). Conclusions: Estimatedseverity scores would help to predict COPD-related medical costs and exacerbation events. For further clinical implementation, this classification system should be re-evaluated using clinical lung functions information indicative COPD severity and treatment choices.
Jul 2017 DOI 10.14302/issn.2476-1710.jdt-17-1564
Caroline Krefis AnneCorresponding author
Institute for Health Services Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-Eppendorf (UKE), Martinistraße 52, 20246 Hamburg, Germany
The objective of this first part of our study was to investigate associations of road traffic noise, socioeconomic and -demographic risk factors, and health access on depression on borough level. We investigated in a large metropolis associations between prevalence rates of depression per borough (n = 67 boroughs) in all age groups (excluding the age group of 0–17 years) using health claims data (year 2011) and the variables “social deprivation” and “number of family members”, which were obtained from a previously conducted principal component analysis, and by using multivariate regression model. Additionally, the proportion of borough area affected by noise > 65 db(A) and physician density used as a surrogate parameter for health access were considered as potentially associated factors for depression. The results demonstrated that depression might be associated with increasing social borough deprivation. Additionally, the number of family members used as a proxy measure for positive family support showed decreasing prevalence rates the more family members were present. Furthermore, proportions of borough areas affected by noise > 65 db(A) was positively associated with depression. Our ecological study design has the advantage that a large number of large-scale, population-based aggregated data could easily be obtained and analysed and first potential associations could be found and discussed. To improve our findings, future studies will use data from a survey and data from the Hamburg City Health Study, a local follow-up health study, to better elucidate the individual risk factors together with environmental living and working conditions.