کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8877333 1624116 2018 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application of Statistical Tools for Data Analysis and Interpretation in Rice Plant Pathology
ترجمه فارسی عنوان
استفاده از ابزارهای آماری برای تجزیه و تحلیل داده ها و تفسیر آن در آسیب شناسی گیاه
کلمات کلیدی
ابزار آماری، تجزیه و تحلیل اطلاعات پاتولوژی گیاه تجزیه و تحلیل چند متغیره، تجزیه و تحلیل غیر پارامتری، تجزیه و تحلیل میکرو آرایه، تئوری تصمیم گیری، بیماری های گیاهی همه گیر، برنج،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی
There has been a significant advancement in the application of statistical tools in plant pathology during the past four decades. These tools include multivariate analysis of disease dynamics involving principal component analysis, cluster analysis, factor analysis, pattern analysis, discriminant analysis, multivariate analysis of variance, correspondence analysis, canonical correlation analysis, redundancy analysis, genetic diversity analysis, and stability analysis, which involve in joint regression, additive main effects and multiplicative interactions, and genotype-by-environment interaction biplot analysis. The advanced statistical tools, such as non-parametric analysis of disease association, meta-analysis, Bayesian analysis, and decision theory, take an important place in analysis of disease dynamics. Disease forecasting methods by simulation models for plant diseases have a great potentiality in practical disease control strategies. Common mathematical tools such as monomolecular, exponential, logistic, Gompertz and linked differential equations take an important place in growth curve analysis of disease epidemics. The highly informative means of displaying a range of numerical data through construction of box and whisker plots has been suggested. The probable applications of recent advanced tools of linear and non-linear mixed models like the linear mixed model, generalized linear model, and generalized linear mixed models have been presented. The most recent technologies such as micro-array analysis, though cost effective, provide estimates of gene expressions for thousands of genes simultaneously and need attention by the molecular biologists. Some of these advanced tools can be well applied in different branches of rice research, including crop improvement, crop production, crop protection, social sciences as well as agricultural engineering. The rice research scientists should take advantage of these new opportunities adequately in adoption of the new highly potential advanced technologies while planning experimental designs, data collection, analysis and interpretation of their research data sets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Rice Science - Volume 25, Issue 1, January 2018, Pages 1-18
نویسندگان
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