Pradeep Mishra – författare

An understanding of the basics, logic, and theory of statistics is essential for agricultural researchers for dealing with the interpretation of data. This volume presents some of the basic and necessary concepts of statistical tools, specifically as applied to the statistics of agriculture and allied fields. It covers basic statistics, design of experiments, sampling techniques, time series, inference outlines, forecasting models, data handling, and statistical software in an easy-to-understand manner that is aimed at students and researchers with little or no mathematical background.

In the agriculture scenario, students and researchers face problems that can be addressed with statistical tools, planning of field experiments, collection of data, analysis, interpretation of the data, etc. In this book, statistical theories are discussed with the help of examples from real-life situations in agriculture and allied fields, followed by worked-out examples. Each chapter is followed by a number of problems and questions that will help readers gain confidence in solving those problems. The volume also provides an analysis of how data is important and introduces the reader to using statistical software such as MS Excel, SAS (Statistical Analysis System), JMP, Minitab, and R (from the R Foundation for Statistical Computing).

An understanding of the basics, logic, and theory of statistics is essential for agricultural researchers for dealing with the interpretation of data. This volume presents some of the basic and necessary concepts of statistical tools, specifically as applied to the statistics of agriculture and allied fields. It covers basic statistics, design of experiments, sampling techniques, time series, inference outlines, forecasting models, data handling, and statistical software in an easy-to-understand manner that is aimed at students and researchers with little or no mathematical background.

In the agriculture scenario, students and researchers face problems that can be addressed with statistical tools, planning of field experiments, collection of data, analysis, interpretation of the data, etc. In this book, statistical theories are discussed with the help of examples from real-life situations in agriculture and allied fields, followed by worked-out examples. Each chapter is followed by a number of problems and questions that will help readers gain confidence in solving those problems. The volume also provides an analysis of how data is important and introduces the reader to using statistical software such as MS Excel, SAS (Statistical Analysis System), JMP, Minitab, and R (from the R Foundation for Statistical Computing).

Recent Advancement in Prodrugs

Drugs used as medicines have many limitations like low chemical stability, aqueous solubility, or oral absorption/bioavailability, rapid presystemic metabolism, toxicity, inadequate site specificity, or poor patient acceptance/compliance (unwanted adverse effects, unacceptable taste or odor, irritation or pain). Prodrugs design is an approach to overcome these limitations.

Key features

This book covers recent advances in the design of prodrugs. It contains all the significant recent examples of prodrug chemistry developments and will aid academics and researchers seeking to generate new projects in the field.

Recent Advancement in Prodrugs

Drugs used as medicines have many limitations like low chemical stability, aqueous solubility, or oral absorption/bioavailability, rapid presystemic metabolism, toxicity, inadequate site specificity, or poor patient acceptance/compliance (unwanted adverse effects, unacceptable taste or odor, irritation or pain). Prodrugs design is an approach to overcome these limitations.

Key features

This book covers recent advances in the design of prodrugs. It contains all the significant recent examples of prodrug chemistry developments and will aid academics and researchers seeking to generate new projects in the field.

This book provides a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation. It presents a detailed explanation of different distribution concepts used in statistics along with their application in real-life situations. Covering the analytical aspects using the latest software, the volume discusses stochastic methods and other statistical methods. It provides an overview of statistical data analysis by taking actual situations and implementing open-source software R version 4.0 and Python 3.0+. A detailed study of the statistical models is also provided with examples related to health, agriculture, insurance, and other sectors.

This book provides a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation. It presents a detailed explanation of different distribution concepts used in statistics along with their application in real-life situations. Covering the analytical aspects using the latest software, the volume discusses stochastic methods and other statistical methods. It provides an overview of statistical data analysis by taking actual situations and implementing open-source software R version 4.0 and Python 3.0+. A detailed study of the statistical models is also provided with examples related to health, agriculture, insurance, and other sectors.

This book aims to explore the groundbreaking intersection of artificial intelligence (AI) and agriculture, focusing on how innovative technologies can be harnessed to create sustainable and resilient food systems. As global challenges such as climate change, population growth, and resource scarcity intensify, this book seeks to provide a comprehensive guide to leveraging AI for optimizing agricultural practices, enhancing productivity, and promoting environmental stewardship. The final chapter summarizes key findings, highlighting the overarching themes, and providing insights into the future of AI in agriculture. Emphasis is placed on the importance of collaboration, ethical considerations, and responsible deployment of AI technologies to ensure a sustainable and equitable food future. This book is intended for a diverse audience, including researchers, academics, policymakers, agri-tech professionals, farmers, and students interested in the future of agriculture, sustainability, and emerging technologies.