Principal Component Regression for Crop Yield Estimation

P. B. Mistry

ISBN 10: 9811006628 / ISBN 13: 9789811006623

Published by Springer Nature Singapore, Springer Nature Singapore, 2016

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book highlights the estimation of crop yield in CentralGujarat, especially with regard to the development of Multiple RegressionModels and Principal Component Regression (PCR) models using climatologicalparameters as independent variables and crop yield as a dependent variable. Itsubsequently compares the multiple linear regression (MLR) and PCR results, anddiscusses the significance of PCR for crop yield estimation. In this context,the book also covers Principal Component Analysis (PCA), a statistical procedureused to reduce a number of correlated variables into a smaller number ofuncorrelated variables called principal components (PC). This book will behelpful to the students and researchers, starting their works on climate andagriculture, mainly focussing on estimation models. The flow of chapters takesthe readers in a smooth path, in understanding climate and weather and impactof climate change, and gradually proceeds towards downscaling techniques andthen finallytowards development of principal component regression models andapplying the same for the crop yield estimation.

Seller Inventory # 9789811006623

Bibliographic Details

• Title: Principal Component Regression for Crop Yield Estimation
• Publisher: Springer Nature Singapore, Springer Nature Singapore
• Publication Date: 2016
• Language: English
• ISBN 10: 9811006628
• ISBN 13: 9789811006623
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 6D millimeters 235 millimeters width by 155 millimeters height by 6 millimeters depth
• Weight: 149 grams

About this title

Synopsis

This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finallytowards development of principal component regression models and applying the same for the crop yield estimation.

About the Author

Dr. T. M. V. Suryanarayana is serving as Associate Professor and recognized Ph.D. Guide in Water Resources Engineering and Management Institute, The M. S. University of Baroda. He is Executive Committee Member of Indian Water Resources Society, Secretary and Treasurer of Gujarat Chapter of Association of Hydrologists of India and Joint Secretary of Indian Society of Geomatics_Vadodara Chapter. He has 74 research papers published in various International/National Journals/ Seminars/ Conferences/ Symposiums.

Mr. P. B. Mistry has obtained B.E. (Civil-Irrigation Water Management) and M.E. (Civil) in Water Resources Engineering from The M.S. University of Baroda and is presently working as Assistant Professor in Parul University, Vadodara. He is a life member of Indian Society of Geomatics and Indian Society for Hydraulics.