Overview
- Provides innovative analysis solutions using machine learning to diagnose and predict banana wilting
- Analyzes soil morphological variables to characterize soil productivity for growing healthy bananas
- Discusses pioneering research in the application of categorical regression
Part of the book series: The Latin American Studies Book Series (LASBS)
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About this book
This book presents an important contribution to the knowledge of the banana soils of Venezuela. Banana, the edible fruit of Musaceae, is a staple food for more than 400 million people worldwide due to their nutritional and energy attributes. This makes Musaceae a crop of worldwide relevance, particularly in tropical regions, highlighting the impact of improved Musaceae cropping systems in the current efforts worldwide oriented towards a new agricultural revolution based on sustainable intensification. To achieve this, better practices for food production based on scientific and technical research capable to consider the complexity and variability within the agri-food sector are necessary. The research presented in this book is oriented towards providing answers to the causes of two aspects considered of high relevance for banana production, both affecting productivity and sustainability, always addressed for the Venezuelan conditions, one of the world’s largest producing countries: 1- The impact of phytosanitary risks related to Fusarium Wilt (FW) and the influence of the soil on the incidence of Banana Wilt (BW); and 2- An observed trend towards loss of productivity and decline of soil quality in some commercial farms of Aragua and Trujillo states in Venezuela.
The book presents a pioneering study in the application of categorical regression (CATREG) in the characterization of banana soils and analyses soil morphological variables, such as texture, dry consistency, biological activity, reaction to HCl, and type of structure to characterize soil productivity for growing healthy bananas. It develops, for the first time in Venezuela, risk analysis and climatic suitability maps for lethal wilt disease in bananas caused by Fusarium oxysporum f. sp. cubense (Foc) Tropical Race 4 (TR4) (syn. Fusarium odoratissimum). Innovative machine learning techniques are used to predict BW so that future crop development can be done more efficiently and sustainably.
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
About the author
Barlin Orlando Olivares Campos is hired as a researcher in the Biodiversity Management Research Group (GESBIO-UCO) and completed his Ph.D. Cum Laude in Agricultural, Food, Forestry Engineering, and Sustainable Rural Development from the Agrifood Campus of International Excellence (CeiA3) of the University of Cordoba (UCO) Spain (2022) through a scholarship from the Iberoamerican Postgraduate University Association (AUIP), his outstanding scientific activity earned him the UCO Extraordinary Ph.D. Award (2022). He is an Agricultural Engineer from the Central University of Venezuela (2009) and a master’s degree in Environmental Technology from the International University of Andalusia, Spain (2015) through a Carolina Foundation scholarship. He is the author of journal articles, books, and chapters book, he also obtained various fellowships, accreditations, and recognitions, as well as participation in projects for the dissemination of agricultural science. He has carried out six research stays in international universities of Argentina, Chile, Costa Rica, Colombia, Spain, and Panama.
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Bibliographic Information
Book Title: Banana Production in Venezuela
Book Subtitle: Novel Solutions to Productivity and Plant Health
Authors: Barlin Orlando Olivares Campos
Series Title: The Latin American Studies Book Series
DOI: https://doi.org/10.1007/978-3-031-34475-6
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-34474-9Published: 13 July 2023
Softcover ISBN: 978-3-031-34477-0Published: 15 July 2024
eBook ISBN: 978-3-031-34475-6Published: 12 July 2023
Series ISSN: 2366-3421
Series E-ISSN: 2366-343X
Edition Number: 1
Number of Pages: XXI, 176
Number of Illustrations: 5 b/w illustrations, 51 illustrations in colour
Topics: Agriculture, Plant Sciences, Plant Sciences