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Integrated UAV-Based Multi-Source Data for Predicting Maize Grain Yield Using Machine Learning Appro...

Integrated UAV-Based Multi-Source Data for Predicting Maize Grain Yield Using Machine Learning Appro...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cf21a5871bc140a5ac2d845aa88d290b

Integrated UAV-Based Multi-Source Data for Predicting Maize Grain Yield Using Machine Learning Approaches

About this item

Full title

Integrated UAV-Based Multi-Source Data for Predicting Maize Grain Yield Using Machine Learning Approaches

Publisher

Basel: MDPI AG

Journal title

Remote sensing (Basel, Switzerland), 2022-12, Vol.14 (24), p.6290

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Increases in temperature have potentially influenced crop growth and reduced agricultural yields. Commonly, more fertilizers have been applied to improve grain yield. There is a need to optimize fertilizers, to reduce environmental pollution, and to increase agricultural production. Maize is the main crop in China, and its ample production is of vi...

Alternative Titles

Full title

Integrated UAV-Based Multi-Source Data for Predicting Maize Grain Yield Using Machine Learning Approaches

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_cf21a5871bc140a5ac2d845aa88d290b

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cf21a5871bc140a5ac2d845aa88d290b

Other Identifiers

ISSN

2072-4292

E-ISSN

2072-4292

DOI

10.3390/rs14246290

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