Sunflower crop yield prediction by advanced statistical modeling using satellite-derived vegetation indices and crop phenology-Reference-Cited by-同舟云学术

Sunflower crop yield prediction by advanced statistical modeling using satellite-derived vegetation indices and crop phenology

Published:2023-04-03 Issue:1 Volume:38 Page:
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Amankulova Khilola¹²^ORCID,Farmonov Nizom¹²^ORCID,Mukhtorov Uzbekkhon²^ORCID,Mucsi László¹^ORCID

Affiliation:

1. Department of Geoinformatics, Physical and Environmental Geography, University of Szeged, Szeged, Hungary

2. “Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, Uzbekistan

Funder

University of Szeged Open Access Fund

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2023.2197509

Reference58 articles.

1. Oilseed crop sunflower ( Helianthus annuus ) as a source of food: Nutritional and health benefits

2. Amankulova K Farmonov N Gudmann A Mucsi L. 2021. Investigation the reason of affected Hybrid Corn in Agricultural Fields by Using Multi-Temporal Sentinel-2 Images in Mezőhegyes South-Eastern Hungary.

3. Time-series analysis of Sentinel-2 satellite images for sunflower yield estimation

4. Prediction of sunflower grain oil concentration as a function of variety, crop management and environment using statistical models

5. Bell MA. 1994. Guide to plant and crops sampling: measurements and observations for agronomic and physiological research in small grain cereals. Mexico: CIMMYT.

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