Limitations and solutions for developing a grain yield and protein content forecasting model based on vegetation indices in organic wheat production – on-farm experimentation-Reference-Cited by-同舟云学术

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Limitations and solutions for developing a grain yield and protein content forecasting model based on vegetation indices in organic wheat production – on-farm experimentation

Published:2024-06-06 Issue:3 Volume:40 Page:190-204
ISSN:0144-8765
Container-title:Biological Agriculture & Horticulture
language:en
Short-container-title:Biological Agriculture & Horticulture

Author:

Szigeti Nóra¹,Sulyán Péter Gábor¹,Labus Balázs¹,Földi Mihály¹,Hunyadi Éva¹,Mikó Péter²,Milibák Flóra¹,Drexler Dóra¹

Affiliation:

1. ÖMKi, Hungarian Research Institute of Organic Agriculture, Budapest, Hungary

2. Agricultural Institute, Centre for Agricultural Research, ELKH, Martonvásár, Hungary

Funder

Hungarian National Rural Network

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01448765.2024.2364304

Reference73 articles.

1. An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture

2. Crop Yield Prediction Using Multi Sensors Remote Sensing (Review Article)

3. Comparison of hydrological and vegetation remote sensing datasets as proxies for rainfed maize yield in Malawi

4. Applicability of machine learning techniques in predicting wheat yield based on remote sensing and climate data in Pakistan, South Asia

5. Mapping Wheat Dry Matter and Nitrogen Content Dynamics and Estimation of Wheat Yield Using UAV Multispectral Imagery Machine Learning and a Variety-Based Approach: Case Study of Morocco

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