Groundnut (Arachis hypogaeaL.) improvement in sub-Saharan Africa: a review-Reference-Cited by-同舟云学术

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Groundnut (Arachis hypogaeaL.) improvement in sub-Saharan Africa: a review

Published:2019-04-07 Issue:6 Volume:69 Page:528-545
ISSN:0906-4710
Container-title:Acta Agriculturae Scandinavica, Section B — Soil & Plant Science
language:en
Short-container-title:Acta Agriculturae Scandinavica, Section B — Soil & Plant Science

Author:

Abady Seltene¹²³⁴,Shimelis Hussein³,Janila Pasupuleti⁴,Mashilo Jacob³

Affiliation:

1. School of Plant Sciences, Haramaya University, Dire Dawa, Ethiopia

2. School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Scottsville, South Africa

3. African Centre for Crop Improvement (ACCI), Pietermaritzburg, South Africa

4. International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Telangana, India

Funder

Haramaya University

ICRISAT

University of KwaZulu-Natal

Publisher

Informa UK Limited

Subject

Soil Science,Agronomy and Crop Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/09064710.2019.1601252

Reference161 articles.

1. Enhanced Expression of AtNHX1, in Transgenic Groundnut (Arachis hypogaea L.) Improves Salt and Drought Tolerence

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modifying row-configuration and vermicompost application reduces intercropped peanut (Arachis hypogaea L.) yield instability and penalty in sorghum at Babile, Eastern Ethiopia;Heliyon;2024-08

2. Evaluation of Production and Pest Management Practices in Peanut (Arachis hypogaea) in Ghana;Agronomy;2024-05-06

3. Comparing Regression and Classification Models to Estimate Leaf Spot Disease in Peanut (Arachis hypogaea L.) for Implementation in Breeding Selection;Agronomy;2024-04-30

4. Pod Yield Stability of Best Groundnut Varieties from National Agricultural Research Stations Program in West Africa;American Journal of Agriculture and Forestry;2024-04-29

5. Estimating rainfed groundnut’s leaf area index using Sentinel-2 based on Machine Learning Regression Algorithms and Empirical Models;Precision Agriculture;2024-02-21

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