| Autor: |
Jing Cui, Juan Manuel Chao de la Barca, Emmanuelle Lamade, Guillaume Tcherkez |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Plants, People, Planet, Vol 3, Iss 4, Pp 350-354 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2572-2611 |
| DOI: |
10.1002/ppp3.10169 |
| Popis: |
Societal Impact Statement Oil palm is the first oil‐producing crop globally, representing nearly 20 million ha. In the recent past, oil palm cultivation has been controversial not only because of land utilisation at the expense of primary tropical forests or health concerns associated with palm oil, but also pollution caused by fertilization (including CO2 produced to synthesise fertilizers). Oil palm fields are heavily fertilized with potassium (K), and thus finding better, more parsimonious methods to monitor K nutrition is more important than ever. Here, we suggest that metabolomics and subsequent machine learning of metabolic signatures represent a promising tool to probe K requirements, opening avenues for precision agriculture in oil palm industry. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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