Identifying the dominant species in cereal-legume cover crop mixtures with remote sensing for nitrogen fertilization management

S.I. Futerman; Y. Laor; G. Eshel; Y. Cohen

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Identifying the dominant species in cereal-legume cover crop mixtures with remote sensing for nitrogen fertilization management

In: Precision agriculture '25

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S.I. Futerman

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Y. Laor

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G. Eshel

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Y. Cohen

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Type:: Chapter

Pages:: 808–813

DOI:: https://doi.org/10.1163/9789004725232_106

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Dar Hadith al Hassania

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The relative proportions of cereals and legumes in cover crop mixtures can be used as a proxy of soil available N. At low N, the ability of legumes to fix atmospheric N provides them with a distinctive advantage and they can outcompete the cereals, while at higher N levels, cereals outcompete the legumes. A clover/oat mixture was sown with four nitrogen treatments that significantly affected their relative abundance within the mixture. Machine learning techniques were used to classify the UAV-RGB images into cereal and legume classes. Classification accuracies were 93, 85 and 76% at 64, 77 and 87 days after sowing (DAS), respectively. Clover volume was generally higher in the lower N application rates while cereal volume was greater in the higher application rates, in agreement with biomass results.

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Precision agriculture '25

E-Book ISBN:: 9789004725232

Publisher:: Wageningen Academic

Print Publication Date:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Identifying the dominant species in cereal-legume cover crop mixtures with remote sensing for nitrogen fertilization management

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Precision agriculture '25

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