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Article History

Received: 10 March 2026

Accepted: 2 September 2026

First Online: 10 September 2026

Declarations

Ethical approval and consent to participate: Not applicable. The present study consisted of image analysis of agricultural crop plant and weed images for developing and comparative evaluation for early-stage detection of weeds using machine learning and deep learning approach. There were no human subjects, human data, identifiable personal data or animal experimentation involved in the research. Therefore, this study did not require institutional ethics approval. The research was carried out based on appropriate institutional and research procedures for the collection, annotation, processing, and analysis of agricultural image data.

Consent to participate: Not applicable. This study was conducted without human participants or personal, identifiable or sensitive human data being collected. The images for the study were datasets comprising agricultural images: maize seedlings and weed types. To create a custom maize seed-ling dataset, image-level labels and pixel-wise segmentation masks were manually annotated by two annotators and an expert re-viewer.

Consent for publication: Not applicable. The manuscript does not include data that could identify personal information, identifiable individual information or images of human participants which would require consent for publication. The manuscript has been read and accepted by all the authors.

Competing interests: There is no conflict of interest in the authors. There is no financial interest that are directly and indirectly related to the work submitted for the publication.