ArticleData in brief2023
Experimental dataset of sugarcane-cover crop intercropping trials to control weeds in Reunion Island.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Predictive modeling, pattern recognition, and spatiotemporal representations of plant growth in simulated and controlled environments: A comprehensive review.Plant phenomics (Washington, D.C.) · 2025Review
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Authors and funding
8 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agroecological studies on sugarcane intercropping commonly generate complex datasets. A generic database (AEGIS - Agro-Ecological Global Information System) has been developed to facilitate the use of these datasets. The data described in this paper includes data from 8 experiments carried out on Reunion Island from 2012 to 2021 under three soil and climatic conditions to assess the capacity of cover crops in the sugarcane inter-row to control weed growth. Each experiment consisted of the comparison of three treatments in the inter-row: i) sugarcane with chemical weeding, ii) sugarcane with a cover crop sowed in the inter-row, and iii) sugarcane with spontaneous weed flora in the inter-row. The datasets contain data for sugarcane and cover crop observations (e.g., yield), weed flora, including 104 weed species (e.g., ground cover), crop management (including manual and chemical weedings), soil analyses, and daily weather. This dataset provides an adequate experimental dataset to calibrate or validate crop model simulations under intercropping.
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