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Application of APSIM model in winter wheat growth monitoring. | LitMetric

AI Article Synopsis

  • This study improves winter wheat growth monitoring by combining traditional vegetation index methods, like NDVI, with field data and Sentinel-2 satellite data.
  • It introduces two new parameters - aboveground biomass (AGB) and leaf area index (LAI) - for a more thorough assessment of growth.
  • The research demonstrates that using AGB and LAI from the APSIM model results in strong correlations with field measures, advancing the accuracy of growth monitoring essential for precision agriculture strategies.

Article Abstract

In the past, the use of remote sensing for winter wheat growth monitoring mainly relied on the relative growth assessment of a single vegetation index, such as normalized Vegetation index (NDVI). This study advanced the methodology by integrating field-measured data with Sentinel-2 data. In addition to NDVI, it innovatively incorporated two parameters, aboveground biomass (AGB) and leaf area index (LAI), for a more comprehensive relative growth assessment. Furthermore, the study employed the agricultural production systems simulator (APSIM) model to use LAI and AGB for absolute growth monitoring. The results showed that the simulated LAI and AGB closely match the field-measured values throughout the entire growth period of winter wheat under various conditions (R > 0.9). For relative growth monitoring, NDVI showed significant linear positive correlations (r > 0.74 and P< 0.05) with both LAI and AGB simulated by the APSIM model. Overall, this research shows that LAI and AGB obtained from the APSIM model provide a more detailed and accurate approach to monitoring of winter wheat growth. This improved monitoring capability can support effective land management arable and provide technical guidance to advance precision agriculture practices.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602316PMC
http://dx.doi.org/10.3389/fpls.2024.1500103DOI Listing

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