Integration of remote sensing and crop modeling for the early assessment of durum wheat harvest at the field scale

2015 - Crop Science, 55, 1-10
Orlando, F., Dalla Marta, A., Mancini, M., Motha, R., Qu, J.J., Orlandini, S.


In the Mediterranean environment, Triticum turgidum L. var. durum is one of the most important winter crops, but a high spatial and temporal variability of grain yield and grain protein concentration (GPC) prevents an adequate agronomic planning at the farm or consortium level. Although there are many studies on monitoring of crop production and early prediction of yields, little has been done at the local scale. The aim of this study was to assess simplified algorithms (SIAs) for integrating remote sensing information with a dynamic mechanistic-crop growth model, in order to forecast the quality (GPC) and quantity (grain yield) of durum wheat harvest at the field scale. To this end, CERES-Wheat model, initialized in absence of detailed input data, was run to simulate the seasonal average of grain yield and GPC in the rural district ‘Val d’ Orcia’ (Tuscany Region, Italy) during 2009-2010 and 2010-2011 growing seasons. The performances of different vegetation indices (NDVI, EVI, LAI, fPAR) from MODIS imagery in harvest forecasting were assessed and compared. The SIA formulation was based on the seasonal average of grain yield and GPC simulated by CERES-Wheat, and on the spatialization of these values in relationship to the intra-annual variability between the fields described by satellite vegetation indices.
The simulated seasonal average values of grain yield traced the observed trend. fPAR was the best index in describing grain yield and the related SIA showed at validation good performance at the field scale (r2 = 0.74). Conversely, the SIA for GPC prediction was not formalized due to the low performance of CERES-Wheat in capturing the inter-annual variability and to the failure of the vegetation index in describing the GPC inter-fields variability at intermediate canopy reflectance values.

Keywords: Durum wheat, vegetation indices, MODIS imagery, CERES-Wheat
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