Abstract
Few studies were focused on yield estimation of perennial fruit tree crops by integrating remotely-sensed information into crop models. This study presented an attempt to assimilate a single leaf area index (LAI) near to maximum vegetative development stages derived from Landsat satellite data into a calibrated WOFOST model to predict yields for jujube fruit trees at the field scale. Field experiments were conducted in three growth seasons to calibrate input parameters for WOFOST model, with a validated phenology error of −2, −3, and −3 days for emergence, flowering, and maturity, as well as an R2 of 0.986 and RMSE of 0.624 t ha−1 for total aboveground biomass (TAGP), R2 of 0.95 and RMSE of 0.19 m2 m−2 for LAI, respectively. Normalized Difference Vegetation Index (NDVI) showed better performance for LAI estimation than a Soil-adjusted Vegetation Index (SAVI), with a better agreement (R2 = 0.79) and prediction accuracy (RMSE = 0.17 m2 m−2). The assimilation after forcing LAI improved the yield prediction accuracy compared with unassimilated simulation and remotely sensed NDVI regression method, showing a R2 of 0.62 and RMSE of 0.74 t ha−1 for 2016, and R2 of 0.59 and RMSE of 0.87 t ha−1 for 2017. This research would provide a strategy to employ remotely sensed state variables and a crop growth model to improve field-scale yield estimates for fruit tree crops.
Highlights
Jujube tree (Zizyphus jujube) is an important economic tree species, which is mainly cultivated in the subtropical and tropical regions in Asia and America with a history of more than 3000 years
The peak correlation based on Normalized Difference Vegetation Index (NDVI) or Soil-adjusted Vegetation Index (SAVI) occurred on the 14th half-month, showing a max value of 0.84 for NDVI, 0.77 for SAVI, respectively
The results showed that the average correlation between NDVI and yield was higher than that of SAVI, with a 10% and 3% improvement of 14th and 15th half-months
Summary
Jujube tree (Zizyphus jujube) is an important economic tree species, which is mainly cultivated in the subtropical and tropical regions in Asia and America with a history of more than 3000 years. The Xinjiang Uygur Autonomous Region of China is the main production area of jujube fruits (>500,000 hectares) due to excellent light and heat conditions. With the expansion of the cultivated area, the regional scale yield prediction before harvest is essential for national planting policies, food security, and export strategies. The field-scale jujube growth and yield estimates before harvest allow farmers to improve yield management decision-making, such as irrigation, fertilization, pruning, and density selection, which is an important research topic of precision agriculture and forestry
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