Abstract
Proximal and remote sensors have proved their effectiveness for the estimation of several biophysical and biochemical variables, including yield, in many different crops. Evaluation of their accuracy in vegetable crops is limited. This study explored the accuracy of proximal hyperspectral and satellite multispectral sensors (Sentinel-2 and WorldView-3) for the prediction of carrot root yield across three growing regions featuring different cropping configurations, seasons and soil conditions. Above ground biomass (AGB), canopy reflectance measurements and corresponding yield measures were collected from 414 sample sites in 24 fields in Western Australia (WA), Queensland (Qld) and Tasmania (Tas), Australia. The optimal sensor (hyperspectral or multispectral) was identified by the highest overall coefficient of determination between yield and different vegetation indices (VIs) whilst linear and non-linear models were tested to determine the best VIs and the impact of the spatial resolution. The optimal regression fit per region was used to extrapolate the point source measurements to all pixels in each sampled crop to produce a forecasted yield map and estimate average carrot root yield (t/ha) at the crop level. The latter were compared to commercial carrot root yield (t/ha) obtained from the growers to determine the accuracy of prediction. The measured yield varied from 17 to 113 t/ha across all crops, with forecasts of average yield achieving overall accuracies (% error) of 9.2% in WA, 10.2% in Qld and 12.7% in Tas. VIs derived from hyperspectral sensors produced poorer yield correlation coefficients (R2 < 0.1) than similar measures from the multispectral sensors (R2 < 0.57, p < 0.05). Increasing the spatial resolution from 10 to 1.2 m improved the regression performance by 69%. It is impossible to non-destructively estimate the pre-harvest spatial yield variability of root vegetables such as carrots. Hence, this method of yield forecasting offers great benefit for managing harvest logistics and forward selling decisions.
Highlights
Carrot (Daucus carota L.), grown in more than 25 countries, is one of the most economically important vegetables in the world because of its significance to food security and dietary benefits to humans
EVI2 performed better in Qld (R2 = 0.55), whilst for the Western Australia (WA) region, GNDVI was optimal (R2 = 0.29). These results indicate that vegetation indices (VIs) were more susceptible to regional changes than the pure reflectance per band as their prediction performance varied across regions while the reflectance curves remained similar (Fig. 7)
This study evaluated the potential of remote sensing for predicting carrot yield and for the derivation of pre-harvest yield maps
Summary
Carrot (Daucus carota L.), grown in more than 25 countries, is one of the most economically important vegetables in the world because of its significance to food security and dietary benefits to humans. In Australia, carrots are the third largest (by volume/tonnage) vegetable crop produced (around 318 000 t) and the fifth most valuable vegetable grown (about $231 million, 2017 value) (Horticulture Innovation Australia Limited 2018). There are five major carrot production areas in Australia: Western Australia (Gingin and Preston), Victoria (East Gippsland), South Australia (Riverland) and Tasmania (Forth). The production area increased by 15% from 2015 to 2016. About two-thirds of consumption is domestic with more than 89% of Australian households regularly purchasing fresh carrots. 10 t were imported, while nearly 103 000 t were exported, in 2016/2017 (Horticulture Innovation Australia Limited 2018)
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