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Proximal fluorescence sensing of potassium responsive crops to develop improved predictions of biomass, yield and grain quality of wheat and barley

Precision Agriculture · 1 Apr 2019 · 10.1007/s11119-018-09629-3

Abstract

Precision nutrient management requires accurate assessment of crop nutrient status. This is common for assessing N status, but much less so for other nutrients. Because fluorescence can indicate crop stress, the robustness of different fluorescence indices was assessed to predict crop nutrient status (K, Mg and Ca). The hypothesis was that crop nutrition limitations, especially K, can be detected using fluorescence proximal sensing to quantify crop response with a high degree of spatial resolution. A factorial experiment was imposed with four treatment factors: crop, K fertilizer rate, lime and row management. The soil at the experimental site was K deficient and the crop variables showed significant treatment effects (e.g. yield, protein). Fluorescence sensing identified a significant positive K response for three chlorophyll related indices (SFR_G, SFR_R and CHL), but not for FLAV; while wheat was significantly different from barley. Using a k-fold cross-validation method promising predictive relationships were found. The strongest predictions were for SFR_R to predict crop biomass, for SFR_G to predict crop K content of inter-row wheat, for CHL to predict crop Ca content of inter-row wheat and for FLAV with barley grain protein in the windrow treatment. The fluorescence indices produced more significant crop variable predictions than measuring NDVI using an active sensor. This study illustrates the utility of fluorescence sensing to measure chlorophyll related signals for capturing the nutritional status of barley and wheat crops. These results show encouraging potential to rapidly detect crop nutrient status for non-N nutrients using fluorescence sensing.

Plant phenotyping relevance

小麦・オオムギの栄養状態、バイオマス、収量等を蛍光近接センシングで推定し、交差検証およびNDVIとの比較で性能を評価しており、フェノタイピング手法が中心である。

abstractUsing a k-fold cross-validation method promising predictive relationships were found.
abstractThis study illustrates the utility of fluorescence sensing to measure chlorophyll related signals for capturing the nutritional status of barley and wheat crops.
abstractThe fluorescence indices produced more significant crop variable predictions than measuring NDVI using an active sensor.

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