Estimating nutrient uptake requirements for wheat in China.
Chuan, L., He, P., Jin, J.Y., Li, S., Grant, C.A., Xu, X., Qiu, S., Zhao, S., and Zhou, W. (2013). "Estimating nutrient uptake requirements for wheat in China.", Field Crops Research, 146, pp. 96-104. doi : 10.1016/j.fcr.2013.02.015 Access to full text
Estimating balanced nutrient requirement for wheat (Triticum aestivum L.) in China is essential to manage nutrient application more effectively for increasing crop yields and reducing risk of negative environmental impact. Datasets from 2000 to 2011 dealing with nitrogen (N), phosphorus (P) and potassium (K) treatments across the winter and spring wheat growing regions in China were collected to assess the relationship between grain yield and nutrient uptake, and to estimate N, P and K optimal nutrient requirements for a target yield using the QUEFTS (Quantitative Evaluation of the Fertility of Tropical Soils) model. In the QUEFTS model, two boundary lines described the minimum and maximum internal efficiencies (IEs, kg grain per kg nutrient in above-ground plant dry matter) of N, P and K. The minimum and maximum IEs for wheat were 28.8 and 62.6 kg grain per kg N, 98.9 and 487.4 kg grain per kg P, and 23.0 and 112.9 kg grain per kg K. The QUEFTS model predicted a linear–parabolic–plateau curve for balanced nutrient uptake with target yield increasing. The linear part continued until the yield was approximately at 60–70% of the potential yield, and 22.8 kg N, 4.4 kg P and 19.0 kg K were required to produce 1000 kg grain. The corresponding N:P:K ratio was 5.18:1:4.32, and the corresponding IEs were 43.9, 227.0 and 52.7 kg grain per kg N, P and K, respectively. The QUEFTS model simulated balanced N, P and K removal by 1000 kg grain were 18.3, 3.6 and 3.5 kg, respectively, with a N:P:K ratio of 5.08:1:0.97. Approximately 80%, 82% and 18% of N, P and K in total above-ground plant material were presented in the grain and removed from the field. The relationship between grain yield and nutrient uptake was also estimated to suggest fertilizer application avoiding excess or deficient nutrient supply. Field experiment validation confirmed that the QUEFTS model could be used as a practical tool for the Nutrient Expert decision support system to make fertilizer recommendation.
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