Using Chlorophyll(SPAD) Meter Reading and Shoot Fresh Weight for Recommending Nitrogen Topdressing Rate at Panicle Initiation Stage of Rice

  • Nguyen, Hung The (Faculty of Resource and Environment Management, Thai Nguyen University of Agriculture and Forestry) ;
  • Nguyen, Lan The (Faculty of Agronomy, Thai Nguyen University of Agriculture and Forestry) ;
  • Yan, Yong-Feng (Department of Plant Science, Seoul National University) ;
  • Lee, Kyu-Jong (Department of Plant Science, Seoul National University) ;
  • Lee, Byun-Woo (Department of Plant Science, Seoul National University)
  • Published : 2007.03.31

Abstract

Nitrogen management at the panicle initiation stage(PI) should be fine-tuned for securing a concurrent high yield and high quality rice production. For calibration and testing of the recommendation models of N topdressing rates at PI for target grain yield and protein content of rice, three split-split-plot design experiments including five rice cultivars and various N rates were conducted at the experimental farm of Seoul National University, Korea from 2003 to 2005. Data from the first two years of experiments were used to calibrate models to predict grain yield and milled-rice protein content using shoot fresh weight(FW), chlorophyll meter value(SPAD), and the N topdressing rate(Npi) at PI by stepwise multiple regression. The calibrated models explained 85 and 87% of the variation in grain yield and protein content, respectively. The calibrated models were used to recommend Npi for the target protein content of 6.8%, with FW and SPAD measured for each plot in 2005. The recommended N rate treatment was characterized by an average protein content of 6.74%(similar to the target protein content), reduced the coefficient of variation in protein content to 2.5%(compared to 4.6% of the fixed rate treatment), and increased grain yield. In the recommended N rate treatments for the target protein content of 6.8%, grain yield was highly dependent on FW and SPAD at PI. In conclusion, the models for N topdressing rate recommendation at PI were successful under present experimental conditions. However, additional testing under more variable environmental conditions should be performed before universal application of such models.