Non-destructive Assessment of Plant Nitrogen Parameters Using Leaf Chlorophyll Measurements in Rice - Ata-Ul-Karim, Syed Tahir; Cao, Qiang; Zhu, Yan; Tang, Liang; Rehmani, Muhammad Ishaq Asif; Cao, Weixing (Frontiers in Plant Science, 2016)
Non-destructive assessment of plant nitrogen (N) status is essential for efficient crop production and N management in intensive rice (Oryza sativa L.) cropping systems. Chlorophyll meter (SPAD-502) has been widely used as a rapid, non-destructive and cost-effective diagnostic tool for in-season assessment of crop N status. The present study was intended to establish the quantitative relationships between chlorophyll meters readings, plant N concentration (PNC), N nutrition index (NNI), accumulated N deficit (AND), and N requirement (NR), as well as to compare the stability of these relationships at different vegetative growth stages in Japonica and Indica rice cultivars. Seven multi-locational field experiments using varied N rates and seven rice cultivars were conducted in east China. The results showed that the PNC and chlorophyll meters readings increased with increasing N application rates across the cultivars, growing seasons, and sites. The PNC and chlorophyll meters readings under varied N rates ranged from 2.29 to 3.21, 1.06 to 1.82 and 37.10 to 45.4 and 37.30 to 46.6, respectively, at TL and HD stages for Japonica rice cultivars, while they ranged from 2.25 to 3.23, 1.34 to 1.91 and 35.6 to 43.3 and 37.3 to 45.5 for Indica rice cultivars, respectively. The quantitative relationships between chlorophyll meters readings, PNC, NNI, AND, and NR established at different crop growth stages in two rice ecotypes, were highly significant with R2 values ranging from 0.69 to 0.93 and 0.71 to 0.86 for Japonica and Indica rice, respectively. The strongest relationships were observed for AND and NR at panicle initiation and booting stages in both rice ecotypes. The validation of the relationships developed in the present study with an independent data exhibited a solid model performance and confirmed their robustness as a reliable and rapid diagnostic tool for in-season estimation of plant N parameters for sustainable N management in rice. The results of this study will offer a suitable approach for managing N application precisely during the growth period of the rice crop in intensive rice cropping systems in east China.