Rapid and nondestructive estimation of the nitrogen nutrition index in winter barley using chlorophyll measurements

•The fourth leaf from top of the canopy could better reflect plant nitrogen (N) status in winter barley.•The chlorophyll meter (CM) readings gradient is a good proxy of leaf N gradient.•The N nutrition index (NNI) and CM reading relations were not stable across cultivars and seasons.•The positional difference chlorophyll measurements index (PDCMI) of different leaves had significant negative relationships with N nutrition index expect for PDCMI12 and PDCMI13.•The NNI and PDCMI14 relations were stable across the cultivars and seasons.

Rapid, accurate and dynamic diagnosis of nitrogen (N) status is essential for evaluating plant vigor, predicting crop production and optimizing N management in winter barley (Hordeum vulgare L.). The objectives of this study were to determine the correlations between N nutrition index (NNI), leaf N gradient and chlorophyll meter (CM) readings gradient for different leaf positions and to compare the stability of the relationships between NNI and CM readings as well as between NNI and positional differences chlorophyll measurements index (PDCMI) in different cultivars and environments. Four multi-locational field experiments using five winter barley cultivars (Supi6, Yangpi4, Yangnongpi8, Supi2, Dan2) and varied N rates (0–300 kg ha−1) were conducted in this study. NNI, leaf N gradient, CM readings, CM readings gradient and PDCMI were determined for growth analyses from Feekes 6 to Feekes 10.51. Our results represented that the NNI and CM readings increased with increasing N application rates. In contrast, the PDCMI decreased with increasing N application rates. Further, the leaf N gradient of the canopy was not uniform, the lower leaf position could better reflect N status in winter barley plants, and the CM readings gradient was a good proxy of leaf N gradient. The CM readings at different leaf positions showed a significantly positive relatation to NNI, yet the relationship varied among cultivars and seasons. In contrast, the PDCMI of different leaves showed significantly negative relation to NNI, with the exception of PDCMI12 and PDCMI13. The strongest correlation between NNI and PDCMI was found for PDCMI14 (NNI = −1.927 × PDCMI14 + 1.17, R = –0.838**), which was stable across the cultivars and seasons. Validation of the relationships with independent data produced a root mean squared error (RMSE) of 0.13 between the predicted and observed NNI values. This robust and stable relationship between PDCMI14 and NNI could be used as a reliable tool to diagnose plant N status of winter barley in eastern China.