Abstract

Rapid and non-destructive diagnostic tools to accurately assess crop nitrogen nutrition index (NNI) are imperative for improving crop nitrogen (N) diagnosis and sustaining crop production. This study was aimed to develop the relationships among NNI, leaf N gradient, chlorophyll meter (CM) readings gradient, and positional differences chlorophyll meter index [PDCMI, the ratio of CM readings between different leaf layers (LLs) of crop canopy] and to validate the accuracy and stability of these relationships across the different LLs, years, sites, and cultivars. Six multi-N rates (0–320 kg ha−1) field experiments were conducted with four summer maize cultivars (Zhengdan958, Denghai605, Xundan20, and Denghai661) at two different sites located in China. Six summer maize plants per plot were harvested at each sampling stage to assess NNI, leaf N concentration and CM readings of different LLs during the vegetative growth period. The results showed that the leaf N gradient, CM readings gradient and PDCMI of different LLs decreased, while the NNI values increased with increasing N supply. The leaf N gradient and CM readings gradient increased gradually from top to bottom of the canopy and CM readings of the bottom LL were more sensitive to changes in plant N concentration. The significantly positive relationship between NNI and CM readings of different LLs (LL1 to LL3) was observed, yet these relationships varied across the years. In contrast, the relationships between NNI and PDCMI of different LLs (LL1 to LL3) were significantly negative. The strongest relationship between PDCMI and NNI which was stable across the cultivars and years was observed for PDCMI1−3 (NNI = −5.74 × PDCMI1−3+1.5, R2 = 0.76**). Additionally, the models developed in this study were validated with the data acquired from two independent experiments to assess their accuracy of prediction. The root mean square error value of 0.1 indicated that the most accurate and robust relationship was observed between PDCMI1–3 and NNI. The projected results would help to develop a simple, non-destructive and reliable approach to accurately assess the crop N status for precisely managing N application during the growth period of summer maize crop.

Highlights

  • Nitrogen nutrition index (NNI) is the most widely recognized diagnostic tool used for accurately diagnosing the in-season crop N status (Lemaire et al, 2008)

  • The results showed that the intercepts (b) of the linear regression models between NNI and chlorophyll meter (CM) readings for LL1, LL2, and LL3 were significantly different in two growing years (P < 0.05)

  • The results showed that root mean square error (RMSE) value between the predicted and observed NNI values were 0.1 for PDCMI1–3 (Figure 6)

Read more

Summary

Introduction

Nitrogen nutrition index (NNI) is the most widely recognized diagnostic tool used for accurately diagnosing the in-season crop N status (Lemaire et al, 2008). Several factors such as plant growth stage, cultivar, specific leaf weight, leaf thickness, leaf position on the plant, measurement location on a leaf as well as environmental stresses and solar radiation could significantly affect CM readings (Ziadi et al, 2008; Ata-Ul-Karim et al, 2016b; Zhao et al, 2016) Variations in these factors lead to the relatively poor relationships between CM readings and leaf N concentration or leaf chlorophyll (Bullock and Anderson, 1998). The adjusted CM readings can significantly improve the estimation of leaf N concentration, yet this estimation is complex, time-consuming, and destructive as compared to the unadjusted CM readings (Peng et al, 1993)

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.