Use of a chlorophyll meter to assess nitrogen nutrition index during the growth cycle in winter wheat

•We studied the relationship between CMR and NNI throughout the growth cycle.•The use of normalized CMR improves the predictive value of NNI.•Growth stage is highly influential, even with normalized measurements.•Biomass and cultivar effects should be taken into account when using absolute CMR. We i...

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Bibliographic Details
Published in:Field crops research 2017-12, Vol.214, p.73-82
Main Authors: Ravier, Clémence, Quemada, Miguel, Jeuffroy, Marie-Hélène
Format: Article
Language:English
Subjects:
Environmental Sciences
Fertilization management
Life Sciences
Multi-model selection
NNI
Soil N
SPAD
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Summary:•We studied the relationship between CMR and NNI throughout the growth cycle.•The use of normalized CMR improves the predictive value of NNI.•Growth stage is highly influential, even with normalized measurements.•Biomass and cultivar effects should be taken into account when using absolute CMR. We investigated the feasibility of predicting crop nitrogen nutrition index (NNI) from chlorophyll meter readings (CMRs) during the crop cycle, for the development of a fertilization method for winter wheat (Triticum aestivum L.) based on the regular monitoring of crop N status. The relationship between NNI and CMR has been studied before, but only for CMRs obtained late in the season. A literature review revealed an absence of consensus concerning the most accurate equation for predicting NNI from CMR. It remains unclear which variables are the most influential and the extent to which it might be possible to overcome these uncertainties by using a normalized chlorophyll meter reading. We therefore carried out multimodel selection, comparing goodness-of-fit, prediction accuracy and likelihood, for linear, quadratic and exponential models, taking into account only biomass, cultivar, biomass plus cultivar and growth stage effects. Models were fitted with absolute and normalized measurements. We also considered the possibility of predicting NNI with a single model or with different models for each growth stage. We found that normalized measurements limited the biomass and cultivar effects, but not the growth stage effect. Furthermore, the use of normalized measurements increased prediction accuracy. However, the prediction error remained very high if the well-fertilized strip was N-deficient (NNI
ISSN:0378-4290
1872-6852
DOI:10.1016/j.fcr.2017.08.023