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The nitrogen nutrition index (NNI) as an effective indicator for monitoring crop nitrogen (N) status has multiple applications in agriculture, such as estimating in-season crop N requirement (NR), predicting crop biomass/yield, and improving N use efficiency. The present study was aimed to develop basil (Ocimum basilicum L.) NR and relative biomass (RB) prediction models based on the concept of critical N concentration. Two experiments were carried out with different N application rates in the research greenhouse of University of Tehran, Iran. Basil NNI values were calculated using the previously developed critical N dilution curve. Subsequently, the in-season basil NR estimation model was developed as a function of NNI, N recovery efficiency (NRE) and plant age. Additionally, basil RB was simulated as a function of the averaged and integrated NNI based on a linear-plateau model. Moreover, a theoretical relationship between N utilization efficiency (NU t E) and the NNI was established. The validation results of the developed NR-NNI model demonstrated a good performance with a root mean square error (RMSE) and a normalized root mean square error (NRMSE) less than 5.28 kg ha −1  and 4.72%, respectively. The results showed that crop biomass and NNI were the most significant explanatory factors for the variations in basil NU t E. Therefore, the crop NNI can serve as a practical in-season diagnostic tool for basil NR and RB prediction, while also contributing to the design of decision support systems and sustainable agro-ecosystems.

Toward potential applications of the nitrogen nutrition index in Sweet basil ( Ocimum basilicum L.) production under greenhouse conditions