Estimation of In-season Basil Nitrogen Requirement Using the Nitrogen Nutrition Index

Document Type : Research Paper

Authors

1 Department of Irrigation and Reclamation Engineering Faculty of Agriculture Engineering and Technology College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

2 Horticultural Sciences Department Faculty of Agriculture Engineering and Technology College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

Abstract

Nitrogen is one of the most widely used nutrients for crop development. Application of nitrogen fertilizers plays a crucial role in increasing agricultural yield and production. In order to achieve maximum crop yield and reduce the negative environmental effects, application of nitrogen fertilizers should be based on the dynamics between nitrogen supply and crop demand. In order to manage the consumption of nitrogen fertilizers, it is necessary to accurately predict the crop nitrogen requirements at different growth stages. In present study, the concept of critical nitrogen concentration (Nc) has been used as an effective approach to determine nitrogen status and estimate nitrogen requirement of basil. For this purpose, basil was cultivated in the research greenhouse of the College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Different nitrogen fertilizer treatments were applied at seven levels with three replications. Crop dry matter and nitrogen concentrations were measured seven times during the growth period. Then nitrogen nutrition index (NNI) and basil nitrogen requirement (NR) were calculated for the first experiment. Results showed that, there was a significant regression relationship between basil NNI and NR (R2> 0.96). Accordingly, the NR prediction model was developed using NNI values and day after planting (DAP). Then, accuracy and performance of the NR-NNI relationship were verified by the second experiment data. The values ​​obtained for RMSE, NMB and NRMSE statistical indicators were less than 1 kg / ha, 0.10% and 3.10%, respectively, which indicates high accuracy of the model for prediction of crop nitrogen requirement. In general, results showed that estimation of crop NR based on the concept of Nc could be used as a scientific and suitable approach for managing nitrogen application in agricultural production.

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References

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Iranian Journal of Soil and Water Research
Volume 51, Issue 8
October 2020
Pages 2039-2049

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