Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy.

Abstract

The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar concentrations of macro and micronutrients in citrus plantations based on rapid non-destructive spectral measurements. To this end, 592 'Clementina de Nules' citrus leaves were collected during several months of growth. In these foliar samples, the spectral absorbance (430-1040 nm) was measured using a portable spectrometer, and the foliar ionomics was determined by emission spectrometry (ICP-OES) for macro and micronutrients, and the Kjeldahl method to quantify N. Models based on partial least squares regression (PLS-R) were calibrated to predict the content of macro and micronutrients in the leaves. The determination coefficients obtained in the model test were between 0.31 and 0.69, the highest values being found for P, K, and B (0.60, 0.63, and 0.69, respectively). Furthermore, the important P, K, and B wavelengths were evaluated using the weighted regression coefficients (BW) obtained from the PLS-R model. The results showed that the selected wavelengths were all in the visible region (430-750 nm) related to foliage pigments. The results indicate that this technique is promising for rapid and non-destructive foliar macro and micronutrient prediction.

Plant phenotyping relevance

携帯型Vis-NIR分光とPLS-Rによる柑橘葉の栄養濃度推定モデルを開発しており、植物形質取得・推定法が研究の中心である。

Code and data availability

The paper's spectral and ionomic citrus-leaf datasets, PLS-R models, and analysis code are not publicly available; the Data Availability Statement reads 'Not applicable' and no repository, supplement, or author URL for data or code is provided. All listed URLs are generic references or the article itself.

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