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Rapid estimation of nutritional elements on citrus leaves by near infrared reflectance spectroscopy

By Luis eGálvez Sola, Francisco eGarcía Sánchez, Juan Gabriel ePérez Pérez, Vicente eGimeno, Josefa eNavarro, Raul eMoral, Juan José eMartínez Nicolás and Manuel eNieves

Abstract

Sufficient nutrient application is one of the most important factors in producing quality citrus fruits. One of the main guides in planning citrus fertilizer programs is by directly monitoring the plant nutrient content. However, this requires analysis of a large number of leaf samples using expensive and time-consuming chemical techniques. Over the last five years, it has been demonstrated that it is possible to quantitatively estimate certain nutritional elements in citrus leaves by using the spectral reflectance values, obtained by using near infrared spectroscopy (NIRS). This technique is rapid, non-destructive, cost-effective and environmentally-friendly. Therefore, the estimation of macro and micronutrients in citrus leaves by this method would be beneficial in identifying the mineral status of the trees. However, to be used effectively NIRS must be evaluated against the standard techniques across different cultivars. In this study, NIRS spectral analysis, and subsequent nutrient estimations for N, K, Ca, Mg, B, Fe, Cu, Mn and Zn content, were performed using 217 leaf samples from different citrus trees species. Partial least square regression and different pre-processing signal treatments were used to generate the best estimation against the current best practice techniques. It was verified a high proficiency in the estimation of N (r=0.99) and Ca (r=0.98) as well as achieving acceptable estimation for K, Mg, Fe and Zn. However, no successful calibrations were obtained for the estimation of B, Cu and Mn

Topics: Calibration, Micronutrients, Nitrogen, NIRS, macronutrients, Nutritional status., Plant culture, SB1-1110
Publisher: Frontiers Media S.A.
Year: 2015
DOI identifier: 10.3389/fpls.2015.00571
OAI identifier: oai:doaj.org/article:a44964f4eef947ae9d2e8f7207f328fe
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