Near infrared methodology for growth monitoring of spinach plants in the field

Abstract

Near Infrared (NIR) Spectroscopy is a powerful technology which can be implemented as a non-destructive tool to make decisions related to cultural practices and harvesting. However, prior to the incorporation of NIR sensors at field level as an analytical technique, a routine analysis procedure should be established. In this sense, this research is focused on the development of a methodology based on the use of a portable NIR instrument to monitor the growth process and to establish the optimum harvest time of spinach plants in the field. For this aim, calibration models for dry matter and nitrate contents were developed by means of Partial Least Squares (PLS) regression, using one spectrum per plant for dry matter content and nine spectra per plant for nitrate content taken with a portable spectrophotometer MicroNIR™ OnSite-W (908– 1676 nm). After that, to set a routine analysis methodology, the validation of the models was carried out using a single spectrum per plant selected at random and the suitability of the predictions was measured considering the Hotelling’s T² statistic, whose control limit value was as inferior to 60. The results demonstrated that once the calibration models were developed, only one spectrum per plant will enable to predict successfully dry matter and nitrate contents. Therefore, the methodology established will allow to monitor spinach plants during their growth in the field based on internal quality and safety indexes.