Torres Irina, Sánchez María-Teresa, Vega-Castellote Miguel, Luqui-Muñoz Natividad, Pérez-Marín Dolores
Department of Bromatology and Food Technology, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
Department of Bromatology and Food Technology, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Feb 5;246:118972. doi: 10.1016/j.saa.2020.118972. Epub 2020 Sep 23.
Cultural practices and harvesting in spinach plants should be based not only on subjective indexes such as freshness and green colour, which are both related with the visual appearance of the plants, but also on objective indexes that can be quantified non-destructively. The aim of this research was to develop a methodology based on the use of near infrared spectroscopy to monitor routinely the growth process of the spinach plants in the field. Using the MicroNIR™ OnSite-W spectrophotometer, which is ideally suited for in situ analysis, 261 spinach plants were analysed. Initially, calibration models for dry matter, soluble solid and nitrate contents were developed using 1 spectrum per plant for dry matter content, and nine spectra per plant for the other two parameters. These models were then validated using the same number of spectra per plant as for calibration purposes. After that, to establish a procedure more suitable to routine analysis in the field, the models were validated with only one spectrum per plant and the suitability of the predictions was measured considering the global and neighbourhood Mahalanobis distances, whose control limit values were defined as inferior to 4.0 and 1.0, respectively. The results showed that once the calibration models were developed, only one spectrum per plant was enough to predict dry matter and nitrate contents successfully. Therefore, the methodology developed will allow us to monitor in real time the complete growth process and to take decisions about spinach cultivation based on internal quality and safety indexes.
菠菜种植中的栽培措施和采收不仅应基于主观指标，如新鲜度和绿色，这两者都与植株的视觉外观有关，还应基于可以无损量化的客观指标。本研究的目的是开发一种基于近红外光谱法的方法，用于常规监测田间菠菜植株的生长过程。使用非常适合现场分析的MicroNIR™ OnSite-W分光光度计，对261株菠菜植株进行了分析。最初，针对干物质、可溶性固形物和硝酸盐含量建立了校准模型，干物质含量采用每株植物1个光谱，其他两个参数采用每株植物9个光谱。然后使用与校准相同数量的每株植物光谱对这些模型进行验证。之后，为了建立更适合田间常规分析的程序，使用每株植物仅1个光谱对模型进行验证，并考虑全局和邻域马氏距离来测量预测的适用性，其控制极限值分别定义为小于4.0和1.0。结果表明，一旦建立了校准模型，每株植物仅1个光谱就足以成功预测干物质和硝酸盐含量。因此，所开发的方法将使我们能够实时监测整个生长过程，并根据内部质量和安全指标对菠菜种植做出决策。
