Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management

How well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Two fields in the Cambridgeshire Fens in eastern England where farmers grow lettuce commercially were studied. Topsoil was sampled and analysed for various nutrients, particle-size distribution, and organic carbon concentration. Crop measurements (lettuce diameter) were derived by photogrammetry. Reflectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering differences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values, with the latter showing a mean squared error (MSE) of 3.90 cm2 for Field 1 and 6.87 cm2 for Field 2. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than those that used the soil spectra as predictor variables (difference in MSE for Field 1: 0.69 cm2 and Field 2: 2.12 cm2). Predictions from LMMs were more precise than those from the raw spectra (by PLSR alone) with a difference in mean squared error (MSE) of 2.12 cm2 for Field 1 and of 5.10 cm2 for Field 2. All model predictions improved when the effects of variety were taken into account. Predictions from the reflectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their fields to maximize the net profit from the crop.