Rapid identification of greenhouse tomato senescent leaves based on the sucrose-spectral quantitative prediction model

Removing senescent leaves is vital for boosting greenhouse tomato yield. This study suggests utilising sucrose concentrations in tomato petiole ends as an indicator for assessing leaf senescence. Sucrose concentrations in different leaf positions were analysed during fruiting, pre-harvesting, and harvesting periods. Leaf area and photosynthetically active radiation (PAR) data from tomato plants were input into tomato photosynthesis and respiration models simulating the yield for each compound leaf. The hyperspectral technique enabled rapid and non-destructive determination of sucrose concentration in tomato petioles using a portable spectroradiometer (ASD Fieldspec® 3) that measured spectral reflectance in 120 petiole samples. Raw spectral reflectance underwent various pretreatments. Principal component analysis (PCA) reduced data dimensions, and sucrose-spectral quantitative prediction models were established using support vector regression (SVR), k-nearest neighbour (KNN), and partial least squares (PLS). The best model for sucrose-spectral quantitative prediction was obtained by moving average (MA) preprocessing, PCA dimensionality reduction and PLS algorithm, resulting in determination coefficient of prediction set (Rp2) of 0.98 and residual predictive deviation (RPD) of 7.12. Sucrose quantitative prediction and photosynthetic respiration models exhibited a parallel trend, with assimilation capacity increasing and then decreasing with leaf position, indicating that functional leaves produce the most assimilates. Young leaves, being immature, produce limited assimilates. Despite well-developed senescent leaves, the occlusion by upper leaves hinders the release of photosynthetic potential, resulting in negative net assimilates. These findings provide compelling evidence that spectroscopy can quantitatively predict sucrose concentration in tomato petioles, aiding in effective senescent leaf identification.