Prediction of physical attributes in fresh grapevine (Vitis vinifera L.) organs using infrared spectroscopy and chemometrics

Spectra obtained from fresh grapevine organs provide information on chemical composition but could also contain valuable information on the morphological and physical attributes. The prediction of grapevine organs physical attributes using infrared spectroscopy is explored for the first time in this study. Near infrared spectroscopy (NIR) using a solid probe (NIR-SP) and a rotating integrating sphere (NIR-RS) and mid infrared (MIR) were used to obtain spectra from fresh and intact grapevine shoots, leaves, and berries. Linear partial least squares (PLS) and non-linear least absolute shrinkage and selection operator (LASSO), and extreme gradient boost (XGBoost) were implemented to predict relevant physical attributes in grapevine organs. NIR-RS using XGBoost showed coefficients of determination in validation (R²val) of 91.01% and root mean square error of prediction (RMSEP) of 0.71 mm (6.80%) for berry diameter. Shoot diameter was predicted at R²val of 62.08% and RMSEP at 0.82 mm (12.75%) using NIR-RS with LASSO regression. Monitoring these attributes throughout the growing season can lead to important viticultural information on grapevine yield, growth, and health.