Near infrared reflectance spectroscopy (NIRS) evaluation of the nutritive value of leaf and green pruning residues of grapevine (Vitis vinifera L.).

The aim of this study has been to investigate the efficiency of NIR scanning to detect differences related to the chemical composition, gross energy, in vitro apparent digestibility (DMD) and relative feed value (RFV) of leaves and green pruning residues (GPRs) of eleven red grapevine cultivars (Barbera, Cabernet Sauvignon, Cabernet Franc, Canaiolo Nero, Carignan Noir, Grenache, Lambrusco Salamino, Nebbiolo, Pinot Noir, Sangiovese and Syrah) and five white grapevine cultivars (Malvasia Bianca, Moscato Bianco, Sauvignon Blanc, Verdicchio and Vernaccia). Vibrational analyses were performed on lyophilized samples in reflectance mode using an NIR-SCÏOTM molecular sensor, that is, a miniaturized web-based device that operates over the 740-1070 nm NIR range. The present study demonstrates that the RFV of the considered grape leaves is 22.5% higher than that of the grape GPRs. This feed value may be predicted by means of NIR spectroscopy of the lyophilized samples; however, such information could also easily be approximated through a rapid NIR tomoscopy of adequate samples of intact leaves. Foliar moisture could be predicted by means of NIR tomoscopy of intact leaves, after the grape dataset has been enlarged appropriately. A concerted elaboration of the chemical and digestibility analyses leads to a significant compositional fingerprint of the sixteen cultivars studied here. NIR tomoscopy can be used to rapidly classify the phenotypes, since other physico-chemical information that is not revealed by means of the usual analyses are incorporated in the electromagnetic spectrum. Other key biological properties (polyphenols, antioxidants, stress reaction, etc.) that are prospected for precision agriculture purposes could be revealed by a rapid NIR scan and perhaps even through remote NIR sensing.