Geodaysit 2023

Foliar NIR Spectroscopy and EOS platform for monitoring polyphenolic maturity in Nebbiolo

A. Cugnetto1, M. Altare2, G. Masoero 1,3, S. Guidoni 3,1.

1 Accademia di Agricoltura di Torino (TO)
2 Az. Vitivinicola Costa di Bussia, Monforte (CN)
3 Dipartimento Scienze Agrarie, Forestali e Alimentari, Università di Torino (TO)

A Nebbiolo vineyard was divided into three vigor zones (High, Medium, Low) according to the NDVI index survey supplied by EOS Crop Monitoring web platform. In four sessions, leaf samples were collected on which petiolar pH [1] and the NIR spectrum were determined using the SCiOTM v 1.2 apparatus (740-1070 nm, 331 reflectance points). From samples of 10 berries the seeds were cleaned and scanned by NIRS obtaining 99 spectra. The polyphenolic maturity of the seeds was expressed based on the Non-Extractable Polyphenols / Extractable Polyphenols (PSM) ratio, analyzed according to the Di Stefano method [2]. The value was estimated by a WinISI-II PLS equation recalculated on published data [3] which has a predictive value of R2 = 0.70 and RMSE error = 8%. From the NIR spectra of 164 leaves a SPAD value was estimated (by unpublished equation) and the PSM of the seeds was regressed on the 16 composition parameters [4]. The most important variables that explain the model, were those related to the bromatological composition of the vegetal wall (Cellulose, ADL, digestible-NDF, non-digestible-NDF, Total digestibility). The fitting of the 10 vines vigor group gave an R2 = 0.88 (Mean RMSE 12%). The petiolar pH did not show significant relations with the seeds PSM. The direct calibration of the NIR spectrum on the seeds PSM made with the WinISI, revealed an R2 = 0.84 (MRMSE 5%, with an outlier group), while using the PLSR of LabSCiO we obtained R2=0.73 (MRMSE 6% with an outlier group).
This part of the work demonstrates that a proximal scrutiny of the NIR spectrum of Nebbiolo leaves allow an estimation of the maturity of the seed polyphenols provided that the result is consolidated with the mean of at least 15 replicate measurements.
Once the individual calculations were examined, the group averages were processed by performing a linear regression of the PSM on the averages of the available variables extracted from the NIR spectra, and on the NDVI measurements taken from the Sentinel-2 satellite. The examined variables had different importance and the SPAD (R2=0.49) had the maximum one. The NDVI from satellite had fitted to the seeds PSM with R2 = 0.34; it was under the forecast accuracy provided by the leaves spectra set, but is worthy of attention for the simplicity of use. The obtained linear equation was PSM = 5.71 + 2.42 * NDVI.

The work demonstrates that with the modern Satellite remote sensing technologies, it is possible to improve the grape sampling during the maturation period, better identifying the internal plot variability, that is related to different seed ripening levels. The leaf NIR spectra detected at ground level with SCIOTM v 1.2, is a rapid proximal method for estimating the Nebbiolo seed ripening, directly in the farm

1 Masoero G, Cugnetto A. 2018 The raw pH in plants: a multifaceted parameter. Journal of Agronomy Research, 1: (2), 18-34. ISSN: 2639-3166. DOI10.14302/issn.2639-3166.jar-18-2397. https://openaccesspub.org/jar/article/871
2 Di Stefano R, Cravero MC. 1991 Metodi per lo studio dei polifenoli nell'uva. Riv. Vitic. Enol, 2, 37-45.
3 Cugnetto A, Masoero G. (2021) Colored anti-hail nets modify the ripening parameters of Nebbiolo (Vitis vinifera L.) and a smart NIRS can predict the polyphenol features. JAR 4 (1), 24-45. https://openaccesspub.org/jar/article/1701
4 Peiretti P G, Masoero G and Tassone S 2017: Comparison of the nutritive value and fatty acid profile of the green pruning residues of six grapevine (Vitis vinifera L.) cultivars. Livestock Research for Rural Development. Volume 29, Article #194.Retrieved October 3, 2017, http://www.lrrd.org/lrrd29/10/pier29194.html