DiSIA - Department of Statistics, Computer Sciences and Applications - PHYTOLAB Laboratory, Scientific and Technological Pole, University of Florence, Via Ugo Schiff, 6, 50019 Sesto Fiorentino, Firenze, Italy.
DiSIA - Department of Statistics, Computer Sciences and Applications - PHYTOLAB Laboratory, Scientific and Technological Pole, University of Florence, Via Ugo Schiff, 6, 50019 Sesto Fiorentino, Firenze, Italy.
Food Chem. 2018 Apr 1;244:213-223. doi: 10.1016/j.foodchem.2017.10.021. Epub 2017 Oct 7.
Fluorescence sensors are useful tools for the non-destructive assessment of grape berry anthocyanins. The Multiplex (Mx) sensor here studied provides two anthocyanin indices: ANTH = log(1/Chl-fluorescence_R) and ANTH = log(Chl-fluorescence_R/Chl-fluorescence_G), based on the chlorophyll (Chl) fluorescence excited with red (R) and green (G) light. These indices were calibrated against wet chemistry. The dependence of anthocyanin prediction models on cultivar, season and site was studied on four cultivars in two Italian regions during three consecutive years. The 2010 global model (all cultivars at both growing sites) gave relative prediction errors on anthocyanin content less than 14.1% (ANTH) and 19.0% (ANTH). The ANTH was independent of season, maintaining a relative error of about 20% in both 2011 and 2012. In field applications of the calibrated Mx, it showed its ability to detect inter-plot and inter-season differences on both growing sites.
荧光传感器是无损评估葡萄浆果花色苷的有用工具。本研究中的 Multiplex（Mx）传感器提供了两个花色苷指数：ANTH=log(1/Chl-fluorescence_R)和 ANTH=log(Chl-fluorescence_R/Chl-fluorescence_G)，基于用红光 (R) 和绿光 (G) 激发的叶绿素 (Chl) 荧光。这些指数是根据湿法化学进行校准的。在三年的时间里，在意大利的两个地区的四个品种上研究了花色苷预测模型对品种、季节和地点的依赖性。2010 年的全球模型（两个生长地点的所有品种）对花色苷含量的相对预测误差小于 14.1%（ANTH）和 19.0%（ANTH）。ANTH 与季节无关，在 2011 年和 2012 年均保持约 20%的相对误差。在 Mx 的校准现场应用中，它显示了在两个生长地点检测小区间和季节间差异的能力。
