Near infrared spectroscopy (NIRS) and mid-infrared spectroscopy (MIRS) in combination with chemometric analysis were applied to discriminate the geographical origin of grapevine leaves belonging to the variety "Touriga Nacional" during different vegetative stages. Leaves were collected from plants of two different wine regions in Portugal (Dão and Douro) over the grapes maturation period. A sampling plan was designed in order to obtain the most variability within the vineyards taking into account variables such as: solar exposition, land inclination, altitude and soil properties, essentially. Principal component analysis (PCA) was used to extract relevant information from the spectral data and presented visible cluster trends. Results, both with NIRS and MIRS, demonstrate that it is possible to discriminate between the two geographical origins with an outstanding accuracy. Spectral patterns of grapevine leaves show significant differences during grape maturation period, with a special emphasis between the months of June and September. Additionally, the quantification of total chlorophyll and total polyphenol content from leaves spectra was attempted by both techniques. For this purpose, partial least squares (PLS) regression was employed. PLS models based on NIRS and MIRS, both demonstrate a statistically significant correlation for the total chlorophyll (R2P = 0.92 and R2P = 0.76, respectively). However, the PLS model for the total polyphenols, may only be considered as a screening method, because significant prediction errors, independently of resourcing on NIRS, MIRS or both techniques simultaneously, were obtained.

译文

近红外光谱 (NIRS) 和中红外光谱 (MIRS) 与化学计量分析相结合,用于区分不同营养阶段属于 “Touriga Nacional” 品种的葡萄叶的地理来源。在葡萄成熟期,从葡萄牙两个不同葡萄酒产区 (d ã o和Douro) 的植物中收集叶子。设计了一个采样计划,以便在葡萄园内获得最大的可变性,并考虑了诸如以下变量: 太阳暴露,土地倾斜度,海拔和土壤特性。主成分分析 (PCA) 用于从光谱数据中提取相关信息,并呈现可见的聚类趋势。NIRS和MIRS的结果都表明,有可能以出色的准确性区分这两个地理起源。葡萄叶片的光谱模式在葡萄成熟期显示出显着差异,尤其是在6月月份和9月月份之间。此外,两种技术都尝试从叶片光谱中定量总叶绿素和总多酚含量。为此,采用偏最小二乘 (PLS) 回归。基于NIRS和MIRS的PLS模型均显示出总叶绿素的统计学显着相关性 (分别为R2P   =   0.92和R2P   =   0.76)。但是,总多酚的PLS模型只能被认为是一种筛选方法,因为获得了明显的预测误差,而与同时使用NIRS,MIRS或两种技术的资源无关。

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