University of La Rioja, Department of Agriculture and Food Science, 26006 Logroño, Spain.
Institute of Grapevine and Wine Sciences (University of La Rioja, Consejo Superior de Investigaciones Científicas, Gobierno de La Rioja), 26007 Logroño, Spain.
Molecules. 2019 Jul 31;24(15):2795. doi: 10.3390/molecules24152795.
Visible-Short Wave Near Infrared (VIS + SW - NIR) spectroscopy is a real alternative to break down the next barrier in precision viticulture allowing a reliable monitoring of grape composition within the vineyard to facilitate the decision-making process dealing with grape quality sorting and harvest scheduling, for example. On-the-go spectral measurements of grape clusters were acquired in the field using a VIS + SW - NIR spectrometer, operating in the 570-990 nm spectral range, from a motorized platform moving at 5 km/h. Spectral measurements were acquired along four dates during grape ripening in 2017 on the east side of the canopy, which had been partially defoliated at cluster closure. Over the whole measuring season, a total of 144 experimental blocks were monitored, sampled and their fruit analyzed for total soluble solids (TSS), anthocyanin and total polyphenols concentrations using standard, wet chemistry reference methods. Partial Least Squares (PLS) regression was used as the algorithm for training the grape composition parameters' prediction models. The best cross-validation and external validation (prediction) models yielded determination coefficients of cross-validation (R) and prediction (R) of 0.92 and 0.95 for TSS, R = 0.75, and R = 0.79 for anthocyanins, and R = 0.42 and R = 0.43 for total polyphenols. The vineyard variability maps generated for the different dates using this technology illustrate the capability to monitor the spatiotemporal dynamics and distribution of total soluble solids, anthocyanins and total polyphenols along grape ripening in a commercial vineyard.
可见-短波近红外（VIS + SW - NIR）光谱学是打破精准葡萄栽培下一壁垒的真正选择，可实现对葡萄园葡萄成分的可靠监测，从而为葡萄质量分拣和收获计划等决策过程提供便利。使用 VIS + SW - NIR 光谱仪在田间对葡萄串进行了现场的光谱测量，该光谱仪在 570-990nm 光谱范围内运行，由以 5 公里/小时的速度移动的电动平台操作。在 2017 年葡萄成熟期间的四个日期，对树冠东侧进行了光谱测量，该东侧在葡萄串关闭时已经部分去叶。在整个测量季节，共监测、采样和分析了 144 个实验块的果实，使用标准的湿化学参考方法测定总可溶性固体（TSS）、花青素和总多酚的浓度。偏最小二乘（PLS）回归被用作训练葡萄成分参数预测模型的算法。最佳的交叉验证和外部验证（预测）模型的交叉验证（R）和预测（R）系数分别为 TSS 的 0.92 和 0.95，花青素的 R = 0.75 和 R = 0.79，总多酚的 R = 0.42 和 R = 0.43。使用这项技术为不同日期生成的葡萄园变异性图说明了监测总可溶性固体、花青素和总多酚在商业葡萄园成熟过程中的时空动态和分布的能力。
