Julius Kühn Institute (JKI), Federal Research Centre of Cultivated Plants, Institute for Grapevine Breeding Geilweilerhof, 76833 Siebeldingen, Germany.
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76131 Karlsruhe, Germany.
Sensors (Basel). 2023 Jun 2;23(11):5287. doi: 10.3390/s23115287.
An automatic determination of grape must ingredients during the harvesting process would support cellar logistics and enables an early termination of the harvest if quality parameters are not met. One of the most important quality-determining characteristics of grape must is its sugar and acid content. Among others, the sugars in particular determine the quality of the must and wine. Chiefly in wine cooperatives, in which a third of all German winegrowers are organized, these quality characteristics serve as the basis for payment. They are acquired upon delivery at the cellar of the cooperative or the winery and result in the acceptance or rejection of grapes and must. The whole process is very time-consuming and expensive, and sometimes grapes that do not meet the quality requirements for sweetness, acidity, or healthiness are destroyed or not used at all, which leads to economic loss. Near-infrared spectroscopy is now a widely used technique to detect a wide variety of ingredients in biological samples. In this study, a miniaturized semi-automated prototype apparatus with a near-infrared sensor and a flow cell was used to acquire spectra (1100 nm to 1350 nm) of grape must at defined temperatures. Data of must samples from four different red and white (L.) varieties were recorded throughout the whole growing season of 2021 in Rhineland Palatinate, Germany. Each sample consisted of 100 randomly sampled berries from the entire vineyard. The contents of the main sugars (glucose and fructose) and acids (malic acid and tartaric acid) were determined with high-performance liquid chromatography. Chemometric methods, using partial least-square regression and leave-one-out cross-validation, provided good estimates of both sugars (RMSEP = 6.06 g/L, = 89.26%), as well as malic acid (RMSEP = 1.22 g/L, = 91.10%). The coefficient of determination () was comparable for glucose and fructose with 89.45% compared to 89.08%, respectively. Although tartaric acid was predictable for only two of the four varieties using near-infrared spectroscopy, calibration and validation for malic acid were accurate for all varieties in an equal extent like the sugars. These high prediction accuracies for the main quality determining grape must ingredients using this miniaturized prototype apparatus might enable an installation on a grape harvester in the future.
在收获过程中自动测定葡萄汁的成分可以支持酒窖物流,并在质量参数不达标时提前结束收获。葡萄汁最重要的质量决定特性之一是其糖和酸含量。特别是糖,主要决定了葡萄汁和葡萄酒的质量。主要在葡萄酒合作社中,德国三分之一的葡萄酒种植者都组织在其中,这些质量特性是支付的基础。它们是在合作社或酿酒厂的酒窖交货时获得的,结果是接受或拒绝葡萄和葡萄汁。整个过程非常耗时且昂贵,有时不符合甜度、酸度或健康要求的葡萄根本不会被使用,这会导致经济损失。近红外光谱是一种广泛用于检测生物样本中各种成分的技术。在这项研究中,使用带有近红外传感器和流动池的小型半自动原型设备来获取 2021 年莱茵兰-普法尔茨整个生长季节在规定温度下的葡萄汁光谱(1100nm 至 1350nm)。记录了来自四个不同的红葡萄和白葡萄品种的葡萄汁样本数据。每个样本由来自整个葡萄园的 100 个随机采样的浆果组成。主要糖(葡萄糖和果糖)和酸(苹果酸和酒石酸)的含量用高效液相色谱法测定。使用偏最小二乘回归和留一法交叉验证的化学计量学方法,对两种糖(RMSEP=6.06g/L,=89.26%)以及苹果酸(RMSEP=1.22g/L,=91.10%)都提供了很好的估计。葡萄糖和果糖的决定系数()分别为 89.45%和 89.08%,具有可比性。尽管使用近红外光谱法仅能预测四种品种中的两种品种的酒石酸,但对所有品种的校准和验证在同等程度上都准确,与糖一样。使用这种小型原型设备对主要质量决定葡萄汁成分的高预测精度可能使未来能够在葡萄收获机上安装该设备。